Articles | Volume 9, issue 5
https://doi.org/10.5194/amt-9-1981-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-1981-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data
Atmosphere and Ocean Research Institute, the University of
Tokyo, Chiba, Japan
Ryoichi Imasu
Atmosphere and Ocean Research Institute, the University of
Tokyo, Chiba, Japan
Naoko Saitoh
Center of Environmental Remote Sensing, Chiba University,
Chiba, Japan
Yoshifumi Ota
Meteorological Research Institute, Tsukuba,
Japan
Kei Shiomi
Japan Aerospace Exploration Agency, Tsukuba,
Japan
Related authors
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
Short summary
Short summary
The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Yu Someya, Ryoichi Imasu, Kei Shiomi, and Naoko Saitoh
Atmos. Meas. Tech., 13, 309–321, https://doi.org/10.5194/amt-13-309-2020, https://doi.org/10.5194/amt-13-309-2020, 2020
Short summary
Short summary
This study presents a novel ammonia retrieval system we developed GOSAT. This system was used to derive estimates of global atmospheric ammonia concentrations between 2009 and 2014. The results demonstrated significantly high concentrations stemming from six anthropogenic emission source areas and four biomass burning ones. Their horizontal and temporal distributions were compared with those from IASI. They were totally consistent and the causes of the differences were discussed.
Tomoo Ogura, Hideo Shiogama, Masahiro Watanabe, Masakazu Yoshimori, Tokuta Yokohata, James D. Annan, Julia C. Hargreaves, Naoto Ushigami, Kazuya Hirota, Yu Someya, Youichi Kamae, Hiroaki Tatebe, and Masahide Kimoto
Geosci. Model Dev., 10, 4647–4664, https://doi.org/10.5194/gmd-10-4647-2017, https://doi.org/10.5194/gmd-10-4647-2017, 2017
Short summary
Short summary
Present-day climate simulated by coupled ocean atmosphere models exhibits significant biases in top-of-atmosphere radiation and clouds. This study shows that only limited part of the biases can be removed by parameter tuning in a climate model. The results underline the importance of improving parameterizations in climate models based on cloud process studies. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
Short summary
Short summary
Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Hirofumi Ohyama, Matthias M. Frey, Isamu Morino, Kei Shiomi, Masahide Nishihashi, Tatsuya Miyauchi, Hiroko Yamada, Makoto Saito, Masanobu Wakasa, Thomas Blumenstock, and Frank Hase
Atmos. Chem. Phys., 23, 15097–15119, https://doi.org/10.5194/acp-23-15097-2023, https://doi.org/10.5194/acp-23-15097-2023, 2023
Short summary
Short summary
We conducted a field campaign for CO2 column measurements in the Tokyo metropolitan area with three ground-based Fourier transform spectrometers. The model simulations using prior CO2 fluxes were generally in good agreement with the observations. We developed an urban-scale inversion system in which spatially resolved CO2 fluxes and a scaling factor of large point source emissions were estimated. The posterior total CO2 emissions agreed with emission inventories within the posterior uncertainty.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-224, https://doi.org/10.5194/amt-2023-224, 2023
Preprint under review for AMT
Short summary
Short summary
This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-331, https://doi.org/10.5194/essd-2023-331, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper describes a new version, called GGG2020, of a dataset containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made towards site-to-site consistency. This dataset plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Mukunda M. Gogoi, S. Suresh Babu, Ryoichi Imasu, and Makiko Hashimoto
Atmos. Chem. Phys., 23, 8059–8079, https://doi.org/10.5194/acp-23-8059-2023, https://doi.org/10.5194/acp-23-8059-2023, 2023
Short summary
Short summary
Considering the climate warming potential of atmospheric black carbon (BC), satellite-based retrieval is a novel idea. This study highlights the regional distribution of BC based on observations by the Cloud and Aerosol Imager-2 on board the GOSAT-2 satellite and near-surface measurements of BC in ARFINET. The satellite retrieval fairly depicts the regional and seasonal features of BC over the Indian region, which are similar to those recorded by surface observations.
Yifan Guan, Gretchen Keppel-Aleks, Scott C. Doney, Christof Petri, Dave Pollard, Debra Wunch, Frank Hase, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Kim Strong, Rigel Kivi, Matthias Buschmann, Nicholas Deutscher, Paul Wennberg, Ralf Sussmann, Voltaire A. Velazco, and Yao Té
Atmos. Chem. Phys., 23, 5355–5372, https://doi.org/10.5194/acp-23-5355-2023, https://doi.org/10.5194/acp-23-5355-2023, 2023
Short summary
Short summary
We characterize spatial–temporal patterns of interannual variability (IAV) in atmospheric CO2 based on NASA’s Orbiting Carbon Observatory-2 (OCO-2). CO2 variation is strongly impacted by climate events, with higher anomalies during El Nino years. We show high correlation in IAV between space-based and ground-based CO2 from long-term sites. Because OCO-2 has near-global coverage, our paper provides a roadmap to study IAV where in situ observation is sparse, such as open oceans and remote lands.
Jagat S. H. Bisht, Prabir K. Patra, Masayuki Takigawa, Takashi Sekiya, Yugo Kanaya, Naoko Saitoh, and Kazuyuki Miyazaki
Geosci. Model Dev., 16, 1823–1838, https://doi.org/10.5194/gmd-16-1823-2023, https://doi.org/10.5194/gmd-16-1823-2023, 2023
Short summary
Short summary
In this study, we estimated CH4 fluxes using an advanced 4D-LETKF method. The system was tested and optimized using observation system simulation experiments (OSSEs), where a known surface emission distribution is retrieved from synthetic observations. The availability of satellite measurements has increased, and there are still many missions focused on greenhouse gas observations that have not yet launched. The technique being referred to has the potential to improve estimates of CH4 fluxes.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
Short summary
Short summary
The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
Short summary
Short summary
Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Hiroshi Suto, Fumie Kataoka, Robert O. Knuteson, Kei Shiomi, Nobuhiro Kikuchi, and Akihiko Kuze
Atmos. Meas. Tech., 15, 5399–5413, https://doi.org/10.5194/amt-15-5399-2022, https://doi.org/10.5194/amt-15-5399-2022, 2022
Short summary
Short summary
TANSO-FTS-2 onboard GOSAT-2 has operated nominally since February 2019, and the atmospheric radiance spectra it has acquired have been released to the public. This paper describes an updated model for spectral radiance calibration of TIR and its validation. The multi-satellite sensor and multi-angle comparison results suggest that the spectral radiance for TANSO-FTS-2 TIR, version v210210, is superior to that of the previous version in its consistency of multi-satellite sensor data.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
Short summary
Short summary
We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
Short summary
Short summary
We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
Short summary
Short summary
Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Akihiro Honda, Nawo Eguchi, and Naoko Saitoh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-46, https://doi.org/10.5194/acp-2022-46, 2022
Revised manuscript not accepted
Short summary
Short summary
The intra-seasonal, seasonal and inter-annual variations of carbon dioxide (CO2) at the upper troposphere and lower stratosphere (UTLS) are investigated by the CO2 profile data derived from the thermal infrared spectra of TANSO-FTS instrument onboard GOSAT satellite, for understanding of the missing sink of CO2 and detail exchange process between UT and LS. There are new findings on the intra-seasonal and inter-annual variations associated with Asian summer monsoon and ENSO, respectively.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
Short summary
Short summary
We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
Short summary
Short summary
This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Matthias M. Frey, Frank Hase, Thomas Blumenstock, Darko Dubravica, Jochen Groß, Frank Göttsche, Martin Handjaba, Petrus Amadhila, Roland Mushi, Isamu Morino, Kei Shiomi, Mahesh Kumar Sha, Martine de Mazière, and David F. Pollard
Atmos. Meas. Tech., 14, 5887–5911, https://doi.org/10.5194/amt-14-5887-2021, https://doi.org/10.5194/amt-14-5887-2021, 2021
Short summary
Short summary
In this study, we present measurements of carbon dioxide, methane and carbon monoxide from a recently established site in Gobabeb, Namibia. Gobabeb is the first site observing these gases on the African mainland and improves the global coverage of measurement sites. Gobabeb is a hyperarid desert site, offering unique characteristics. Measurements started 2015 as part of the COllaborative Carbon Column Observing Network. We compare our results with other datasets and find a good agreement.
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021, https://doi.org/10.5194/amt-14-4689-2021, 2021
Short summary
Short summary
We present the Adaptable 4A Inversion (5AI), an implementation of the optimal estimation (OE) algorithm, relying on the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer model, that enables the retrieval of greenhouse gas atmospheric weighted columns from infrared measurements. It is tested on a sample of Orbiting Carbon Observatory-2 observations, and its results satisfactorily compare to several reference products, thus showing the reliability of 5AI OE implementation.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, James R. Podolske, David F. Pollard, Mahesh Kumar Sha, Kei Shiomi, Ralf Sussmann, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 3837–3869, https://doi.org/10.5194/amt-14-3837-2021, https://doi.org/10.5194/amt-14-3837-2021, 2021
Short summary
Short summary
We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm. Comparisons of the GOSAT-FOCAL product with other data reveal long-term agreement within about 1 ppm over 1 decade, differences in seasonal variations of about 0.5 ppm, and a mean regional bias to ground-based TCCON data of 0.56 ppm with a mean scatter of 1.89 ppm. GOSAT-2-FOCAL data are preliminary only, but first comparisons show that they compare well with the GOSAT-FOCAL results and TCCON.
Hiroshi Suto, Fumie Kataoka, Nobuhiro Kikuchi, Robert O. Knuteson, Andre Butz, Markus Haun, Henry Buijs, Kei Shiomi, Hiroko Imai, and Akihiko Kuze
Atmos. Meas. Tech., 14, 2013–2039, https://doi.org/10.5194/amt-14-2013-2021, https://doi.org/10.5194/amt-14-2013-2021, 2021
Short summary
Short summary
The Japanese Greenhouse gases Observing SATellite-2 (GOSAT-2), in orbit since October 2018, is the follow-up mission of GOSAT, which has been operating since January 2009. Both satellites are dedicated to the monitoring of global carbon dioxide and methane to further knowledge of the global carbon cycle. This paper has reported on the function and performance of the TANSO-FTS-2 instrument, level-1 data processing, and calibrations for the first year of GOSAT-2 observation.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
Short summary
Short summary
TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
Short summary
Short summary
This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Dmitry A. Belikov, Naoko Saitoh, Prabir K. Patra, and Naveen Chandra
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-101, https://doi.org/10.5194/amt-2020-101, 2020
Preprint withdrawn
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
Short summary
Short summary
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Jonas Simon Wilzewski, Anke Roiger, Johan Strandgren, Jochen Landgraf, Dietrich G. Feist, Voltaire A. Velazco, Nicholas M. Deutscher, Isamu Morino, Hirofumi Ohyama, Yao Té, Rigel Kivi, Thorsten Warneke, Justus Notholt, Manvendra Dubey, Ralf Sussmann, Markus Rettinger, Frank Hase, Kei Shiomi, and André Butz
Atmos. Meas. Tech., 13, 731–745, https://doi.org/10.5194/amt-13-731-2020, https://doi.org/10.5194/amt-13-731-2020, 2020
Short summary
Short summary
Through spectral degradation of GOSAT measurements in the 1.6 and 2.0 μm spectral bands, we mimic a single-band, passive satellite sensor for monitoring of CO2 emissions at fine spatial scales. We compare retrievals of XCO2 from these bands to TCCON and native GOSAT retrievals. At spectral resolutions near 1.3 nm, XCO2 retrievals from both bands show promising performance, but the 2.0 μm band is favorable due to better noise performance and the potential to retrieve some aerosol information.
Yu Someya, Ryoichi Imasu, Kei Shiomi, and Naoko Saitoh
Atmos. Meas. Tech., 13, 309–321, https://doi.org/10.5194/amt-13-309-2020, https://doi.org/10.5194/amt-13-309-2020, 2020
Short summary
Short summary
This study presents a novel ammonia retrieval system we developed GOSAT. This system was used to derive estimates of global atmospheric ammonia concentrations between 2009 and 2014. The results demonstrated significantly high concentrations stemming from six anthropogenic emission source areas and four biomass burning ones. Their horizontal and temporal distributions were compared with those from IASI. They were totally consistent and the causes of the differences were discussed.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Tobias Borsdorff, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Christian Hermans, Laura T. Iraci, Rigel Kivi, Jochen Landgraf, Isamu Morino, Justus Notholt, Christof Petri, David F. Pollard, Sébastien Roche, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Voltaire A. Velazco, Thorsten Warneke, and Debra Wunch
Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, https://doi.org/10.5194/amt-12-6771-2019, 2019
Short summary
Short summary
We introduce an algorithm that is used to simultaneously derive the abundances of the important atmospheric constituents carbon monoxide and methane from the TROPOMI instrument onboard the Sentinel-5 Precursor satellite, which enables the determination of both gases with an unprecedented level of detail on a global scale. The quality of the resulting data sets is assessed and the first results are presented.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
Short summary
Short summary
This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Mai Ouchi, Yutaka Matsumi, Tomoki Nakayama, Kensaku Shimizu, Takehiko Sawada, Toshinobu Machida, Hidekazu Matsueda, Yousuke Sawa, Isamu Morino, Osamu Uchino, Tomoaki Tanaka, and Ryoichi Imasu
Atmos. Meas. Tech., 12, 5639–5653, https://doi.org/10.5194/amt-12-5639-2019, https://doi.org/10.5194/amt-12-5639-2019, 2019
Short summary
Short summary
A novel, practical observation system for measuring tropospheric carbon dioxide (CO2) concentrations carried by a small helium-filled balloon (CO2 sonde) has been developed for the first time. The low-cost CO2 sondes can potentially be used for frequent measurements of vertical profiles of CO2 in any parts of the world, providing useful information to understand the global and regional carbon budgets by replenishing the present sparse observation coverage.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
Short summary
Short summary
We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
Matthias Frey, Mahesh K. Sha, Frank Hase, Matthäus Kiel, Thomas Blumenstock, Roland Harig, Gregor Surawicz, Nicholas M. Deutscher, Kei Shiomi, Jonathan E. Franklin, Hartmut Bösch, Jia Chen, Michel Grutter, Hirofumi Ohyama, Youwen Sun, André Butz, Gizaw Mengistu Tsidu, Dragos Ene, Debra Wunch, Zhensong Cao, Omaira Garcia, Michel Ramonet, Felix Vogel, and Johannes Orphal
Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, https://doi.org/10.5194/amt-12-1513-2019, 2019
Short summary
Short summary
In a 3.5-year long study, the long-term performance of a mobile EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference spectrometer. We find that the EM27/SUN is stable on timescales of several years, qualifying it for permanent carbon cycle studies.
The performance of an ensemble of 30 EM27/SUN spectrometers was also tested in the framework of the COllaborative Carbon Column Observing Network (COCCON) and found to be very uniform.
Lianghai Wu, Otto Hasekamp, Haili Hu, Jochen Landgraf, Andre Butz, Joost aan de Brugh, Ilse Aben, Dave F. Pollard, David W. T. Griffith, Dietrich G. Feist, Dmitry Koshelev, Frank Hase, Geoffrey C. Toon, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Laura Iraci, Matthias Schneider, Martine de Mazière, Ralf Sussmann, Rigel Kivi, Thorsten Warneke, Tae-Young Goo, and Yao Té
Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, https://doi.org/10.5194/amt-11-3111-2018, 2018
Yannick Kangah, Philippe Ricaud, Jean-Luc Attié, Naoko Saitoh, Jérôme Vidot, Pascal Brunel, and Samuel Quesada-Ruiz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-21, https://doi.org/10.5194/amt-2018-21, 2018
Revised manuscript not accepted
Tomohiro O. Sato, Takao M. Sato, Hideo Sagawa, Katsuyuki Noguchi, Naoko Saitoh, Hitoshi Irie, Kazuyuki Kita, Mona E. Mahani, Koji Zettsu, Ryoichi Imasu, Sachiko Hayashida, and Yasuko Kasai
Atmos. Meas. Tech., 11, 1653–1668, https://doi.org/10.5194/amt-11-1653-2018, https://doi.org/10.5194/amt-11-1653-2018, 2018
Short summary
Short summary
Air pollution is one of the world's greatest environmental health risks. Ozone adversely affects human health and agricultural production, and the tropospheric ozone has been increasing globally over the past few decades. We report an advanced method to derive the ozone amount in the lowermost troposphere using multi-spectral measurements (UV, thermal infrared and microwave). Combining the MW measurement with the UV and thermal infrared measurements certainly increased the sensitivity.
Tomoo Ogura, Hideo Shiogama, Masahiro Watanabe, Masakazu Yoshimori, Tokuta Yokohata, James D. Annan, Julia C. Hargreaves, Naoto Ushigami, Kazuya Hirota, Yu Someya, Youichi Kamae, Hiroaki Tatebe, and Masahide Kimoto
Geosci. Model Dev., 10, 4647–4664, https://doi.org/10.5194/gmd-10-4647-2017, https://doi.org/10.5194/gmd-10-4647-2017, 2017
Short summary
Short summary
Present-day climate simulated by coupled ocean atmosphere models exhibits significant biases in top-of-atmosphere radiation and clouds. This study shows that only limited part of the biases can be removed by parameter tuning in a climate model. The results underline the importance of improving parameterizations in climate models based on cloud process studies. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases.
Naoko Saitoh, Shuhei Kimoto, Ryo Sugimura, Ryoichi Imasu, Kei Shiomi, Akihiko Kuze, Yosuke Niwa, Toshinobu Machida, Yousuke Sawa, and Hidekazu Matsueda
Atmos. Meas. Tech., 10, 3877–3892, https://doi.org/10.5194/amt-10-3877-2017, https://doi.org/10.5194/amt-10-3877-2017, 2017
Short summary
Short summary
This study evaluated biases in GOSAT/TANSO-FTS thermal infrared (TIR) V1 CO2 product on 736–287 hPa on the basis of comparisons with CONTRAIL CME CO2 data over airports. TIR V1 CO2 data had consistent negative biases of 1–1.5 %, with the largest negative biases at 541–398 hPa. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by NICAM-TM confirmed the validity of the bias-correction values evaluated over airports in limited areas.
Kevin S. Olsen, Kimberly Strong, Kaley A. Walker, Chris D. Boone, Piera Raspollini, Johannes Plieninger, Whitney Bader, Stephanie Conway, Michel Grutter, James W. Hannigan, Frank Hase, Nicholas Jones, Martine de Mazière, Justus Notholt, Matthias Schneider, Dan Smale, Ralf Sussmann, and Naoko Saitoh
Atmos. Meas. Tech., 10, 3697–3718, https://doi.org/10.5194/amt-10-3697-2017, https://doi.org/10.5194/amt-10-3697-2017, 2017
Short summary
Short summary
The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier transform spectrometer (FTS). TANSO-FTS has a thermal infrared channel to retrieve vertical profiles of CO2 and CH4 volume mixing ratios in the troposphere. We compare the retrieved vertical profiles of CH4 from TANSO-FTS with those from two other spaceborne FTSs and with ground-based FTS observatories to assess their quality.
Yosuke Niwa, Yosuke Fujii, Yousuke Sawa, Yosuke Iida, Akihiko Ito, Masaki Satoh, Ryoichi Imasu, Kazuhiro Tsuboi, Hidekazu Matsueda, and Nobuko Saigusa
Geosci. Model Dev., 10, 2201–2219, https://doi.org/10.5194/gmd-10-2201-2017, https://doi.org/10.5194/gmd-10-2201-2017, 2017
Short summary
Short summary
A new 4D-Var inversion system based on the icosahedral grid model, NICAM, is introduced and tested. Adding to the offline forward and adjoint models, this study has introduced the optimization method of POpULar; it does not require difficult decomposition of a matrix that establishes the correlation among the prior flux errors. In identical twin experiments of atmospheric CO2 inversion, the system successfully reproduces the spatiotemporal variations of the surface fluxes.
Yosuke Niwa, Hirofumi Tomita, Masaki Satoh, Ryoichi Imasu, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Toshinobu Machida, Motoki Sasakawa, Boris Belan, and Nobuko Saigusa
Geosci. Model Dev., 10, 1157–1174, https://doi.org/10.5194/gmd-10-1157-2017, https://doi.org/10.5194/gmd-10-1157-2017, 2017
Short summary
Short summary
We have developed forward and adjoint models based on NICAM-TM, as part of the 4D-Var system for atmospheric GHGs inversions. The models are computationally efficient enough to make the 4D-Var iterative calculation feasible. Trajectory analysis for high-CO2 concentration events are performed to test adjoint sensitivities; we also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport.
Mingmin Zou, Xiaozhen Xiong, Naoko Saitoh, Juying Warner, Ying Zhang, Liangfu Chen, Fuzhong Weng, and Meng Fan
Atmos. Meas. Tech., 9, 3567–3576, https://doi.org/10.5194/amt-9-3567-2016, https://doi.org/10.5194/amt-9-3567-2016, 2016
Short summary
Short summary
Both AIRS and GOSAT TANSO-FTS TIR have been used to retrieve atmosphere CH4. The purpose of an intercomparison is to provide useful information to users on the characteristics of these two different products when they investigate the spatial and temporal variation of CH4. On the other hand, AIRS V6 CH4 data were already validated by comparing with aircraft data. This intercomparison is also a kind of indirect validation to GOSAT data.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
Short summary
Short summary
In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Shuji Kawakami, Makoto Tanaka, Yoko Ueda, Akira Deguchi, Jun Yoshida, Yoshifumi Yamamoto, Fumie Kataoka, Thomas E. Taylor, and Henry L. Buijs
Atmos. Meas. Tech., 9, 2445–2461, https://doi.org/10.5194/amt-9-2445-2016, https://doi.org/10.5194/amt-9-2445-2016, 2016
Short summary
Short summary
A more than 6-year data set has been acquired by TANSO-FTS onboard GOSAT. This paper provides updates on the performance and describes important changes to the data product for the typical accuracy of retrieved CO2 and CH4 of 2 ppm and 13 ppb, respectively. The V201 Level 1B have long-term uniform quality and provide consistent retrieval accuracy even after the three anomalies of the satellite system. In addition, we discuss the unique observation abilities by an agile pointing mechanism.
Naoko Saitoh, Shuhei Kimoto, Ryo Sugimura, Ryoichi Imasu, Shuji Kawakami, Kei Shiomi, Akihiko Kuze, Toshinobu Machida, Yousuke Sawa, and Hidekazu Matsueda
Atmos. Meas. Tech., 9, 2119–2134, https://doi.org/10.5194/amt-9-2119-2016, https://doi.org/10.5194/amt-9-2119-2016, 2016
Short summary
Short summary
This study compared GOSAT/TANSO-FTS thermal infrared (TIR) V1 and CONTRAIL CME CO2 data in the upper troposphere and lower stratosphere. The TIR CO2 averages agreed with the CME CO2 averages within 0.1 and 0.5 % in the Southern and Northern Hemisphere. At northern low and middle latitudes, their agreements were worse in spring and summer. The negative bias there made the maximum of TIR data being lower than that of CME data, which leads to underestimating the amplitude of CO2 seasonal variation.
Gerrit Holl, Kaley A. Walker, Stephanie Conway, Naoko Saitoh, Chris D. Boone, Kimberly Strong, and James R. Drummond
Atmos. Meas. Tech., 9, 1961–1980, https://doi.org/10.5194/amt-9-1961-2016, https://doi.org/10.5194/amt-9-1961-2016, 2016
Short summary
Short summary
Methane is a powerful greenhouse gas, and we need to measure it globally with satellite instruments. We compare measurements from two satellites with measurements from the ground in Eureka, Nunavut, Canada to assess their different strengths and weaknesses. The differences between measurements are discussed and assessed considering the details of each measurement technique and processing. Recommendations are provided for utilization of these data sets for monitoring methane in the high Arctic.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
Short summary
Short summary
To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
P. Ricaud, B. Sič, L. El Amraoui, J.-L. Attié, R. Zbinden, P. Huszar, S. Szopa, J. Parmentier, N. Jaidan, M. Michou, R. Abida, F. Carminati, D. Hauglustaine, T. August, J. Warner, R. Imasu, N. Saitoh, and V.-H. Peuch
Atmos. Chem. Phys., 14, 11427–11446, https://doi.org/10.5194/acp-14-11427-2014, https://doi.org/10.5194/acp-14-11427-2014, 2014
N. V. Rokotyan, V. I. Zakharov, K. G. Gribanov, M. Schneider, F.-M. Bréon, J. Jouzel, R. Imasu, M. Werner, M. Butzin, C. Petri, T. Warneke, and J. Notholt
Atmos. Meas. Tech., 7, 2567–2580, https://doi.org/10.5194/amt-7-2567-2014, https://doi.org/10.5194/amt-7-2567-2014, 2014
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations
Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations
Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations
The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission
High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Improved spectral processing for a multi-mode pulse compression Ka–Ku-band cloud radar system
Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption
Ice water path retrievals from Meteosat-9 using quantile regression neural networks
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
Short summary
Short summary
We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
Short summary
Short summary
In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
Short summary
Short summary
The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
Short summary
Short summary
We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
Short summary
Short summary
The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
Short summary
Short summary
The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
Short summary
Short summary
The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
Short summary
Short summary
The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
Short summary
Short summary
Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
Short summary
Short summary
A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
Short summary
Short summary
Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
Short summary
Short summary
The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
Short summary
Short summary
We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
Short summary
Short summary
Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
Short summary
Short summary
We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
Short summary
Short summary
We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
Short summary
Short summary
The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
Short summary
Short summary
We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
Short summary
Short summary
The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
Short summary
Short summary
JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
Short summary
Short summary
This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
Short summary
Short summary
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
Short summary
Short summary
The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-109, https://doi.org/10.5194/amt-2023-109, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals is always decreasing with the increasing distance from the cloud far edge. The decreasing is the direct consequence of the fact that the forward peak of particles phase functions is much larger than the receiver field of view.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
Short summary
Short summary
We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
Short summary
Short summary
The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
Short summary
Short summary
This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
Short summary
Short summary
This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
Short summary
Short summary
We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
Short summary
Short summary
We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
Short summary
Short summary
Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
Short summary
Short summary
The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
Short summary
Short summary
Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
Short summary
Short summary
Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
Short summary
Short summary
We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
Short summary
Short summary
Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
Short summary
Short summary
This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
Short summary
Short summary
In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
Short summary
Short summary
SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
Short summary
Short summary
Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
Short summary
Short summary
Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
Short summary
Short summary
With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
Short summary
Short summary
This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
Short summary
Short summary
The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
Short summary
Short summary
In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
Short summary
Short summary
Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
Short summary
Short summary
Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
Short summary
Short summary
Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
Short summary
Short summary
This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
Short summary
Short summary
A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Cited articles
Baldridge, A. M., Hook, S. J., Grove, C. I., and Rivera, G.: The ASTER spectral library ver. 2.0, Remote Sens. Environ., 113, 711–715, 2009.
Chahine, M. T.: Remote Sounding of Cloudy Atmospheres 1, Single Cloud Layer, J. Atmos. Sci., 31, 233–243, 1974.
Chang, F. L., Minnis, P., Lin, B., Khaiyer, M. M., Palikonda, R., and Spangenberg, D. A.: A modified method for inferring upper troposphere cloud top height using the GOES 12 imager 10.7 and 13.3 µm data, J. Geophys. Res.-Atmos., 115, D06208, https://doi.org/10.1029/2009jd012304, 2010.
Clough, S. A., Shephard, M. W., Mlawer, E., Delamere, J. S., Iacono, M., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, 2005.
Gero, P. J., Knuteson, R. O., Shiomi, K., Kuze, A., Kataoka, F., Revercomb, H. E., Tobin, D. C., Taylor, J. K., and Best, F. A.: GOSAT TANSO FTS TIR band calibration: a five year review, Proc. SPIE, 9263, 926316, 2014.
Hawkinson, J. A., Feltz, W., and Ackerman, S. A.: A comparison of GOES sounder and cloud lidar- and radar-retrieved cloud-top heights, J. Appl. Meteorol., 44, 1234–1242, 2005.
Holz, R. E., Ackerman, S., Antonelli, P., Nagle, F., Knuteson, R. O., McGill, M., Hlavka, D. L., and Hart, W. D.: An improvement to the high-spectral-resolution CO2-slicing cloud-top altitude retrieval, J. Atmos. Ocean. Technol., 23, 653–670, 2006.
Imasu, R., Hayashi, Y., Inagoya, A., Saitoh, N., and Shiomi, K.: Retrieval of minor constituents from thermal infrared spectra observed by GOSAT TANSO-FTS sensor, P. SPIE, 7857, 785708, https://doi.org/10.1117/12.870684, 2010.
Ishida, H. and Nakajima, T. Y.: Development of an unbiased cloud detection algorithm for a spaceborne multispectral imager, J. Geophys. Res.-Atmos., 114, D07206, https://doi.org/10.1029/2008jd010710, 2009.
Kataoka, F., Knuteson, R. O., Kuze, A., Suto, H., Shiomi, K., Harada, M., Garms, E. M., Roman, J. A., Tobin, D. C., Taylor, J. K., Revercomb, T. H., Sekio, N., Higuchi, R., and Mitomi, Y.: TIR Spectral Radiance Calibration of the GOSAT Satellite Borne TANSO-FTS With the Aircraft-Based S-HIS and the Ground-Based S-AERI at the Railroad Valley Desert Playa, IEEE T. Geosci. Remote , 52, 89–105, 2014.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Opt., 48, 6716–6733, https://doi.org/10.1364/ao.48.006716, 2009.
Kuze, A., Suto, H., Shiomi, K., Urabe, T., Nakajima, M., Yoshida, J., Kawashima, T., Yamamoto, Y., Kataoka, F., and Buijs, H.: Level 1 algorithms for TANSO on GOSAT: processing and on-orbit calibrations, Atmos. Meas. Tech., 5, 2447–2467, https://doi.org/10.5194/amt-5-2447-2012, 2012.
Martins, E., Noel, V., and Chepfer, H.: Properties of cirrus and subvisible cirrus from nighttime Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), related to atmospheric dynamics and water vapor, J. Geophys. Res.-Atmos., 116, D02208, https://doi.org/10.1029/2010jd014519, 2011.
McGill, M. J., Vaughan, M. A., Trepte, C. R., Hart, W. D., Hlavka, D. L., Winker, D. M., and Kuehn, R.: Airborne validation of spatial properties measured by the CALIPSO lidar, J. Geophys. Res.-Atmos., 112, D20201, https://doi.org/10.1029/2007jd008768, 2007.
Menzel, W. P., Smith, W. L., and Stewart, T. R.: Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS, J. Climate Appl. Meteorol., 22, 377–384, 1983.
Menzel, W. P., Wylie, D. P., and Strabala, K. I.: Seasonal and Diurnal Changes in Cirrus Clouds as Seen in 4 Years of Observations with the VAS, J. Appl. Meteorol., 31, 370–385, 1992.
Menzel, W. P., Frey, R. A., Zhang, H., Wylie, D. P., Moeller, C. C., Holz, R. E., Maddux, B., Baum, B. A., Strabala, K. I., and Gumley, L. E.: MODIS global cloud-top pressure and amount estimation: Algorithm description and results, J. Appl. Meteorol. Climatol., 47, 1175–1198, 2008.
Morino, I., Uchino, O., Inoue, M., Yoshida, Y., Yokota, T., Wennberg, P. O., Toon, G. C., Wunch, D., Roehl, C. M., Notholt, J., Warneke, T., Messerschmidt, J., Griffith, D. W. T., Deutscher, N. M., Sherlock, V., Connor, B., Robinson, J., Sussmann, R., and Rettinger, M.: Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra, Atmos. Meas. Tech., 4, 1061–1076, https://doi.org/10.5194/amt-4-1061-2011, 2011.
Ota, Y., Higurashi, A., Nakajima, T., and Yokota, T.: Matrix formulations of radiative transfer including the polarization effect in a coupled atmosphere-ocean system, J. Quant. Spectrosc. Ra., 111, 878–894, 2010.
Rothman, L. S., Jacquemart, D., Barbe, A., Benner, D. C., Birk, M., Brown, L. R., Carleer, M. R., Chackerian, C., Chance, K., Coudert, L. H., Dana, V., Devi, V. M., Flaud, J. M., Gamache, R. R., Goldman, A., Hartmann, J. M., Jucks, K. W., Maki, A. G., Mandin, J. Y., Massie, S. T., Orphal, J., Perrin, A., Rinsland, C. P., Smith, M. A. H., Tennyson, J., Tolchenov, R. N., Toth, R. A., Vander Auwera, J., Varanasi, P., and Wagner, G.: The HITRAN 2004 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 96, 139–204, https://doi.org/10.1016/j.jqsrt.2004.10.008, 2005.
Saitoh, N., Imasu, R., Ota, Y., and Niwa, Y.: CO2 retrieval algorithm for the thermal infrared spectra of the Greenhouse Gases Observing Satellite: Potential of retrieving CO2 vertical profile from high-resolution FTS sensor, J. Geophys. Res.-Atmos., 114, D17305, https://doi.org/10.1029/2008jd011500, 2009.
Sassen, K., Wang, Z., and Liu, D.: Cirrus clouds and deep convection in the tropics: Insights from CALIPSO and CloudSat, J. Geophys. Res.-Atmos., 114, D00H06, https://doi.org/10.1029/2009jd011916, 2009.
Smith, W. L. and Platt, C. M. R.: Comparison of Satellite-Deduced Cloud Heights with Indications From Radiosonde and Ground-Based Laser Measurements, J. Appl. Meteorol., 17, 1796–1802, 1978.
Stubenrauch, C., Rossow, W., and Kinne, S.: Assessment of Global Cloud Data Sets from Satellites, WCRP report, 23, 2012.
Sun, W., Videen, G., and Mishchenko, M. I.: Detecting super- thin clouds with polarized sunlight, Geophys. Res. Lett., 41, 688–693, https://doi.org/10.1002/2013gl058840, 2014.
Sun, W., Baize, R. R., Videen, G., Hu, Y., and Fu, Q.: A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight, Atmos. Chem. Phys., 15, 11909–11918, https://doi.org/10.5194/acp-15-11909-2015, 2015.
Uchino, O., Kikuchi, N., Sakai, T., Morino, I., Yoshida, Y., Nagai, T., Shimizu, A., Shibata, T., Yamazaki, A., Uchiyama, A., Kikuchi, N., Oshchepkov, S., Bril, A., and Yokota, T.: Influence of aerosols and thin cirrus clouds on the GOSAT–observed CO2: a case study over Tsukuba, Atmos. Chem. Phys., 12, 3393–3404, https://doi.org/10.5194/acp-12-3393-2012, 2012.
Wielicki, B. A. and Coakley, J. A.: Cloud Retrieval Using Infrared Sounder Data – Error Analysis, J. Appl. Meteorol., 20, 157–169, 1981.
Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, L19803, https://doi.org/10.1029/2007gl030135, 2007.
WMO: WMO Greenhouse Gas Bulletin (GHG Bulletin) No. 10, ISSN:2078-0796, 2014.
Wu, D., Hu, Y. X., McCormick, M. P., and Yan, F. Q.: Global cloud-layer distribution statistics from 1 year CALIPSO lidar observations, Int. J. Remote Sens., 32, 1269–1288, 2011.
Wu, D. L., Ackerman, S. A., Davies, R., Diner, D. J., Garay, M. J., Kahn, B. H., Maddux, B. C., Moroney, C. M., Stephens, G. L., Veefkind, J. P., and Vaughan, M. A.: Vertical distributions and relationships of cloud occurrence frequency as observed by MISR, AIRS, MODIS, OMI, CALIPSO, and CloudSat, Geophys. Res. Lett., 36, L09821, https://doi.org/10.1029/2009gl037464, 2009.
Wunch, D., Toon, G. C., Blavier, J.-F. L., Washenfelder, R. A., Notholt, J., Connor, B. J., Griffith, D. W. T., Sherlock, V., and Wennberg, P. O.: The Total Carbon Column Observing Network, Philos. T. R. Soc. A, 369, 2087–2112, 2011.
Wylie, D. P. and Menzel, W. P.: Two Years of Cloud Cover Statistics Using VAS, J. Climate, 2, 380–392, 1989.
Wylie, D. P. and Menzel, W. P.: Eight years of high cloud statistics using HIRS, J. Climate, 12, 170–184, 1999.
Wylie, D. P. and Wang, P. H.: Comparison of SAGE-II and HIRS co-located cloud height measurements, Geophys. Res. Lett., 26, 3373–3375, https://doi.org/10.1029/1999gl010857, 1999.
Wylie, D. P., Menzel, W. P., Woolf, H. M., and Strabala, K. I.: 4 Years of Global Cirrus Cloud Statistics Using HIRS, J. Climate, 7, 1972–1986, 1994.
Wylie, D., Jackson, D. L., Menzel, W. P., and Bates, J. J.: Trends in global cloud cover in two decades of HIRS observations, J. Climate, 18, 3021–3031, 2005.
Wylie, D., Eloranta, E., Spinhirne, J. D., and Palm, S. P.: Comparison of cloud cover statistics from the GLAS lidar with HIRS, J. Climate, 20, 4968–4981, https://doi.org/10.1175/jcli4269.1, 2007.
Yoshida, Y., Kikuchi, N., Morino, I., Uchino, O., Oshchepkov, S., Bril, A., Saeki, T., Schutgens, N., Toon, G. C., Wunch, D., Roehl, C. M., Wennberg, P. O., Griffith, D. W. T., Deutscher, N. M., Warneke, T., Notholt, J., Robinson, J., Sherlock, V., Connor, B., Rettinger, M., Sussmann, R., Ahonen, P., Heikkinen, P., Kyrö, E., Mendonca, J., Strong, K., Hase, F., Dohe, S., and Yokota, T.: Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data, Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013.
Zhang, H. and Menzel, W. P.: Improvement in thin cirrus retrievals using an emissivity-adjusted CO2 slicing algorithm, J. Geophys. Res.-Atmos., 107, 4327, https://doi.org/10.1029/2001jd001037, 2002.
Short summary
This article presents an algorithm for cloud detection using TIR radiance spectra based on the CO2 slicing technique for improvement of GHG observation from space. The key techniques of the algorithm are channel reconstruction and their optimization for increasing sensitivity and accuracy. The analysis results using GOSAT data show general agreement with those from CALIPSO. It can be expected that this algorithm would improve the accuracy of cloud screening and gas retrievals from GOSAT data.
This article presents an algorithm for cloud detection using TIR radiance spectra based on the...