Articles | Volume 13, issue 10
Atmos. Meas. Tech., 13, 5481–5490, 2020
https://doi.org/10.5194/amt-13-5481-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 13, 5481–5490, 2020
https://doi.org/10.5194/amt-13-5481-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 14 Oct 2020
Research article | 14 Oct 2020
Inter-calibrating SMMR brightness temperatures over continental surfaces
Samuel Favrichon et al.
Related authors
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
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Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Ronny Meier, Edouard Léopold Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia Isabelle Seneviratne
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-300, https://doi.org/10.5194/gmd-2021-300, 2021
Preprint under review for GMD
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We revise the roughness of the land surface in the climate model CESM. Guided by observational data, we increase the surface roughness of forests and decrease the one of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-315, https://doi.org/10.5194/hess-2021-315, 2021
Preprint under review for HESS
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This study presents a better characterization of surface hydrology variability in the Congo River Basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River Basin annual flood dynamic including its peculiar bi-modal pattern.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Toby Richard Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-109, https://doi.org/10.5194/hess-2021-109, 2021
Revised manuscript under review for HESS
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and nonrandom biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-32, https://doi.org/10.5194/gmd-2021-32, 2021
Revised manuscript accepted for GMD
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Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Lise Kilic, Catherine Prigent, Carlos Jimenez, and Craig Donlon
Ocean Sci., 17, 455–461, https://doi.org/10.5194/os-17-455-2021, https://doi.org/10.5194/os-17-455-2021, 2021
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The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority satellite missions of the Copernicus program within the European Space Agency. It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precisions, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities.
In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Altug Ekici, Hanna Lee, David M. Lawrence, Sean C. Swenson, and Catherine Prigent
Geosci. Model Dev., 12, 5291–5300, https://doi.org/10.5194/gmd-12-5291-2019, https://doi.org/10.5194/gmd-12-5291-2019, 2019
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Ice-rich permafrost thaw can create expanding thermokarst lakes as well as shrinking large wetlands. Such processes can have major biogeochemical implications and feedbacks to climate systems by altering the pathways and rates of permafrost carbon release. We developed a new model parameterization that allows a direct representation of surface water dynamics with subsidence. Our results show increased surface water fractions around western Siberian plains and northeastern territories of Canada.
Lise Kilic, Rasmus Tage Tonboe, Catherine Prigent, and Georg Heygster
The Cryosphere, 13, 1283–1296, https://doi.org/10.5194/tc-13-1283-2019, https://doi.org/10.5194/tc-13-1283-2019, 2019
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In this study, we develop and present simple algorithms to derive the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice. This is achieved using satellite observations collocated with buoy measurements. The errors of the retrieved parameters are estimated and compared with independent data. These parameters are useful for sea ice concentration mapping, understanding sea ice properties and variability, and for atmospheric sounding applications.
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
Short summary
Short summary
Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, https://doi.org/10.5194/hess-22-5341-2018, 2018
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A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Victoria Sol Galligani, Die Wang, Milagros Alvarez Imaz, Paola Salio, and Catherine Prigent
Atmos. Meas. Tech., 10, 3627–3649, https://doi.org/10.5194/amt-10-3627-2017, https://doi.org/10.5194/amt-10-3627-2017, 2017
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Three meteorological events with deep convection and severe weather, characteristic of the SESA region, are considered. High-resolution models, a powerful tool to study convection, can be operated with different microphysics schemes (predict the development of hydrometeors, their interactions, growth, precipitation). We present a systematic evaluation of the microphysical schemes available in the WRF model by a direct comparison between satellite-based simulated and observed microwave radiances.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
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In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
H. Norouzi, M. Temimi, C. Prigent, J. Turk, R. Khanbilvardi, Y. Tian, F. A. Furuzawa, and H. Masunaga
Atmos. Meas. Tech., 8, 1197–1205, https://doi.org/10.5194/amt-8-1197-2015, https://doi.org/10.5194/amt-8-1197-2015, 2015
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-3441-2014, https://doi.org/10.5194/gmdd-7-3441-2014, 2014
Revised manuscript not accepted
I. Pison, B. Ringeval, P. Bousquet, C. Prigent, and F. Papa
Atmos. Chem. Phys., 13, 11609–11623, https://doi.org/10.5194/acp-13-11609-2013, https://doi.org/10.5194/acp-13-11609-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Evaluating the use of Aeolus satellite observations in the regional numerical weather prediction (NWP) model Harmonie–Arome
Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system
Validation of Aeolus winds using ground-based radars in Antarctica and in northern Sweden
Intercomparison review of IPWV retrieved from INSAT-3DR sounder, GNSS and CAMS reanalysis data
Sensitivity of Aeolus HLOS winds to temperature and pressure specification in the L2B processor
Airborne lidar observations of wind, water vapor, and aerosol profiles during the NASA Aeolus calibration and validation (Cal/Val) test flight campaign
Improved method of estimating temperatures at meteor peak heights
Error analyses of a multistatic meteor radar system to obtain a three-dimensional spatial-resolution distribution
Validation of wind measurements of two mesosphere–stratosphere–troposphere radars in northern Sweden and in Antarctica
Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia
A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw
Using machine learning to model uncertainty for water vapor atmospheric motion vectors
Validation of pure rotational Raman temperature data from the Raman Lidar for Meteorological Observations (RALMO) at Payerne
Flywheel calibration of a continuous-wave coherent Doppler wind lidar
Monitoring the TROPOMI-SWIR module instrument stability using desert sites
Validation of the TROPOspheric Monitoring Instrument (TROPOMI) surface UV radiation product
Improvement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var study
Validation of Aeolus wind products above the Atlantic Ocean
Commercial microwave links as a tool for operational rainfall monitoring in Northern Italy
Inter-calibration of nine UV sensing instruments over Antarctica and Greenland since 1980
Validating HY-2A CMR precipitable water vapor using ground-based and shipborne GNSS observations
Retrieval of lower-order moments of the drop size distribution using CSU-CHILL X-band polarimetric radar: a case study
Gradient boosting machine learning to improve satellite-derived column water vapor measurement error
Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record
Consistency and structural uncertainty of multi-mission GPS radio occultation records
First validation of Aeolus wind observations by airborne Doppler wind lidar measurements
Intercomparison of wind observations from the European Space Agency's Aeolus satellite mission and the ALADIN Airborne Demonstrator
Calibration and validation of the Polarimetric Radio Occultation and Heavy Precipitation experiment aboard the PAZ satellite
Automatic quality control of the Meteosat First Generation measurements
Concurrent satellite and ground-based lightning observations from the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency network Meteorage and the SAETTA Lightning Mapping Array (LMA) in the northwestern Mediterranean region
Using ground radar overlaps to verify the retrieval of calibration bias estimates from spaceborne platforms
A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 2: Evaluation over open ocean
On the zero-level offset in the GOSAT TANSO-FTS O2 A band and the quality of solar-induced chlorophyll fluorescence (SIF): comparison of SIF between GOSAT and OCO-2
Evaluation of GPM-DPR precipitation estimates with WegenerNet gauge data
A study of a two-dimensional scanned lunar image for Advanced Technology Microwave Sounder (ATMS) geometric calibration
Multistatic meteor radar observations of gravity-wave–tidal interaction over southern Australia
A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 1: Evaluation over land surfaces using measurements from OMI at 466 nm
Retrieval of convective available potential energy from INSAT-3D measurements: comparison with radiosonde data and their spatial–temporal variations
Lidar temperature series in the middle atmosphere as a reference data set – Part 2: Assessment of temperature observations from MLS/Aura and SABER/TIMED satellites
Potential of INSAT-3D sounder-derived total precipitable water product for weather forecast
Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars
Enhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filter
Rainfall retrieval with commercial microwave links in São Paulo, Brazil
Evaluating two methods of estimating error variances using simulated data sets with known errors
Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign
Inter-channel uniformity of a microwave sounder in space
From model to radar variables: a new forward polarimetric radar operator for COSMO
Evaluating tropospheric humidity from GPS radio occultation, radiosonde, and AIRS from high-resolution time series
Reducing representativeness and sampling errors in radio occultation–radiosonde comparisons
Evaluating the lower-tropospheric COSMIC GPS radio occultation sounding quality over the Arctic
Susanna Hagelin, Roohollah Azad, Magnus Lindskog, Harald Schyberg, and Heiner Körnich
Atmos. Meas. Tech., 14, 5925–5938, https://doi.org/10.5194/amt-14-5925-2021, https://doi.org/10.5194/amt-14-5925-2021, 2021
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In this paper we study the impact of using wind observations from the Aeolus satellite, which provides wind speed profiles globally, in our numerical weather prediction system using a regional model covering the Nordic countries. The wind speed profiles from Aeolus are assimilated by the model, and we see that they have an impact on both the model analysis and forecast, though given the relatively few observations available the impact is often small.
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756, https://doi.org/10.5194/amt-14-5735-2021, https://doi.org/10.5194/amt-14-5735-2021, 2021
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Observation errors (OEs) of radar measurements are correlated. The Desroziers method has been often used to estimate statistics of OE in data assimilation. However, the resulting statistics consist of contributions from different sources and are difficult to interpret. Here, we use an approach based on samples for truncation error to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with OE statistics estimated by the Desroziers method.
Evgenia Belova, Sheila Kirkwood, Peter Voelger, Sourav Chatterjee, Karathazhiyath Satheesan, Susanna Hagelin, Magnus Lindskog, and Heiner Körnich
Atmos. Meas. Tech., 14, 5415–5428, https://doi.org/10.5194/amt-14-5415-2021, https://doi.org/10.5194/amt-14-5415-2021, 2021
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Wind measurements from two radars (ESRAD in Arctic Sweden and MARA at the Indian Antarctic station Maitri) are compared with lidar winds from the ESA satellite Aeolus, for July–December 2019. The aim is to check if Aeolus data processing is adequate for the sunlit conditions of polar summer. Agreement is generally good with bias in Aeolus winds < 1 m/s in most circumstances. The exception is a large bias (7 m/s) when the satellite has crossed a sunlit Antarctic ice cap before passing MARA.
Ramashray Yadav, Ram Kumar Giri, and Virendra Singh
Atmos. Meas. Tech., 14, 4857–4877, https://doi.org/10.5194/amt-14-4857-2021, https://doi.org/10.5194/amt-14-4857-2021, 2021
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We performed an intercomparison of seasonal and annual studies of retrievals of integrated precipitable water vapor (IPWV) carried out by INSAT-3DR satellite-borne infrared radiometer sounding and CAMS reanalysis data with ground-based Indian GNSS data. The magnitude and sign of the bias of INSAT-3DR and CAMS with respect to GNSS IPWV differs from station to station and season to season. A statistical evaluation of the collocated data sets was done to improve day-to-day weather forecasting.
Matic Šavli, Vivien Pourret, Christophe Payan, and Jean-François Mahfouf
Atmos. Meas. Tech., 14, 4721–4736, https://doi.org/10.5194/amt-14-4721-2021, https://doi.org/10.5194/amt-14-4721-2021, 2021
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The ESA's Aeolus satellite wind retrieval is provided through a series of processors. It depends on the temperature and pressure specification, which, however, are not measured by the satellite. The numerical weather predicted values are used instead, but these are erroneous. This article studies the sensitivity of the wind retrieval by introducing errors in temperature and pressure. This has been found to be small for Aeolus but is expected to be more crucial for future missions.
Kristopher M. Bedka, Amin R. Nehrir, Michael Kavaya, Rory Barton-Grimley, Mark Beaubien, Brian Carroll, James Collins, John Cooney, G. David Emmitt, Steven Greco, Susan Kooi, Tsengdar Lee, Zhaoyan Liu, Sharon Rodier, and Gail Skofronick-Jackson
Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, https://doi.org/10.5194/amt-14-4305-2021, 2021
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This paper demonstrates the Doppler Aerosol WiNd (DAWN) lidar and High Altitude Lidar Observatory (HALO) measurement capabilities across a range of atmospheric conditions, compares DAWN and HALO measurements with Aeolus satellite Doppler wind lidar to gain an initial perspective of Aeolus performance, and discusses how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, water vapour, and aerosol profile observations.
Emranul Sarkar, Alexander Kozlovsky, Thomas Ulich, Ilkka Virtanen, Mark Lester, and Bernd Kaifler
Atmos. Meas. Tech., 14, 4157–4169, https://doi.org/10.5194/amt-14-4157-2021, https://doi.org/10.5194/amt-14-4157-2021, 2021
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The biasing effect in meteor radar temperature has been a pressing issue for the last 2 decades. This paper has addressed the underlying reasons for such a biasing effect on both theoretical and experimental grounds. An improved statistical method has been developed which allows atmospheric temperatures at around 90 km to be measured with meteor radar in an independent way such that any subsequent bias correction or calibration is no longer required.
Wei Zhong, Xianghui Xue, Wen Yi, Iain M. Reid, Tingdi Chen, and Xiankang Dou
Atmos. Meas. Tech., 14, 3973–3988, https://doi.org/10.5194/amt-14-3973-2021, https://doi.org/10.5194/amt-14-3973-2021, 2021
Evgenia Belova, Peter Voelger, Sheila Kirkwood, Susanna Hagelin, Magnus Lindskog, Heiner Körnich, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 14, 2813–2825, https://doi.org/10.5194/amt-14-2813-2021, https://doi.org/10.5194/amt-14-2813-2021, 2021
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We validate horizontal wind measurements at altitudes of 0.5–14 km made with atmospheric radars: ESRAD located near Kiruna in the Swedish Arctic and MARA at the Indian research station Maitri in Antarctica, by comparison with radiosondes, the regional model HARMONIE-AROME and the ECMWF ERA5 reanalysis. Good agreement was found in general, and radar bias and uncertainty were estimated. These radars are planned to be used for validation of winds measured by lidar by the ESA satellite Aeolus.
Gizachew Kabite Wedajo, Misgana Kebede Muleta, and Berhan Gessesse Awoke
Atmos. Meas. Tech., 14, 2299–2316, https://doi.org/10.5194/amt-14-2299-2021, https://doi.org/10.5194/amt-14-2299-2021, 2021
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Satellite rainfall estimates (SREs) are alternative data sources for data-scarce basins. However, the accuracy of the products is plagued by multiple sources of errors. Therefore, SREs should be evaluated for particular basins before being used for other applications. The results of the study showed that CHIRPS2 and IMERG6 estimated rainfall and predicted hydrologic simulations well for Dhidhessa River Basin, which shows remote sensing technology could improve hydrologic studies.
Steven Knoop, Fred C. Bosveld, Marijn J. de Haij, and Arnoud Apituley
Atmos. Meas. Tech., 14, 2219–2235, https://doi.org/10.5194/amt-14-2219-2021, https://doi.org/10.5194/amt-14-2219-2021, 2021
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Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few hundred metres or even a few kilometres. Their data can improve weather models and help forecasters. To investigate their accuracy and required meteorological conditions, we have carried out a 2-year measurement campaign of a wind lidar at our Cabauw test site and made a comparison with cup anemometers and wind vanes at several levels in a 213 m tall meteorological mast.
Joaquim V. Teixeira, Hai Nguyen, Derek J. Posselt, Hui Su, and Longtao Wu
Atmos. Meas. Tech., 14, 1941–1957, https://doi.org/10.5194/amt-14-1941-2021, https://doi.org/10.5194/amt-14-1941-2021, 2021
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Wind-tracking algorithms produce atmospheric motion vectors (AMVs) by tracking satellite observations. Accurately characterizing the uncertainties in AMVs is essential in assimilating them into data assimilation models. We develop a machine-learning-based approach for error characterization which involves Gaussian mixture model clustering and random forest using a simulation dataset of water vapor, AMVs, and true winds. We show that our method improves on existing AMV error characterizations.
Giovanni Martucci, Francisco Navas-Guzmán, Ludovic Renaud, Gonzague Romanens, S. Mahagammulla Gamage, Maxime Hervo, Pierre Jeannet, and Alexander Haefele
Atmos. Meas. Tech., 14, 1333–1353, https://doi.org/10.5194/amt-14-1333-2021, https://doi.org/10.5194/amt-14-1333-2021, 2021
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This article presents a validation of 1.5 years of pure rotational temperature data measured by the Raman lidar RALMO installed at the MeteoSwiss station of Payerne. The statistical results are in terms of bias and standard deviation with respect to two well-established radiosounding systems. The statistics are divided into daytime (bias = 0.28 K, SD = 0.62±0.03 K) and nighttime (bias = 0.29 K, SD = 0.66±0.06 K). The lidar temperature profiles are applied to cloud supersaturation studies.
Anders Tegtmeier Pedersen and Michael Courtney
Atmos. Meas. Tech., 14, 889–903, https://doi.org/10.5194/amt-14-889-2021, https://doi.org/10.5194/amt-14-889-2021, 2021
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This paper suggests and describes a method for calibrating wind lidars using a rotating flywheel. An uncertainty analysis shows that a standard uncertainty of 0.1 % can be achieved, with the main contributor being the width of the laser beam which is in agreement with experimental results. The method can potentially lower the calibration uncertainty of wind lidars, which today is often based on cup anemometers, and thus lead to better wind assessments and perhaps more widespread use.
Tim A. van Kempen, Filippo Oggionni, and Richard M. van Hees
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-433, https://doi.org/10.5194/amt-2020-433, 2021
Preprint under review for AMT
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Validation of the instrument stability of the TROPOMI-SWIR module is done by monitoring the a group of very stable and remote locations in the Saharan and Arabian deserts. These confirm the excellent stability and lack of degradation of the TROPOMI-SWIR module derived from the internal calibration sources. The method was done for the first time on a spectrometer in the short-wave infrared and ensures TROPOMI-SWIR can be used for atmospheric research for years to come.
Kaisa Lakkala, Jukka Kujanpää, Colette Brogniez, Nicolas Henriot, Antti Arola, Margit Aun, Frédérique Auriol, Alkiviadis F. Bais, Germar Bernhard, Veerle De Bock, Maxime Catalfamo, Christine Deroo, Henri Diémoz, Luca Egli, Jean-Baptiste Forestier, Ilias Fountoulakis, Katerina Garane, Rosa Delia Garcia, Julian Gröbner, Seppo Hassinen, Anu Heikkilä, Stuart Henderson, Gregor Hülsen, Bjørn Johnsen, Niilo Kalakoski, Angelos Karanikolas, Tomi Karppinen, Kevin Lamy, Sergio F. León-Luis, Anders V. Lindfors, Jean-Marc Metzger, Fanny Minvielle, Harel B. Muskatel, Thierry Portafaix, Alberto Redondas, Ricardo Sanchez, Anna Maria Siani, Tove Svendby, and Johanna Tamminen
Atmos. Meas. Tech., 13, 6999–7024, https://doi.org/10.5194/amt-13-6999-2020, https://doi.org/10.5194/amt-13-6999-2020, 2020
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The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. Ground-based data from 25 sites located in Arctic, subarctic, temperate, equatorial and Antarctic
areas were used for the validation of the TROPOMI surface ultraviolet (UV) radiation product. For most sites 60 %–80 % of TROPOMI data was within ± 20 % of ground-based data.
Pauline Martinet, Domenico Cimini, Frédéric Burnet, Benjamin Ménétrier, Yann Michel, and Vinciane Unger
Atmos. Meas. Tech., 13, 6593–6611, https://doi.org/10.5194/amt-13-6593-2020, https://doi.org/10.5194/amt-13-6593-2020, 2020
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Each year large human and economical losses are due to fog episodes. However, fog forecasts remain quite inaccurate, partly due to a lack of observations in the atmospheric boundary layer. The benefit of ground-based microwave radiometers has been investigated and has demonstrated their capability of significantly improving the initial state of temperature and liquid water content profiles in current numerical weather prediction models, paving the way for improved fog forecasts in the future.
Holger Baars, Alina Herzog, Birgit Heese, Kevin Ohneiser, Karsten Hanbuch, Julian Hofer, Zhenping Yin, Ronny Engelmann, and Ulla Wandinger
Atmos. Meas. Tech., 13, 6007–6024, https://doi.org/10.5194/amt-13-6007-2020, https://doi.org/10.5194/amt-13-6007-2020, 2020
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A first validation for the European satellite Aeolus is presented. Aeolus is the first satellite that can actively measure horizontal wind profiles from space.
Radiosonde launches on board the German research vessel Polarstern have been utilized to validate Aeolus observations over the Atlantic Ocean, a region where almost no other reference measurements are available. It is shown that Aeolus is able to measure accurately atmospheric winds and thus may significantly improve weather forecasts.
Giacomo Roversi, Pier Paolo Alberoni, Anna Fornasiero, and Federico Porcù
Atmos. Meas. Tech., 13, 5779–5797, https://doi.org/10.5194/amt-13-5779-2020, https://doi.org/10.5194/amt-13-5779-2020, 2020
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The microwave signal travelling between two antennas of the commercial mobile backhaul network is strongly attenuated by rainfall. The open-source RAINLINK algorithm extracts rainfall rate maps, processing the attenuation data recorded by the transmission system. In this work, we applied RAINLINK to 357 Vodafone links in northern Italy and compared the outputs with the operational rain products of the local weather service (Arpae), outlining pros and cons and discussing error structure.
Clark J. Weaver, Pawan K. Bhartia, Dong L. Wu, Gordon J. Labow, and David E. Haffner
Atmos. Meas. Tech., 13, 5715–5723, https://doi.org/10.5194/amt-13-5715-2020, https://doi.org/10.5194/amt-13-5715-2020, 2020
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Currently, we do not know whether clouds will accelerate or moderate climate. We look to the past and ask whether cloudiness has changed over the last 4 decades. Using a suite of nine satellite instruments, we need to ensure that the first satellite, which was launched in 1980 and died in 1991, observed the same measurement as the eight other satellite instruments used in the record. If the instruments were measuring length and observing a 1.00 m long stick, they would all see 0.99 to 1.01 m.
Zhilu Wu, Yanxiong Liu, Yang Liu, Jungang Wang, Xiufeng He, Wenxue Xu, Maorong Ge, and Harald Schuh
Atmos. Meas. Tech., 13, 4963–4972, https://doi.org/10.5194/amt-13-4963-2020, https://doi.org/10.5194/amt-13-4963-2020, 2020
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The HY-2A calibration microwave radiometer (CMR) water vapor product is validated using ground-based GNSS observations along the coastline and shipborne GNSS observations over the Indian Ocean. The validation result shows that HY-2A CMR PWV agrees well with ground-based GNSS PWV, with 2.67 mm in rms within 100 km and an RMS of 1.57 mm with shipborne GNSS for the distance threshold of 100 km. Ground-based GNSS and shipborne GNSS agree with HY-2A CMR well.
Viswanathan Bringi, Kumar Vijay Mishra, Merhala Thurai, Patrick C. Kennedy, and Timothy H. Raupach
Atmos. Meas. Tech., 13, 4727–4750, https://doi.org/10.5194/amt-13-4727-2020, https://doi.org/10.5194/amt-13-4727-2020, 2020
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The raindrop size distribution and its moments are fundamental in many areas, such as radar measurement of rainfall using polarimetry and numerical modeling of the microphysical processes of rain formation and evolution. We develop a technique which uses advanced radar measurements and complete drop size distributions using two collocated instruments to retrieve the lower-order moments such as total drop concentration and rain water content. We demonstrate a proof-of-concept using a case study.
Allan C. Just, Yang Liu, Meytar Sorek-Hamer, Johnathan Rush, Michael Dorman, Robert Chatfield, Yujie Wang, Alexei Lyapustin, and Itai Kloog
Atmos. Meas. Tech., 13, 4669–4681, https://doi.org/10.5194/amt-13-4669-2020, https://doi.org/10.5194/amt-13-4669-2020, 2020
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A flexible machine-learning model was fit to explain the differences between estimates of water vapor from satellites versus ground stations in Northeastern USA. We use nine variables derived from the satellite acquisition and ground characteristics to explain this measurement error. Our results showed overall good agreement, but data from the Terra satellite were drifting too high in recent summers. Our model reduces measurement error and works well in new locations in the northeast.
Hans Gleisner, Kent B. Lauritsen, Johannes K. Nielsen, and Stig Syndergaard
Atmos. Meas. Tech., 13, 3081–3098, https://doi.org/10.5194/amt-13-3081-2020, https://doi.org/10.5194/amt-13-3081-2020, 2020
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Data from GPS radio occultation (RO) instruments aboard a series of satellites have been reprocessed by the ROM SAF. We describe the monthly mean RO climate data records (CDRs) and the methods for removing sampling errors. The quality of the CDRs is evaluated, with a focus on systematic differences between satellite missions. Between 8 and 30 km, the data quality and the inter-mission differences are small enough to allow the generation of combined multi-mission data records starting in 2001.
Andrea K. Steiner, Florian Ladstädter, Chi O. Ao, Hans Gleisner, Shu-Peng Ho, Doug Hunt, Torsten Schmidt, Ulrich Foelsche, Gottfried Kirchengast, Ying-Hwa Kuo, Kent B. Lauritsen, Anthony J. Mannucci, Johannes K. Nielsen, William Schreiner, Marc Schwärz, Sergey Sokolovskiy, Stig Syndergaard, and Jens Wickert
Atmos. Meas. Tech., 13, 2547–2575, https://doi.org/10.5194/amt-13-2547-2020, https://doi.org/10.5194/amt-13-2547-2020, 2020
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High-quality observations are critically important for monitoring the Earth’s changing climate. We provide information on the consistency and long-term stability of observations from GPS radio occultation (RO). We assess, for the first time, RO records from multiple RO missions and all major RO data providers. Our results quantify where RO can be used for reliable trend assessment and confirm its climate quality.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, and Fabian Weiler
Atmos. Meas. Tech., 13, 2381–2396, https://doi.org/10.5194/amt-13-2381-2020, https://doi.org/10.5194/amt-13-2381-2020, 2020
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Aeolus, the first ever wind lidar in space, has been providing wind profiles on a global scale since its launch. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (DLR) recently performed two airborne campaigns over central Europe deploying two different Doppler wind lidars. A total of 10 satellite underflights were performed and used to validate the early-stage wind data product of Aeolus by means of collocated airborne wind lidar observations.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, and Oliver Reitebuch
Atmos. Meas. Tech., 13, 2075–2097, https://doi.org/10.5194/amt-13-2075-2020, https://doi.org/10.5194/amt-13-2075-2020, 2020
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This work reports on the first airborne validation campaign of ESA’s Earth Explorer mission Aeolus, conducted in central Europe during the commissioning phase in November 2018. After presenting the methodology used to compare the data sets from the satellite, the airborne wind lidar and the ECWMF model, the wind results from the underflights performed are analyzed and discussed, providing a first assessment of the accuracy and precision of the preliminary Aeolus wind data.
Ramon Padullés, Chi O. Ao, F. Joseph Turk, Manuel de la Torre Juárez, Byron Iijima, Kuo Nung Wang, and Estel Cardellach
Atmos. Meas. Tech., 13, 1299–1313, https://doi.org/10.5194/amt-13-1299-2020, https://doi.org/10.5194/amt-13-1299-2020, 2020
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In this study we thoroughly address the calibration and validation of the new polarimetric radio occultation (PRO) observables. These represent an innovative way to obtain vertical profiles of precipitation along with thermodynamic observations of the same scene. First we perform the on-orbit calibration of the measurement. Then, we show how the PRO observables are sensitive to the presence and intensity of rain by looking for coincident precipitation measurements from independent missions.
Freek Liefhebber, Sarah Lammens, Paul W. G. Brussee, André Bos, Viju O. John, Frank Rüthrich, Jacobus Onderwaater, Michael G. Grant, and Jörg Schulz
Atmos. Meas. Tech., 13, 1167–1179, https://doi.org/10.5194/amt-13-1167-2020, https://doi.org/10.5194/amt-13-1167-2020, 2020
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The paper addresses the need for automatic quality control of a whole series of Earth observation (EO) time series extending a period of over 40 years. Such a dataset is valuable and may provide important information about trends related to geo-physical processes. Furthermore, as the dataset is that large, there is a need to completely automate the processes, as otherwise the effort would become impracticable. The result is a system with a high probability of detection and low false alarm rate.
Felix Erdmann, Eric Defer, Olivier Caumont, Richard J. Blakeslee, Stéphane Pédeboy, and Sylvain Coquillat
Atmos. Meas. Tech., 13, 853–875, https://doi.org/10.5194/amt-13-853-2020, https://doi.org/10.5194/amt-13-853-2020, 2020
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This article compares lightning observations from an optical sensor onboard the International Space Station to two ground-based networks using different radio frequencies. The location and timing of coincident flashes agree well for the three instruments. Differences exist for the detected number of flashes and the characteristics. Small flashes in particular are not always detected by all three instruments. About half of the flashes at altitudes below 10 km are not seen by the satellite sensor.
Irene Crisologo and Maik Heistermann
Atmos. Meas. Tech., 13, 645–659, https://doi.org/10.5194/amt-13-645-2020, https://doi.org/10.5194/amt-13-645-2020, 2020
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Archives of radar observations often suffer from errors, one of which is calibration. However, it is possible to correct them after the fact by using satellite radars as a calibration reference. We propose improvements to this calibration method by considering factors that affect the data quality, such that poor quality data gets filtered out in the bias calculation by assigning weights. We also show that the bias can be interpolated in time even for days when there are no satellite data.
Zachary Fasnacht, Alexander Vasilkov, David Haffner, Wenhan Qin, Joanna Joiner, Nickolay Krotkov, Andrew M. Sayer, and Robert Spurr
Atmos. Meas. Tech., 12, 6749–6769, https://doi.org/10.5194/amt-12-6749-2019, https://doi.org/10.5194/amt-12-6749-2019, 2019
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The anisotropy of Earth's surface reflection plays an important role in satellite-based retrievals of cloud, aerosol, and trace gases. Most current ultraviolet and visible satellite retrievals utilize climatological surface reflectivity databases that do not account for surface anisotropy. The GLER concept was introduced to account for such features. Here we evaluate GLER for water surfaces by comparing with OMI measurements and show that it captures these surface anisotropy features.
Haruki Oshio, Yukio Yoshida, and Tsuneo Matsunaga
Atmos. Meas. Tech., 12, 6721–6735, https://doi.org/10.5194/amt-12-6721-2019, https://doi.org/10.5194/amt-12-6721-2019, 2019
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We investigate the radiance offset in the O2 A band of GOSAT spectrometer and quality of the offset-corrected solar-induced chlorophyll fluorescence (SIF). An analysis of temporal variation of the offset suggests that the radiometric sensitivity of the spectrometer changed after switching the optics path selector in January 2015. Comparisons at multiple spatial scales show good agreement between GOSAT SIF and OCO-2 SIF, which supports the consistency among the present satellite SIF data.
Martin Lasser, Sungmin O, and Ulrich Foelsche
Atmos. Meas. Tech., 12, 5055–5070, https://doi.org/10.5194/amt-12-5055-2019, https://doi.org/10.5194/amt-12-5055-2019, 2019
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This paper evaluates the rain rate estimates from the Global Precipitation Measurement (GPM) mission's radar instrument by comparing them to the data of the WegenerNet, a local-scale high-resolution network of meteorological stations. Our results show that the GPM-DPR estimates basically match with the WegenerNet measurements, but absolute quantities are biased.
Jun Zhou and Hu Yang
Atmos. Meas. Tech., 12, 4983–4992, https://doi.org/10.5194/amt-12-4983-2019, https://doi.org/10.5194/amt-12-4983-2019, 2019
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Evaluating the on-orbit geolocation accuracy of the ATMS is of great importance. The widely used Earth-target-dependent methods are crippled by the strong atmospheric absorption at sounding channels and cloud contamination at window channels. To solve these issues, this study developed a geolocation evaluation algorithm based on a unique 2-D lunar scan dataset captured by the ATMS during a NOAA-20 pitch-over maneuver operation. The results are validated by the coastline inflection point method.
Andrew John Spargo, Iain Murray Reid, and Andrew David MacKinnon
Atmos. Meas. Tech., 12, 4791–4812, https://doi.org/10.5194/amt-12-4791-2019, https://doi.org/10.5194/amt-12-4791-2019, 2019
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We simulate the ability of a recently installed multistation meteor detection radar to measure characteristics of turbulence in the Earth's lower ionosphere. After verifying that it performs reasonably well, we use the radar's data to study an interaction between turbulence and tidal effects. We performed the study because no one has yet applied a multistation radar to this problem before and because multistation radars like this are becoming increasingly common worldwide.
Wenhan Qin, Zachary Fasnacht, David Haffner, Alexander Vasilkov, Joanna Joiner, Nickolay Krotkov, Bradford Fisher, and Robert Spurr
Atmos. Meas. Tech., 12, 3997–4017, https://doi.org/10.5194/amt-12-3997-2019, https://doi.org/10.5194/amt-12-3997-2019, 2019
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Satellite observations depend on Sun and view angles due to anisotropy of the Earth's atmosphere and surface reflection. But most of the ultraviolet and visible cloud, aerosol, and trace-gas algorithms utilize surface reflectivity databases that do not account for surface anisotropy. We create a surface database using the GLER concept which adequately accounts for surface anisotropy, validate it with independent satellite data, and provide a simple implementation to the current algorithms.
Uriya Veerendra Murali Krishna, Subrata Kumar Das, Kizhathur Narasimhan Uma, and Govindan Pandithurai
Atmos. Meas. Tech., 12, 777–790, https://doi.org/10.5194/amt-12-777-2019, https://doi.org/10.5194/amt-12-777-2019, 2019
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Convective available potential energy (CAPE) is an indicator of the occurrence of extreme weather. For the first time over India, this study estimated CAPE from high spatial–temporal resolution measurements of the geostationary satellite, INSAT-3D. INSAT-3D estimates that CAPE reasonably represents the radiosonde CAPE. This study allows the atmospheric science community to select the best available dataset for their use in nowcasting and making severe weather warnings based on numerical models.
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, and Emily M. McCullough
Atmos. Meas. Tech., 11, 6703–6717, https://doi.org/10.5194/amt-11-6703-2018, https://doi.org/10.5194/amt-11-6703-2018, 2018
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We have compared 2433 nights of OHP lidar temperatures (2002–2018) to temperatures derived from the satellites SABER and MLS. We have found a winter stratopause cold bias in the satellite measurements with respect to the lidar (−6 K for SABER and −17 K for MLS), a summer mesospheric warm bias for SABER (6 K near 60 km), and a vertically structured bias for MLS (−4 to 4 K). We have corrected the satellite data based on the lidar-determined stratopause height and found a significant improvement.
Shailesh Parihar, Ashim Kumar Mitra, Mrutyunjay Mohapatra, and Rajjev Bhatla
Atmos. Meas. Tech., 11, 6003–6012, https://doi.org/10.5194/amt-11-6003-2018, https://doi.org/10.5194/amt-11-6003-2018, 2018
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This paper is based on operational work carried out at IMD, New Delhi using the INSAT-3D satellite-derived sounder product TPW for weather events such as rainfall and thunderstorms. The INSAT-3D TPW has been used by forecasters as well as many other users over the last 2 years. This work mainly brings out an in-depth validation with in situ ground measurement data as well as a GNSS system for its suitability in weather prediction. This paper can be utilized operationally for weather purposes.
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, Emily M. McCullough, Jean-François Mariscal, and Éric d'Almeida
Atmos. Meas. Tech., 11, 5531–5547, https://doi.org/10.5194/amt-11-5531-2018, https://doi.org/10.5194/amt-11-5531-2018, 2018
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The objective of this work is to minimize the errors at the highest altitudes of a lidar temperature profile which arise due to background estimation and a priori choice. The systematic method in this paper has the effect of cooling the temperatures at the top of a lidar profile by up to 20 K – bringing them into better agreement with satellite temperatures. Following the description of the algorithm is a 20-year cross-validation of two lidars which establishes the stability of the technique.
Irene Crisologo, Robert A. Warren, Kai Mühlbauer, and Maik Heistermann
Atmos. Meas. Tech., 11, 5223–5236, https://doi.org/10.5194/amt-11-5223-2018, https://doi.org/10.5194/amt-11-5223-2018, 2018
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The calibration of ground-based weather radar (GR) can be improved a posteriori by comparing observed GR reflectivity to well-established spaceborne radar platforms (SR), such as TRMM or GPM. Our study shows that the consistency between GR and SR reflectivity measurements can be enhanced by considering the quality of GR data from areas where signals may have been blocked due to the surrounding terrain, and provides an open-source toolset to carry out corresponding analyses.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476, https://doi.org/10.5194/amt-11-4465-2018, https://doi.org/10.5194/amt-11-4465-2018, 2018
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Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
Therese Rieckh and Richard Anthes
Atmos. Meas. Tech., 11, 4309–4325, https://doi.org/10.5194/amt-11-4309-2018, https://doi.org/10.5194/amt-11-4309-2018, 2018
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We compare the two-cornered hat (2CH) and three-cornered hat (3CH) method for estimating the error variances of two or more independent data sets using simulated data with various error correlations and biases.
We assess the accuracy of the 3CH and 2CH estimates and examine the sensitivity of the estimated error variances to the degree of error correlation between the data sets as well as sample size. The 3CH method is less sensitive to these factors and hence more accurate.
Nicola Bodini, Julie K. Lundquist, and Rob K. Newsom
Atmos. Meas. Tech., 11, 4291–4308, https://doi.org/10.5194/amt-11-4291-2018, https://doi.org/10.5194/amt-11-4291-2018, 2018
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Turbulence within the atmospheric boundary layer is critically important to transfer heat, momentum, and moisture. Currently, improved turbulence parametrizations are crucially needed to refine the accuracy of model results at fine horizontal scales. In this study, we calculate turbulence dissipation rate from sonic anemometers and discuss a novel approach to derive turbulence dissipation from profiling lidar measurements.
Martin Burgdorf, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 4005–4014, https://doi.org/10.5194/amt-11-4005-2018, https://doi.org/10.5194/amt-11-4005-2018, 2018
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We analysed observations of the Moon with the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite in order to search for bias in the sounding channels. Significant bias had been detected in the past on the basis of simultaneous nadir overpasses. With the Moon providing a quite different reference flux than the on-board calibration target and Earth scenes, radio-frequency interference emerged as the best explanation for the anomalies of channel 20 of AMSU-B on NOAA-16.
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018, https://doi.org/10.5194/amt-11-3883-2018, 2018
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This work presents a polarimetric forward operator for the COSMO weather prediction model. This tool is able to simulate radar observables from the state of the atmosphere simulated by the model, taking into account most physical aspects of radar beam propagation and backscattering. This operator was validated with a large dataset of radar observations from several instruments and it was shown that is able to simulate a realistic radar signature in liquid precipitation.
Therese Rieckh, Richard Anthes, William Randel, Shu-Peng Ho, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 3091–3109, https://doi.org/10.5194/amt-11-3091-2018, https://doi.org/10.5194/amt-11-3091-2018, 2018
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Water vapor is the most important tropospheric greenhouse gas and is also highly variable in space and time. We study the vertical structure and variability of tropospheric humidity using various observing techniques (GPS radio occultation, radiosondes, Atmospheric Infrared Sounder) and models. Time–height cross sections reveal seasonal biases for different pressure layers. We find that radio occultation humidity has high accuracy and can contribute valuable information in data assimilation.
Shay Gilpin, Therese Rieckh, and Richard Anthes
Atmos. Meas. Tech., 11, 2567–2582, https://doi.org/10.5194/amt-11-2567-2018, https://doi.org/10.5194/amt-11-2567-2018, 2018
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Comparing observational systems when observations are not taken at the exact same time or location can introduce sampling errors that can be come significant during error analysis. In this study, we develop two methods to reduce sampling errors: using ellipse distance constraints rather than circles and subtracting model background. We found that both the ellipses and subtracting model background from
the observations reduce sampling errors caused by spatial and temporal differences.
Xiao Yu, Feiqin Xie, and Chi O. Ao
Atmos. Meas. Tech., 11, 2051–2066, https://doi.org/10.5194/amt-11-2051-2018, https://doi.org/10.5194/amt-11-2051-2018, 2018
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Atmospheric observations from GPS receiver satellites offer uniform spatial coverage over the Arctic. The GPS profiles sensing deep into the lowest 300 m of the atmosphere only reach 50–60 % in summer but over 70 % in other seasons. The profile uncertainty due to different data centers is within 0.07 % in refractivity, 0.72 K in temperature, and 0.05 g kg-1 in humidity below 10 km. A systematic negative bias of 1 % in refractivity below 2 km is only seen in the summer due to moisture impact.
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Short summary
Long-term monitoring of satellite-derived variables is necessary for a better understanding of the evolution of Earth parameters at global scale. However different instruments' observations used over the years need to be inter-calibrated with each other to provide meaningful information. This paper describes how a linear correction can improve the observations from the Scanning Multichannel Microwave Radiometer over continental surfaces to be more consistent with more recent radiometers.
Long-term monitoring of satellite-derived variables is necessary for a better understanding of...
