Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1793-2018
© Author(s) 2018. 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-11-1793-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Mar 2018
Research article |
| 29 Mar 2018
Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters
Julian Liman
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Karsten Fennig
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Axel Andersson
Marine Data Centre, Deutscher Wetterdienst, Bernhard-Nocht-Straße 76, 20359 Hamburg, Germany
Rainer Hollmann
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Related authors
Karl Bumke, Gert König-Langlo, Julian Kinzel, and Marc Schröder
Atmos. Meas. Tech., 9, 2409–2423, https://doi.org/10.5194/amt-9-2409-2016, https://doi.org/10.5194/amt-9-2409-2016, 2016
Short summary
Short summary
Satellite-derived HOAPS and ERA-Interim reanalysis data were validated against shipboard precipitation measurements. Results show that HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially at low latitudes. However, HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide precipitation rate is close to measurements. ERA-Interim strongly overestimates it in the intertropical convergence zone and southern subtropics.
Hannes Konrad, Rémy Roca, Anja Niedorf, Stephan Finkensieper, Marc Schröder, Sophie Cloché, Giulia Panegrossi, Paolo Sanò, Christopher Kidd, Rômulo Augusto Jucá Oliveira, Karsten Fennig, Thomas Sikorski, Madeleine Lemoine, and Rainer Hollmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-568, https://doi.org/10.5194/essd-2024-568, 2025
Preprint under review for ESSD
Short summary
Short summary
GIRAFE v1 is a global satellite-based precipitation dataset covering 2002 to 2022. It combines high-accuracy microwave and high-resolution infrared observations for retrieving daily precipitation, a respective sampling uncertainty for a more robust analysis, and monthly means. It is intended and suitable for climate monitoring and research, allowing also studies for water management, agriculture, and disaster risk reduction. A continuous extension from 2023 onwards will be implemented in 2025.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
Short summary
Short summary
The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
Short summary
Short summary
This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
Short summary
Short summary
This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
Short summary
Short summary
Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
Short summary
Short summary
Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
Short summary
Short summary
The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Caroline A. Poulsen, Gregory R. McGarragh, Gareth E. Thomas, Martin Stengel, Matthew W. Christensen, Adam C. Povey, Simon R. Proud, Elisa Carboni, Rainer Hollmann, and Roy G. Grainger
Earth Syst. Sci. Data, 12, 2121–2135, https://doi.org/10.5194/essd-12-2121-2020, https://doi.org/10.5194/essd-12-2121-2020, 2020
Short summary
Short summary
We have created a satellite cloud and radiation climatology from the ATSR-2 and AATSR on board ERS-2 and Envisat, respectively, which spans the period 1995–2012. The data set was created using a combination of optimal estimation and neural net techniques. The data set was created as part of the ESA Climate Change Initiative program. The data set has been compared with active CALIOP lidar measurements and compared with MAC-LWP AND CERES-EBAF measurements and is shown to have good performance.
Karsten Fennig, Marc Schröder, Axel Andersson, and Rainer Hollmann
Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, https://doi.org/10.5194/essd-12-647-2020, 2020
Short summary
Short summary
A Fundamental Climate Data Record (FCDR) from satellite-borne microwave radiometers has been created, covering the time period from October 1978 to December 2015. This article describes how the observations are processed, calibrated, corrected, inter-calibrated, and evaluated in order to provide a homogeneous data record of brightness temperatures across 10 different instruments aboard three different satellite platforms.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Stephan Finkensieper, Benjamin Würzler, Daniel Philipp, Rainer Hollmann, Caroline Poulsen, Matthew Christensen, and Gregory McGarragh
Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, https://doi.org/10.5194/essd-12-41-2020, 2020
Short summary
Short summary
The Cloud_cci AVHRR-PMv3 dataset contains global, cloud and radiative flux properties covering the period of 1982 to 2016. The properties were retrieved from AVHRR measurements recorded by afternoon satellites of the NOAA POES missions. Validation against CALIOP, BSRN and CERES demonstrates the high quality of the data. The Cloud_cci AVHRR-PMv3 dataset allows for a large variety of climate applications that build on cloud properties, radiative flux properties and/or the link between them.
Soheila Jafariserajehlou, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann
Atmos. Meas. Tech., 12, 1059–1076, https://doi.org/10.5194/amt-12-1059-2019, https://doi.org/10.5194/amt-12-1059-2019, 2019
Short summary
Short summary
We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B.
The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.
Rita Glowienka-Hense, Andreas Hense, Thomas Spangehl, and Marc Schröder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-141, https://doi.org/10.5194/gmd-2018-141, 2018
Revised manuscript not accepted
Short summary
Short summary
Ensemble forecast verification treats the issues of forecast errors and uncertainty estimated from ensemble spread. We suggest measures based on relative entropy. For continuous variables correlation and the mean ratio of the ensemble spread to climate variance (analysis of variance (anova)) are related to these entropies. For categorical data corresponding scores are deduced that allow the comparison with continuous data.
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/10.5194/essd-10-1093-2018, https://doi.org/10.5194/essd-10-1093-2018, 2018
Short summary
Short summary
This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
Gregory R. McGarragh, Caroline A. Poulsen, Gareth E. Thomas, Adam C. Povey, Oliver Sus, Stefan Stapelberg, Cornelia Schlundt, Simon Proud, Matthew W. Christensen, Martin Stengel, Rainer Hollmann, and Roy G. Grainger
Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018, https://doi.org/10.5194/amt-11-3397-2018, 2018
Short summary
Short summary
Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Oliver Sus, Martin Stengel, Stefan Stapelberg, Gregory McGarragh, Caroline Poulsen, Adam C. Povey, Cornelia Schlundt, Gareth Thomas, Matthew Christensen, Simon Proud, Matthias Jerg, Roy Grainger, and Rainer Hollmann
Atmos. Meas. Tech., 11, 3373–3396, https://doi.org/10.5194/amt-11-3373-2018, https://doi.org/10.5194/amt-11-3373-2018, 2018
Short summary
Short summary
This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
Uwe Pfeifroth, Jedrzej S. Bojanowski, Nicolas Clerbaux, Veronica Manara, Arturo Sanchez-Lorenzo, Jörg Trentmann, Jakub P. Walawender, and Rainer Hollmann
Adv. Sci. Res., 15, 31–37, https://doi.org/10.5194/asr-15-31-2018, https://doi.org/10.5194/asr-15-31-2018, 2018
Short summary
Short summary
Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. Trends in EUMETSAT CM SAF satellite-based climate data records of solar radiation and clouds are analysed during 1992–2015 in Europe. More surface solar radiation and less top-of-atmosphere reflected radiation and cloud cover is found. This study indicates that one of the main reasons for the positive trend in surface solar radiation is a decrease in cloud cover.
Steffen Beirle, Johannes Lampel, Yang Wang, Kornelia Mies, Steffen Dörner, Margherita Grossi, Diego Loyola, Angelika Dehn, Anja Danielczok, Marc Schröder, and Thomas Wagner
Earth Syst. Sci. Data, 10, 449–468, https://doi.org/10.5194/essd-10-449-2018, https://doi.org/10.5194/essd-10-449-2018, 2018
Short summary
Short summary
We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting
Climateproduct allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl-Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf Bennartz, Jedrzej S. Bojanowski, and Rainer Hollmann
Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, https://doi.org/10.5194/essd-9-881-2017, 2017
Short summary
Short summary
We present new cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS. Retrieval systems were developed that include cloud detection and cloud typing followed by optimal estimation retrievals of cloud properties (e.g. cloud-top pressure, effective radius, optical thickness, water path). Special features of all datasets are spectral consistency and rigorous uncertainty propagation from pixel-level data to monthly properties.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
Short summary
Short summary
Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Nikos Benas, Stephan Finkensieper, Martin Stengel, Gerd-Jan van Zadelhoff, Timo Hanschmann, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 9, 415–434, https://doi.org/10.5194/essd-9-415-2017, https://doi.org/10.5194/essd-9-415-2017, 2017
Short summary
Short summary
This study focuses on an evaluation of CLAAS-2 (Cloud property dAtAset using SEVIRI, Edition 2), which was created based on observations from geostationary Meteosat satellites. Using a variety of reference datasets, very good overall agreement is found. This suggests the usefulness of CLAAS-2 in applications ranging from high spatial and temporal resolution cloud process studies to the evaluation of regional climate models.
Karl-Göran Karlsson, Kati Anttila, Jörg Trentmann, Martin Stengel, Jan Fokke Meirink, Abhay Devasthale, Timo Hanschmann, Steffen Kothe, Emmihenna Jääskeläinen, Joseph Sedlar, Nikos Benas, Gerd-Jan van Zadelhoff, Cornelia Schlundt, Diana Stein, Stefan Finkensieper, Nina Håkansson, and Rainer Hollmann
Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, https://doi.org/10.5194/acp-17-5809-2017, 2017
Short summary
Short summary
The paper presents the second version of a global climate data record based on satellite measurements from polar orbiting weather satellites. It describes the global evolution of cloudiness, surface albedo and surface radiation during the time period 1982–2015. The main improvements of algorithms are described together with some validation results. In addition, some early analysis is presented of some particularly interesting climate features (Arctic albedo and cloudiness + global cloudiness).
Ralf Bennartz, Heidrun Höschen, Bruno Picard, Marc Schröder, Martin Stengel, Oliver Sus, Bojan Bojkov, Stefano Casadio, Hannes Diedrich, Salomon Eliasson, Frank Fell, Jürgen Fischer, Rainer Hollmann, Rene Preusker, and Ulrika Willén
Atmos. Meas. Tech., 10, 1387–1402, https://doi.org/10.5194/amt-10-1387-2017, https://doi.org/10.5194/amt-10-1387-2017, 2017
Short summary
Short summary
The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
Karl Bumke, Gert König-Langlo, Julian Kinzel, and Marc Schröder
Atmos. Meas. Tech., 9, 2409–2423, https://doi.org/10.5194/amt-9-2409-2016, https://doi.org/10.5194/amt-9-2409-2016, 2016
Short summary
Short summary
Satellite-derived HOAPS and ERA-Interim reanalysis data were validated against shipboard precipitation measurements. Results show that HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially at low latitudes. However, HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide precipitation rate is close to measurements. ERA-Interim strongly overestimates it in the intertropical convergence zone and southern subtropics.
N. Courcoux and M. Schröder
Earth Syst. Sci. Data, 7, 397–414, https://doi.org/10.5194/essd-7-397-2015, https://doi.org/10.5194/essd-7-397-2015, 2015
Short summary
Short summary
Despite its great importance for the climate, the behaviour and content of water vapour in the troposphere is insufficiently known. The ATOVS instruments onboard polar-orbiting satellites allow the retrieval of water vapour at different altitudes and on global scale. Here a consistent reprocessing of water vapour products derived from the ATOVS instrument from 1999 to 2011 is presented and compared to time series derived from other instruments. The data are freely available at www.cmsaf.eu/wui.
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148, https://doi.org/10.5194/acp-14-11129-2014, https://doi.org/10.5194/acp-14-11129-2014, 2014
R. Lindstrot, M. Stengel, M. Schröder, J. Fischer, R. Preusker, N. Schneider, T. Steenbergen, and B. R. Bojkov
Earth Syst. Sci. Data, 6, 221–233, https://doi.org/10.5194/essd-6-221-2014, https://doi.org/10.5194/essd-6-221-2014, 2014
M. Stengel, A. Kniffka, J. F. Meirink, M. Lockhoff, J. Tan, and R. Hollmann
Atmos. Chem. Phys., 14, 4297–4311, https://doi.org/10.5194/acp-14-4297-2014, https://doi.org/10.5194/acp-14-4297-2014, 2014
A. Kniffka, M. Stengel, M. Lockhoff, R. Bennartz, and R. Hollmann
Atmos. Meas. Tech., 7, 887–905, https://doi.org/10.5194/amt-7-887-2014, https://doi.org/10.5194/amt-7-887-2014, 2014
K. Schamm, M. Ziese, A. Becker, P. Finger, A. Meyer-Christoffer, U. Schneider, M. Schröder, and P. Stender
Earth Syst. Sci. Data, 6, 49–60, https://doi.org/10.5194/essd-6-49-2014, https://doi.org/10.5194/essd-6-49-2014, 2014
B. Dürr, M. Schröder, R. Stöckli, and R. Posselt
Atmos. Meas. Tech., 6, 1883–1901, https://doi.org/10.5194/amt-6-1883-2013, https://doi.org/10.5194/amt-6-1883-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
M. Schröder, M. Jonas, R. Lindau, J. Schulz, and K. Fennig
Atmos. Meas. Tech., 6, 765–775, https://doi.org/10.5194/amt-6-765-2013, https://doi.org/10.5194/amt-6-765-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Comparison of temperature and wind profiles between ground-based remote sensing observations and numerical weather prediction model in complex Alpine topography: the Meiringen campaign
Cluster analysis of vertical polarimetric radio occultation profiles and corresponding liquid and ice water paths from Global Precipitation Measurement (GPM) microwave data
Enhanced quantitative precipitation estimation through the opportunistic use of Ku TV-SAT links via a dual-channel procedure
The added value and potential of long-term radio occultation data for climatological wind field monitoring
Exploring dual-lidar mean and turbulence measurements over Perdigão's complex terrain
Description and validation of the Japanese algorithm for radiative flux and heating rate products with all four EarthCARE instruments: pre-launch test with A-Train
Atmospheric stability from microwave radiometer observations for on/offshore wind energy applications
Improving the estimate of higher-order moments from lidar observations near the top of the convective boundary layer
Turbulence kinetic energy dissipation rate estimated from a WindCube Doppler Lidar and the LQ7 1.3 GHz radar wind profiler in the convective boundary layer
Research on Atmospheric Temperature Fine Measurements from near surface to 60 km Altitude Based on An Integrated LIDAR System
Quality Assessment of YUNYAO GNSS-RO Refractivity Data in the Neutral Atmosphere
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the Equator
Verification of weather-radar-based hail metrics with crowdsourced observations from Switzerland
Observing atmospheric rivers using GNSS radio occultation data
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Exploring commercial GNSS RO products for Planetary Boundary Layer studies in the Arctic Region
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Solar Background Radiation Temperature Calibration of a Pure Rotational Raman Lidar
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
Verification of parameterizations for clear sky downwelling longwave irradiance in the Arctic
Global evaluation of fast radiative transfer model coefficients for early meteorological satellite sensors
GPROF V7 and beyond: assessment of current and potential future versions of the GPROF passive microwave precipitation retrievals against ground radar measurements over the continental US and the Pacific Ocean
Assessing sampling and retrieval errors of GPROF precipitation estimates over the Netherlands
Comparisons and quality control of wind observations in a mountainous city using wind profile radar and the Aeolus satellite
On the use of routine airborne observations for evaluation and monitoring of satellite observations of thermodynamic profiles
Daily satellite-based sunshine duration estimates over Brazil: validation and intercomparison
Statistical assessment of a Doppler radar model of TKE dissipation rate for low Richardson numbers
Testing ground based observations of wave activity in the (lower and upper) atmosphere as possible (complementary) indicators of streamer events
Extended validation of Aeolus winds with wind-profiling radars in Antarctica and Arctic Sweden
The impact of Aeolus winds on near-surface wind forecasts over tropical ocean and high-latitude regions
Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile, and Leipzig, Germany
Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements
The impacts of assimilating Aeolus horizontal line-of-sight winds on numerical predictions of Hurricane Ida (2021) and a mesoscale convective system over the Atlantic Ocean
Evaluation of tropospheric water vapour and temperature profiles retrieved from MetOp-A by the Infrared and Microwave Sounding scheme
Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics
An improved vertical correction method for the inter-comparison and inter-validation of integrated water vapour measurements
An assessment of reprocessed GPS/MET observations spanning 1995–1997
Turbulence parameters measured by the Beijing mesosphere–stratosphere–troposphere radar in the troposphere and lower stratosphere with three models: comparison and analyses
Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data
Behavior and mechanisms of Doppler wind lidar error in varying stability regimes
Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1
Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia
Comparison of global UV spectral irradiance measurements between a BTS CCD-array and a Brewer spectroradiometer
Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty
Modelling the spectral shape of continuous-wave lidar measurements in a turbulent wind tunnel
Three-way calibration checks using ground-based, ship-based, and spaceborne radars
Rainfall retrieval algorithm for commercial microwave links: stochastic calibration
Alexandre Bugnard, Martine Collaud Coen, Maxime Hervo, Daniel Leuenberger, Marco Arpagaus, and Samuel Monhart
Atmos. Meas. Tech., 18, 1039–1061, https://doi.org/10.5194/amt-18-1039-2025, https://doi.org/10.5194/amt-18-1039-2025, 2025
Short summary
Short summary
Temperature (T) and wind profiles were measured by a Doppler wind lidar and a microwave radiometer in Meiringen in a medium-sized Alpine valley. Ground-based T inversions and thermal winds were studied during the 10 months of the campaign. The comparison between the observations and the COSMO-1E model provides good model performance for monthly climatologies. T inversions are however frequently missed, and important differences for particular cases are found, especially for foehn events.
Jonas E. Katona, Manuel de la Torre Juárez, Terence L. Kubar, F. Joseph Turk, Kuo-Nung Wang, and Ramon Padullés
Atmos. Meas. Tech., 18, 953–970, https://doi.org/10.5194/amt-18-953-2025, https://doi.org/10.5194/amt-18-953-2025, 2025
Short summary
Short summary
Polarimetric radio occultations (PROs) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over 2 years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).
Louise Gelbart, Laurent Barthès, François Mercier-Tigrine, Aymeric Chazottes, and Cécile Mallet
Atmos. Meas. Tech., 18, 351–370, https://doi.org/10.5194/amt-18-351-2025, https://doi.org/10.5194/amt-18-351-2025, 2025
Short summary
Short summary
In this paper, we present and evaluate a new method for the quantitative estimation of precipitation from a low-cost sensor. Based on previous work measuring the attenuation of an electromagnetic signal from a broadcast television satellite, we make this approach more accurate so it can be easily deployed and used operationally in areas where rainfall measurements are critical for applications like flood monitoring. In this article, the method is validated in France and applied in Côte d'Ivoire.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech., 18, 265–286, https://doi.org/10.5194/amt-18-265-2025, https://doi.org/10.5194/amt-18-265-2025, 2025
Short summary
Short summary
Due to the shortcomings of available observations, having accurate global 3D wind fields remains a challenge. A promising option is radio occultation (RO) satellite data, which enable the derivation of winds based on wind approximations. We test how well RO winds describe the ERA5 winds. We separate the total wind difference into the approximation bias and the systematic difference between the two datasets. The results show the utility of RO winds for climate monitoring and analyses.
Isadora L. Coimbra, Jakob Mann, José M. L. M. Palma, and Vasco T. P. Batista
Atmos. Meas. Tech., 18, 287–303, https://doi.org/10.5194/amt-18-287-2025, https://doi.org/10.5194/amt-18-287-2025, 2025
Short summary
Short summary
Dual-lidar measurements are explored here as a cost-effective alternative for measuring the wind at great heights. From measurements at a mountainous site, we showed that this methodology can accurately capture mean wind speeds and turbulence under different flow conditions, and we recommended optimal lidar placement and sampling rates. This methodology allows the construction of vertical wind profiles up to 430 m, surpassing traditional meteorological mast heights and single-lidar capabilities.
Akira Yamauchi, Kentaroh Suzuki, Eiji Oikawa, Miho Sekiguchi, Takashi M. Nagao, and Haruma Ishida
Atmos. Meas. Tech., 17, 6751–6767, https://doi.org/10.5194/amt-17-6751-2024, https://doi.org/10.5194/amt-17-6751-2024, 2024
Short summary
Short summary
A Japanese team developed the Level 2 atmospheric radiation flux and heating rate product for EarthCARE, which offers vertical profiles of longwave and shortwave radiative fluxes and heating rates. This study outlines the algorithm for the radiative product and its comparative validation against satellite and ground-based observations. It also analyzes errors in radiative fluxes at various scales and their dependence on cloud type, with ice-containing clouds identified as a primary error source.
Domenico Cimini, Rémi Gandoin, Stephanie Fiedler, Claudia Acquistapace, Andrea Balotti, Sabrina Gentile, Edoardo Geraldi, Christine Knist, Pauline Martinet, Saverio T. Nilo, Giandomenico Pace, Bernhard Pospichal, and Filomena Romano
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-186, https://doi.org/10.5194/amt-2024-186, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Atmospheric stability indicates whether air vertical motion is dumped or amplified. This is important for wind energy applications as it affects wind turbine wakes and thus the yield of wind parks. The paper provides an assessment of stability metrics measured by ground-based microwave radiometers in different climatological conditions and with instrument types, on- and offshore. Results indicate that special precaution may be required offshore to achieve typical onshore performances.
Tessa E. Rosenberger, David D. Turner, Thijs Heus, Girish N. Raghunathan, Timothy J. Wagner, and Julia Simonson
Atmos. Meas. Tech., 17, 6595–6602, https://doi.org/10.5194/amt-17-6595-2024, https://doi.org/10.5194/amt-17-6595-2024, 2024
Short summary
Short summary
This work used model output to show that considering the changes in boundary layer depth over time in the calculations of variables such as fluxes and variance yields more accurate results than cases where calculations were done at a constant height. This work was done to improve future observations of these variables at the top of the boundary layer.
Hubert Luce and Masanori Yabuki
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-111, https://doi.org/10.5194/amt-2024-111, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
For around 3 weeks, simultaneous measurements were carried out with a Doppler lidar and a UHF wind profiler at the Shigaraki MU observatory, Japan. Despite the lack of range overlap between the instruments, the turbulence kinetic energy dissipation rate was estimated from both measurements using different methods in convective boundary layers. Hourly averaged estimates compare well (within a factor of ~2), indicating that instruments and methods provide consistent values of dissipation rates.
Zhangjun Wang, Tiantian Guo, Xianxin Li, Chao Chen, Dong Liu, Luoyuan Qu, Hui Li, and Xiufen Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2647, https://doi.org/10.5194/egusphere-2024-2647, 2024
Short summary
Short summary
A dual-field, integrated lidar system has been developed to detect atmospheric temperatures from near surface to 60 km over Qingdao, China. Temperature profiles from near surface to 60 km are derived by pure rotational Raman and Rayleigh scattering techniques using a single integrated lidar system. The results prove the system can make fine measurements of the atmospheric temperature profiles from near surface to 60 km.
Xiaoze Xu, Wei Han, Jincheng Wang, Zhiqiu Gao, Fenghui Li, Yan Cheng, and Naifeng Fu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-150, https://doi.org/10.5194/amt-2024-150, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Commercial GNSS-RO satellites are generally low-cost and can generate a large volume of globally distributed observations in a short period of time. To evaluate the practical application value of these data, it is necessary to assess their quality. This study evaluates the refractivity profile data quality from 8 YUNYAO satellites. By using the "three-cornered hat" (3CH) method and comparing with data from Metop-C and COSMIC-2, it was found that the YUNYAO GNSS-RO data has high data quality.
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024, https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Short summary
We investigated the potential of radio occultation (RO) data for climate-oriented wind field monitoring, focusing on the equatorial band within ±5° latitude. In this region, the geostrophic balance breaks down, and the equatorial balance approximation takes over. The study encourages the use of RO wind fields for mesoscale climate monitoring for the equatorial region, showing a small improvement in the troposphere when including the meridional wind in the zonal-mean total wind speed.
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024, https://doi.org/10.5194/amt-17-4529-2024, 2024
Short summary
Short summary
We present a verification of two products based on weather radars to detect the presence of hail and estimate its size. Radar products are remote detection of hail, so they must be verified against ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated and that estimating the hail size with radar is more challenging.
Bahareh Rahimi and Ulrich Foelsche
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-81, https://doi.org/10.5194/amt-2024-81, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study explores the use of GNSS-RO data to improve understanding of the vertical structure of humidity in Atmospheric Rivers (ARs). Specific humidity profiles and IWV values from GNSS-RO are evaluated to assess if this method offers additional insights into ARs' vertical characteristics. The results suggest that combining GNSS-RO data, with its high vertical resolution, with SSMI/S data, known for high horizontal resolution, provides a more complete view of the 3D structure of ARs.
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024, https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Short summary
Accurate global wind estimation is crucial for weather prediction and environmental modeling. Our study investigates a method to refine atmospheric motion vectors (AMVs) by comparing them with high-precision active-sensor winds. Leveraging supervised learning, we discovered that using high-precision active-sensor data can significantly reduce biases in passive-sensor winds in addition to providing estimates of the wind errors, thereby improving their reliability.
Manisha Ganeshan, Dong L. Wu, Joseph A. Santanello, Jie Gong, Chi O. Ao, Panagiotis Vergados, and Kevin Nelson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-83, https://doi.org/10.5194/amt-2024-83, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study explores the potential of two newly launched commercial GNSS RO satellite missions for advancing Arctic lower atmospheric studies. The products have a good sampling of the lower Arctic atmosphere, and are useful to derive the planetary boundary layer (PBL) height during winter months. This research is a step towards closing the observation gap in polar regions due to the decomissioning of COSMIC-1 GNSS RO mission, and the lack of high latitude coverage by its successor (COSMIC-2).
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024, https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Short summary
Three-dimensional wind fields can be accurately measured by sonic anemometers. However, the traditional mast-mounted sonic anemometers are not flexible in various applications, which can be potentially overcome by drones. Therefore, we conducted a proof-of-concept study by applying three continuous-wave Doppler lidars to characterize the complex flow around a drone to validate the results obtained by CFD simulations. Both methods show good agreement, with a velocity difference of 0.1 m s-1.
Vasura Jayaweera, Robert J. Sica, Giovanni Martucci, and Alexander Haefele
EGUsphere, https://doi.org/10.5194/egusphere-2024-1081, https://doi.org/10.5194/egusphere-2024-1081, 2024
Short summary
Short summary
Our study presents a new method, the solar background calibration method, which improves temperature determinations in rotational Raman lidar systems. By utilizing backgrounds solar radiation, this technique offers more continuous and reliable temperatures independent of external measuring instruments. This new method enhances our ability to monitor and understand atmospheric trends and their association to climate change with greater accuracy.
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464, https://doi.org/10.5194/amt-17-2451-2024, https://doi.org/10.5194/amt-17-2451-2024, 2024
Short summary
Short summary
The use of sodar data to support an air quality forecasting system is encouraging.
The sodar model is a complement to forecasting methods because it is useful due to its simplicity and speed of calculations. It does not require emission data, for which it is difficult to quickly verify temporal and spatial variability.
The use of simple formulas of regression models in forecasting, while maintaining their multivariate nature, facilitates the optimisation of the prediction process.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024, https://doi.org/10.5194/amt-17-2219-2024, 2024
Short summary
Short summary
We conducted a radiance closure experiment using a unique combination of two hyperspectral radiometers, one operating in the microwave and the other in the infrared. By comparing the measurements of the two hyperspectrometers to synthetic radiance simulated from collocated atmospheric profiles, we affirmed the proper performance of the two instruments and quantified their radiometric uncertainty for atmospheric sounding applications.
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877, https://doi.org/10.5194/amt-17-1851-2024, https://doi.org/10.5194/amt-17-1851-2024, 2024
Short summary
Short summary
The upgraded systems SENSE2 and NextSENSE2 focus on improving the quality of solar nowcasting and forecasting. SENSE2 provides real-time estimates of solar irradiance across a wide region every 15 min. NextSENSE2 offers short-term forecasts of irradiance up to 3 h ahead. Evaluation with actual data showed that the instantaneous comparison yields the most discrepancies due to the uncertainties of cloud-related information and satellite versus ground-based spatial representativeness limitations.
Giandomenico Pace, Alcide di Sarra, Filippo Cali Quaglia, Virginia Ciardini, Tatiana Di Iorio, Antonio Iaccarino, Daniela Meloni, Giovanni Muscari, and Claudio Scarchilli
Atmos. Meas. Tech., 17, 1617–1632, https://doi.org/10.5194/amt-17-1617-2024, https://doi.org/10.5194/amt-17-1617-2024, 2024
Short summary
Short summary
This study investigates the performances of 17 formulas to determine the clear sky longwave downward irradiance in the Arctic environment. The formulas need to be tuned to the environmental conditions of the studied region and, to date, few of them have been developed and/or tested in the Arctic. The best formulas provide biases and root mean squared errors respectively smaller than 1 and 5 W m-2. We intend to use these results to estimate the longwave cloud radiative perturbation.
Bruna Barbosa Silveira, Emma Catherine Turner, and Jérôme Vidot
Atmos. Meas. Tech., 17, 1279–1296, https://doi.org/10.5194/amt-17-1279-2024, https://doi.org/10.5194/amt-17-1279-2024, 2024
Short summary
Short summary
A fast radiative transfer model, used to speed up the full spectral simulation of meteorological satellite channels in weather forecast models, is tested using 25 000 modelled atmospheres. The differences between calculations from the fast and the high-resolution reference models are examined for nine historic weather satellite instruments. The study confirms that a reduced set of 83 atmospheric profiles is robust enough to estimate the scale of the differences obtained from the larger sample.
Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson
Atmos. Meas. Tech., 17, 515–538, https://doi.org/10.5194/amt-17-515-2024, https://doi.org/10.5194/amt-17-515-2024, 2024
Short summary
Short summary
The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Hua Lu, Min Xie, Wei Zhao, Bojun Liu, Tijian Wang, and Bingliang Zhuang
Atmos. Meas. Tech., 17, 167–179, https://doi.org/10.5194/amt-17-167-2024, https://doi.org/10.5194/amt-17-167-2024, 2024
Short summary
Short summary
Observations of vertical wind in regions with complex terrain are essential, but they are always sparse and have poor representation. Data verification and quality control are conducted on the wind profile radar and Aeolus wind products in this study, trying to compensate for the limitations of wind field observations. The results shed light on the comprehensive applications of multi-source wind profile data in complicated terrain regions with sparse ground-based wind observations.
Timothy J. Wagner, Thomas August, Tim Hultberg, and Ralph A. Petersen
Atmos. Meas. Tech., 17, 1–14, https://doi.org/10.5194/amt-17-1-2024, https://doi.org/10.5194/amt-17-1-2024, 2024
Short summary
Short summary
Commercial passenger and freight aircraft need to know the temperature and pressure of the environments they fly through in order to safely operate. In this paper, we investigate how these observations can be used to evaluate and monitor the performance of satellite observations. Normally weather balloons are used for this, but in places like the United States there are many more airplane flights than weather balloon launches. This makes it much easier to compare them to satellites.
Maria Lívia L. M. Gava, Simone M. S. Costa, and Anthony C. S. Porfírio
Atmos. Meas. Tech., 16, 5429–5441, https://doi.org/10.5194/amt-16-5429-2023, https://doi.org/10.5194/amt-16-5429-2023, 2023
Short summary
Short summary
This study assesses the effectiveness of two geostationary satellite-based sunshine duration datasets over Brazil. Statistical parameters were used to evaluate the performance of the products. The results showed generally good agreement between satellite and ground observations, with some regional discrepancies. Overall, both satellite products offer reliable data for various applications, which benefit from their high spatial resolution and low time latency.
Hubert Luce, Lakshmi Kantha, and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 16, 5091–5101, https://doi.org/10.5194/amt-16-5091-2023, https://doi.org/10.5194/amt-16-5091-2023, 2023
Short summary
Short summary
The potential ability of clear air radars to measure turbulence kinetic energy (TKE) dissipation rate ε in the atmosphere is a major asset of these instruments because of their continuous measurements. In the present work, we successfully tested the relevance of a model relating ε to the width of the Doppler spectrum peak and wind shear for shear-generated turbulence and we provide a physical interpretation of an empirical model in this context.
Michal Kozubek, Lisa Kuchelbacher, Jaroslav Chum, Tereza Sindelarova, Franziska Trinkl, and Katerina Podolska
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-167, https://doi.org/10.5194/amt-2023-167, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
Waves are very important as main drivers of different patterns (streamers) in stratosphere. We analyze some changes of these waves or infrasound characteristics related to streamers using continuous Doppler soundings, array of microbarometers in the Czechia. Ground measurements using the WBCI array showed that GW propagation azimuths were more random during streamers than during calm conditions. Measurements in the ionosphere during streamers did not differ from those expected for the given time
Sheila Kirkwood, Evgenia Belova, Peter Voelger, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 16, 4215–4227, https://doi.org/10.5194/amt-16-4215-2023, https://doi.org/10.5194/amt-16-4215-2023, 2023
Short summary
Short summary
We compared 2 years of wind measurements by the Aeolus satellite with winds from two wind-profiler radars in Arctic Sweden and coastal Antarctica. Biases are similar in magnitude to results from other locations. They are smaller than in earlier studies due to more comparison points and improved criteria for data rejection. On the other hand, the standard deviation is somewhat higher because of degradation of the Aeolus lidar.
Haichen Zuo and Charlotte Bay Hasager
Atmos. Meas. Tech., 16, 3901–3913, https://doi.org/10.5194/amt-16-3901-2023, https://doi.org/10.5194/amt-16-3901-2023, 2023
Short summary
Short summary
Aeolus is a satellite equipped with a Doppler wind lidar to detect global wind profiles. This study evaluates the impact of Aeolus winds on surface wind forecasts over tropical oceans and high-latitude regions based on the ECMWF observing system experiments. We find that Aeolus can slightly improve surface wind forecasts for the region > 60° N, especially from day 5 onwards. For other study regions, the impact of Aeolus is nearly neutral or limited, which requires further investigation.
Holger Baars, Joshua Walchester, Elizaveta Basharova, Henriette Gebauer, Martin Radenz, Johannes Bühl, Boris Barja, Ulla Wandinger, and Patric Seifert
Atmos. Meas. Tech., 16, 3809–3834, https://doi.org/10.5194/amt-16-3809-2023, https://doi.org/10.5194/amt-16-3809-2023, 2023
Short summary
Short summary
In 2018, the Aeolus satellite of the European Space Agency (ESA) was launched to improve weather forecasts through global measurements of wind profiles. Given the novel lidar technique onboard, extensive validation efforts have been needed to verify the observations. For this reason, we performed long-term validation measurements in Germany and Chile. We found significant improvement in the data products due to a new algorithm version and can confirm the general validity of Aeolus observations.
Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Abhiram Doddi, Tyler Mixa, and Masanori Yabuki
Atmos. Meas. Tech., 16, 3561–3580, https://doi.org/10.5194/amt-16-3561-2023, https://doi.org/10.5194/amt-16-3561-2023, 2023
Short summary
Short summary
Doppler radars can be used to estimate turbulence kinetic energy dissipation rates in the atmosphere. The performance of various models is evaluated from comparisons between UHF wind profiler and in situ measurements with UAVs. For the first time, we assess a model supposed to be valid for weak stratification or strong shear conditions. This model provides better agreements with in situ measurements than the classical model based on the hypothesis of a stable stratification.
Chengfeng Feng and Zhaoxia Pu
Atmos. Meas. Tech., 16, 2691–2708, https://doi.org/10.5194/amt-16-2691-2023, https://doi.org/10.5194/amt-16-2691-2023, 2023
Short summary
Short summary
This study demonstrates the positive impacts of assimilating Aeolus Mie-cloudy and Rayleigh-clear near-real-time horizontal line-of-sight winds on the analysis and forecasts of Hurricane Ida (2021) and a mesoscale convective system associated with an African easterly wave using the mesoscale community Weather Research and Forecasting model and the NCEP Gridpoint Statistical Interpolation-based three-dimensional ensemble-variational hybrid data assimilation system.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
Short summary
Short summary
Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, Andreas Schäfler, and Fabian Weiler
Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, https://doi.org/10.5194/amt-15-7049-2022, 2022
Short summary
Short summary
In August 2018, the first wind lidar Aeolus was launched into space and has since then been providing data of the global wind field. The primary goal of Aeolus was the improvement of numerical weather prediction. To verify the quality of Aeolus wind data, DLR performed four airborne validation campaigns with two wind lidar systems. In this paper, we report on results from the two later campaigns, performed in Iceland and the tropics.
Olivier Bock, Pierre Bosser, and Carl Mears
Atmos. Meas. Tech., 15, 5643–5665, https://doi.org/10.5194/amt-15-5643-2022, https://doi.org/10.5194/amt-15-5643-2022, 2022
Short summary
Short summary
Integrated water vapour measurements are often compared for the calibration and validation of instruments or techniques. Measurements made at different altitudes must be corrected to account for the vertical variation of water vapour. This paper shows that the widely used empirical correction model has severe limitations that are overcome using the proposed model. The method is applied to the inter-comparison of GPS and satellite microwave radiometer data in a tropical mountainous area.
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022, https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Short summary
The Global Positioning System (GPS) radio occultation (RO) technique is a satellite-based method for producing highly accurate vertical profiles of atmospheric temperature and pressure. RO profiles are used to monitor global climate trends, particularly in that region of the atmosphere that includes the lower stratosphere. Two data sets spanning 1995–1997 that were produced from the first RO satellite are highly accurate and can be used to assess global atmospheric models.
Ze Chen, Yufang Tian, Yinan Wang, Yongheng Bi, Xue Wu, Juan Huo, Linjun Pan, Yong Wang, and Daren Lü
Atmos. Meas. Tech., 15, 4785–4800, https://doi.org/10.5194/amt-15-4785-2022, https://doi.org/10.5194/amt-15-4785-2022, 2022
Short summary
Short summary
Small-scale turbulence plays a vital role in the vertical exchange of heat, momentum and mass in the atmosphere. There are currently three models that can use spectrum width data of MST radar to calculate turbulence parameters. However, few studies have explored the applicability of the three calculation models. We compared and analysed the turbulence parameters calculated by three models. These results can provide a reference for the selection of models for calculating turbulence parameters.
Damao Zhang, Jennifer Comstock, and Victor Morris
Atmos. Meas. Tech., 15, 4735–4749, https://doi.org/10.5194/amt-15-4735-2022, https://doi.org/10.5194/amt-15-4735-2022, 2022
Short summary
Short summary
The planetary boundary layer is the lowest part of the atmosphere. Its structure and depth (PBLHT) significantly impact air quality, global climate, land–atmosphere interactions, and a wide range of atmospheric processes. To test the robustness of the ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. DOE ARM measurements at various ARM observatories located around the world.
Rachel Robey and Julie K. Lundquist
Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022, https://doi.org/10.5194/amt-15-4585-2022, 2022
Short summary
Short summary
Our work investigates the behavior of errors in remote-sensing wind lidar measurements due to turbulence. Using a virtual instrument, we measured winds in simulated atmospheric flows and decomposed the resulting error. Dominant error mechanisms, particularly vertical velocity variations and interactions with shear, were identified in ensemble data over three test cases. By analyzing the underlying mechanisms, the response of the error behavior to further varying flow conditions may be projected.
Donato Summa, Fabio Madonna, Noemi Franco, Benedetto De Rosa, and Paolo Di Girolamo
Atmos. Meas. Tech., 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022, https://doi.org/10.5194/amt-15-4153-2022, 2022
Short summary
Short summary
The evolution of the atmospheric boundary layer height (ABLH) has an important impact on meteorology. However, the complexity of the phenomena occurring within the ABL and the influence of advection and local accumulation processes often prevent an unambiguous determination of the ABLH. The paper reports results from an inter-comparison effort involving different sensors and techniques to measure the ABLH. Correlations between the ABLH and other atmospheric variables are also assessed.
Haichen Zuo, Charlotte Bay Hasager, Ioanna Karagali, Ad Stoffelen, Gert-Jan Marseille, and Jos de Kloe
Atmos. Meas. Tech., 15, 4107–4124, https://doi.org/10.5194/amt-15-4107-2022, https://doi.org/10.5194/amt-15-4107-2022, 2022
Short summary
Short summary
The Aeolus satellite was launched in 2018 for global wind profile measurement. After successful operation, the error characteristics of Aeolus wind products have not yet been studied over Australia. To complement earlier validation studies, we evaluated the Aeolus Level-2B11 wind product over Australia with ground-based wind profiling radar measurements and numerical weather prediction model equivalents. The results show that the Aeolus can detect winds with sufficient accuracy over Australia.
Carmen González, José M. Vilaplana, José A. Bogeat, and Antonio Serrano
Atmos. Meas. Tech., 15, 4125–4133, https://doi.org/10.5194/amt-15-4125-2022, https://doi.org/10.5194/amt-15-4125-2022, 2022
Short summary
Short summary
Monitoring ultraviolet (UV) radiation is important since it can have harmful effects on the biosphere. Array spectroradiometers are increasingly used to measure UV as they are more versatile than scanning spectroradiometers. In this study, the long-term performance of the BTS-2048-UV-S-WP array spectroradiometer was assessed. The results show that the BTS can reliably measure both the UV index and UV radiation in the 300–360 nm range. Moreover, the BTS was stable and showed no seasonal behavior.
Charlotte Rahlves, Frank Beyrich, and Siegfried Raasch
Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022, https://doi.org/10.5194/amt-15-2839-2022, 2022
Short summary
Short summary
Lidars can measure the wind profile in the lower part of the atmosphere, provided that the wind field is horizontally uniform and does not change during the time of the measurement. These requirements are mostly not fulfilled in reality, and the lidar wind measurement will thus hold a certain error. We investigate different strategies for lidar wind profiling using a lidar simulator implemented in a numerical simulation of the wind field. Our findings can help to improve wind measurements.
Katherine E. Lukens, Kayo Ide, Kevin Garrett, Hui Liu, David Santek, Brett Hoover, and Ross N. Hoffman
Atmos. Meas. Tech., 15, 2719–2743, https://doi.org/10.5194/amt-15-2719-2022, https://doi.org/10.5194/amt-15-2719-2022, 2022
Short summary
Short summary
Winds that are crucial to weather forecasting derived from two different techniques – tracking satellite images (AMVs) and direct measurement of molecular and aerosol motions by Doppler lidar (Aeolus satellite winds) – are compared. We find that AMVs and Aeolus winds are highly correlated. Aeolus Mie-cloudy winds have great potential value as a comparison standard for AMVs. Larger differences are found in the Southern Hemisphere related to higher wind speed and higher vertical variation in wind.
Marijn Floris van Dooren, Anantha Padmanabhan Kidambi Sekar, Lars Neuhaus, Torben Mikkelsen, Michael Hölling, and Martin Kühn
Atmos. Meas. Tech., 15, 1355–1372, https://doi.org/10.5194/amt-15-1355-2022, https://doi.org/10.5194/amt-15-1355-2022, 2022
Short summary
Short summary
The remote sensing technique lidar is widely used for wind speed measurements for both industrial and academic applications. Lidars can measure wind statistics accurately but cannot fully capture turbulent fluctuations in the high-frequency range, since they are partly filtered out. This paper therefore investigates the turbulence spectrum measured by a continuous-wave lidar and analytically models the lidar's measured spectrum with a Lorentzian filter function and a white noise term.
Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
Short summary
Short summary
This study uses collocated ship-based, ground-based, and spaceborne radar observations to validate the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks to the accuracy required for operational severe weather applications such as rainfall and hail nowcasting.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Cited articles
Andersson, A., Fennig, K.,
Klepp, C., Bakan, S., Graßl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data –
HOAPS-3, Earth Syst. Sci. Data, 2, 215–234, https://doi.org/10.5194/essd-2-215-2010, 2010. a, b, c, d
Andersson, A., Graw, K., Schröder, M., Fennig, K., Liman, J., Bakan, S., Hollmann, R., and Klepp, C.: Hamburg Ocean Atmosphere
Parameters and Fluxes from Satellite Data – HOAPS 4.0, https://doi.org/10.5676/EUM_SAF_CM/HOAPS/V002, 2017. a
Bentamy, A.,
Grodsky, S. A., Katsaros, K. B., Mestas-Nuñez, A. M., Blanke, B., and Desbiolles, F.: Improvement in air-sea flux estimates
derived from satellite observations, Int. J. Remote Sens., 34, 5243–5261, https://doi.org/10.1080/01431161.2013.787502, 2013. a, b, c
Berry, D. I. and Kent, E. C.: A new Air-Sea Interaction Gridded Dataset from ICOADS
with Uncertainty Estimates, B. Am. Meteorol. Soc., 90, 645–656, https://doi.org/10.1175/2008BAMS2639.1, 2009. a
Bourassa, M. A., Gille, S. T., Bitz, C., Carlson, D.,
Cerovecki, I., Clayson, C. A., Cronin, M. F., Drennan, W. M., Fairall, C. W., Hoffman, R. N., Magnusdottir, G., Pinker, R. T.,
Renfrew, I. A., Serreze, M., Speer, K., Talley, L. D., and Wick, G. A.: High-Latitude Ocean and Sea Ice Surface Fluxes: Challenges
for Climate Research, B. Am. Meteorol. Soc., 94, 401–423, https://doi.org/10.1175/BAMS-D-11-00244.1, 2013. a, b, c, d
Brodeau, L., Barnier, B., Gulev, S. K., and
Woods, C.: Climatologically Significant Effects of Some Approximations in the Bulk Paramererizations of Turbulent Air-Sea Fluxes,
J. Phys. Oceanogr., 47, 5–28, https://doi.org/10.1175/JPO-D-16-0169.1, 2017. a
Brunke, M. A., Zeng, X., and Anderson, S.: Uncertainties
in sea surface turbulent flux algorithms and data sets, J. Geophys. Res., 107, C103141, https://doi.org/10.1029/2001JC000992, 2002. a
Brunke, M. A., Fairall, C. W., Zeng, X.,
Eymard, L., and Curry, J. A.: Which Bulk Aerodynamic Algorithms are Least Problematic in Computing Ocean Surface Turbulent
Fluxes?, J. Climate, 16, 619–635, https://doi.org/10.1175/1520-0442(2003)016<0619:WBAAAL>2.0.CO;2, 2003. a, b
Brunke, M. A., Wang, Z., Zeng, X.,
Bosilovich, M., and Shie, C.-L.: An Asessment of the Uncertainties in Ocean Surface Turbulent Fluxes in 11 Reanalysis,
Satellite-Derived, and Combined Global Datasets, J. Climate, 24, 5469–5493, https://doi.org/10.1175/2011JCLI4223.1, 2011. a, b, c
Burdanowitz, J., Klepp, C., and Bakan, S.: An
automatic precipitation-phase distinction algorithm for optical disdrometer data over the global ocean, Atmos. Meas. Tech., 9,
1637–1652, https://doi.org/10.5194/amt-9-1637-2016, 2016. a
Casey, K. S., Brandon, T. B., Cornillon, P., and
Evans, R.: The Past, Present and Future of the AVHRR Pathfinder SST Program, in: Oceanography from Space: Revisited, edited by:
Barale, V., Gower, J. F. R., and Alberotanza, L., Springer, Dordrecht, Netherlands, https://doi.org/10.1007/978-90-481-8681-5_16, 2010. a
Cess, R. D. and Udelhofen, P. M.: Climate change during 1985–1999: cloud
interactions determined from satellite measurements, Geophys. Res. Lett., 30, 1019, https://doi.org/10.1029/2002GL016128, 2003. a
Chou, S.-H., Nelkin, E. J., Ardizzone, J., and
Atlas, R. M.: A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products, J. Climate, 17, 3973–3989,
https://doi.org/10.1175/1520-0442(2004)017<3973:ACOLHF>2.0.CO;2, 2004. a, b
Clayson, C. A., Roberts, J. B., and
Bogdanoff, A. S.: The SeaFlux Turbulent Flux Dataset Version 1.0 Documentation (Version 1.2), Tech. rep., Woods Hole Oceanographic
Institution, Woods Hole, MA, available at:
http://seaflux.org/seaflux_data/DOCUMENTATION/SeaFluxV1.0Documentation.pdf (last access: 20 March 2018), 2015. a
Curry, J. A., Bentamy, A.,
Bourassa, M. A., Bourras, D., Bradley, E. F., Brunke, M., Castro, S., Chou, S. H., Clayson, C. A., Emery, W. J., Eymard, L.,
Fairall, C. W., Kubota, M. K., Lin, B., Perrie, W., Reeder, R. A., Renfrew, I. A., Rossow, W. B., Schulz, J., Smith, S. R.,
Webster, P. J., Wick, G. A., and Zeng, X.: SEAFLUX, B. Am. Meteorol. Soc., 85, 409–424, https://doi.org/10.1175/BAMS-85-3-409, 2004. a
de Kloe, J., Stoffelen, A., and Verhoef, A.:
Improved Use of Scatterometer Measurementrs by Using Stress-Equivalent Reference Winds, IEEE J. Sel. Top. Appl., 10, 2340–2347,
https://doi.org/10.1109/JSTARS.2017.2685242, 2017. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G.,
Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M.,
Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M.,
McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Donlon, C. J.,
Minnett, P. J., Gentemann, C., Nightingale, T. J., Barton, I. J., Ward, B., and Murray, M. J.: Toward Improved Valudation of
Satellite Sea Surface Skin Temperature Measurements for Climate Research, J. Climate, 15, 353–369,
https://doi.org/10.1175/1520-0442(2002)015<0353:TIVOSS>2.0.CO;2, 2002. a
Durack, P. J., Wijffels, S. E., and Matear, R. J.: Ocean
Salinities Reveal Strong Global Water Cycle Intensification during 1950 to 2000, Science, 336, 455–458,
https://doi.org/10.1126/science.1212222, 2012. a
Fennig, K., Andersson, A., Bakan, S., Klepp, C., and Schröder, M.: Hamburg
Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS 3.2 –
Monthly Means/6-Hourly Composites, https://doi.org/10.5676/EUM_SAF_CM/HOAPS/V001,
2012. a, b, c
Fennig, K., Andersson, A., Bakan, S., and Schröder, M.: Fundamental
climate data record of SSM/I brightness temperatures,
https://doi.org/10.5676/EUM_SAF_CM/FCDR_SSMI/V001, 2013. a, b
Freeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C.,
Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G.,
and Smith, S. R.: ICOADS Release 3.0: a major update to the historical marine climate record, Int. J. Climatol., 37, 2211–2232, https://doi.org/10.1002/joc.4775,
2017. a, b
Fuhrhop, R. and Simmer, C.: SSM/I Brightness Termperature Corrections for
Incidence Angle Variations, J. Atmos. Ocean. Tech., 13, 246–254,
https://doi.org/10.1175/1520-0426(1996)013<0246:SBTCFI>2.0.CO;2, 1996. a
Gleckler, P. J. and Weare, B. C.: Uncertainties in Global Ocean Surface Heat
Flux Climatologies Derived from Ship Observations, J. Climate, 16, 2764–2781,
https://doi.org/10.1175/1520-0442(1997)010<2764:UIGOSH>2.0.CO;2, 1997. a, b, c
Grodsky, S. A., Bentamy, A., Carton, J. A., and
Pinker, R. T.: Intraseasonal Latent Heat Flux Based on Satellite Observations, J. Climate, 22, 4539–4556,
https://doi.org/10.1175/2009JCLI2901.1, 2009. a, b, c
Gulev, S., Jung, T., and Ruprecht, E.: Estimation of the
Impact of Sampling Errors in the VOS Observations on Air-Sea Fluxes. Part I: Uncertainties in Climate Means, J. Climate, 20,
279–301, https://doi.org/10.1175/JCLI4010.1, 2007. a, b
Gulev, S. K., Josey, S. A., Bourassa, M., Breivik, L.-A.,
Cronin, M. F., Fairall, C., Gille, S., Kent, E. C., Lee, C. M., McPhaden, M. J., Monteiro, P. M. S., Schuster, U., Smith, S.,
Trenberth, K. E., Wallace, D., and Woodruff, S. D.: Surface Energy, CO2 Fluxes and Sea Ice, in: Proceedings of OceanObs'09: Sustained
Ocean Observations and Information for Society, edited by: Hall, J., Harrison, D. E., and Stammer, D., 193–211, European Space
Agency, ESA Publication WPP-306, https://doi.org/10.5270/OceanObs09.pp.19, 2010. a
Immler, F. J., Dykema, J.,
Gardiner, T., Whiteman, D. N., Thorne, P. W., and Vömel, H.: Reference Quality Upper-Air Measurements: guidance for developing
GRUAN data products, Atmos. Meas. Tech., 3, 1217–1231, https://doi.org/10.5194/amt-3-1217-2010, 2010. a
Jackson, D. L., Wick, G. A., and Robertson, F. R.:
Improved multisensor approach to satellite-retrieved near-surface specific humidity observations, J. Geophys. Res., 114, D16303,
https://doi.org/10.1029/2008JD011341, 2009. a
Josey, S. A.: Air-Sea Fluxes of Heat, Freshwater and Momentum, in: Operational Oceanography in the
21st Century, edited by: Schiller, A. and Brasington, G. B., Springer, Dordrecht, Netherlands, https://doi.org/10.1007/978-94-007-0332-2_6,
2011. a
Kelly, B. C.: Some Aspects of Measurement Error in Linear Regression of Astronomical Data,
Astrophys. J., 665, 1489–1506, https://doi.org/10.1086/519947, 2007. a, b
Kent, E. C. and Taylor, P. K.: Accuracy of Humidity Measurements on Ships:
Consideration of Solar Radiation Effects, J. Atmos. Ocean. Tech., 13, 1317–1321,
https://doi.org/10.1175/1520-0426(1996)013<1317:AOHMOS>2.0.CO;2, 1996. a
Kent, E. C. and Taylor, P. K.: Toward estimating climatic trends in SS T. Part II:
Random Errors, J. Atmos. Ocean. Tech., 23, 475–486, https://doi.org/10.1175/JTECH1844.1, 2006. a
Kent, E. C., Taylor, P. K., Truscott, B. S., and
Hopkins, J. S.: The Accuracy of Voluntary Observing Ship's Meteorological Observations – Results of the
VSOP-NA, J. Atmos. Ocean. Tech., 10, 591–608, https://doi.org/10.1175/1520-0426(1993)010<0591:TAOVOS>2.0.CO;2, 1993. a
Kent, E. C., Berry, D. I., Prytherch, J., and
Roberts, J. B.: A comparison of global marine surface-specific humidity datasets from in situ observations and atmospheric
reanalysis, Int. J. Climatol., 34, 355–376, https://doi.org/10.1002/joc.3691, 2014. a, b
Kinzel, J.: Validation of HOAPS latent heat fluxes against parameterizations applied to R/V
Polarstern data for 1995–1997, Master's thesis, University of Kiel, Germany, available at:
http://core.kmi.open.ac.uk/display/16271577 (last access: 20 March 2018), 2013. a
Kinzel, J., Fennig, K.,
Schröder, M., Andersson, A., Bumke, K., and Hollmann, R.: Decomposition of Random Errors Inherent to HOAPS-3.2 Near-Surface
Humidity Estimates Using Multiple Triple Collocation Analysis, J. Atmos. Ocean. Tech., 33, 1455–1471,
https://doi.org/10.1175/JTECH-D-15-0122.1, 2016. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Klepp, C.: The Oceanic Shipboard Precipitation Measurement Network for Surface Validation –
OceanRAIN, Atmos. Res., Special issue of the International Precipitation Working Group, 163, 74–90,
https://doi.org/10.1016/j.atmosres.2014.12.014, 2015. a
Klepp, C., Andersson, A., and Bakan, S.: The HOAPS
climatology: evaluation of latent heat flux, Flux News: Newsletter of the WCRP Working Group on Surface Fluxes, 5, 30–32,
available at: http://hdl.handle.net/11858/00-001M-0000-0011-FA76-C (last access: 20 March 2018), 2008. a
Köhl, A.: Evaluation of the GECCO2 Ocean Synthesis: Transports of Volume, Heat and Freshwater
in the Atlantic, Q. J. Roy. Meteorol. Soc., 141, 166–181, https://doi.org/10.1002/qj.2347, 2015. a
Köhl, A. and Stammer, D.: Variability of the Meridional Overturning in the
North Atlantic from the 50 years GECCO State Estimation, J. Phys. Oceanogr., 38, 1913–1930, https://doi.org/10.1175/2008JPO3775.1, 2008. a
Krasnopolsky, V. M., Breaker, L. C., and
Gemmil, W. H.: A Neural Network as a Nonlinear Transfer Function Model for Retrieving Surface Wind Speeds from the Special Sensor
Microwave Imager, J. Geophys. Res.-Oceans, 100, 11003–11045, https://doi.org/10.1029/95JC00857, 1995. a
Kubota, M. K., Iwasaka, N., Kizu, S.,
Konda, M., and Kutsuwada, K.: Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations (J-OFURO), J. Oceanogr., 58,
213–225, https://doi.org/10.1023/A:1015845321836, 2002. a
Kubota, M. K., Kano, A., Muramatsu, H., and
Tomita, H.: Intercomparison of Various Surface Latent Heat Flux Fields, J. Climate, 16, 670–678,
https://doi.org/10.1175/1520-0442(2003)016<0670:IOVSLH>2.0.CO;2, 2003. a
Liu, J. and Curry, J. A.: Variability of the tropical and subtropical ocean surface
latent heat flux during 1989–2000, Geophys. Res. Lett., 33, L05706, https://doi.org/10.1029/2005GL024809, 2006. a, b, c, d
Liu, W., Zhang, A., and Bishop, J.: Evaporation and solar irradiance
as regulators of sea surface temperature in annual and interannual changes, J. Geophys. Res., 99, 12623–12638,
https://doi.org/10.1029/94JC00604, 1994. a
Loew, A., Bell, W., Brocca, L., Bulgin, C., Burdanowith, J.,
Calbet, X., Donner, R. V., Ghent, D., Gruber, A., Kaminski, T., Kinzel, J., Klepp, C., Lambert, J.-C., Schaepman-Strub, G.,
Schröder, M., and Verhoelst, T.: Validation Practices for Earth Observation Data Across Communities, Rev. Geophys., 55, 779–817, https://doi.org/10.1002/2017RG000562, 2017. a
McClain, E. P.: Global sea surface temperatures and cloud clearing for aerosol optical depth
estimates, Int. J. Remote Sens., 10, 763–769, https://doi.org/10.1080/01431168908903917, 1989. a
Mehta, V. M., DeCandis, A. J., and Mehta, A. V.:
Remote-sensing-based estimates of the fundamental global water cycle: annual cycle, J. Geophys. Res., 110, D22103,
https://doi.org/10.1029/2004JD005672, 2005. a
Mohanty, U. C., Ramesh, K. J., and Pant, M. C.: Certain
Seasonal Characteristic Features of Oceanic Heat Budget Components over the Indian Seas in Relation to the Summer Monsoon Activity
over India, Int. J. Climatol., 16, 243–264,
https://doi.org/10.1002/(SICI)1097-0088(199603)16:3<243::AID-JOC2>3.0.CO;2-B, 1996. a
Murray, F. W.: On the computation of saturation vapor pressure, J. Appl. Meteorol., 6,
203–204, https://doi.org/10.1175/1520-0450(1967)006<0203:OTCOSV>2.0.CO;2, 1967. a
O'Carroll, A. G., Eyre, J. R., and Saunders, R. W.:
Three-way Error Analysis Between AATSR, AMSR-E, and In Situ Sea Surface Temperature Observations, J. Atmos. Ocean. Tech., 25,
1197–1207, https://doi.org/10.1175/2007JTECHO542.1, 2008. a
Prytherch, J., Kent, E. C., Fangohr, S., and
Berry, D. I.: A comparison of SSM/I-derived global marine surface-specific humidity datasets, Int. J. Climatol., 35, 2359–2381, https://doi.org/10.1002/joc.4150, 2014. a, b, c, d
Reynolds, R. W., Smith, T. M.,
Liu, C., Chelton, D. B., Casey, K., and Schlax, M. G.: Daily High-Resolution-Blended Analyses for Sea Surface
Temperature, J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1, 2007. a
Roberts, J. B., Clayson, C. A.,
Robertson, F. R., and Jackson, D. L.: Prediciting near-surface atmospheric variables from Special Sensor Microwave/Imager using
neural networks with a first-guess approach, J. Geophys. Res., 115, D19113, https://doi.org/10.1029/2009JD013099, 2010. a
Romanova, V., Köhl, A.,
Stammer, D., Klepp, C., and Andersson, A.: Sea surface freshwater flux estimates from GECCO, HOAPS and NCEP, Tellus, 62, 435–452,
https://doi.org/10.1111/j.1600-0870.2010.00447.x, 2010. a, b, c
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J.,
Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-Y., Juang, H.-M. H., Sela, J.,
Iredell, M., Treadon, R., Kleist, D., van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S.,
van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P.,
Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: The
NCEP Climate Forecast System Reanalysis, B. Am. Meteorol. Soc., 91, 1015–1057, https://doi.org/10.1175/2010BAMS3001.1, 2010. a
Santorelli, A., Pinker, R. T., Bentamy, A., Katsaros, K. B., Drennan, W. M., Mestas-Nuñez, A. M., and Carton, J. A.: Differences
between two estimates of air-sea turbulent heat fluxes over the Atlantic Ocean, J. Geophys. Res., 116, C09028,
https://doi.org/10.1029/2010JC006927, 2011. a, b, c, d
Schlosser, A. and Houser, R.: Assessing a satellite-era perspective of
the global water cycle, J. Climate, 20, 1316–1338, https://doi.org/10.1175/JCLI4057.1, 2006. a
Schlüssel, P.: Satellite Remote Sensing of Evaporation over Sea, in: Radiation and
Water in the Climate System: Remote measurements, Vol. 45, NATO ASI Series, 431–461, Springer-Verlag, Berlin, Germany, 1996. a
Schulz, J., Schlüssel, P., and Grassl, H.: Water
vapor in the atmospheric boundary layer over oceans from SSM/I measurements, Int. J. Remote Sens., 14, 2773–2789,
https://doi.org/10.1080/01431169308904308, 1993. a
Shearman, R. J. and Zelenko, A. A.: Wind measurements reduction to a
standard level. Marine Meteorology and Related Oceanographic Activities Rep. 22, Tech. rep., WMO TD 311, Geneva, CH, 1989. a
Shie, C.-L., Hilburn, K.,
Chiu, L. S., Adler, R., Lin, I.-I., Nelkin, E. J., Ardizzone, J., and Gao, S.: Goddard Satellite-Based Surface Turbulent Fluxes,
Daily Grid F13, Version 3, edited by: Savtchenko, A., Tech. Rep., Goddhard Earth Science Data and Information Services Center (GES
DISC), Greenbelt, MD, USA, https://doi.org/10.5067/MEASURES/GSSTF/DATA304, 2012. a, b
Smith, S. R., Hughes, P. J., and Bourassa, M. A.: A
comparison of nine monthly air-sea flux products, Int. J. Climatol., 31, 1002–1027, https://doi.org/10.1002/joc.2225, 2011. a
Sohn, B.-J. and Park, S.-C.: Strengthened tropical circulations in past three decades
inferred from water vapor transport, J. Geophys. Res., 115, D15112, https://doi.org/10.1029/2009JD013713, 2010. a
Sohn, B.-J., Smith, E. A., Robertson, F. R., and
Park, S.-C.: Derived Over-Ocean Water Vapor Transports from Satellite-Retrieved E–P Datasets, J. Climate, 17, 1352–1365,
https://doi.org/10.1175/1520-0442(2004)017<1352:DOWVTF>2.0.CO;2, 2004. a
Stendardo, I., Rhein, M., and Hollmann, R.: A
high resolution salinity time series 1993–2012 in the North Atlantic from Argo and Altimeter data, J. Geophys. Res. Oceans, 121,
2523–2551, https://doi.org/10.1002/2015JC011439, 2016. a
Stoffelen, A.: Toward the true near-surface wind speed: Error modeling and calibration
using triple collocation, J. Geophys. Res., 103, 7755–7766, https://doi.org/10.1029/97JC03180, 1998. a, b
Tomita, H. and Kubota, M. K.: An analysis of the accuracy of Japanese ocean
flux data sets with use of remote sensing observations (J-OFURO) satellite-derived latent heat flux using moored buoy
data, J. Geophys. Res., 32, C07007, https://doi.org/10.1029/2005JC003013, 2006. a
Tomita, H. and Kubota, M. K.: Sampling error of daily mean surface wind speed
and air specific humidity due to sun-snychronous satellite sampling and its reduction by multi-satellite sampling, Int. J. Remote
Sens., 32, 3389–3404, https://doi.org/10.1080/01431161003749428, 2011. a, b, c, d
Trenberth, K. E., Smith, L., Qian, T.,
Dai, A., and Fasullo, J.: Estimates of the global water budget and its annual cycle using observational and model data,
J. Hydrometeorol., 8, 758–769, https://doi.org/10.1175/JHM600.1, 2007. a
Verhoef, A., Vogelzang, J.,
Verspeek, J., and Stoffelen, A.: Long-Term Scatterometer Wind Climate Data Records, IEEE J. Sel. Top. Appl., 10, 2186–2194,
https://doi.org/10.1109/JSTARS.2016.2615873, 2017. a
Wang, W. and McPhaden, M. J.: What is the mean seasonal cycle of surface heat
flux in the equatorial Pacific?, J. Geophys. Res., 106, 837–857, https://doi.org/10.1029/1999JC000076, 2001. a
Weller, R. A.,
Bradley, E. F., Edson, J. B., Fairall, C. W., Brooks, I., Yelland, M. J., and Pascal, R. W.: Sensors for physical fluxes at the sea
surface: energy, heat, water, salt, Ocean Sci., 4, 5247–263, https://doi.org/10.5194/os-4-247-2008, 2008. a
Wells, N. and King-Hele, S.: Parameterization of tropical ocean heat
flux, Q. J. Roy. Meteorol. Soc., 116, 1213–1224, https://doi.org/10.1002/qj.49711649511, 1990. a
Wilkinson, K., von Zabern, M., and
Scherzer, J.: Global Freshwater Fluxes into the World Oceans, Tech. rep., Federal Institute of Hydrology, Koblenz,
https://doi.org/10.5675/GRDC_Report_44, 2014.
a
Winterfeldt, J. A.,
Andersson, A., Klepp, C., Bakan, S., and Weisse, R.: Comparison of HOAPS, QuikSCAT, and Buoy Wind Speed in the Eastern North
Atlantic and the North Sea, IEEE T. Geosci. Remote, 48, 338–348, https://doi.org/10.1109/TGRS.2009.2023982, 2010. a, b
Woodruff, S. D., Worley, S. J., Lubker, S. J., Ji, Z., Freeman, J. E., Berry, D. I., Brohan, P.,
Kent, E. C., Reynolds, R. W., Smith, S. R., and Wilkinson, C.: ICOADS Release 2.5: extensions an enhancements to the surface marine
meteorological archive, Int. J. Climatol., 31, 951–967, https://doi.org/10.1002/joc.2103, 2011. a
Yu, L. and Weller, R. A.: Objectively Analyzed Air–Sea Heat Fluxes for the Global
Ice-Free Oceans (1981–2005), B. Am. Meteorol. Soc., 88, 527–539, https://doi.org/10.1175/BAMS-88-4-527, 2007. a, b, c
Yu, L., Zhang, Z., Zhong, S., Zhou, M., Gao, Z.,
Wu, H., and Sun, B.: An inter-comparison of six latent and sensible heat flux products over the Southern Ocean, Polar Res., 30,
10167, https://doi.org/10.3402/polar.v30i0.10167, 2011. a, b
Short summary
Latent heat fluxes (LHF) play a major role in the climate system. Over open ocean, they are increasingly observed by satellite instruments. To access their quality, this research focuses on thorough uncertainty analysis of all LHF-related variables of the HOAPS satellite climatology, in parts making use of novel analysis approaches. Results indicate climatological LHF uncertainies up to 50 W m−2, whereby underlying specific humidities tend to be more uncertain than contributing wind speeds.
Latent heat fluxes (LHF) play a major role in the climate system. Over open ocean, they are...
