Articles | Volume 15, issue 4
https://doi.org/10.5194/amt-15-879-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-879-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2022
Research article |
| 21 Feb 2022
| 21 Feb 2022
Cloud-probability-based estimation of black-sky surface albedo from AVHRR data
Terhikki Manninen
CORRESPONDING AUTHOR
Meteorological Research, Finnish Meteorological Institute, Helsinki, 00101, Finland
Emmihenna Jääskeläinen
Meteorological Research, Finnish Meteorological Institute, Helsinki, 00101, Finland
Niilo Siljamo
Meteorological Research, Finnish Meteorological Institute, Helsinki, 00101, Finland
Aku Riihelä
Meteorological Research, Finnish Meteorological Institute, Helsinki, 00101, Finland
Karl-Göran Karlsson
Atmospheric Remote Sensing Unit, Research Department, Swedish
Meteorological and Hydrological Institute, Norrköping, 60176
Norrköping, Sweden
Related authors
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
Short summary
Short summary
The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Terhikki Manninen, Tuula Aalto, Tiina Markkanen, Mikko Peltoniemi, Kristin Böttcher, Sari Metsämäki, Kati Anttila, Pentti Pirinen, Antti Leppänen, and Ali Nadir Arslan
Biogeosciences, 16, 223–240, https://doi.org/10.5194/bg-16-223-2019, https://doi.org/10.5194/bg-16-223-2019, 2019
Short summary
Short summary
The surface albedo time series CLARA-A2 SAL was used to study trends in the timing of the melting season of snow and preceding albedo value in Finland during 1982–2016 to assess climate change. The results were in line with operational snow depth data, JSBACH land ecosystem model, SYKE fractional snow cover and greening-up data. In the north a clear trend to earlier snowmelt onset, increasing melting season length, and decrease in pre-melt albedo (related to increased stem volume) was observed.
Emmihenna Jääskeläinen, Terhikki Manninen, Johanna Tamminen, and Marko Laine
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-180, https://doi.org/10.5194/amt-2016-180, 2016
Revised manuscript not accepted
O. Meinander, A. Kontu, A. Virkkula, A. Arola, L. Backman, P. Dagsson-Waldhauserová, O. Järvinen, T. Manninen, J. Svensson, G. de Leeuw, and M. Leppäranta
The Cryosphere, 8, 991–995, https://doi.org/10.5194/tc-8-991-2014, https://doi.org/10.5194/tc-8-991-2014, 2014
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
Karl-Göran Karlsson, Nina Håkansson, Salomon Eliasson, Erwin Wolters, and Ronald Scheirer
EGUsphere, https://doi.org/10.5194/egusphere-2025-379, https://doi.org/10.5194/egusphere-2025-379, 2025
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The topic is finding methods to extend climate data records from single-instrument satellite observations, in this case the Advanced Very High Resolution Radiometer (AVHRR). Several modern instruments include AVHRR-heritage channels but some corrections are necessary to account for some differences. We have simulated AVHRR data from the VIIIRS sensor on NOAA polar satellites. We find that methods based on machine learning are capable of performing these corrections.
Emmihenna Jääskeläinen, Miska Luoto, Pauli Putkiranta, Mika Aurela, and Tarmo Virtanen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-390, https://doi.org/10.5194/hess-2024-390, 2025
Preprint under review for HESS
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The challenge with current satellite-based soil moisture products is their coarse resolution. Therefore, we used machine-learning model to improve spatial resolution of well-known SMAP soil moisture data, by using in situ soil moisture observations and additional soil and vegetation properties. Comparisons against independent data set show that the model estimated soil moisture values have better agreement with in situ observations compared to other SMAP-related soil moisture data.
Emmihenna Jääskeläinen, Kerttu Kouki, and Aku Riihelä
Hydrol. Earth Syst. Sci., 28, 3855–3870, https://doi.org/10.5194/hess-28-3855-2024, https://doi.org/10.5194/hess-28-3855-2024, 2024
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Snow cover is an important variable when studying the effect of climate change in the Arctic. Therefore, the correct detection of snowfall is important. In this study, we present methods to detect snowfall accurately using satellite observations. The snowfall event detection results of our limited area are encouraging. We find that further development could enable application over the whole Arctic, providing necessary information on precipitation occurrence over remote areas.
Abhay Devasthale, Sandra Andersson, Erik Engström, Frank Kaspar, Jörg Trentmann, Anke Duguay-Tetzlaff, Jan Fokke Meirink, Erik Kjellström, Tomas Landelius, Manu Anna Thomas, and Karl-Göran Karlsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1805, https://doi.org/10.5194/egusphere-2024-1805, 2024
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Using the satellite-based climate data record CLARA-A3 spanning 1982–2020 and ERA5 reanalysis, we present climate regimes that are favourable or unfavourable for solar energy applications. We show that the favourable climate regimes are emerging over much of Europe during spring and early summer for solar energy exploitation.
Adriano Lemos and Aku Riihelä
EGUsphere, https://doi.org/10.5194/egusphere-2024-869, https://doi.org/10.5194/egusphere-2024-869, 2024
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Here we used satellite imagery to measure snow depth in northern Finland and compared to on-site weather stations from 2019–2022. We correlated snow depths and vegetation coverage, and found thicker snow over non-vegetated areas and frozen water bodies due to the satellite's sensitivity. Our estimates showed underestimated results of snow depth and need further investigation, but they highlight the potential in monitoring seasonal snow changes, particularly where direct measurements are lacking.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
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We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
Kerttu Kouki, Kari Luojus, and Aku Riihelä
The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, https://doi.org/10.5194/tc-17-5007-2023, 2023
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We evaluated snow cover properties in state-of-the-art reanalyses (ERA5 and ERA5-Land) with satellite-based datasets. Both ERA5 and ERA5-Land overestimate snow mass, whereas albedo estimates are more consistent between the datasets. Snow cover extent (SCE) is accurately described in ERA5-Land, while ERA5 shows larger SCE than the satellite-based datasets. The trends in snow mass, SCE, and albedo are mostly negative in 1982–2018, and the negative trends become more apparent when spring advances.
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
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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
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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.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
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We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
Short summary
Short summary
The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Salomon Eliasson, Karl-Göran Karlsson, and Ulrika Willén
Geosci. Model Dev., 13, 297–314, https://doi.org/10.5194/gmd-13-297-2020, https://doi.org/10.5194/gmd-13-297-2020, 2020
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This paper describes a new satellite simulator. Its purpose is to simulate the CLARA-A2 climate data record from a climate model atmosphere. We explain how the simulator takes into account the regionally variable cloud detection skill of the observations. The simulator makes use of the long/lat-gridded validation between CLARA-A2 and the CALIOP satellite-borne lidar dataset. Using the EC-Earth climate model, we show a sizable impact on climate model validation, especially at high latitudes.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, https://doi.org/10.5194/acp-20-457-2020, 2020
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In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
Aku Riihelä, Michalea D. King, and Kati Anttila
The Cryosphere, 13, 2597–2614, https://doi.org/10.5194/tc-13-2597-2019, https://doi.org/10.5194/tc-13-2597-2019, 2019
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We used a 1982–2015 time series of satellite observations to examine changes in surface reflectivity (albedo) of the Greenland Ice Sheet. We found notable decreases in albedo over most of the ice sheet margins in July and August, particularly over the west coast and between 2000 and 2015. The results indicate that significant melt now occurs in areas 50 to 100 m higher up the ice sheet relative to the early 1980s. The albedo decrease is consistent and covarying with modelled ice sheet mass loss.
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829–847, https://doi.org/10.5194/gmd-12-829-2019, https://doi.org/10.5194/gmd-12-829-2019, 2019
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To enable fair comparisons of clouds between climate models and the
ESA Cloud_cci climate data record (CDR), we present a tool called the
Cloud_cci simulator. The tool takes into account the geometry and
cloud detection capabilities of the Cloud_cci CDR to allow fair
comparisons. We demonstrate the simulator on two climate models. We
find the impact of time sampling has a large effect on simulated cloud
water amount and that the simulator reduces the cloud cover by about
10 % globally.
Terhikki Manninen, Tuula Aalto, Tiina Markkanen, Mikko Peltoniemi, Kristin Böttcher, Sari Metsämäki, Kati Anttila, Pentti Pirinen, Antti Leppänen, and Ali Nadir Arslan
Biogeosciences, 16, 223–240, https://doi.org/10.5194/bg-16-223-2019, https://doi.org/10.5194/bg-16-223-2019, 2019
Short summary
Short summary
The surface albedo time series CLARA-A2 SAL was used to study trends in the timing of the melting season of snow and preceding albedo value in Finland during 1982–2016 to assess climate change. The results were in line with operational snow depth data, JSBACH land ecosystem model, SYKE fractional snow cover and greening-up data. In the north a clear trend to earlier snowmelt onset, increasing melting season length, and decrease in pre-melt albedo (related to increased stem volume) was observed.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
Preprint withdrawn
Short summary
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In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Karl-Göran Karlsson and Nina Håkansson
Atmos. Meas. Tech., 11, 633–649, https://doi.org/10.5194/amt-11-633-2018, https://doi.org/10.5194/amt-11-633-2018, 2018
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Data from the high-sensitivity CALIOP cloud lidar onboard the CALIPSO satellite have been used to evaluate cloud amounts estimated from satellite imagery and, specifically, from the climate data record CLARA-A2. The main purpose has been to study the limit of how thin clouds that can be detected efficiently (i.e., detected at the 50 % level) in CLARA-A2 data and how this limit varies globally. The study revealed very large geographical differences in the cloud detection efficiency.
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
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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.
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
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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).
Emmihenna Jääskeläinen, Terhikki Manninen, Johanna Tamminen, and Marko Laine
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-180, https://doi.org/10.5194/amt-2016-180, 2016
Revised manuscript not accepted
P. Räisänen, A. Luomaranta, H. Järvinen, M. Takala, K. Jylhä, O. N. Bulygina, K. Luojus, A. Riihelä, A. Laaksonen, J. Koskinen, and J. Pulliainen
Geosci. Model Dev., 7, 3037–3057, https://doi.org/10.5194/gmd-7-3037-2014, https://doi.org/10.5194/gmd-7-3037-2014, 2014
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Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
O. Meinander, A. Kontu, A. Virkkula, A. Arola, L. Backman, P. Dagsson-Waldhauserová, O. Järvinen, T. Manninen, J. Svensson, G. de Leeuw, and M. Leppäranta
The Cryosphere, 8, 991–995, https://doi.org/10.5194/tc-8-991-2014, https://doi.org/10.5194/tc-8-991-2014, 2014
T. Koenigk, A. Devasthale, and K.-G. Karlsson
Atmos. Chem. Phys., 14, 1987–1998, https://doi.org/10.5194/acp-14-1987-2014, https://doi.org/10.5194/acp-14-1987-2014, 2014
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
K.-G. Karlsson and E. Johansson
Atmos. Meas. Tech., 6, 1271–1286, https://doi.org/10.5194/amt-6-1271-2013, https://doi.org/10.5194/amt-6-1271-2013, 2013
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025, https://doi.org/10.5194/amt-18-1961-2025, 2025
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Long-term records of plant fluorescence offer vital insights into changing vegetation activity. The GOME-2A sensor provides extensive global observations but suffers from calibration and instrument degradation, which affects data consistency. This study presents the SIFTER v3 algorithm, which effectively resolves these issues and includes other improvements, resulting in robust, accurate, and consistent GOME-2A fluorescence measurements from 2007 to 2017.
Nadia Smith and Christopher D. Barnet
Atmos. Meas. Tech., 18, 1823–1839, https://doi.org/10.5194/amt-18-1823-2025, https://doi.org/10.5194/amt-18-1823-2025, 2025
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CLIMCAPS extends the Aqua AIRS+AMSU record with retrievals from CrIS+ATMS on Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System series (JPSS-1 to JPSS-4). With “continuous”, we mean a data record that is consistent in its characterization of natural variation despite changes in source instrumentation. Here we investigate how sounding continuity can improve across the full CLIMCAPS record (2002 to the present day), spanning multiple instruments and satellites.
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech., 18, 1841–1857, https://doi.org/10.5194/amt-18-1841-2025, https://doi.org/10.5194/amt-18-1841-2025, 2025
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This study analyzes three years of wind lidar measurements to explore the dynamics of the urban planetary boundary layer in Hefei, China. Results reveal that nocturnal low-level jets are most frequent in spring and intensify in summer, significantly enhancing turbulence and shear near the surface, particularly at night. Additionally, cloud cover raises the mixing layer height by approximately 100 m at night due to the greenhouse effect but reduces it by up to 200 m in the afternoon.
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025, https://doi.org/10.5194/amt-18-1731-2025, 2025
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This paper provides a comprehensive evaluation of the quality of radar-based precipitation estimation in mountainous areas and presents a method to mitigate the main shortcomings identified. It then compares three different ensemble analysis methods that combine radar-based precipitation estimates with forecasts from an ensemble numerical weather prediction model.
Sabine Wüst, Lisa Küchelbacher, Franziska Trinkl, and Michael Bittner
Atmos. Meas. Tech., 18, 1591–1607, https://doi.org/10.5194/amt-18-1591-2025, https://doi.org/10.5194/amt-18-1591-2025, 2025
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Information on the energy transported by atmospheric gravity waves (GWs) is crucial for improving atmosphere models. Most space-based studies report the potential energy. We use Aeolus wind data to estimate the kinetic energy (density). However, the data quality is a challenge for such analyses, as the accuracy of the data is in the range of typical GW amplitudes. We find a temporal coincidence between enhanced or breaking planetary waves and enhanced gravity wave kinetic energy density.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
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A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Chengli Ji, Qiankai Jin, Feilong Li, Yuyang Liu, Zhicheng Wang, Jiajia Mao, Xiaoyu Ren, Yan Xiang, Wanlin Jian, Peitao Zhao, and Zhenyi Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1171, https://doi.org/10.5194/egusphere-2025-1171, 2025
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This study presents the humidity measurements with a synergetic algorithm combining Raman lidar, MVR, and satellite. The results from 47 sites in China show the best correlation over 0.9 concerning the radiosonde measurements. It validates the RH accuracy with various data integrations. Three representative sites present the different seasonal characteristics indicating the geographic and height influences on the RH vertical distribution.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025, https://doi.org/10.5194/amt-18-1269-2025, 2025
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This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025, https://doi.org/10.5194/amt-18-1185-2025, 2025
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This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Réunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
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Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech., 18, 793–816, https://doi.org/10.5194/amt-18-793-2025, https://doi.org/10.5194/amt-18-793-2025, 2025
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Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 18, 471–485, https://doi.org/10.5194/amt-18-471-2025, https://doi.org/10.5194/amt-18-471-2025, 2025
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground–airborne synergy between the two instruments yielded optimal sounding results.
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
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This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
Luuk D. van der Valk, Oscar K. Hartogensis, Miriam Coenders-Gerrits, Rolf W. Hut, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2974, https://doi.org/10.5194/egusphere-2024-2974, 2025
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Xiaoye Wang, Jing Xu, Songhua Wu, Qichao Wang, Guangyao Dai, Peizhi Zhu, Zhizhong Su, Sai Chen, Xiaomeng Shi, and Mengqi Fan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-156, https://doi.org/10.5194/amt-2024-156, 2024
Revised manuscript accepted for AMT
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In this paper, we proposed a data fusion method to obtain the no-blind zone wind speed profiles covering the whole Atmospheric Boundary Layer based on the joint measurements of coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS). Since above instruments are widely deployed in China, we believe this method has broad application prospects on the improvement of the boundary layer parameterization scheme in numerical forecast models.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Erlend Øydvin, Renaud Gaban, Jafet Andersson, Remco van de Beek, Mareile Astrid Wolff, Nils-Otto Kitterød, Christian Chwala, and Vegard Nilsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2625, https://doi.org/10.5194/egusphere-2024-2625, 2024
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We present a novel method for classifying rain and snow by combining data from Commercial Microwave Links (CMLs) with weather radar. We compare this to a reference method using dew point temperature for precipitation type classification. Evaluations with nearby disdrometers show that CMLs improve the classification of dry snow and rainfall, outperforming the reference method.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
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We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
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The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
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Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
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The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
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The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
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This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Sebastiano Padovan, Axel Von Engeln, Saverio Paolella, Yago Andres, Chad R. Galley, Riccardo Notarpietro, Veronica Rivas Boscán, Francisco Sancho, Francisco Martin Alemany, Nicolas Morew, and Christian Marquardt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-80, https://doi.org/10.5194/amt-2024-80, 2024
Revised manuscript accepted for AMT
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Radio Occultation (RO) measurements are an important contribution to numerical weather predictions and long-term climate studies. Using more than a hundred thousand occultations recorded by instruments onboard the Sentinel-6A and Cosmic-2 satellites, this work studies the effects of the clock data rate of the Global Navigation Satellite System on the RO data quality. GLONASS occultations benefit of high-rate clock data (1 second), GPS occultation have high quality already at 30 seconds.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
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This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
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We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
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Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
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This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
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The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
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This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
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Short summary
A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
A new method for cloud-correcting observations of surface albedo is presented for AVHRR data....
