Articles | Volume 8, issue 3
https://doi.org/10.5194/amt-8-1197-2015
© Author(s) 2015. 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-8-1197-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Assessment of the consistency among global microwave land surface emissivity products
Department of Construction Management and Civil Engineering Technology, New York City College of Technology, Brooklyn, New York, USA
M. Temimi
Civil Engineering Department, NOAA-CREST, the City College of New York, New York, New York, USA
Masdar Institute of Science and Technology, Institute Center for Water and Environment (iWater), Abu Dhabi, United Arab Emirates
C. Prigent
Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères, Centre National de la Recherché Scientifique, Paris, France
J. Turk
Jet Propulsion Laboratory, Pasadena, California, USA
R. Khanbilvardi
Civil Engineering Department, NOAA-CREST, the City College of New York, New York, New York, USA
Y. Tian
Univ. Maryland College Park, College Park, Maryland, USA
NASA's Goddard Space Flight Center, Greenbelt, Maryland, USA
F. A. Furuzawa
Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan
H. Masunaga
Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan
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Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
EGUsphere, https://doi.org/10.5194/egusphere-2024-179, https://doi.org/10.5194/egusphere-2024-179, 2024
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Satellite passive microwave observations are crucial for monitoring the Arctic's sea ice and atmosphere. To do this effectively, it's important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we've improved our understanding, identifying four distinct emission types and expanding current knowledge towards higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
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This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev., 14, 6403–6444, https://doi.org/10.5194/gmd-14-6403-2021, https://doi.org/10.5194/gmd-14-6403-2021, 2021
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Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Lise Kilic, Catherine Prigent, Carlos Jimenez, and Craig Donlon
Ocean Sci., 17, 455–461, https://doi.org/10.5194/os-17-455-2021, https://doi.org/10.5194/os-17-455-2021, 2021
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The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority satellite missions of the Copernicus program within the European Space Agency. It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precisions, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities.
In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels.
Samuel Favrichon, Carlos Jimenez, and Catherine Prigent
Atmos. Meas. Tech., 13, 5481–5490, https://doi.org/10.5194/amt-13-5481-2020, https://doi.org/10.5194/amt-13-5481-2020, 2020
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Long-term monitoring of satellite-derived variables is necessary for a better understanding of the evolution of Earth parameters at global scale. However different instruments' observations used over the years need to be inter-calibrated with each other to provide meaningful information. This paper describes how a linear correction can improve the observations from the Scanning Multichannel Microwave Radiometer over continental surfaces to be more consistent with more recent radiometers.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Altug Ekici, Hanna Lee, David M. Lawrence, Sean C. Swenson, and Catherine Prigent
Geosci. Model Dev., 12, 5291–5300, https://doi.org/10.5194/gmd-12-5291-2019, https://doi.org/10.5194/gmd-12-5291-2019, 2019
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Ice-rich permafrost thaw can create expanding thermokarst lakes as well as shrinking large wetlands. Such processes can have major biogeochemical implications and feedbacks to climate systems by altering the pathways and rates of permafrost carbon release. We developed a new model parameterization that allows a direct representation of surface water dynamics with subsidence. Our results show increased surface water fractions around western Siberian plains and northeastern territories of Canada.
Lise Kilic, Rasmus Tage Tonboe, Catherine Prigent, and Georg Heygster
The Cryosphere, 13, 1283–1296, https://doi.org/10.5194/tc-13-1283-2019, https://doi.org/10.5194/tc-13-1283-2019, 2019
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In this study, we develop and present simple algorithms to derive the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice. This is achieved using satellite observations collocated with buoy measurements. The errors of the retrieved parameters are estimated and compared with independent data. These parameters are useful for sea ice concentration mapping, understanding sea ice properties and variability, and for atmospheric sounding applications.
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
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Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, https://doi.org/10.5194/hess-22-5341-2018, 2018
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A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Victoria Sol Galligani, Die Wang, Milagros Alvarez Imaz, Paola Salio, and Catherine Prigent
Atmos. Meas. Tech., 10, 3627–3649, https://doi.org/10.5194/amt-10-3627-2017, https://doi.org/10.5194/amt-10-3627-2017, 2017
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Three meteorological events with deep convection and severe weather, characteristic of the SESA region, are considered. High-resolution models, a powerful tool to study convection, can be operated with different microphysics schemes (predict the development of hydrometeors, their interactions, growth, precipitation). We present a systematic evaluation of the microphysical schemes available in the WRF model by a direct comparison between satellite-based simulated and observed microwave radiances.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
R. Padullés, E. Cardellach, M. de la Torre Juárez, S. Tomás, F. J. Turk, S. Oliveras, C. O. Ao, and A. Rius
Atmos. Chem. Phys., 16, 635–649, https://doi.org/10.5194/acp-16-635-2016, https://doi.org/10.5194/acp-16-635-2016, 2016
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The ROHP-PAZ mission will collect, for the first time, GPS radio occultations at two polarizations with the aim of characterizing rain. Prior to the mission's launch (2016), a field campaign has been conducted to identify and understand the measurements. In this study we present the set-up and the results of such a campaign: the main finding is the confirmation of sensitivity to heavy rain and, unexpectedly, to other frozen hydrometeors. This is key information for the spaceborne experiment.
C. L. Pérez Díaz, T. Lakhankar, P. Romanov, J. Muñoz, R. Khanbilvardi, and Y. Yu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-7665-2015, https://doi.org/10.5194/hessd-12-7665-2015, 2015
Manuscript not accepted for further review
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-3441-2014, https://doi.org/10.5194/gmdd-7-3441-2014, 2014
Revised manuscript not accepted
I. Pison, B. Ringeval, P. Bousquet, C. Prigent, and F. Papa
Atmos. Chem. Phys., 13, 11609–11623, https://doi.org/10.5194/acp-13-11609-2013, https://doi.org/10.5194/acp-13-11609-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer
Forward operator for polarimetric radio occultation measurements
Assessing atmospheric gravity wave spectra in the presence of observational gaps
Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations
Mispointing characterization and Doppler velocity correction for the conically scanning WIVERN Doppler radar
Radar and environment-based hail damage estimates using machine learning
A new power-law model for μ–Λ relationships in convective and stratiform rainfall
Suppression of precipitation bias in wind velocities from continuous-wave Doppler lidars
Difference spectrum fitting of the ion–neutral collision frequency from dual-frequency EISCAT measurements
Performance evaluation of three bio-optical models in aerosol and ocean color joint retrievals
Observation of horizontal temperature variations by a spatial heterodyne interferometer using single-sided interferograms
Version 8 IMK–IAA MIPAS temperatures from 12–15 µm spectra: Middle and Upper Atmosphere modes
GNSS radio occultation excess-phase processing for climate applications including uncertainty estimation
Impact analysis of processing strategies for long-term GPS zenith tropospheric delay (ZTD)
A directional surface reflectance climatology determined from TROPOMI observations
A multi-decadal time series of upper stratospheric temperature profiles from Odin-OSIRIS limb scattered spectra
Irradiance and cloud optical properties from solar photovoltaic systems
Single field-of-view sounder atmospheric product retrieval algorithm: establishing radiometric consistency for hyper-spectral sounder retrievals
Higher-order calibration on WindRAD (Wind Radar) scatterometer winds
On the polarimetric backscatter by a still or quasi-still wind turbine
OH airglow observations with two identical spectrometers: benefits of increased data homogeneity in the identification of variations induced by the 11-year solar cycle, the QBO, and other factors
Improved rain event detection in Commercial Microwave Link time series via combination with MSG SEVIRI data
Enhancing Consistency of Microphysical Properties of Precipitation across the Melting Layer in the Dual-Frequency Precipitation Radar Data
Broadband radiative quantities for the EarthCARE mission: the ACM-COM and ACM-RT products
Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)
An Improved BRDF Hotspot Model and its Use in VLIDORT to Study the Impact of Atmospheric Scattering on Hotspot Directional Signatures in the Atmosphere
Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations
Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar
Angular sampling of a monochromatic, wide-field-of-view camera to augment next-generation Earth radiation budget satellite observations
Next-generation radiance unfiltering process for the Clouds and Earth’s Radiant Energy System instrument
Drone-based photogrammetry combined with deep-learning to estimate hail size distributions and melting of hail on the ground
Investigation of Gravity Waves using Measurements from a Sodium Temperature/Wind Lidar Operated in Multi-Direction Mode
Efficient collocation of global navigation satellite system radio occultation soundings with passive nadir microwave soundings
Analysis of 2D airglow imager data with respect to dynamics using machine learning
Estimation of extreme precipitation events in Estonia and Italy using dual-polarization weather radar quantitative precipitation estimations
CALOTRITON: A convective boundary layer height estimation algorithm from UHF wind profiler data
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for the snowfall retrieval at high latitudes
Detection and localization of F-layer ionospheric irregularities with the back-propagation method along the radio occultation ray path
Observations of anomalous propagation over waters near Sweden
Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence
Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach
High-resolution 3D winds derived from a modified WISSDOM synthesis scheme using multiple Doppler lidars and observations
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Spectral replacement using machine learning methods for continuous mapping of the Geostationary Environment Monitoring Spectrometer (GEMS)
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning
Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems
Satellite observations of gravity wave momentum flux in the mesosphere and lower thermosphere (MLT): feasibility and requirements
An improved near-real-time precipitation retrieval for Brazil
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
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A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Daisuke Hotta, Katrin Lonitz, and Sean Healy
Atmos. Meas. Tech., 17, 1075–1089, https://doi.org/10.5194/amt-17-1075-2024, https://doi.org/10.5194/amt-17-1075-2024, 2024
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Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a new type of GNSS observations that can detect heavy precipitation along the ray path between the emitter and receiver satellites. As a first step towards using these observations in numerical weather prediction (NWP), we developed a computer code that simulates GNSS-PRO observations from forecast fields produced by an NWP model. The quality of the developed simulator is evaluated with a number of case studies.
Mohamed Mossad, Irina Strelnikova, Robin Wing, and Gerd Baumgarten
Atmos. Meas. Tech., 17, 783–799, https://doi.org/10.5194/amt-17-783-2024, https://doi.org/10.5194/amt-17-783-2024, 2024
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This numerical study addresses observational gaps' impact on atmospheric gravity wave spectra. Three methods, fast Fourier transform (FFT), generalized Lomb–Scargle periodogram (GLS), and Haar structure function (HSF), were tested on synthetic data. HSF is best for spectra with negative slopes. GLS excels for flat and positive slopes and identifying dominant frequencies. Accurately estimating these aspects is crucial for understanding gravity wave dynamics and energy transfer in the atmosphere.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
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In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Filippo Emilio Scarsi, Alessandro Battaglia, Frederic Tridon, Paolo Martire, Ranvir Dhillon, and Anthony Illingworth
Atmos. Meas. Tech., 17, 499–514, https://doi.org/10.5194/amt-17-499-2024, https://doi.org/10.5194/amt-17-499-2024, 2024
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The WIVERN mission, one of the two candidates to be the ESA's Earth Explorer 11 mission, aims at providing measurements of horizontal winds in cloud and precipitation systems through a conically scanning W-band Doppler radar. This work discusses four methods that can be used to characterize and correct the Doppler velocity error induced by the antenna mispointing. The proposed methodologies can be extended to other Doppler concepts featuring conically scanning or slant viewing Doppler systems.
Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder
Atmos. Meas. Tech., 17, 407–422, https://doi.org/10.5194/amt-17-407-2024, https://doi.org/10.5194/amt-17-407-2024, 2024
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The paper addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilizes a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regard.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 17, 235–245, https://doi.org/10.5194/amt-17-235-2024, https://doi.org/10.5194/amt-17-235-2024, 2024
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A common method to retrieve important information about the microphysical structure of rain (DSD retrievals) requires a constrained relationship between the drop size distribution parameters. The most widely accepted empirical relationship is between μ and Λ. The relationship shows variability across the different types of rainfall (convective or stratiform). The new proposed power-law model to represent the μ–Λ relation provides a better physical interpretation of the relationship coefficients.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
Atmos. Meas. Tech., 16, 6007–6023, https://doi.org/10.5194/amt-16-6007-2023, https://doi.org/10.5194/amt-16-6007-2023, 2023
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By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
Florian Günzkofer, Gunter Stober, Dimitry Pokhotelov, Yasunobu Miyoshi, and Claudia Borries
Atmos. Meas. Tech., 16, 5897–5907, https://doi.org/10.5194/amt-16-5897-2023, https://doi.org/10.5194/amt-16-5897-2023, 2023
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Electric currents in the ionosphere can impact both satellite and ground-based infrastructure. These currents depend strongly on the collisions of ions and neutral particles. Measuring ion–neutral collisions is often only possible via certain assumptions. The direct measurement of ion–neutral collision frequencies is possible with multifrequency incoherent scatter radar measurements. This paper presents one analysis method of such measurements and discusses its advantages and disadvantages.
Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns
Atmos. Meas. Tech., 16, 5749–5770, https://doi.org/10.5194/amt-16-5749-2023, https://doi.org/10.5194/amt-16-5749-2023, 2023
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We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the three- and seven-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the one-parameter model has smaller retrieval uncertainty over open water.
Konstantin Ntokas, Jörn Ungermann, Martin Kaufmann, Tom Neubert, and Martin Riese
Atmos. Meas. Tech., 16, 5681–5696, https://doi.org/10.5194/amt-16-5681-2023, https://doi.org/10.5194/amt-16-5681-2023, 2023
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A nanosatellite was developed to obtain 1-D vertical temperature profiles in the mesosphere and lower thermosphere, which can be used to derive wave parameters needed for atmospheric models. A new processing method is shown, which allows one to extract two 1-D temperature profiles. The location of the two profiles is analyzed, as it is needed for deriving wave parameters. We show that this method is feasible, which however will increase the requirements of an accurate calibration and processing.
Maya García-Comas, Bernd Funke, Manuel López-Puertas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Belén Martínez-Mondéjar, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 5357–5386, https://doi.org/10.5194/amt-16-5357-2023, https://doi.org/10.5194/amt-16-5357-2023, 2023
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We have released version 8 of MIPAS IMK–IAA temperatures and pointing information retrieved from MIPAS Middle and Upper Atmosphere mode version 8.03 calibrated spectra, covering 20–115 km altitude. We considered non-local thermodynamic equilibrium emission explicitly for each limb scan, essential to retrieve accurate temperatures above the mid-mesosphere. Comparisons of this temperature dataset with SABER measurements show excellent agreement, improving those of previous MIPAS versions.
Josef Innerkofler, Gottfried Kirchengast, Marc Schwärz, Christian Marquardt, and Yago Andres
Atmos. Meas. Tech., 16, 5217–5247, https://doi.org/10.5194/amt-16-5217-2023, https://doi.org/10.5194/amt-16-5217-2023, 2023
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Atmosphere remote sensing using GNSS radio occultation provides a highly valuable basis for atmospheric and climate science. For the highest-quality demands, the Wegener Center set up a rigorous system for processing low-level measurement data. This excess-phase processing setup includes integrated quality control and uncertainty estimation. It was successfully evaluated and inter-compared, ensuring the capability of producing reliable long-term data records for climate applications.
Jingna Bai, Yidong Lou, Weixing Zhang, Yaozong Zhou, Zhenyi Zhang, Chuang Shi, and Jingnan Liu
Atmos. Meas. Tech., 16, 5249–5259, https://doi.org/10.5194/amt-16-5249-2023, https://doi.org/10.5194/amt-16-5249-2023, 2023
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Homogenized atmospheric water vapor data are an important prerequisite for climate analysis. Compared to other techniques, GPS has an inherent homogeneity advantage but requires reprocessing and homogenization to eliminate impacts of applied strategy and observation environmental changes. The low-elevation cut-off angles are suggested for the best estimates of zenith tropospheric delay (ZTD) reprocessing time series when compared to homogenized radiosonde data or ERA5 reference time series.
Lieuwe G. Tilstra, Martin de Graaf, Victor Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-222, https://doi.org/10.5194/amt-2023-222, 2023
Revised manuscript accepted for AMT
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This paper introduced a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by the TROPOMI instrument on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Daniel J. Zawada, Kimberlee Robyn Dubé, Taran W. Warnock, Adam Edward Bourassa, Susann Tegtmeier, and Douglas A. Degenstein
EGUsphere, https://doi.org/10.5194/egusphere-2023-2264, https://doi.org/10.5194/egusphere-2023-2264, 2023
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There remain large uncertainties in long term changes of stratospheric atmospheric temperatures. We have produced a more than 20 year time series of satellite-based temperature measurements from the OSIRIS instrument in the upper-middle stratosphere. The dataset is publicly available, and intended to be used to better understand changes in stratospheric temperatures.
James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
Atmos. Meas. Tech., 16, 4975–5007, https://doi.org/10.5194/amt-16-4975-2023, https://doi.org/10.5194/amt-16-4975-2023, 2023
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Measured power data from solar photovoltaic (PV) systems contain information about the state of the atmosphere. In this work, power data from PV systems in the Allgäu region in Germany were used to determine the solar irradiance at each location, using state-of-the-art simulation and modelling. The results were validated using concurrent measurements of the incoming solar radiation in each case. If applied on a wider scale, this algorithm could help improve weather and climate models.
Wan Wu, Xu Liu, Liqiao Lei, Xiaozhen Xiong, Qiguang Yang, Qing Yue, Daniel K. Zhou, and Allen M. Larar
Atmos. Meas. Tech., 16, 4807–4832, https://doi.org/10.5194/amt-16-4807-2023, https://doi.org/10.5194/amt-16-4807-2023, 2023
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We present a new operational physical retrieval algorithm that is used to retrieve atmospheric properties for each single field-of-view measurement of hyper-spectral IR sounders. The physical scheme includes a cloud-scattering calculation in its forward-simulation part. The data product generated using this algorithm has an advantage over traditional IR sounder data production algorithms in terms of improved spatial resolution and minimized error due to cloud contamination.
Zhen Li, Ad Stoffelen, Anton Verhoef, Zhixiong Wang, Jian Shang, and Honggang Yin
Atmos. Meas. Tech., 16, 4769–4783, https://doi.org/10.5194/amt-16-4769-2023, https://doi.org/10.5194/amt-16-4769-2023, 2023
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WindRAD (Wind Radar) is the first dual-frequency rotating fan-beam scatterometer in orbit. We observe non-linearity in the backscatter distribution. Therefore, higher-order calibration (HOC) is proposed, which removes the non-linearities per incidence angle. The combination of HOC and NOCant is discussed. It can remove not only the non-linearity but also the anomalous harmonic azimuth dependencies caused by the antenna rotation; hence the optimal winds can be achieved with this combination.
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023, https://doi.org/10.5194/amt-16-4409-2023, 2023
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A still wind turbine observed with a fixed-pointing radar antenna has shown distinctive polarimetric signatures: the correlation coefficient between the two orthogonal polarization states was persistently equal to 1. The differential reflectivity and the radar reflectivity factors were also stable in time. Over 2 min (2000 Hz, 128 pulses were used; consequently, the sampling time was 64 ms), the standard deviation of the differential backscattering phase shift was only a few degrees.
Carsten Schmidt, Lisa Küchelbacher, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 16, 4331–4356, https://doi.org/10.5194/amt-16-4331-2023, https://doi.org/10.5194/amt-16-4331-2023, 2023
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Two identical instruments in a parallel setup were used to observe the mesospheric OH airglow for more than 10 years (2009–2020) at 47.42°N, 10.98°E. This allows unique analyses of data quality aspects and their impact on the obtained results. During solar cycle 24 the influence of the sun was strong (∼6 K per 100 sfu). A quasi-2-year oscillation (QBO) of ±1 K is observed mainly during the maximum of the solar cycle. Unlike the stratospheric QBO the variation has a period of or below 24 months.
Andreas Wagner, Christian Chwala, Maximilian Graf, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, and Harald Kunstmann
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-175, https://doi.org/10.5194/amt-2023-175, 2023
Revised manuscript accepted for AMT
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Commercial Microwave Links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is the most important processing step. We investigate the usage of rainfall information from MSG SEVIRI for this task, compare these methods to existing methods, and finally combined both approaches. The results show advantages for SEVIRI based methods for light rain and poor performing CMLs. Our newly developed combination reveals the best overall performance.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
EGUsphere, https://doi.org/10.5194/egusphere-2023-2117, https://doi.org/10.5194/egusphere-2023-2117, 2023
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In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Jason N. S. Cole, Howard W. Barker, Zhipeng Qu, Najda Villefranque, and Mark W. Shephard
Atmos. Meas. Tech., 16, 4271–4288, https://doi.org/10.5194/amt-16-4271-2023, https://doi.org/10.5194/amt-16-4271-2023, 2023
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Measurements from the EarthCARE satellite mission will be used to retrieve profiles of cloud and aerosol properties. These retrievals are combined with auxiliary information about surface properties and atmospheric state, e.g., temperature and water vapor. This information allows computation of 1D and 3D solar and thermal radiative transfer for small domains, which are compared with coincident radiometer observations to continually assess EarthCARE retrievals.
Anna Jurczyk, Katarzyna Ośródka, Jan Szturc, Magdalena Pasierb, and Agnieszka Kurcz
Atmos. Meas. Tech., 16, 4067–4079, https://doi.org/10.5194/amt-16-4067-2023, https://doi.org/10.5194/amt-16-4067-2023, 2023
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A data-processing algorithm, RainGRS Clim, has been developed to work on precipitation accumulations such as daily or monthly totals. The algorithm makes the most of additional opportunities: access to high-quality data that are not operationally available and greater efficiency of the algorithms for data quality control and merging for longer accumulations. Monthly accumulations estimated by RainGRS Clim were found to be significantly more reliable than accumulations generated operationally.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-159, https://doi.org/10.5194/amt-2023-159, 2023
Revised manuscript accepted for AMT
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The term “hotspot” refers to the sharp increase of reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper developed an improved hotspot BRDF model that converges much faster and was tested in a model.
Sophie Rosenburg, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 16, 3915–3930, https://doi.org/10.5194/amt-16-3915-2023, https://doi.org/10.5194/amt-16-3915-2023, 2023
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Snow layer melting and melt pond formation on Arctic sea ice are important seasonal processes affecting the surface reflection and energy budget. Sea ice reflectivity was surveyed by airborne imaging spectrometers in May–June 2017. Adapted retrieval approaches were applied to find snow layer liquid water fraction, snow grain effective radius, and melt pond depth. The retrievals show the potential and limitations of spectral airborne imaging to map melting snow layer and melt pond properties.
Sunil Baidar, Timothy J. Wagner, David D. Turner, and W. Alan Brewer
Atmos. Meas. Tech., 16, 3715–3726, https://doi.org/10.5194/amt-16-3715-2023, https://doi.org/10.5194/amt-16-3715-2023, 2023
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This paper provides a new method to retrieve wind profiles from coherent Doppler lidar (CDL) measurements. It takes advantage of layer-to-layer correlation in wind profiles to provide continuous profiles of up to 3 km by filling in the gaps where the CDL signal is too small to retrieve reliable results by itself. Comparison with the current method and collocated radiosonde wind measurements showed excellent agreement with no degradation in results where the current method gives valid results.
Jake J. Gristey, K. Sebastian Schmidt, Hong Chen, Daniel R. Feldman, Bruce C. Kindel, Joshua Mauss, Mathew van den Heever, Maria Z. Hakuba, and Peter Pilewskie
Atmos. Meas. Tech., 16, 3609–3630, https://doi.org/10.5194/amt-16-3609-2023, https://doi.org/10.5194/amt-16-3609-2023, 2023
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The concept of a satellite-based camera is demonstrated for sampling the angular distribution of outgoing radiance from Earth needed to generate data products for new radiation budget spectral channels.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary A. Eitzen, and Norman G. Loeb
EGUsphere, https://doi.org/10.5194/egusphere-2023-1670, https://doi.org/10.5194/egusphere-2023-1670, 2023
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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 resulted global mean of instantaneous SW and LW fluxes are changed by less than 0.5 Wm-2 with regional differences can be as large as 2.0 Wm-2.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-89, https://doi.org/10.5194/amt-2023-89, 2023
Revised manuscript accepted for AMT
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We present an approach for hail size estimation combining drone-based photogrammetry with a deep-learning object detection model. The method is applied to a hail event of a supercell that crossed Switzerland on June 20, 2021, allowing an accurate estimation of the hail size distribution (>18000 samples). Results are then compared with data from nearby automatic hail sensors and radar-based hail products. The opportunity to monitor the hail melting on the ground is also investigated.
Bing Cao and Alan Z. Liu
EGUsphere, https://doi.org/10.5194/egusphere-2023-1563, https://doi.org/10.5194/egusphere-2023-1563, 2023
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A narrow-band sodium lidar measures atmospheric waves but focuses on vertical variations. By analyzing phase shifts among laser beams in different directions, horizontal wave information can be derived. With this method, two wave packets were identified, propagating in different directions. These waves interacted with thin evanescent layers, reflecting partially but transmitting energy to higher altitudes. The method can be used to detect more gravity waves from similar lidar systems worldwide.
Alex Meredith, Stephen Leroy, Lucy Halperin, and Kerri Cahoy
Atmos. Meas. Tech., 16, 3345–3361, https://doi.org/10.5194/amt-16-3345-2023, https://doi.org/10.5194/amt-16-3345-2023, 2023
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We developed a new efficient algorithm leveraging orbital dynamics to collocate radio occultation soundings with microwave radiance soundings. This new algorithm is 99 % accurate and is much faster than traditional collocation-finding approaches. Speeding up collocation finding is useful for calibrating and validating microwave radiometers and for data assimilation into numerical weather prediction models. Our algorithm can also be used to predict collocation yield for new satellite missions.
René Sedlak, Andreas Welscher, Patrick Hannawald, Sabine Wüst, Rainer Lienhart, and Michael Bittner
Atmos. Meas. Tech., 16, 3141–3153, https://doi.org/10.5194/amt-16-3141-2023, https://doi.org/10.5194/amt-16-3141-2023, 2023
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We show that machine learning can help in classifying images of the OH* airglow, a thin layer in the middle atmosphere (ca. 86 km height) emitting infrared radiation, in an efficient way. By doing this,
dynamicepisodes of strong movement in the OH* airglow caused predominantly by waves can be extracted automatically from large data sets. Within these dynamic episodes, turbulent wave breaking can also be found. We use these observations of turbulence to derive the energy released by waves.
Roberto Cremonini, Tanel Voormansik, Piia Post, and Dmitri Moisseev
Atmos. Meas. Tech., 16, 2943–2956, https://doi.org/10.5194/amt-16-2943-2023, https://doi.org/10.5194/amt-16-2943-2023, 2023
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Extreme rainfall for a specific location is commonly evaluated when designing stormwater management systems. This study investigates the use of quantitative precipitation estimations (QPEs) based on polarimetric weather radar data, without rain gauge corrections, to estimate 1 h rainfall total maxima in Italy and Estonia. We show that dual-polarization weather radar provides reliable QPEs and effective estimations of return periods for extreme rainfall in climatologically homogeneous regions.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer Brooke
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-95, https://doi.org/10.5194/amt-2023-95, 2023
Revised manuscript accepted for AMT
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We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with Ultra High Frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease of turbulence. It is evaluated with ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-94, https://doi.org/10.5194/amt-2023-94, 2023
Revised manuscript accepted for AMT
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A new snowfall retrieval algorithm developed especially for high latitude environmental conditions and based on Advanced Technology Microwave Sounder (ATMS) observations is described. The algorithm exploits ATMS low-frequency channels to retrieve the surface emissivity and compute the clear-sky brightness temperature, to highlight the snowfall signature. This information is used in a neural network based snowfall retrieval, trained against Cloud Profiling Radar snowfall products.
Vinícius Ludwig-Barbosa, Joel Rasch, Thomas Sievert, Anders Carlström, Mats I. Pettersson, Viet Thuy Vu, and Jacob Christensen
Atmos. Meas. Tech., 16, 1849–1864, https://doi.org/10.5194/amt-16-1849-2023, https://doi.org/10.5194/amt-16-1849-2023, 2023
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In this paper, the back-propagation method's capabilities and limitations regarding the location of irregularity regions in the ionosphere, e.g. equatorial plasma bubbles, are evaluated. The assessment was performed with simulations in which different scenarios were assumed. The results showed that the location estimate is possible if the amplitude of the ionospheric disturbance is stronger than the instrument noise level. Further, multiple patches can be located if regions are well separated.
Lars Norin
Atmos. Meas. Tech., 16, 1789–1801, https://doi.org/10.5194/amt-16-1789-2023, https://doi.org/10.5194/amt-16-1789-2023, 2023
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The atmosphere can cause radar beams to bend more or less towards the ground. When the atmosphere differs from standard atmospheric conditions, the propagation is considered anomalous. Radars affected by anomalous propagation can observe ground clutter far beyond the radar horizon. Here, 4.5 years' worth of data from five operational Swedish weather radars are presented. Analyses of the data reveal a strong seasonal cycle and weaker diurnal cycle in ground clutter from across nearby waters.
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, https://doi.org/10.5194/amt-16-997-2023, 2023
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Aeolus is the first spaceborne wind lidar providing global wind measurements since 2018. This study offers a comprehensive analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023, https://doi.org/10.5194/amt-16-911-2023, 2023
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Better understanding and modeling snowfall properties and processes is relevant to many fields, ranging from weather forecasting to aircraft safety. Meteorological radars can be used to gain insights into the microphysics of snowfall. In this work, we propose a new method to retrieve snowfall properties from measurements of radars with different frequencies. It relies on an original deep-learning framework, which incorporates knowledge of the underlying physics, i.e., electromagnetic scattering.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Yeeun Lee, Myoung-Hwan Ahn, Mina Kang, and Mijin Eo
Atmos. Meas. Tech., 16, 153–168, https://doi.org/10.5194/amt-16-153-2023, https://doi.org/10.5194/amt-16-153-2023, 2023
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This study aims to verify that a partly defective hyperspectral measurement can be successfully reproduced with concise machine learning models coupled with principal component analysis. Evaluation of the approach is performed with radiances and retrieval results of ozone and cloud properties. Considering that GEMS is the first geostationary UV–VIS hyperspectral spectrometer, we expect our findings can be introduced further to similar geostationary environmental instruments to be launched soon.
Mathias Gergely, Maximilian Schaper, Matthias Toussaint, and Michael Frech
Atmos. Meas. Tech., 15, 7315–7335, https://doi.org/10.5194/amt-15-7315-2022, https://doi.org/10.5194/amt-15-7315-2022, 2022
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This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
Kenneth A. Brown and Thomas G. Herges
Atmos. Meas. Tech., 15, 7211–7234, https://doi.org/10.5194/amt-15-7211-2022, https://doi.org/10.5194/amt-15-7211-2022, 2022
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The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022, https://doi.org/10.5194/amt-15-7105-2022, 2022
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Water vapor concentration in the atmosphere at small scales (< 6 km) is considered. The measurements show Gaussian random field behavior following Kolmogorov's theory of turbulence two-thirds law. These properties can be useful when estimating the water vapor variability within a given observed satellite scene or when different water vapor measurements have to be merged consistently.
Qiuyu Chen, Konstantin Ntokas, Björn Linder, Lukas Krasauskas, Manfred Ern, Peter Preusse, Jörn Ungermann, Erich Becker, Martin Kaufmann, and Martin Riese
Atmos. Meas. Tech., 15, 7071–7103, https://doi.org/10.5194/amt-15-7071-2022, https://doi.org/10.5194/amt-15-7071-2022, 2022
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Observations of phase speed and direction spectra as well as zonal mean net gravity wave momentum flux are required to understand how gravity waves reach the mesosphere–lower thermosphere and how they there interact with background flow. To this end we propose flying two CubeSats, each deploying a spatial heterodyne spectrometer for limb observation of the airglow. End-to-end simulations demonstrate that individual gravity waves are retrieved faithfully for the expected instrument performance.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
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