Articles | Volume 8, issue 3
https://doi.org/10.5194/amt-8-1055-2015
© 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-8-1055-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Mar 2015
Research article |
| 04 Mar 2015
A layer-averaged relative humidity profile retrieval for microwave observations: design and results for the Megha-Tropiques payload
R. G. Sivira
Université Versailles St-Quentin; Sorbonne Universités, UPMC Univ. Paris 06; CNRS/INSU, LATMOS-IPSL, Guyancourt, France
now at: Meteo Protect SAS, Paris, France
H. Brogniez
CORRESPONDING AUTHOR
Université Versailles St-Quentin; Sorbonne Universités, UPMC Univ. Paris 06; CNRS/INSU, LATMOS-IPSL, Guyancourt, France
C. Mallet
Université Versailles St-Quentin; Sorbonne Universités, UPMC Univ. Paris 06; CNRS/INSU, LATMOS-IPSL, Guyancourt, France
Y. Oussar
Laboratoire de Physique et d'Etudes des Matériaux (LPEM), UMR8213, ESPCI-ParisTech, Paris, France
Related authors
No articles found.
Tim Trent, Marc Schroeder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinsk, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2808, https://doi.org/10.5194/egusphere-2023-2808, 2023
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 & 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends & differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends
Rodrigo Andres Rivera Martinez, Pramod Kumar, Olivier Laurent, Grégoire Broquet, Christopher Caldow, Ford Cropley, Diego Santaren, Adil Shah, Cécile Mallet, Michel Ramonet, Leonard Rivier, Catherine Juery, Olivier Duclaux, Caroline Bouchet, Elisa Allegrini, Hervé Utard, and Philippe Ciais
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-52, https://doi.org/10.5194/amt-2023-52, 2023
Revised manuscript under review for AMT
Short summary
Short summary
This study explores the use of Metal Oxide Sensors (MOS) as a low-cost alternative for detecting and measuring CH4 emissions from industrial facilities. MOS were exposed to several controlled releases to test their accuracy in detecting and quantifying emissions. Two reconstruction models were compared, and emission estimates were computed using a Gaussian dispersion model. Findings show that MOS can provide accurate emission estimates with a 25 % emission rate error and a 9.5 m location error.
Rodrigo Andres Rivera Martinez, Diego Santaren, Olivier Laurent, Gregoire Broquet, Ford Cropley, Cécile Mallet, Michel Ramonet, Adil Shah, Leonard Rivier, Caroline Bouchet, Catherine Juery, Olivier Duclaux, and Philippe Ciais
Atmos. Meas. Tech., 16, 2209–2235, https://doi.org/10.5194/amt-16-2209-2023, https://doi.org/10.5194/amt-16-2209-2023, 2023
Short summary
Short summary
A network of low-cost sensors is a good alternative to improve the detection of fugitive CH4 emissions. We present the results of four tests conducted with two types of Figaro sensors that were assembled on four chambers in a laboratory experiment: a comparison of five models to reconstruct the CH4 signal, a strategy to reduce the training set size, a detection of age effects in the sensors and a test of the capability to transfer a model between chambers for the same type of sensor.
Jia He, Helene Brogniez, and Laurence Picon
Atmos. Chem. Phys., 22, 12591–12606, https://doi.org/10.5194/acp-22-12591-2022, https://doi.org/10.5194/acp-22-12591-2022, 2022
Short summary
Short summary
A 2003–2017 satellite-based atmospheric water vapour climate data record is used to assess climate models and reanalyses. The focus is on the tropical belt, whose regional variations in the hydrological cycle are related to the tropospheric overturning circulation. While there are similarities in the interannual variability, the major discrepancies can be explained by the presence of clouds, the representation of moisture fluxes at the surface and cloud processes in the models.
Chloé Radice, Hélène Brogniez, Pierre-Emmanuel Kirstetter, and Philippe Chambon
Atmos. Chem. Phys., 22, 3811–3825, https://doi.org/10.5194/acp-22-3811-2022, https://doi.org/10.5194/acp-22-3811-2022, 2022
Short summary
Short summary
A novel probabilistic approach is proposed to evaluate relative humidity (RH) profiles simulated by an atmospheric model with respect to satellite-based RH defined from probability distributions. It improves upon deterministic comparisons by enhancing the information content to enable a finer assessment of each model–observation discrepancy, highlighting significant departures within a deterministic confidence range. Geographical and vertical distributions of the model biases are discussed.
Giulia Carella, Mathieu Vrac, Hélène Brogniez, Pascal Yiou, and Hélène Chepfer
Earth Syst. Sci. Data, 12, 1–20, https://doi.org/10.5194/essd-12-1-2020, https://doi.org/10.5194/essd-12-1-2020, 2020
Short summary
Short summary
Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By providing a method to generate pseudo-observations of relative humidity at high spatial resolution, this work will help revisit some of the current key barriers in atmospheric science.
Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes
Atmos. Meas. Tech., 10, 1557–1574, https://doi.org/10.5194/amt-10-1557-2017, https://doi.org/10.5194/amt-10-1557-2017, 2017
Short summary
Short summary
The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.
François Mercier, Aymeric Chazottes, Laurent Barthès, and Cécile Mallet
Atmos. Meas. Tech., 9, 3145–3163, https://doi.org/10.5194/amt-9-3145-2016, https://doi.org/10.5194/amt-9-3145-2016, 2016
Short summary
Short summary
The aim of this study is to retrieve vertical profiles of raindrop size distributions and vertical winds from radar and ground measurements. This is crucial to understand the phenomena acting on the raindrops at small scale during their fall and then to be able to merge measurements of rain at different heights and scales (from radar, rain gauges, satellites etc.). It could also help to improve the treatment of radar data and to better parameterize rain in numerical weather prediction models.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
Short summary
Short summary
Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148, https://doi.org/10.5194/acp-14-11129-2014, https://doi.org/10.5194/acp-14-11129-2014, 2014
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument
Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data
A directional surface reflectance climatology determined from TROPOMI observations
Investigation of gravity waves using measurements from a sodium temperature/wind lidar operated in multi-direction mode
An improved BRDF hotspot model and its use in VLIDORT for studying the impact of atmospheric scattering on hotspot directional signatures in the atmosphere
A multi-decadal time series of upper stratospheric temperature profiles from Odin-OSIRIS limb-scattered spectra
CALOTRITON: a convective boundary layer height estimation algorithm from ultra-high-frequency (UHF) wind profiler data
Enhancing consistency of microphysical properties of precipitation across the melting layer in dual-frequency precipitation radar data
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
Scale separation for gravity wave analysis from 3D temperature observations in the MLT region
Radar and environment-based hail damage estimates using machine learning
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
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)
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
Broadband radiative quantities for the EarthCARE mission: the ACM-COM and ACM-RT products
HSRL-2 Retrievals of Ocean Surface Wind Speeds
Measuring rainfall using microwave links: the influence of temporal sampling
Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)
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
Noise filtering options for conically scanning Doppler LiDAR measurements with low pulse accumulation
Drone-based photogrammetry combined with deep-learning to estimate hail size distributions and melting of hail on the ground
Estimating the refractivity bias of Formosat-7/COSMIC-II GNSS Radio Occultation in the planetary boundary layer
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
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
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
Short summary
Short summary
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
Short summary
Short summary
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.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
Short summary
Short summary
Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
Short summary
Short summary
This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI 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.
Bing Cao and Alan Z. Liu
Atmos. Meas. Tech., 17, 2123–2146, https://doi.org/10.5194/amt-17-2123-2024, https://doi.org/10.5194/amt-17-2123-2024, 2024
Short summary
Short summary
A narrow-band sodium lidar measures atmospheric waves but is limited to vertical variations. We propose to utilize phase shifts among observations from different laser beams to derive horizontal wave information. Two gravity wave packets were identified by this method. Both waves were found to interact with thin evanescent layers, partially reflected, but transmitted energy to higher altitudes. The method can detect more medium-frequency gravity waves for similar lidar systems worldwide.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
Short summary
Short summary
The term “hotspot” refers to the sharp increase in 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 provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Daniel Zawada, Kimberlee Dubé, Taran Warnock, Adam Bourassa, Susann Tegtmeier, and Douglas Degenstein
Atmos. Meas. Tech., 17, 1995–2010, https://doi.org/10.5194/amt-17-1995-2024, https://doi.org/10.5194/amt-17-1995-2024, 2024
Short summary
Short summary
There remain large uncertainties in long-term changes of stratospheric–atmospheric temperatures. We have produced a time series of more than 20 years of satellite-based temperature measurements from the OSIRIS instrument in the upper–middle stratosphere. The dataset is publicly available and intended to be used for a better understanding of changes in stratospheric temperatures.
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 K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
Short summary
Short summary
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 in turbulence. It is evaluated using 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.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
Atmos. Meas. Tech., 17, 1577–1597, https://doi.org/10.5194/amt-17-1577-2024, https://doi.org/10.5194/amt-17-1577-2024, 2024
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
EGUsphere, https://doi.org/10.5194/egusphere-2024-136, https://doi.org/10.5194/egusphere-2024-136, 2024
Short summary
Short summary
The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the Mesosphere and the lower Thermosphere. The 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.
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
Short summary
Short summary
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.
Laura Mary Tomkins, Sandra E. Yuter, and Matthew A. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2888, https://doi.org/10.5194/egusphere-2023-2888, 2024
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1943, https://doi.org/10.5194/egusphere-2023-1943, 2023
Short summary
Short summary
This study introduces and evaluates a new ocean surface wind speed product from NASA Langley Research Center’s (LARC’s) airborne High Spectral Resolution Lidar – generation 2 (HSRL-2) using NASA ACTIVATE field data. We show that HSRL-2 wind speed retrievals have small errors when compared to wind speeds directly measured by NCAR AVAPS dropsondes. This novel retrieval method provides a way to obtain accurate, high resolution wind speed data in airborne field campaigns.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2023-1971, https://doi.org/10.5194/egusphere-2023-1971, 2023
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-153, https://doi.org/10.5194/amt-2023-153, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng-Yung Huang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1246, https://doi.org/10.5194/egusphere-2023-1246, 2023
Short summary
Short summary
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and their dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We proposed methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the bias under different atmospheric conditions and thus improves the applications of the GNSS RO data in the planetary boundary layer.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Aires, F. and Prigent, C.: A new neural network approach including first guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature, and emissivities over land from satellite microwave observations, J. Geophys. Res., 106, 14887–14907, 2001.
Aires, F., Bernardo, F., Brogniez, H., and Prigent, C.: An innovative calibration method for the inversion of satellite observations, J. Appl. Meteor. Climatol., 49, 2458–2473, 2010.
Aires, F., Prigent, C., Bernardo, F., Jimenez, C., Saunders, R., and Brunel, P.: A Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM) for use in numerical weather prediction, Q. J. Roy. Meteorol. Soc., 137(A), 690–699, 2011.
Aires, F., Bernardo, F., and Prigent, C.: Atmospheric water-vapour profiling from passive microwave sounders over ocean and land. Part I: Methodology for the Megha-Tropiques mission, Q. J. Roy. Meteorol. Soc., 139, 852–864, 2013.
Anandhi, A., Srinivas, V., Nanjundiah, R., and Kumar, D.: Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine, Int. J. Climatol., 28, 401–420, 2008.
Aumann, H., Chahine, M., Gautier, C., Goldberg, M., Kalnay, E., McMillin, L., Revercomb, H., Rosenkranz, P., Smith, W., Staelin, D., Strow, L., and Sussking, J.: AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products and processing systems, IEEE Trans. Geosci. Remote Sens., 41, 253–264, 2003.
Balabin, R. and Lomakina, E.: Support vector machine regression (SVR/LS-SVM). An alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data, Analyst, 136, 1703–1712, 2011.
Beckmann, B. and Buishand, T.: Statistical downscaling relationships for precipitations in The Netherlands and North Germany, Int. J. Climatol., 22, 15–32, 2002.
Belsley, D., Kuh, E., and Welsch, R.: Regression Diagnostics, in: Regression Diagnostics: identifying influential data and sources of collinearity, John Wiley & Sons Inc., 1980.
Bennartz, R. and Bauer, P.: Sensitivity of microwave radiances at 85–183 GHz to precipitating ice particles, Radio Sci., 38, 8075, https://doi.org/10.1029/2002RS002626, 2003.
Bishop, C.: Neural networks for pattern recognition, vol. 1, Clarendon Press, Oxford, 1995.
Blackwell, W.: A neural-network technique for the retrieval of atmospheric temperature and moisture profiles from high spectral resolution sounding data, IEEE Trans. Geosci. Remote Sens., 43, 2535–2546, 2005.
Blankenship, C., Al-Khalaf, A., and Wilheit, T.: Retrieval of Water Vapor Profiles Using SSM/T-2 and SSM/I Data, J. Atmos. Sci., 57, 939–955, 2000.
Brogniez, H. and Pierrehumbert, R.: Using microwave observations to assess large-scale control of free tropospheric water vapor in the mid-latitudes, Geophys. Res. Lett., 33, L14801, https://doi.org/10.1029/2006GL026240, 2006.
Brogniez, H., Kirstetter, P.-E., and Eymard, L.: Expected improvements in the atmospheric humidity profile retrieval using the Megha-Tropiques microwave payload, Q. J. Roy. Meteorol. Soc., 139, 842–851, https://doi.org/10.1002/qj.1869, 2013.
Buehler, S. and John, V. O.: A simple method to relate microwave radiances to Upper Tropospheric Humidity, J. Geophys. Res., 110, D02110, https://doi.org/10.1029/2004JD005111, 2004.
Buehler, S. A., Kuvatov, M., and John, V. O.: Comparison of microwave satellite humidity data and radiosonde profiles: A case study, J. Geophys. Res., 109, D13103, https://doi.org/10.1029/2004JD004605, 2004.
Buehler, S. A., Kuvatov, M., and John, V. O.: Scan asymmetries in AMSU-B data, Geophys. Res. Lett., 32, L24810, https://doi.org/10.1029/2005GL024747, 2005.
Cabrera-Mercadier, C. and Staelin, D.: Passive microwave relative humidity retrievals using feedforward neural networks, IEEE Trans. Geosci. Remote Sens., 33, 1324–1328, 1995.
Cawley, G. and Talbot, N.: Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters, J. Machine Learning Res., 8, 841–861, 2007.
Chen, S., Billings, S., and Luo, W.: Orthogonal least squares methods and their application to non-linear system identification, Int. J. Control, 50, 1873–1896, 1989.
Ciesielski, P., Yu, H., Johnson, R., Yoneyama, K., Katsumata, M., Long, C., Wang, J., Loehrer, S., Young, K., Williams, S., Brown, W., Braun, J., and Van Hove, T.: Quality-controlled upper-air sounding dayaset for DYNAMO/CINDY/AMIE: development and corrections, J. Atmos. Oceanic Technol., 31, 741–764, https://doi.org/10.1175/JTECH-D-13-00165.1, 2015.
Clain, G., Brogniez, H., Payne, V. H., John, V. O., and Ming, L.: An assessment of SAPHIR calibration using quality tropical soundings, J. Atmos. Oceanic Technol., 32, 61–78, https://doi.org/10.1175/JTECH-D-14-00054.1, 2015.
Davis, J., Eder, B., Nychka, D., and Yang, Q.: Modeling the effects of eteorology on Ozone in Houston using cluster analysis and generalized additive models, Atmos. Environ., 32, 2505–2520, 1998.
Deblonde, G. and English, S.: Evaluation of the FASTEM-2 fast microwave oceanic surface emissivity model, Tech. Proc., 2001.
Durre, I., Vose, R., and Wuertz, D.: Overview of the Integrated Global Radiosonde Archive, J. Climate, 19, 53–68, 2006.
English, S., Guillou, C., Prigent, C., and Jones, D.: Aircraft measurements of water vapour continuum absorption at millimetre wavelengths, Q. J. Roy. Meteorol. Soc., 120, 603–625, 1994.
Fetzer, E., Hulley, G., Lambrigsten, B., Manning, E., Blaisdell, J., Iredell, L., Sussking, J., Warner, J., Wei, Z., and Blackwell, W.: AIRS/AMSU/HSB version 6 changes from version 5, Tech. rep., NASA Jet Propulsion Laboratory, 2013.
Franquet, S.: Contribution à l'étude du cycle hydologique par radiométrie hyperfréquence: algorithme de restitution (réseaux de neurones) et validation pour la vapeur d'eau (AMSU, SAPHIR) et les précipitations (AMSU, radars au sol BALTRAD), PhD thesis, Université de Paris 7, 2003.
Gierens, K., Schumann, U., Helten, M., Smit, H., and Marenco, A.: A distribution law for relative humidity in the upper troposphere and lower stratosphere derived from three years of MOZAIC measurements, Ann. Geophys., 17, 1218–1226, https://doi.org/10.1007/s00585-999-1218-7, 1999.
Gohil, B., Gairola, R., Mathur, A., Varma, A., Mahesh, C., Gangwar, R., and Pal, P.: Algorithms for retrieving geophysical parameters from the MADRAS and SAPHIR sensors of the Megha-Tropiques satellites: Indian scenario, Q. J. Roy. Meteorol. Soc., 139, 954–963, 2013.
Goldberg, M., Crosby, D., and Zhou, L.: The Limb Adjustment of AMSU-A Observations: Methodology and Validation, J. Appl. Meteor., 40, 70–83, 2000.
Hall, A. and Manabe, S.: Effect of water vapor feedback on internal and anthropogenic variations of the global hydrological cycleø, J. Geophys. Res., 105, 6935–6944, 2000.
Hastie, T. and Tibshirani, R.: Generalized Additive Models, Chapman & Hall/CRC, 1990.
Hastie, T., Tibshirani, R., and Friedman, J.: The elements of statistical learning, Springer, 2009.
Haykin, S.: Neural Networks: A Comprehensive Foundation, IEEE Press, New York, NY, USA, 1994.
Held, I. and Soden, B.: Water vapour feedback and global warming, Annu. Rev. Energy Environn., 25, 441–475, 2000.
Held, I. and Soden, B.: Robust responses of the hydrological cycle to global warming, J. Climate, 19, 3354–3360, 2006.
Hong, G., Heygster, G., Miao, J., and Kunzi, K.: Detection of tropical deep convective clouds from AMSU-B water vapor channels measurements, J. Geophys. Res., 110, D05205, https://doi.org/10.1029/2004JD004949, 2005.
Houze, R. and Betts, A.: Convection in GATE, Rev. Geophys., 19, 541–576, 1981.
Karbou, F., Aires, F., Prigent, C., and Eymard, L.: Potential of Advanced Microwaves Sounding Unit-A (AMSU-A) and AMSU-B measurements for atmospheric temperature and humidity profiling over land, J. Geophys. Res., 110, D07109, https://doi.org/10.1029/2004JD005318, 2005.
Karouche, N., Goldstein, C., Rosak, A., Malassingne, C., and Raju, G.: Megha-Tropiques satellite mission: in flight performances results, Geosci. Remote Sens. Symposium (IGARSS), 4684–4687, https://doi.org/10.1109/IGARSS.2012.6350420, 2012.
Kohonen, T.: Self-organizing formation of topologically correct feature maps, Biological Cybernetics, 46, 59–69, 1982.
Kohonen, T.: Self-Organizing maps, Springer series in Informations Sciences, 3rd edn., 2001.
Kuo, C., Staelin, D., and Rosenkranz, P.: Statistical iterative scheme for estimating atmospheric relative humidity profiles, IEEE Transactions on Geoscience and Remote Sensing, 32, 254–260, 1994.
Laurent, R. T. and Cook, R.: Leverage, local influence and curvature in nonlinear regression, Biometrika, 80, 99–106, 1993.
Lee, Y., Wahba, G., and Ackerman, S.: Cloud classification of satellite radiance data by Multicategory Support Vectore Machines, J. Atmos. Oceanic Technol., 21, 159–169, 2004.
Liu, Q. and Weng, F.: One-dimensional variational retrieval algorithm of temperature, water vapor and cloud water profiles from Advanced Microwave Sounding Unit (AMSU), IEEE Trans. Geosci. Remote Sens., 43, 1087–1095, 2005.
Mallet, C., Moreau, E., Casagrande, L., and Klapisz, C.: Determination of integrated cloud liquid water path and total precipitable water from SSM/I data using a neural network algorithm, Int. J. Remote Sens., 23, 661–674, 1993.
Matricardi, M., Chevallier, F., Kelly, G., and Thépaut, J.: An improved general fast radiative transfer model for the assimilation of radiance observations, Am. Meteorol. Soc., 130, 153–173, 2004.
Mestre, O. and Hallegatte, S.: Predictors of tropical cyclone numbers and extreme hurricane intensities over the North Atlantic using Generalized Additive and Linear Models, J. Climate, 22, 633–648, 2009.
Moradi, I., Soden, B., Ferraro, R., Arkin, P., and Vömel, H.: Assessing the quality of humidity measurements from global operational radiosonde sensors, J. Geophys. Res., 118, 8040–8053, 2013.
Nash, J., Smout, R., Oakley, T., Pathack, B., and Kurnosenko, S.: WMO intercomparison of high quality radiosonde systems : Final report, WMO Report, p. 118, 2005.
Pierrehumbert, R. and Roca, R.: Evidence for control of Atlantic subtropical humidity by large-scale advection, Geophys. Res. Lett., 25, 4537–4540, 1998.
Pierrehumbert, R., Brogniez, H., and Roca, R.: On the relative humidity of the Earth's atmosphere, in: The Global Circulation of the Atmosphere, Princeton University Press, 143–185, 2007.
Prigent, C., Aires, F., and Rossow, W.: Land surface microwave emissivities over the globe for a decade, B. Am. Meteorol. Soc., 87, 1572–1584, 2006.
Qu, Z.: Cooperative Control of Dynamical Systems, 2009.
Read, W. G., Waters, J. W., Wu, D. L., Stone, E., Shippony, Z., Smedley, A. C., Smallcomb, C. C., Oltmans, S., Kley, D., Smit, H. G. J., Mergenthaler, J., and Karki, M.: UARS Microwave Limb Sounder upper tropospheric humidity measurement: Method and validation, J. Geophys. Res., 106, 32207–32258, 2001.
Read, W. G., Lambert, A., Bacmeister, J., Cofield, R. E., Christensen, L. E., Cuddy, D. T., Daffer, W. H., Drouin, B. J., Fetzer, E., Froidevaux, L., Fuller, R., Herman, R., Jarnot, R. F., Jiang, J. H., Jiang, Y. B., Kelly, K., Knosp, B. W., Kovalenko, L. J., Livesey, N. J., Liu, H.-C., Manney, G. L., Pickett, H. M., Pumphrey, H. C., Rosenlof, K. H., Sabounchi, X., Santee, M. L., Schwartz, M. J., Snyder, W. V., Stek, P. C., Su, H., Takacs, L. L., Thurstans, R. P., Vömel, H., Wagner, P. A., Waters, J. W., Webster, C. R., Weinstock, E. M., and Wu, D. L.: Aura Microwave Limb Sounder upper tropospheric and lower stratospheric H2O and relative humidity with respect to ice validation, J. Geophys. Res., 112, D24S35, https://doi.org/10.1029/2007JD008752, 2007.
Rieder, M. and Kirchengast, G.: Physical-statistical retrieval of water vapor profiles using SSM/T-2 sounder data, Geophys. Res. Lett., 26, 1397–1400, 1999.
Roca, R., Bergès, J.-C., Brogniez, H., Capderou, M., Chambon, P., Chomette, O., Cloché, S., Fiolleau, T., Jobard, I., Lémond, J., Ly, M., Picon, L., Raberanto, P., Szantai, A., and Viollier, M.: On the water and energy cycles in the Tropics, C.R. Geoscience, 342, 390–402, 2010.
Rumelhart, D., Hinton†, G., and Williams, R.: Learning internal representation by error propagation. in: Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1, edited by: Rumelhart, D. E. and McClelland, J. L., 1986.
Schaerer, G. and Wilheit, T. T.: A passive microwave technique for profiling of atmospheric water vapor, Radio Sci., 14, 371–375, 1979.
Schmetz, J. and Turpeinen, O.: Estimation of the Upper Tropospheric Relative Humidity field from METEOSAT water vapor image data, J. Appl. Meteor., 27, 889–899, 1988.
Scholkopf, B. and Smola, A.: Learning with Kernels, MIT Press, 2002.
Sherwood, S., Roca, R., Weckwerth, T., and Andronova, N.: Tropospheric water vapor, convection and climate, Rev. Geophys., 48, RG2001, https://doi.org/10.1029/2009RG000301, 2010.
Soden, B. and Bretherton, F.: Upper Tropospheric Relative Humidity from the GOES 6.7 Channel: Method and Climatology for July 1987, J. Geophys. Res., 98, 16669–16688, 1993.
Spencer, R. and Braswell, W.: How dry is the tropical free troposphere? Implications for a global warming theory, B. Am. Meteorol. Soc., 78, 1097–1106, 1997.
Stephens, G.: On the relationship between water vapor over the oceans and sea surface temperature, J. Climate, 3, 634–645, 1990.
Stephens, G., Jackson, D., and Wittmeyer, I.: Global observations of Upper-Tropospheric water vapor derived from TOVSQ radiance data, J. Climate, 9, 305–326, 1996.
Student: The probable error of a mean, Biometrika, 6, 1–25, 1908.
Sun, B.-Y., Huang, D.-S., and Fang, H.-T.: Lidar signal denoising using Least-Squares Support Vector Machine, IEEE Signal Processing Lett., 12, 101–104, 2005.
Suykens, J. A., Gestel, T. V., de Brabanter, J., de Moor, B., and Vandewalle, J.: Least Squares Support Vector Machines, World Scientific, 2002.
Tripathi, S., Srinivas, V., and Nanjundiah, R.: Downscaling of precipitation for climate change scenarios: a support vectore machine approach, J. Hydrol., 330, 621–640, 2006.
Ulaby, F., Moore, R., and Fung, A.: Microwave Remote Sensing Active and Passing Vol. 1: Microwave Remote Sensing Fundamentals and Radiometry, vol. 1, Addison-Wesley, 1981.
Underwood, F.: Describing long-term trends in precipitation using generalized additive models, J. Hydrol., 364, 285–297, 2009.
Van Dang, H., Lambrigsten, B., and Manning, E.: AIRS/AMSU/HSB version 6 Level 2 performance and test report, Tech. rep., NASA Jet Propulsion Laboratory, 2012.
Venkat Ratnam, M., Basha, G., Krishna Murthy, B., and Jayaraman, A.: Relative humidity distribution from SAPHIR experiment onboard Megha-Tropiques satellite mission: Comparison with global radiosonde and other satellite and reanalysis datasets, J. Geophys. Res., 118, 9622–9630, 2013.
Vrac, M., Marbaix, P., Paillard, D., and Naveau, P.: Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe, Clim. Past, 3, 669–682, https://doi.org/10.5194/cp-3-669-2007, 2007.
Wang, J. and Zhang, L.: Systematic Errors in Global Radiosonde Precipitable Water Data from Comparisons with Ground-Based GPS Measurements, J. Climate, 21, 2218–2238, 2008.
Wood, S.: Stable and efficient multiple smoothing parameter estimation for generalized additive models, J. Am. Statist. Assoc., 99, 673–686, 2004.
Wood, S.: Generalized Additive Models, an Introduction with R, Chapman & Hall/CRC, 2006.
Wun-Hua, C., Jen-Ying, S., and Soushan, W.: Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock, Inderscience Enterprises Ltd, 1, 49–67, 2006.
