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.
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 Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
Rodrigo Rivera-Martinez, Pramod Kumar, Olivier Laurent, Gregoire 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., 17, 4257–4290, https://doi.org/10.5194/amt-17-4257-2024, https://doi.org/10.5194/amt-17-4257-2024, 2024
Short summary
Short summary
We explore the use of metal oxide semiconductors (MOSs) as a low-cost alternative for detecting and measuring CH4 emissions from industrial facilities. MOSs 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 MOSs can provide accurate emission estimates with a 25 % emission rate error and a 9.5 m location error.
Louise Gelbart, Laurent Barthès, François Mercier-Tigrine, Aymeric Chazottes, and Cecile Mallet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-88, https://doi.org/10.5194/amt-2024-88, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
In this paper, we present and evaluate a new method for the quantitative estimation of precipitation from a low-cost sensor. Based on previous work measuring the attenuation of an electromagnetic signal from a broadcast television satellite, we make this approach more accurate so that to be easily deployed and used operationally in areas where rainfall measurements are critical for applications like flood monitoring. In this article, the method is validated in France and applied in Ivory Coast.
Maurin Zouzoua, Sophie Bastin, Marjolaine Chiriaco, Fabienne Lohou, Marie Lothon, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
EGUsphere, https://doi.org/10.5194/egusphere-2024-568, https://doi.org/10.5194/egusphere-2024-568, 2024
Short summary
Short summary
This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observation and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
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
An improved geolocation methodology for spaceborne radar and lidar systems
Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products
HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution
Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT
Retrieval of pseudo-BRDF-adjusted surface reflectance at 440 nm from the Geostationary Environmental Monitoring Spectrometer (GEMS)
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Global sensitivity analysis of simulated remote sensing polarimetric observations over snow
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
Limitations in wavelet analysis of non-stationary atmospheric gravity wave signatures in temperature profiles
A new non-linearity correction method for the spectrum from the Geostationary Inferometric Infrared Sounder on board Fengyun-4 satellites and its preliminary assessments
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM-RAD product
Variance estimations in the presence of intermittent interference and their applications to incoherent scatter radar signal processing
A clustering-based method for identifying and tracking squall lines
A multi-instrument fuzzy logic boundary-layer-top detection algorithm
Aeolus Lidar Surface Returns (LSR) at 355 nm as a new Aeolus L2A Phase-F product
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Scale separation for gravity wave analysis from 3D temperature observations in the mesosphere and lower thermosphere (MLT) region
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation
Retrieval of top-of-atmosphere fluxes from combined EarthCARE LiDAR, imager and broadband radiometer observations: the BMA-FLX product
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation
Measuring rainfall using microwave links: the influence of temporal sampling
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Improving solution availability and temporal consistency of an optimal estimation physical retrieval for ground-based thermodynamic boundary layer profiling
Determination of low-level temperature profiles from microwave radiometer observations during rain
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
Sampling the diurnal and annual cycles of the Earth’s energy imbalance with constellations of satellite-borne radiometers
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
Observations of Tall-Building Wakes Using a Scanning Doppler Lidar
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
Analysis of the measurement uncertainty for a 3D wind-LiDAR
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
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
Short summary
Short summary
The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
Short summary
Short summary
We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
Short summary
Short summary
The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
Short summary
Short summary
We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
Short summary
Short summary
This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
Short summary
Short summary
A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
Short summary
Short summary
Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
Short summary
Short summary
We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
Short summary
Short summary
A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
Short summary
Short summary
We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
Short summary
Short summary
Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
Short summary
Short summary
Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
Short summary
Short summary
Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
Short summary
Short summary
The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
Short summary
Short summary
We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
Short summary
Short summary
The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
Short summary
Short summary
Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
EGUsphere, https://doi.org/10.5194/egusphere-2024-1926, https://doi.org/10.5194/egusphere-2024-1926, 2024
Short summary
Short summary
The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm, producing Aeolus lidar surface returns (LSR) containing useful information for measuring UV reflectivity. Aeolus LSR matched well with existing UV reflectivity data from other satellites like GOME-2 and TROPOMI and demonstrated excellent sensitivity to modelled snow cover.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
Short summary
Short summary
The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
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 lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
Short summary
Short summary
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
Short summary
Short summary
This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
EGUsphere, https://doi.org/10.5194/egusphere-2024-1539, https://doi.org/10.5194/egusphere-2024-1539, 2024
Short summary
Short summary
This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along-track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft) are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
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.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
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.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
Short summary
Short summary
This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
EGUsphere, https://doi.org/10.5194/egusphere-2024-714, https://doi.org/10.5194/egusphere-2024-714, 2024
Short summary
Short summary
Profiles of temperature and humidity in the atmospheric boundary layer can be retrieved from passive ground-based remote sensors such as microwave radiometers and infrared spectrometers. In this work, we present improvements to the optimal estimation physical retrieval framework TROPoe, which increase the availability of retrieved profiles and temporal consistency and enhance the value of TROPoe for the study of atmospheric processes.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2024-919, https://doi.org/10.5194/egusphere-2024-919, 2024
Short summary
Short summary
Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. Here, we present a method based on a selection of specific frequencies and elevation angles from the microwave radiometer observation. A comparison with a numerical weather prediction model shows that the presented method allows to resolve temperature profiles during rain with rain rates up to 2 mm h−1 which was not possible before with state-of-the-art retrievals.
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.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
EGUsphere, https://doi.org/10.5194/egusphere-2024-356, https://doi.org/10.5194/egusphere-2024-356, 2024
Short summary
Short summary
The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back to space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance, and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
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.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
EGUsphere, https://doi.org/10.5194/egusphere-2024-937, https://doi.org/10.5194/egusphere-2024-937, 2024
Short summary
Short summary
A doppler lidar was placed in highly built-up area in London to measure wakes from tall buildings during a period of one year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
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.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-184, https://doi.org/10.5194/amt-2023-184, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind-LiDAR designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose an optimized post-processing for error reduction.
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.
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.
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.
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.