Articles | Volume 8, issue 2
https://doi.org/10.5194/amt-8-837-2015
© 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-8-837-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 Feb 2015
Research article |
| 19 Feb 2015
The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
G. Panegrossi
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
D. Casella
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
F. Di Paola
Institute of Methodologies for Environmental Analysis (IMAA), Italian National Research Council (CNR), C.da S.Loja, Tito Scalo, 85050 Potenza, Italy
L. Milani
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
A. Mugnai
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
M. Petracca
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
S. Dietrich
Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), 00133 Rome, Italy
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N. Roberto, E. Adirosi, L. Baldini, D. Casella, S. Dietrich, P. Gatlin, G. Panegrossi, M. Petracca, P. Sanò, and A. Tokay
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D. Casella, G. Panegrossi, P. Sanò, L. Milani, M. Petracca, and S. Dietrich
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L. Milani, F. Porcù, D. Casella, S. Dietrich, G. Panegrossi, M. Petracca, and P. Sanò
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S. Federico, E. Avolio, M. Petracca, G. Panegrossi, P. Sanò, D. Casella, and S. Dietrich
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E. Ricciardelli, D. Cimini, F. Di Paola, F. Romano, and M. Viggiano
Hydrol. Earth Syst. Sci., 18, 2559–2576, https://doi.org/10.5194/hess-18-2559-2014, https://doi.org/10.5194/hess-18-2559-2014, 2014
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
D. Cimini, F. Romano, E. Ricciardelli, F. Di Paola, M. Viggiano, F. S. Marzano, V. Colaiuda, E. Picciotti, G. Vulpiani, and V. Cuomo
Atmos. Meas. Tech., 6, 3181–3196, https://doi.org/10.5194/amt-6-3181-2013, https://doi.org/10.5194/amt-6-3181-2013, 2013
A. Mugnai, D. Casella, E. Cattani, S. Dietrich, S. Laviola, V. Levizzani, G. Panegrossi, M. Petracca, P. Sanò, F. Di Paola, D. Biron, L. De Leonibus, D. Melfi, P. Rosci, A. Vocino, F. Zauli, P. Pagliara, S. Puca, A. Rinollo, L. Milani, F. Porcù, and F. Gattari
Nat. Hazards Earth Syst. Sci., 13, 1959–1981, https://doi.org/10.5194/nhess-13-1959-2013, https://doi.org/10.5194/nhess-13-1959-2013, 2013
E. A. Smith, H. W.-Y. Leung, J. B. Elsner, A. V. Mehta, G. J. Tripoli, D. Casella, S. Dietrich, A. Mugnai, G. Panegrossi, and P. Sanò
Nat. Hazards Earth Syst. Sci., 13, 1185–1208, https://doi.org/10.5194/nhess-13-1185-2013, https://doi.org/10.5194/nhess-13-1185-2013, 2013
M. Formenton, G. Panegrossi, D. Casella, S. Dietrich, A. Mugnai, P. Sanò, F. Di Paola, H.-D. Betz, C. Price, and Y. Yair
Nat. Hazards Earth Syst. Sci., 13, 1085–1104, https://doi.org/10.5194/nhess-13-1085-2013, https://doi.org/10.5194/nhess-13-1085-2013, 2013
A. Mugnai, E. A. Smith, G. J. Tripoli, B. Bizzarri, D. Casella, S. Dietrich, F. Di Paola, G. Panegrossi, and P. Sanò
Nat. Hazards Earth Syst. Sci., 13, 887–912, https://doi.org/10.5194/nhess-13-887-2013, https://doi.org/10.5194/nhess-13-887-2013, 2013
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Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-155, https://doi.org/10.5194/amt-2024-155, 2024
Revised manuscript accepted for AMT
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Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as framework for the examination. Our study provides guidance in the performance, uncertainties and optimisation of the methods, focusing mainly on accuracy and robustness.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Thiruvengadam Padmanabhan, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-117, https://doi.org/10.5194/amt-2024-117, 2024
Revised manuscript accepted for AMT
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This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Reunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
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We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
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The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
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Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
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The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
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The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
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This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
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This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
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We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
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Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
EGUsphere, https://doi.org/10.5194/egusphere-2024-1045, https://doi.org/10.5194/egusphere-2024-1045, 2024
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground-airborne synergy between the two instruments yielded optimal-sounding results.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae H. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-51, https://doi.org/10.5194/amt-2024-51, 2024
Revised manuscript accepted for AMT
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Radio occultation (RO) observations play an important role in monitoring climate changes and numerical weather forecasts. The residual ionospheric error (RIE) in RO measurements is critical to accurately retrieve atmospheric temperature and refractivity. This study shows that RIF impacts on temperature analysis are mainly confined to the polar stratosphere with amplitude of 1–4 K. These results further highlight the need for RO RIE correction in the modern data assimilation systems.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
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This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-37, https://doi.org/10.5194/amt-2024-37, 2024
Revised manuscript accepted for AMT
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This paper introduces a machine-learning approach to automatically isolate Nocturnal Low-Level Jets (NLLJs) using observations from Maryland’s Radar Wind Profiler (RWP) network. Initial findings identify 90 south-westerly NLLJs from May to September 2017–2021, showcasing core parameters and jet morphology. The research aims to establish a foundation for understanding the formation mechanisms of Mid-Atlantic NLLJs and their impact on air quality.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
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The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
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This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
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
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Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is 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
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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
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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
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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
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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
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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
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We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease 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
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In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
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A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Daisuke Hotta, Katrin Lonitz, and Sean Healy
Atmos. Meas. Tech., 17, 1075–1089, https://doi.org/10.5194/amt-17-1075-2024, https://doi.org/10.5194/amt-17-1075-2024, 2024
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Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a new type of GNSS observations that can detect heavy precipitation along the ray path between the emitter and receiver satellites. As a first step towards using these observations in numerical weather prediction (NWP), we developed a computer code that simulates GNSS-PRO observations from forecast fields produced by an NWP model. The quality of the developed simulator is evaluated with a number of case studies.
Mohamed Mossad, Irina Strelnikova, Robin Wing, and Gerd Baumgarten
Atmos. Meas. Tech., 17, 783–799, https://doi.org/10.5194/amt-17-783-2024, https://doi.org/10.5194/amt-17-783-2024, 2024
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This numerical study addresses observational gaps' impact on atmospheric gravity wave spectra. Three methods, fast Fourier transform (FFT), generalized Lomb–Scargle periodogram (GLS), and Haar structure function (HSF), were tested on synthetic data. HSF is best for spectra with negative slopes. GLS excels for flat and positive slopes and identifying dominant frequencies. Accurately estimating these aspects is crucial for understanding gravity wave dynamics and energy transfer in the atmosphere.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
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In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Cited articles
Anagnostou, E. N. and Krajewski, W. F.: Real-time radar rainfall estimation. Part I: Algorithm formulation, J. Atmos. Ocean. Tech., 16, 189–197, 1999.
Anders, U. and Korn, O.: Model selection in neural networks, Neural Netw., 12, 309–323, 1999.
Bauer, P., Moreau, E., and Di Michele, S.: Hydrometeor retrieval accuracy using microwave window and sounding channel observations, J. Appl. Meteorol., 44, 1016–1032, https://doi.org/10.1175/JAM2257.1, 2005.
Bellerby, T. J.: Satellite rainfall uncertainty estimation using an artificial neural network, J. Hydrometeorol., 8, 1397–1412, 2007.
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.
Bennartz, R. and Petty, G. W.: The sensitivity of microwave remote sensing observations of precipitation to ice particle size distributions, J. Appl. Meteorol., 40, 345–364, 2001.
Blackwell, W. J. and Chen, F. W.: Neural network applications in high-resolution atmospheric remote sensing, Lincoln Lab. J., 15, 299–322, 2005.
Burns, B. A., Wu, X., and Diak, G. R.: Effects of precipitation and cloud ice on brightness temperatures in AMSU moisture channels, IEEE T. Geosci. Remote, 35, 1429–1437, 1997.
Casella, D., Dietrich, S., Formenton, M., Mugnai, A., Panegrossi, G., Sanò, P., Smith, E. A., and Tripoli G. J.: Verification of Cloud Dynamics and Radiation Database (CDRD) passive microwave precipitation retrieval algorithm using TRMM satellite radar and radiometer measurements over Southern Mediterranean Basin, Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2012 12th Specialist Meeting, 1–4, 2012.
Casella, D., Panegrossi, G., Sanò, P., Mugnai, A., Smith, E. A., Tripoli, G. J., Dietrich, S., Formenton, M., Leung, W. Y., and Mehta, A.: Transitioning from CRD to CDRD in bayesian retrieval of rainfall from satellite passive microwave measurements: Part 2. Overcoming database profile selection ambiguity by consideration of meteorological control on microphysics, IEEE T. Geosci. Remote, 51, 4650–4671, 2013.
Casella, D., Panegrossi, G., Sanò, P., Milani, L., Petracca, M., and Dietrich, S.: A novel algorithm for detection of precipitation in tropical regions using PMW radiometers, Atmos. Meas. Tech. Discuss., 7, 9237–9274, https://doi.org/10.5194/amtd-7-9237-2014, 2014.
Chen, F. W. and Staelin, D. H.: AIRS/AMSU/HSB precipitation estimates, IEEE T. Geosci. Remote, 41, 410–417, 2003.
Chen, Y., Aires, F., Francis, J. A., and Miller, J. R.: Observed relationships between artic longwave cloud forcing and cloud parameters using a neural network, J. Climate, 19, 4087–4104, 2006.
Deeter, M. N. and Vivekanandan, J.: AMSU-B Observations of mixed-phase clouds over land, J. Appl. Meteorol., 44, 72–85, 2005.
Di Tommaso, E., Romano, F., and Cuomo, V.: Rainfall estimation from satellite passive microwave observations in the range 89 GHz to 190 GHz, J. Geophys. Res., 114, D18203, https://doi.org/10.1029/2009JD011746, 2009.
Ferraro, R. R.: The Status of the NOAA/NESDIS Operational AMSU Precipitation Algorithm, 2nd Workshop of the International Precipitation Working Group, Monterey, 9 pp., 2004.
Ferraro, R. R. and Marks, G. F.: The development of SSM/I rain-rate retrieval algorithms using ground-based radar measurements, J. Atmos. Ocean. Tech., 12, 755–770, 1995.
Ferraro, R. R., Smith, E. A., Berg, W., and Huffman, G. J.: A screening methodology for passive microwave precipitation retrieval algorithms, J. Atmos. Sci., 55, 1583–1600, 1998.
Ferraro, R. R., Weng, F., Grody, N. C., and Zhao, L.: Precipitation characteristics over land from the NOAA-15 AMSU sensor, Geophys. Res. Lett., 27, 2669–2672, 2000.
Ferraro, R. R., Weng, F., Grody, N. C., Zhao, L., Meng, H., Kongoli, C., Pellegrino, P., Qiu, S., and Dean, C.: NOAA operational hydrological products derived from the advanced microwave sounding unit, IEEE T. Geosci. Remote, 43, 1036–1049, 2005.
Funatsu, B. M., Claud, C., and Chaboureau, J.-P.: Potential of Advanced Microwave Sounding Unit to identify precipitating systems and associated upper-level features in the Mediterranean region: case studies, J. Geophys. Res., 112, D17113, https://doi.org/10.1029/2006JD008297, 2007.
Funatsu, B. M., Claud, C., and Chaboureau, J.-P.: Comparison between the large-scale environments of moderate and intense precipitating systems in the Mediterranean region, Mon. Weather Rev., 137, 3933–3959, 2009.
Funatsu, B. M., Dubreuil, V., Claud, C., Arvor, D., and Gan, M. A.: Convective activity in Mato Grosso state (Brazil) from microwave satellite observations: comparisons between AMSU and TRMM data sets, J. Geophys. Res., 117, D16109, https://doi.org/10.1029/2011JD017259, 2012.
Goldberg, M. D., Crosby, D. S., and Zhou, L.: The limb adjustment of AMSU-A observations: methodology and validation, J. Appl. Meteorol., 40, 70–83, 2001.
Greenwald, T. J. and Christopher, S. A.: Effect of cold clouds on satellite measurements near 183 GHz, J. Geophys. Res.-Atmos., 107, AAC 3/1–AAC 3/8, 2002.
Grody, N., Weng, F., and Ferraro, R.: Application of AMSU for obtaining hydrological parameters, in: Microwave Radiometry and Remote Sensing of the Earth's Surface and Atmosphere, edited by: Pampaloni, P. and Paloscia, S., VSP, 339–352, 2000.
Hair, J. F., Tatham, R. L., Anderson, R. E., and Black, W.: Multivariate Data Analysis, 5th Edition, Prentice Hall, Inc., ISBN-13: 978-0138948580, 1998.
Hong, G., Heygster, G., Miao, J., and Kunzl, K.: Detection of tropical deep convective clouds from AMSU-B vater vapor channels measurements, J. Geophys. Res., 110, D05205, https://doi.org/10.1029/2004JD004949, 2005.
Hong, Y., Hsu, K.-L., Sorooshian, S., and Gao, X.: Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system, J. Appl. Meteorol., 43, 1834–1853, 2004.
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The global precipitation measurement mission, B. Am. Meteorol. Soc., 95, 701–722, https://doi.org/10.1175/BAMS-D-13-00164.1, 2014.
Hsu, K.-L., Gao, X., Sorooshian, S., and Gupta, H. V.: Precipitation estimation from remotely sensed information using artificial neural networks, J. Appl. Meteorol., 36, 1176–1190, 1997.
Johnson, B. T., Petty, G. W., and Skofronick-Jackson, G.: Microwave properties of ice-phase hydrometeors for radar and radiometers: sensitivity to model assumptions, J. Appl. Meteorol. Climatol., 51, 2152–2171, https://doi.org/10.1175/JAMC-D-11-0138.1, 2012.
Jolliffe, I. T.: Principal Component Analysis, 2nd Edition, Springer Series in Statistics, ISBN-13: 978-0387954424, 2002.
Kongoli, C., Pellegrino, P., Ferraro, R. R., Grody, N. C., and Meng, H.: A new snowfall detection algorithm over land using measurements from the Advanced Microwave Sounding Unit (AMSU), Geophys. Res. Lett., 30, L1756, https://doi.org/10.1029/2003GL017177, 2003.
Kongoli, C., Ferraro, R. R., Pellegrino, P., Meng, H., and Dean, C.: Utilization of the AMSU high frequency measurements for improved coastal rain retrievals, Geophys. Res. Lett., 34, L17809, https://doi.org/10.1029/2007GL029940, 2007.
Krasnopolsky, V. M., Fox-Rabinovitz, M. S., and Belochitski, A. A.: Decadal climate simulations using accurate and fast neural network emulation of full, longwave and shortwave, radiation, Mon. Weather Rev., 136, 3683–3695, https://doi.org/10.1175/2008MWR2385.1, 2008.
Kulie, M. S., Bennartz, R., Greenwald, T. J., Chen, Y., and Weng, F.: Uncertainties in microwave properties of frozen precipitation: implications for remote sensing and data assimilation, J. Atmos. Sci., 67, 3471–3487, https://doi.org/10.1175/2010JAS3520.1, 2010.
Kummerow, C., Simpson, J., Thiele, O., Barnes, W., Chang, A. T. C., Stocker, E., Adler, R. F., Hou, A., Kakar, R., Wentz, F., Ashcroft, P., Kozu, T., Hong, Y., Okamoto, K., Iguchi, T., Kuroiwa, H., Im, E., Haddad, Z., Huffman, G., Ferrier, B., Olson, W. S., Zipser, E., Smith, E. A., Wilheit, T. T., North, G., Krishnamurti, T., and Nakamura, K.: The Status of the tropical rainfall measuring mission (TRMM) after two years in orbit, J. Appl. Meteorol., 39, 1965–1982, 2000.
Kummerow, C., Hong, Y., Olson, W. S., Yang, S., Adler, R. F., McCollum, J., Ferraro, R., Petty, G., Shin, D. B., and Wilheit, T. T.: The evolution of the Goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors, J. Appl. Meteorol., 40, 1801–1820, 2001.
Laviola S. and Levizzani, V.: The 183-WLS fast rain rate retrieval algorithm. Part I: Retrieval design, Atmos. Res., 99, 443–461, 2011.
Leslie, R. V., Blackwell, W. J., Bickmeier, L. J., and Jaram, L. G.: Neural network microwave precipitation retrievals and modeling results, Proc. SPIE, 7154, 715406-8, https://doi.org/10.1117/12.804815, 2008.
Lin X. and Hou, A. Y.: Evaluation of coincident passive microwave estimates using TRRM PR and ground measurements as references, J. Appl. Meteorol. Climatol., 47, 3170–3187, 2008.
Marzano, F. S., Mugnai, A., Panegrossi, G., Pierdicca, N., Smith, E. A., and Turk, J.: Bayesian estimation of precipitating cloud parameters from combined measurements of spaceborne microwave radiometer and radar, IEEE T. Geosci. Remote, 37, 596–612, 1999.
Marzban C.: Basic statistics and basic AI: neural networks, in: Artificial Intelligence Methods in the Environmental Science, edited by: Haupt, S. E., Pasini, A., and Marzban, C., Springer, 15–47, 2009.
Mugnai, A., Cooper, H. J., Smith, E. A., and Tripoli, G. J.: Simulation of microwave brightness temperatures of an evolving hailstorm at SSM/I frequencies, B. Am. Meteorol. Soc., 71, 2–13, 1990.
Mugnai, A., Smith, E. A., and Tripoli, G. J.: Foundations for statistical physical precipitation retrieval from passive microwave satellite measurement. Part II : Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model, J. Appl. Meteorol, 32, 17–39, 1993.
Mugnai, A., Di Michele, S., Marzano, F. S., and Tassa, A.: Cloud-model based Bayesian techniques for precipitation profile retrieval from TRMM microwave sensors, Proc. ECMWF/EuroTRMM Workshop on Assimilation of Clouds and Precipitation, ECMWF, Reading, UK, 323–345, 2001.
Mugnai, A., Casella, D., Cattani, E., Dietrich, S., Laviola, S., Levizzani, V., Panegrossi, G., Petracca, M., Sanò, P., Di Paola, F., Biron, D., De Leonibus, L., Melfi, D., Rosci, P., Vocino, A., Zauli, F., Pagliara, P., Puca, S., Rinollo, A., Milani, L., Porc\`u, F., and Gattari, F.: Precipitation products from the hydrology SAF, Nat. Hazards Earth Syst. Sci., 13, 1959–1981, https://doi.org/10.5194/nhess-13-1959-2013, 2013a.
Mugnai, A., Smith, E. A., Tripoli, G. J., Bizzarri, B., Casella, D., Dietrich, S., Di Paola, F., Panegrossi, G., and Sanò, P.: CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations, Nat. Hazards Earth Syst. Sci., 13, 887–912, https://doi.org/10.5194/nhess-13-887-2013, 2013b.
Nurmi, P.: Recommendations on the verification of local weather forecasts, 11 ECMWF Tech. Memo. N. 430, 19 pp., 2003.
Panegrossi, G., Dietrich, S., Marzano, F. S., Mugnai, A., Smith, E. A., Xiang, X., Tripoli, G. J., Wang, P. K., and Poiares Baptista, J. V. P.: Use of cloud model microphysics for passive microwave-based precipitation retrieval: significance of consistency between model and measurement manifolds, J. Atmos. Sci., 55, 1644–1673, 1998.
Panegrossi, G., Casella, D., Dietrich, S., Sanò, P., Petracca, M., and Mugnai, A.: A verification study over Europe of AMSU/MHS and SSMIS passive microwave precipitation retrieval, Proc. 2013 Joint EUMETSAT/AMS Meteorological Satellite Conference, 8 pp., 2013.
Panegrossi, G., Casella, D., Dietrich, S., Marra, A. C., Milani, L., Petracca, M., Sanò, P., and Mugnai, A.: CDRD and PNPR passive microwave precipitation retrieval algorithms: extension to the MSG full disk area, Proc. 2014 EUMETSAT Meteorological Satellite Conference, Geneva, https://www.eumetsat.int/website/home/News/ConferencesandEvents/DAT_2076129.html, last access: 18 February 2014.
Porc\`u, F., Milani, L., and Petracca, M.: On the uncertainties in validating satellite instantaneous rainfall estimates with raingauge operational network, Atmos. Res., 144, 73–81, https://doi.org/10.1016/j.atmosres.2013.12.007, 2014.
Puca, S., Porcu, F., Rinollo, A., Vulpiani, G., Baguis, P., Balabanova, S., Campione, E., Ertürk, A., Gabellani, S., Iwanski, R., Jurašek, M., Kaňák, J., Kerényi, J., Koshinchanov, G., Kozinarova, G., Krahe, P., Lapeta, B., Lábó, E., Milani, L., Okon, L'., Öztopal, A., Pagliara, P., Pignone, F., Rachimow, C., Rebora, N., Roulin, E., Sönmez, I., Toniazzo, A., Biron, D., Casella, D., Cattani, E., Dietrich, S., Di Paola, F., Laviola, S., Levizzani, V., Melfi, D., Mugnai, A., Panegrossi, G., Petracca, M., Sanò, P., Zauli, F., Rosci, P., De Leonibus, L., Agosta, E., and Gattari, F.: The validation service of the hydrological SAF geostationary and polar satellite precipitation products, Nat. Hazards Earth Syst. Sci., 14, 871–889, https://doi.org/10.5194/nhess-14-871-2014, 2014.
Qiu, S., Pellegrino, P., Ferraro, R., and Zhao, L.: The improved AMSU rain-rate algorithm and its evaluation for a cool season event in the Western United States, Weather Forecast., 20, 761–774, 2005.
Rachimow, C. and Krahe, P.: Validation report for H-SAF product H01 (PR-OBS-1, precipitation rate at ground) in Germany, Federal Institute of Hydrology (BfG), Koblenz, p. 16, 2011.
Rebora, N., Molini, L., Casella, E., Comellas, A., Fiori, E., Pignone, F., Siccardi, F., Silvestro, F., Tanelli, S., and Parodi, A.: Extreme rainfall in the Mediterranean: what can we learn from observations?, J. Hydrometeorol., 14, 906–922, https://doi.org/10.1175/JHM-D-12-083.1, 2013.
Rinollo, A., Vulpiani, G., Puca, S., Pagliara, P., Kaňák, J., Lábó, E., Okon, L'., Roulin, E., Baguis, P., Cattani, E., Laviola, S., and Levizzani, V.: Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation, Nat. Hazards Earth Syst. Sci., 13, 2695–2705, https://doi.org/10.5194/nhess-13-2695-2013, 2013.
Rosenkranz, P. W.: Rapid radiative transfer model for AMSU/HSB channels, IEEE T. Geosci. Remote, 41, 362–368, 2003.
Sanò, P., Casella, D., Mugnai, A., Schiavon, G., Smith, E. A., and Tripoli, G. J.: Transitioning from CRD to CDRD in bayesian retrieval of rainfall from satellite passive microwave measurements: Part 1. Algorithm description and testing, IEEE T. Geosci. Remote, 51, 4119–4143, 2013.
Shi, L.: Retrieval of atmospheric temperature profiles from AMSU-A measurement using a neural network approach, J. Atmos. Ocean. Tech., 18, 340–347, 2001.
Skofronick-Jackson, G. and Johnson, B. T.: Surface and atmospheric contributions to passive microwave brightness temperatures for falling snow events, J. Geophys. Res., 116, D02213, https://doi.org/10.1029/2010JD014438, 2011.
Skofronick-Jackson, G. M., Johnson, B. T., and Munchak, S. J.: Detection thresholds of falling snow from satellite-borne active and passive sensors, IEEE T. Geosci. Remote, 51, 4177–4189, https://doi.org/10.1109/TGRS.2012.2227763, 2013.
Smith, E. A., Lamm, J. E, Adler, R., Alishouse, J., Aonashi, K., Barrett, E., Bauer, P., Berg, W., Chang, A., Ferraro, R., Ferriday, J., Goodman, S., Grody, N., Kidd, C., Kniveton, D., Kummerow, C., Liu, G., Marzano, F. S., Mugnai, A., Olson, W., Petty, G., Shibata, A., Spencer, R., Wentz, F., Wilheit, T., and Zipser, E.: Results of WetNet PIP-2 project, J. Atmos. Sci., 55, 1483–1536, 1998.
Smith, E. A., Bauer, P., Marzano, F. S., Kummerow, C. D., McKague, D., Mugnai, A., and Panegrossi, G.: Intercomparison of microwave radiative transfer models for precipitating clouds, IEEE T. Geosci. Remote, 40, 541–549, 2002.
Smith, E. A., Leung, H. W.-Y., Elsner, J. B., Mehta, A. V., Tripoli, G. J., Casella, D., Dietrich, S., Mugnai, A., Panegrossi, G., and Sanò, P.: Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 3 –Identification of optimal meteorological tags, Nat. Hazards Earth Syst. Sci., 13, 1185–1208, https://doi.org/10.5194/nhess-13-1185-2013, 2013.
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V., Imam, B., and Braithwaite, D.: Evaluation of PERSIANN system satellite-based estimates of tropical rainfall, B. Am. Meteorol. Soc., 81, 2035–2046, 2000.
Staelin, D. H. and Chen, F. W.: Precipitation observations near 54 and 183 GHz using the NOAA-15 satellite, IEEE T. Geosci. Remote, 38, 2322–2332, 2000.
Staelin, D. H. and Surussavadee, C.: Precipitation retrieval accuracies for geo-microwave sounders, IEEE T. Geosci. Remote, 45, 3150–3159, 2007.
Staelin, D. H., Chen, F. W., and Fuentes, A.: Precipitation measurements using 183-GHz AMSU satellite observations, Geoscience and Remote Sensing Symposium 1999, IGARSS '99 Proceedings. IEEE 1999 International, 4, 2069–2071, 1999.
Stephens, G. L. and Kummerow, C. D.: The remote sensing of clouds and precipitation from space: a review, J. Atmos. Sci., 64, 3742–3765, 2007.
Surussavadee, C. and Staelin, D. H.: Millimeter-wave precipitation retrievals and observed-vs.-simulated radiance distributions: sensitivity to assumptions, J. Atmos. Sci., 64, 3808–3826, 2007.
Surussavadee, C. and Staelin, D. H.: Global millimeter-wave precipitation retrievals trained with a cloud-resolving numerical weather prediction model, Part I: Retrieval design, IEEE T. Geosci. Remote, 46, 99–108, 2008a.
Surussavadee, C. and Staelin, D. H.: Global millimeter-wave precipitation retrievals trained with a cloud-resolving numerical weather prediction model, Part II: Performance evaluation, IEEE T. Geosci. Remote, 46, 109–118, 2008b.
Surussavadee, C. and Staelin, D. H.: Satellite Retrievals of Artic and Equatorial Rain and Snowfall Rates Using Millimeter Wavelengths, IEEE Trans. Geosci. Remote Sens., 47, 3697–3707, 2009.
Surussavadee, C. and Staelin, D. H.: Global precipitation retrievals using the NOAA AMSU millimeter-wave channels: comparisons with rain gauges, J. Appl. Meteorol. Climatol., 49, 124–135, 2010.
Surussavadee, C., Blackwell, W. J., Entekhabi, D., and Leslie, R. V.: A global precipitation retrieval algorithm for SUOMI NPP ATMS, IGARSS 2012, IEEE International Geoscience and Remote Sensing Symposium, https://doi.org/10.1109/IGARSS.2012.6351128, Munich, 2012.
Tripoli, G. J.: A nonhydrostatic mesoscale model designed to simulate scale interaction, Mon. Weather Rev., 120, 1342–1359, 1992.
Tripoli, G. J. and Smith, E. A.: Introducing Variable-Step Topography (VST) coordinates within dynamically constrained Nonhydrostatic Modeling Systems (NMW), part 1: VST formulation within NMS host model framework, Dynam. Atmos. Oceans, 66, 28–57, https://doi.org/10.1016/j.dynatmoce.2014.01.001, 2014a.
Tripoli, G. J. and Smith, E. A.: Introducing Variable-Step Topography (VST) coordinates within dynamically constrained Nonhydrostatic Modeling Systems (NMW), part 2: VST performance on orthodox obstacle flows, Dynam. Atmos. Oceans, 66, 10–27, https://doi.org/10.1016/j.dynatmoce.2014.01.003, 2014b.
Wang, J. R., Wilheit, T. T., and Chang, L. A.: Retrieval of total precipitable water using radiometric measurements near 92 and 183 GHz, J. Appl. Meteorol., 28, 146–154, 1989.
Wang, J. R., Zhan, J., and Racette, P.: Storm-associated microwave radiometric signatures in the frequency range of 90–220 GHz, J. Atmos. Ocean. Tech., 14, 13–31, 1997.
Weng, F. and Grody, N. C.: Retrieval of ice cloud parameters using a microwave imaging radiometer, J. Atmos. Sci., 57, 1069–1081, 2000.
Weng, F., Zhao, L., Ferraro, R. R., Poe, G., Li, X., and Grody, N. C.: Advanced microwave sounding unit cloud and precipitation algorithms, Radio Sci., 38, 8068–8079, 2003.
Wilheit, T., Adler, R., Avery, S., Barret, E., Bauer, P., Berg, W., Chang, A., Ferriday, J., Grody, N., Goodman, S., Kidd, C., Kniveton, D., Kummerow, C., Mugnai, A., Olson, W., Petty, G., Shibata, A., and Smith, E.: Algorithms for the retrieval of rainfall from passive microwave measurements, Remote Sensing Rev., 11, 163–194, 1994.
Wilks, D. S.: Statistical methods in the atmospheric sciences: an introduction, Academic Press, ISBN: 0-12-751965-3, 1995.
Young, G. S.: Implementing a neural network emulation of a satellite retrieval algorithm, in: Artificial Intelligence Methods in the Environmental Science, edited by: Haupt, S. E., Pasini, A., and Marzban C., Springer, 207–216, 2009.
Zhao, L. and Weng, F.: Retrieval of ice cloud parameters using the advanced microwave sounding unit, J. Appl. Meteorol., 41, 384–395, 2002.
