Articles | Volume 7, issue 9
https://doi.org/10.5194/amt-7-2919-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/amt-7-2919-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Sep 2014
Research article |
| 12 Sep 2014
Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR
I. Maiello
Centre of Excellence CETEMPS, L'Aquila, Italy
R. Ferretti
Centre of Excellence CETEMPS, L'Aquila, Italy
Department of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy
S. Gentile
Centre of Excellence CETEMPS, L'Aquila, Italy
M. Montopoli
Centre of Excellence CETEMPS, L'Aquila, Italy
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy
E. Picciotti
Centre of Excellence CETEMPS, L'Aquila, Italy
HIMET s.r.l., L'Aquila, Italy
F. S. Marzano
Centre of Excellence CETEMPS, L'Aquila, Italy
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy
C. Faccani
ENAV S.p.A. – Academy, Forlì, Italy
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Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
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Winds that are crucial to weather forecasting derived from two different techniques – tracking satellite images (AMVs) and direct measurement of molecular and aerosol motions by Doppler lidar (Aeolus satellite winds) – are compared. We find that AMVs and Aeolus winds are highly correlated. Aeolus Mie-cloudy winds have great potential value as a comparison standard for AMVs. Larger differences are found in the Southern Hemisphere related to higher wind speed and higher vertical variation in wind.
Marijn Floris van Dooren, Anantha Padmanabhan Kidambi Sekar, Lars Neuhaus, Torben Mikkelsen, Michael Hölling, and Martin Kühn
Atmos. Meas. Tech., 15, 1355–1372, https://doi.org/10.5194/amt-15-1355-2022, https://doi.org/10.5194/amt-15-1355-2022, 2022
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The remote sensing technique lidar is widely used for wind speed measurements for both industrial and academic applications. Lidars can measure wind statistics accurately but cannot fully capture turbulent fluctuations in the high-frequency range, since they are partly filtered out. This paper therefore investigates the turbulence spectrum measured by a continuous-wave lidar and analytically models the lidar's measured spectrum with a Lorentzian filter function and a white noise term.
Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
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This study uses collocated ship-based, ground-based, and spaceborne radar observations to validate the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks to the accuracy required for operational severe weather applications such as rainfall and hail nowcasting.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
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The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Songhua Wu, Kangwen Sun, Guangyao Dai, Xiaoye Wang, Xiaoying Liu, Bingyi Liu, Xiaoquan Song, Oliver Reitebuch, Rongzhong Li, Jiaping Yin, and Xitao Wang
Atmos. Meas. Tech., 15, 131–148, https://doi.org/10.5194/amt-15-131-2022, https://doi.org/10.5194/amt-15-131-2022, 2022
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During the VAL-OUC campaign, we established a coherent Doppler lidar (CDL) network over China to verify the Level 2B (L2B) products from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations, the L2B products from Aeolus are compared with those from CDLs. To our knowledge, the VAL-OUC campaign is the most extensive so far between CDLs and Aeolus in the lower troposphere for different atmospheric scenes. The vertical velocity impact on the HLOS retrieval from Aeolus is evaluated.
Karina Wilgan, Galina Dick, Florian Zus, and Jens Wickert
Atmos. Meas. Tech., 15, 21–39, https://doi.org/10.5194/amt-15-21-2022, https://doi.org/10.5194/amt-15-21-2022, 2022
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The assimilation of GNSS data in weather models has a positive impact on the forecasts. The impact is still limited due to using only the GPS zenith direction parameters. We calculate and validate more advanced tropospheric products from three satellite systems: the US American GPS, Russian GLONASS and European Galileo. The quality of all the solutions is comparable; however, combining more GNSS systems enhances the observations' geometry and improves the quality of the weather forecasts.
Hironori Iwai, Makoto Aoki, Mitsuru Oshiro, and Shoken Ishii
Atmos. Meas. Tech., 14, 7255–7275, https://doi.org/10.5194/amt-14-7255-2021, https://doi.org/10.5194/amt-14-7255-2021, 2021
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The first space-based Doppler wind lidar on board the Aeolus satellite was launched on 22 August 2018 to obtain global horizontal wind profiles. In this study, wind profilers, ground-based coherent Doppler wind lidars, and GPS radiosondes were used to validate the quality of Aeolus Level 2B wind products over Japan during three different periods. The results show that Aeolus can measure the horizontal winds over Japan accurately.
Tim A. van Kempen, Filippo Oggionni, and Richard M. van Hees
Atmos. Meas. Tech., 14, 6711–6722, https://doi.org/10.5194/amt-14-6711-2021, https://doi.org/10.5194/amt-14-6711-2021, 2021
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Validation of the instrument stability of the TROPOMI-SWIR module is done by monitoring a group of very stable and remote locations in the Saharan and Arabian deserts. These results confirm the excellent stability and lack of degradation of the TROPOMI-SWIR module derived from the internal calibration sources. The method was done for the first time on a spectrometer in the short-wave infrared and ensures TROPOMI-SWIR can be used for atmospheric research for years to come.
Susanna Hagelin, Roohollah Azad, Magnus Lindskog, Harald Schyberg, and Heiner Körnich
Atmos. Meas. Tech., 14, 5925–5938, https://doi.org/10.5194/amt-14-5925-2021, https://doi.org/10.5194/amt-14-5925-2021, 2021
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In this paper we study the impact of using wind observations from the Aeolus satellite, which provides wind speed profiles globally, in our numerical weather prediction system using a regional model covering the Nordic countries. The wind speed profiles from Aeolus are assimilated by the model, and we see that they have an impact on both the model analysis and forecast, though given the relatively few observations available the impact is often small.
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756, https://doi.org/10.5194/amt-14-5735-2021, https://doi.org/10.5194/amt-14-5735-2021, 2021
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Observation errors (OEs) of radar measurements are correlated. The Desroziers method has been often used to estimate statistics of OE in data assimilation. However, the resulting statistics consist of contributions from different sources and are difficult to interpret. Here, we use an approach based on samples for truncation error to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with OE statistics estimated by the Desroziers method.
Evgenia Belova, Sheila Kirkwood, Peter Voelger, Sourav Chatterjee, Karathazhiyath Satheesan, Susanna Hagelin, Magnus Lindskog, and Heiner Körnich
Atmos. Meas. Tech., 14, 5415–5428, https://doi.org/10.5194/amt-14-5415-2021, https://doi.org/10.5194/amt-14-5415-2021, 2021
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Wind measurements from two radars (ESRAD in Arctic Sweden and MARA at the Indian Antarctic station Maitri) are compared with lidar winds from the ESA satellite Aeolus, for July–December 2019. The aim is to check if Aeolus data processing is adequate for the sunlit conditions of polar summer. Agreement is generally good with bias in Aeolus winds < 1 m/s in most circumstances. The exception is a large bias (7 m/s) when the satellite has crossed a sunlit Antarctic ice cap before passing MARA.
Ramashray Yadav, Ram Kumar Giri, and Virendra Singh
Atmos. Meas. Tech., 14, 4857–4877, https://doi.org/10.5194/amt-14-4857-2021, https://doi.org/10.5194/amt-14-4857-2021, 2021
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We performed an intercomparison of seasonal and annual studies of retrievals of integrated precipitable water vapor (IPWV) carried out by INSAT-3DR satellite-borne infrared radiometer sounding and CAMS reanalysis data with ground-based Indian GNSS data. The magnitude and sign of the bias of INSAT-3DR and CAMS with respect to GNSS IPWV differs from station to station and season to season. A statistical evaluation of the collocated data sets was done to improve day-to-day weather forecasting.
Matic Šavli, Vivien Pourret, Christophe Payan, and Jean-François Mahfouf
Atmos. Meas. Tech., 14, 4721–4736, https://doi.org/10.5194/amt-14-4721-2021, https://doi.org/10.5194/amt-14-4721-2021, 2021
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The ESA's Aeolus satellite wind retrieval is provided through a series of processors. It depends on the temperature and pressure specification, which, however, are not measured by the satellite. The numerical weather predicted values are used instead, but these are erroneous. This article studies the sensitivity of the wind retrieval by introducing errors in temperature and pressure. This has been found to be small for Aeolus but is expected to be more crucial for future missions.
Kristopher M. Bedka, Amin R. Nehrir, Michael Kavaya, Rory Barton-Grimley, Mark Beaubien, Brian Carroll, James Collins, John Cooney, G. David Emmitt, Steven Greco, Susan Kooi, Tsengdar Lee, Zhaoyan Liu, Sharon Rodier, and Gail Skofronick-Jackson
Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, https://doi.org/10.5194/amt-14-4305-2021, 2021
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This paper demonstrates the Doppler Aerosol WiNd (DAWN) lidar and High Altitude Lidar Observatory (HALO) measurement capabilities across a range of atmospheric conditions, compares DAWN and HALO measurements with Aeolus satellite Doppler wind lidar to gain an initial perspective of Aeolus performance, and discusses how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, water vapour, and aerosol profile observations.
Emranul Sarkar, Alexander Kozlovsky, Thomas Ulich, Ilkka Virtanen, Mark Lester, and Bernd Kaifler
Atmos. Meas. Tech., 14, 4157–4169, https://doi.org/10.5194/amt-14-4157-2021, https://doi.org/10.5194/amt-14-4157-2021, 2021
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The biasing effect in meteor radar temperature has been a pressing issue for the last 2 decades. This paper has addressed the underlying reasons for such a biasing effect on both theoretical and experimental grounds. An improved statistical method has been developed which allows atmospheric temperatures at around 90 km to be measured with meteor radar in an independent way such that any subsequent bias correction or calibration is no longer required.
Wei Zhong, Xianghui Xue, Wen Yi, Iain M. Reid, Tingdi Chen, and Xiankang Dou
Atmos. Meas. Tech., 14, 3973–3988, https://doi.org/10.5194/amt-14-3973-2021, https://doi.org/10.5194/amt-14-3973-2021, 2021
Evgenia Belova, Peter Voelger, Sheila Kirkwood, Susanna Hagelin, Magnus Lindskog, Heiner Körnich, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 14, 2813–2825, https://doi.org/10.5194/amt-14-2813-2021, https://doi.org/10.5194/amt-14-2813-2021, 2021
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We validate horizontal wind measurements at altitudes of 0.5–14 km made with atmospheric radars: ESRAD located near Kiruna in the Swedish Arctic and MARA at the Indian research station Maitri in Antarctica, by comparison with radiosondes, the regional model HARMONIE-AROME and the ECMWF ERA5 reanalysis. Good agreement was found in general, and radar bias and uncertainty were estimated. These radars are planned to be used for validation of winds measured by lidar by the ESA satellite Aeolus.
Gizachew Kabite Wedajo, Misgana Kebede Muleta, and Berhan Gessesse Awoke
Atmos. Meas. Tech., 14, 2299–2316, https://doi.org/10.5194/amt-14-2299-2021, https://doi.org/10.5194/amt-14-2299-2021, 2021
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Satellite rainfall estimates (SREs) are alternative data sources for data-scarce basins. However, the accuracy of the products is plagued by multiple sources of errors. Therefore, SREs should be evaluated for particular basins before being used for other applications. The results of the study showed that CHIRPS2 and IMERG6 estimated rainfall and predicted hydrologic simulations well for Dhidhessa River Basin, which shows remote sensing technology could improve hydrologic studies.
Steven Knoop, Fred C. Bosveld, Marijn J. de Haij, and Arnoud Apituley
Atmos. Meas. Tech., 14, 2219–2235, https://doi.org/10.5194/amt-14-2219-2021, https://doi.org/10.5194/amt-14-2219-2021, 2021
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Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few hundred metres or even a few kilometres. Their data can improve weather models and help forecasters. To investigate their accuracy and required meteorological conditions, we have carried out a 2-year measurement campaign of a wind lidar at our Cabauw test site and made a comparison with cup anemometers and wind vanes at several levels in a 213 m tall meteorological mast.
Joaquim V. Teixeira, Hai Nguyen, Derek J. Posselt, Hui Su, and Longtao Wu
Atmos. Meas. Tech., 14, 1941–1957, https://doi.org/10.5194/amt-14-1941-2021, https://doi.org/10.5194/amt-14-1941-2021, 2021
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Wind-tracking algorithms produce atmospheric motion vectors (AMVs) by tracking satellite observations. Accurately characterizing the uncertainties in AMVs is essential in assimilating them into data assimilation models. We develop a machine-learning-based approach for error characterization which involves Gaussian mixture model clustering and random forest using a simulation dataset of water vapor, AMVs, and true winds. We show that our method improves on existing AMV error characterizations.
Giovanni Martucci, Francisco Navas-Guzmán, Ludovic Renaud, Gonzague Romanens, S. Mahagammulla Gamage, Maxime Hervo, Pierre Jeannet, and Alexander Haefele
Atmos. Meas. Tech., 14, 1333–1353, https://doi.org/10.5194/amt-14-1333-2021, https://doi.org/10.5194/amt-14-1333-2021, 2021
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This article presents a validation of 1.5 years of pure rotational temperature data measured by the Raman lidar RALMO installed at the MeteoSwiss station of Payerne. The statistical results are in terms of bias and standard deviation with respect to two well-established radiosounding systems. The statistics are divided into daytime (bias = 0.28 K, SD = 0.62±0.03 K) and nighttime (bias = 0.29 K, SD = 0.66±0.06 K). The lidar temperature profiles are applied to cloud supersaturation studies.
Anders Tegtmeier Pedersen and Michael Courtney
Atmos. Meas. Tech., 14, 889–903, https://doi.org/10.5194/amt-14-889-2021, https://doi.org/10.5194/amt-14-889-2021, 2021
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This paper suggests and describes a method for calibrating wind lidars using a rotating flywheel. An uncertainty analysis shows that a standard uncertainty of 0.1 % can be achieved, with the main contributor being the width of the laser beam which is in agreement with experimental results. The method can potentially lower the calibration uncertainty of wind lidars, which today is often based on cup anemometers, and thus lead to better wind assessments and perhaps more widespread use.
Kaisa Lakkala, Jukka Kujanpää, Colette Brogniez, Nicolas Henriot, Antti Arola, Margit Aun, Frédérique Auriol, Alkiviadis F. Bais, Germar Bernhard, Veerle De Bock, Maxime Catalfamo, Christine Deroo, Henri Diémoz, Luca Egli, Jean-Baptiste Forestier, Ilias Fountoulakis, Katerina Garane, Rosa Delia Garcia, Julian Gröbner, Seppo Hassinen, Anu Heikkilä, Stuart Henderson, Gregor Hülsen, Bjørn Johnsen, Niilo Kalakoski, Angelos Karanikolas, Tomi Karppinen, Kevin Lamy, Sergio F. León-Luis, Anders V. Lindfors, Jean-Marc Metzger, Fanny Minvielle, Harel B. Muskatel, Thierry Portafaix, Alberto Redondas, Ricardo Sanchez, Anna Maria Siani, Tove Svendby, and Johanna Tamminen
Atmos. Meas. Tech., 13, 6999–7024, https://doi.org/10.5194/amt-13-6999-2020, https://doi.org/10.5194/amt-13-6999-2020, 2020
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The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. Ground-based data from 25 sites located in Arctic, subarctic, temperate, equatorial and Antarctic
areas were used for the validation of the TROPOMI surface ultraviolet (UV) radiation product. For most sites 60 %–80 % of TROPOMI data was within ± 20 % of ground-based data.
Pauline Martinet, Domenico Cimini, Frédéric Burnet, Benjamin Ménétrier, Yann Michel, and Vinciane Unger
Atmos. Meas. Tech., 13, 6593–6611, https://doi.org/10.5194/amt-13-6593-2020, https://doi.org/10.5194/amt-13-6593-2020, 2020
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Each year large human and economical losses are due to fog episodes. However, fog forecasts remain quite inaccurate, partly due to a lack of observations in the atmospheric boundary layer. The benefit of ground-based microwave radiometers has been investigated and has demonstrated their capability of significantly improving the initial state of temperature and liquid water content profiles in current numerical weather prediction models, paving the way for improved fog forecasts in the future.
Holger Baars, Alina Herzog, Birgit Heese, Kevin Ohneiser, Karsten Hanbuch, Julian Hofer, Zhenping Yin, Ronny Engelmann, and Ulla Wandinger
Atmos. Meas. Tech., 13, 6007–6024, https://doi.org/10.5194/amt-13-6007-2020, https://doi.org/10.5194/amt-13-6007-2020, 2020
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A first validation for the European satellite Aeolus is presented. Aeolus is the first satellite that can actively measure horizontal wind profiles from space.
Radiosonde launches on board the German research vessel Polarstern have been utilized to validate Aeolus observations over the Atlantic Ocean, a region where almost no other reference measurements are available. It is shown that Aeolus is able to measure accurately atmospheric winds and thus may significantly improve weather forecasts.
Giacomo Roversi, Pier Paolo Alberoni, Anna Fornasiero, and Federico Porcù
Atmos. Meas. Tech., 13, 5779–5797, https://doi.org/10.5194/amt-13-5779-2020, https://doi.org/10.5194/amt-13-5779-2020, 2020
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The microwave signal travelling between two antennas of the commercial mobile backhaul network is strongly attenuated by rainfall. The open-source RAINLINK algorithm extracts rainfall rate maps, processing the attenuation data recorded by the transmission system. In this work, we applied RAINLINK to 357 Vodafone links in northern Italy and compared the outputs with the operational rain products of the local weather service (Arpae), outlining pros and cons and discussing error structure.
Clark J. Weaver, Pawan K. Bhartia, Dong L. Wu, Gordon J. Labow, and David E. Haffner
Atmos. Meas. Tech., 13, 5715–5723, https://doi.org/10.5194/amt-13-5715-2020, https://doi.org/10.5194/amt-13-5715-2020, 2020
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Currently, we do not know whether clouds will accelerate or moderate climate. We look to the past and ask whether cloudiness has changed over the last 4 decades. Using a suite of nine satellite instruments, we need to ensure that the first satellite, which was launched in 1980 and died in 1991, observed the same measurement as the eight other satellite instruments used in the record. If the instruments were measuring length and observing a 1.00 m long stick, they would all see 0.99 to 1.01 m.
Samuel Favrichon, Carlos Jimenez, and Catherine Prigent
Atmos. Meas. Tech., 13, 5481–5490, https://doi.org/10.5194/amt-13-5481-2020, https://doi.org/10.5194/amt-13-5481-2020, 2020
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Long-term monitoring of satellite-derived variables is necessary for a better understanding of the evolution of Earth parameters at global scale. However different instruments' observations used over the years need to be inter-calibrated with each other to provide meaningful information. This paper describes how a linear correction can improve the observations from the Scanning Multichannel Microwave Radiometer over continental surfaces to be more consistent with more recent radiometers.
Zhilu Wu, Yanxiong Liu, Yang Liu, Jungang Wang, Xiufeng He, Wenxue Xu, Maorong Ge, and Harald Schuh
Atmos. Meas. Tech., 13, 4963–4972, https://doi.org/10.5194/amt-13-4963-2020, https://doi.org/10.5194/amt-13-4963-2020, 2020
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The HY-2A calibration microwave radiometer (CMR) water vapor product is validated using ground-based GNSS observations along the coastline and shipborne GNSS observations over the Indian Ocean. The validation result shows that HY-2A CMR PWV agrees well with ground-based GNSS PWV, with 2.67 mm in rms within 100 km and an RMS of 1.57 mm with shipborne GNSS for the distance threshold of 100 km. Ground-based GNSS and shipborne GNSS agree with HY-2A CMR well.
Viswanathan Bringi, Kumar Vijay Mishra, Merhala Thurai, Patrick C. Kennedy, and Timothy H. Raupach
Atmos. Meas. Tech., 13, 4727–4750, https://doi.org/10.5194/amt-13-4727-2020, https://doi.org/10.5194/amt-13-4727-2020, 2020
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The raindrop size distribution and its moments are fundamental in many areas, such as radar measurement of rainfall using polarimetry and numerical modeling of the microphysical processes of rain formation and evolution. We develop a technique which uses advanced radar measurements and complete drop size distributions using two collocated instruments to retrieve the lower-order moments such as total drop concentration and rain water content. We demonstrate a proof-of-concept using a case study.
Allan C. Just, Yang Liu, Meytar Sorek-Hamer, Johnathan Rush, Michael Dorman, Robert Chatfield, Yujie Wang, Alexei Lyapustin, and Itai Kloog
Atmos. Meas. Tech., 13, 4669–4681, https://doi.org/10.5194/amt-13-4669-2020, https://doi.org/10.5194/amt-13-4669-2020, 2020
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A flexible machine-learning model was fit to explain the differences between estimates of water vapor from satellites versus ground stations in Northeastern USA. We use nine variables derived from the satellite acquisition and ground characteristics to explain this measurement error. Our results showed overall good agreement, but data from the Terra satellite were drifting too high in recent summers. Our model reduces measurement error and works well in new locations in the northeast.
Hans Gleisner, Kent B. Lauritsen, Johannes K. Nielsen, and Stig Syndergaard
Atmos. Meas. Tech., 13, 3081–3098, https://doi.org/10.5194/amt-13-3081-2020, https://doi.org/10.5194/amt-13-3081-2020, 2020
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Data from GPS radio occultation (RO) instruments aboard a series of satellites have been reprocessed by the ROM SAF. We describe the monthly mean RO climate data records (CDRs) and the methods for removing sampling errors. The quality of the CDRs is evaluated, with a focus on systematic differences between satellite missions. Between 8 and 30 km, the data quality and the inter-mission differences are small enough to allow the generation of combined multi-mission data records starting in 2001.
Andrea K. Steiner, Florian Ladstädter, Chi O. Ao, Hans Gleisner, Shu-Peng Ho, Doug Hunt, Torsten Schmidt, Ulrich Foelsche, Gottfried Kirchengast, Ying-Hwa Kuo, Kent B. Lauritsen, Anthony J. Mannucci, Johannes K. Nielsen, William Schreiner, Marc Schwärz, Sergey Sokolovskiy, Stig Syndergaard, and Jens Wickert
Atmos. Meas. Tech., 13, 2547–2575, https://doi.org/10.5194/amt-13-2547-2020, https://doi.org/10.5194/amt-13-2547-2020, 2020
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High-quality observations are critically important for monitoring the Earth’s changing climate. We provide information on the consistency and long-term stability of observations from GPS radio occultation (RO). We assess, for the first time, RO records from multiple RO missions and all major RO data providers. Our results quantify where RO can be used for reliable trend assessment and confirm its climate quality.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, and Fabian Weiler
Atmos. Meas. Tech., 13, 2381–2396, https://doi.org/10.5194/amt-13-2381-2020, https://doi.org/10.5194/amt-13-2381-2020, 2020
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Aeolus, the first ever wind lidar in space, has been providing wind profiles on a global scale since its launch. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (DLR) recently performed two airborne campaigns over central Europe deploying two different Doppler wind lidars. A total of 10 satellite underflights were performed and used to validate the early-stage wind data product of Aeolus by means of collocated airborne wind lidar observations.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, and Oliver Reitebuch
Atmos. Meas. Tech., 13, 2075–2097, https://doi.org/10.5194/amt-13-2075-2020, https://doi.org/10.5194/amt-13-2075-2020, 2020
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This work reports on the first airborne validation campaign of ESA’s Earth Explorer mission Aeolus, conducted in central Europe during the commissioning phase in November 2018. After presenting the methodology used to compare the data sets from the satellite, the airborne wind lidar and the ECWMF model, the wind results from the underflights performed are analyzed and discussed, providing a first assessment of the accuracy and precision of the preliminary Aeolus wind data.
Ramon Padullés, Chi O. Ao, F. Joseph Turk, Manuel de la Torre Juárez, Byron Iijima, Kuo Nung Wang, and Estel Cardellach
Atmos. Meas. Tech., 13, 1299–1313, https://doi.org/10.5194/amt-13-1299-2020, https://doi.org/10.5194/amt-13-1299-2020, 2020
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In this study we thoroughly address the calibration and validation of the new polarimetric radio occultation (PRO) observables. These represent an innovative way to obtain vertical profiles of precipitation along with thermodynamic observations of the same scene. First we perform the on-orbit calibration of the measurement. Then, we show how the PRO observables are sensitive to the presence and intensity of rain by looking for coincident precipitation measurements from independent missions.
Freek Liefhebber, Sarah Lammens, Paul W. G. Brussee, André Bos, Viju O. John, Frank Rüthrich, Jacobus Onderwaater, Michael G. Grant, and Jörg Schulz
Atmos. Meas. Tech., 13, 1167–1179, https://doi.org/10.5194/amt-13-1167-2020, https://doi.org/10.5194/amt-13-1167-2020, 2020
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The paper addresses the need for automatic quality control of a whole series of Earth observation (EO) time series extending a period of over 40 years. Such a dataset is valuable and may provide important information about trends related to geo-physical processes. Furthermore, as the dataset is that large, there is a need to completely automate the processes, as otherwise the effort would become impracticable. The result is a system with a high probability of detection and low false alarm rate.
Felix Erdmann, Eric Defer, Olivier Caumont, Richard J. Blakeslee, Stéphane Pédeboy, and Sylvain Coquillat
Atmos. Meas. Tech., 13, 853–875, https://doi.org/10.5194/amt-13-853-2020, https://doi.org/10.5194/amt-13-853-2020, 2020
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This article compares lightning observations from an optical sensor onboard the International Space Station to two ground-based networks using different radio frequencies. The location and timing of coincident flashes agree well for the three instruments. Differences exist for the detected number of flashes and the characteristics. Small flashes in particular are not always detected by all three instruments. About half of the flashes at altitudes below 10 km are not seen by the satellite sensor.
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Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A., and Xiao, Q.: A Three-Dimensional Variational (3DVAR) Data Assimilation System For Use With MM5: Implementation and Initial Results, Mon. Weather Rev., 132, 897–914, 2004.
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