Articles | Volume 13, issue 9
Research article 02 Sep 2020
Research article | 02 Sep 2020
Gradient boosting machine learning to improve satellite-derived column water vapor measurement error
Allan C. Just et al.
No articles found.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys. Discuss.,
Preprint under review for ACPShort summary
This paper presents a retrieval algorithm of iron oxides species (hematite, goethite) content in the atmosphere from observation of EPIC satellite instrument. Our results display variations within the published range of hematite, goethite both spatially and temporally over the main dust source regions. It implies single-viewing satellite instruments may provide essential information in shortwave dust direct radiative effects study of climate modeling.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David Giles, and Pablo E. Saide
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of twelve real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles, for improving smoke forecasts.
Robert B. Chatfield, Meinrat O. Andreae, ARCTAS Science Team, and SEAC4RS Science Team
Atmos. Meas. Tech., 13, 7069–7096,Short summary
Forest burning affects air pollution and global climate. A NASA aircraft studied fire emissions including the Rim Fire near Yosemite. We found frequent confusions between the actual fire emission factors and other effects on the air samples. Effects on CO2 and CO can originate far upwind; the gases can mix variably into a smoke plume. We devised a theory of constant features in plumes. A statistical mixed-effects analysis of a co-emitted tracers model disentangles such mixing from fire effects.
Cheng Chen, Oleg Dubovik, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Fabrice Ducos, Yevgeny Derimian, Maurice Herman, Didier Tanré, Lorraine A. Remer, Alexei Lyapustin, Andrew M. Sayer, Robert C. Levy, N. Christina Hsu, Jacques Descloitres, Lei Li, Benjamin Torres, Yana Karol, Milagros Herrera, Marcos Herreras, Michael Aspetsberger, Moritz Wanzenboeck, Lukas Bindreiter, Daniel Marth, Andreas Hangler, and Christian Federspiel
Earth Syst. Sci. Data, 12, 3573–3620,Short summary
Aerosol products obtained from POLDER/PARASOL processed by the GRASP algorithm have been released. The entire archive of PARASOL/GRASP aerosol products is evaluated against AERONET and compared with MODIS (DT, DB and MAIAC), as well as PARASOL/Operational products. PARASOL/GRASP aerosol products provide spectral 443–1020 nm AOD correlating well with AERONET with a maximum bias of 0.02. Finally, GRASP shows capability to derive detailed spectral properties, including aerosol absorption.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457,Short summary
We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Sergey Korkin, Joel S. Schafer, Alexander Smirnov, Mikhail Sorokin, and Alexei Lyapustin
Atmos. Meas. Tech., 13, 3375–3411,
Robert B. Chatfield, Meytar Sorek-Hamer, Robert F. Esswein, and Alexei Lyapustin
Atmos. Chem. Phys., 20, 4379–4397,Short summary
There is a great need to define health-affecting pollution by small particles as “respirable aerosol”. The wintertime San Joaquin Valley experiences severe episodes that need full maps. A few air pollution monitors are set out by agencies in such regions. Satellite data on haziness and daily calibration using the monitors map out improved pollution estimates for the winter of 2012–2013. These show patterns of valuable empirical information about sources, transport, and cleanout of pollution.
Jing Wei, Zhanqing Li, Maureen Cribb, Wei Huang, Wenhao Xue, Lin Sun, Jianping Guo, Yiran Peng, Jing Li, Alexei Lyapustin, Lei Liu, Hao Wu, and Yimeng Song
Atmos. Chem. Phys., 20, 3273–3289,Short summary
This study introduced an enhanced space–time extremely randomized trees (STET) approach to improve the 1 km resolution ground-level PM2.5 estimates across China using the remote sensing technology. The STET model shows high accuracy and strong predictive power and appears to outperform most models reported by previous studies. Thus, it is of great importance for future air pollution studies at medium- or small-scale areas and will be applied to generate the historical PM2.5 dataset across China.
Larisa Sogacheva, Thomas Popp, Andrew M. Sayer, Oleg Dubovik, Michael J. Garay, Andreas Heckel, N. Christina Hsu, Hiren Jethva, Ralph A. Kahn, Pekka Kolmonen, Miriam Kosmale, Gerrit de Leeuw, Robert C. Levy, Pavel Litvinov, Alexei Lyapustin, Peter North, Omar Torres, and Antti Arola
Atmos. Chem. Phys., 20, 2031–2056,Short summary
The typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies the usage of multiple satellite sensors should be considered. Here we introduce and evaluate a monthly AOD merged product and AOD global and regional time series for the period 1995–2017 created from 12 individual satellite AOD products, which provide a long-term perspective on AOD changes over different regions of the globe.
Ekaterina Y. Zhdanova, Natalia Y. Chubarova, and Alexei I. Lyapustin
Atmos. Meas. Tech., 13, 877–891,Short summary
We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC satellite aerosol product from May to September over the years 2000–2017. We revealed that the MAIAC product is a reliable instrument for assessing the spatial features of urban aerosol pollution and its temporal dynamics. The local aerosol effect is about 0.02–0.04 in AOT in the visible spectral range over the Moscow megacity.
David M. Giles, Alexander Sinyuk, Mikhail G. Sorokin, Joel S. Schafer, Alexander Smirnov, Ilya Slutsker, Thomas F. Eck, Brent N. Holben, Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sergey V. Korkin, and Alexei I. Lyapustin
Atmos. Meas. Tech., 12, 169–209,Short summary
Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate aerosol optical depth (AOD). This study presents a new algorithm of automated near-real-time (NRT) quality controls with improved cloud screening for AERONET AOD measurements. Results from the new and old algorithms have excellent agreement for the highest-quality AOD level, while the new algorithm provides higher-quality NRT AOD for applications such as data assimilation and satellite evaluation.
Xiaomeng Jin, Arlene M. Fiore, Gabriele Curci, Alexei Lyapustin, Kevin Civerolo, Michael Ku, Aaron van Donkelaar, and Randall V. Martin
Atmos. Chem. Phys., 19, 295–313,Short summary
We use a forward geophysical approach to derive surface PM2.5 distribution from satellite AOD over the northeastern US by applying relationships between surface PM2.5 and column AOD from a regional air quality model (CMAQ). We use multi-platform surface, aircraft, and radiosonde measurements to quantify different sources of uncertainties. We highlight model representation of aerosol vertical distribution and speciation as major sources of uncertainties for satellite-derived PM2.5.
Alexei Lyapustin, Yujie Wang, Sergey Korkin, and Dong Huang
Atmos. Meas. Tech., 11, 5741–5765,Short summary
MAIAC algorithm used for the MODIS C6 processing is described. MAIAC combines time series analysis and pixel/image-based processing to improve the accuracy of cloud detection, aerosol retrievals and atmospheric correction. MAIAC offers an interdisciplinary suite of atmospheric, land surface and snow products. Due to generally high quality, high resolution and high coverage, MAIAC AOD and surface reflectance/BRDF have been widely used for air quality and land research and applications.
Nandita Singh, Tirthankar Banerjee, Made P. Raju, Karine Deboudt, Meytar Sorek-Hamer, Ram S. Singh, and Rajesh K. Mall
Atmos. Chem. Phys., 18, 14197–14215,Short summary
Airborne particulate emissions from burning of agricultural residue over the Indo-Gangetic Plain have often been associated with formation of haze and adverse health impacts. Short-term variations in aerosol climatology during extreme biomass burning emissions were investigated using both ground and spaceborne sensors. Results highlight three exclusive but interrelated mechanisms, i.e., aerosol chemistry, regional transport, and radiative forcing, which may be useful in regional climate models.
Robert C. Levy, Shana Mattoo, Virginia Sawyer, Yingxi Shi, Peter R. Colarco, Alexei I. Lyapustin, Yujie Wang, and Lorraine A. Remer
Atmos. Meas. Tech., 11, 4073–4092,Short summary
Global aerosol data sets are essential for assessing climate-related questions. When comparing data sets derived from twin satellite sensors, we find consistent global offsets between morning and afternoon observations. Applying satellite-like sampling to a global model derives much weaker morning/afternoon offsets, suggesting that the observational differences are due to calibration. However, applying additional calibration corrections appears to reduce (but not remove) the global offsets.
Matthew J. Cooper, Randall V. Martin, Alexei I. Lyapustin, and Chris A. McLinden
Atmos. Meas. Tech., 11, 2983–2994,Short summary
To accurately infer air pollutant concentrations from satellite observations, we must first know the reflectivity of the Earth’s surface. Using a model, we show that satellite observations are better able to observe NO2 near the surface if snow is present. However, knowing when snow is present is difficult due to its variability. We test seven existing snow cover data sets to assess their ability to inform future satellite observations and find that the IMS data set is best suited for this task.
I. Veselovskii, D. N Whiteman, M. Korenskiy, A. Suvorina, A. Kolgotin, A. Lyapustin, Y. Wang, M. Chin, H. Bian, T. L. Kucsera, D. Pérez-Ramírez, and B. Holben
Atmos. Chem. Phys., 15, 1647–1660,Short summary
The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26-28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires. The NASA GSFC multi-wavelength Mie-Raman lidar was used to profile the smoke particle parameters such as volume density, effective radius and the real part of the refractive index.
B. Arvani, R. B. Pierce, A. I. Lyapustin, Y. Wang, G. Ghermandi, and S. Teggi
Atmos. Chem. Phys. Discuss.,
Revised manuscript not acceptedShort summary
The manuscript compares 10km Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 and new 1 km Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) retrievals to small (<10 micron) particulate matter (PM10) surface measurements from monitoring stations within the Po Valley in Northern Italy during 2012. When the depth of the planetary boundary layer (PBL) is used to normalize the AOD, we find PM – AOD correlations of 0.98 for both retrievals.
A. Lyapustin, Y. Wang, X. Xiong, G. Meister, S. Platnick, R. Levy, B. Franz, S. Korkin, T. Hilker, J. Tucker, F. Hall, P. Sellers, A. Wu, and A. Angal
Atmos. Meas. Tech., 7, 4353–4365,
T. F. Eck, B. N. Holben, J. S. Reid, A. Arola, R. A. Ferrare, C. A. Hostetler, S. N. Crumeyrolle, T. A. Berkoff, E. J. Welton, S. Lolli, A. Lyapustin, Y. Wang, J. S. Schafer, D. M. Giles, B. E. Anderson, K. L. Thornhill, P. Minnis, K. E. Pickering, C. P. Loughner, A. Smirnov, and A. Sinyuk
Atmos. Chem. Phys., 14, 11633–11656,
J. Strandgren, L. Mei, M. Vountas, J. P. Burrows, A. Lyapustin, and Y. Wang
Atmos. Chem. Phys. Discuss.,
Revised manuscript not accepted
X. Hu, L. A. Waller, A. Lyapustin, Y. Wang, and Y. Liu
Atmos. Chem. Phys., 14, 6301–6314,
A. Chudnovsky, C. Tang, A. Lyapustin, Y. Wang, J. Schwartz, and P. Koutrakis
Atmos. Chem. Phys., 13, 10907–10917,
H. Zhang, R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin
Atmos. Meas. Tech., 6, 471–486,
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and IntercomparisonsEvaluating the use of Aeolus satellite observations in the regional numerical weather prediction (NWP) model Harmonie–AromeInterpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA systemValidation of Aeolus winds using ground-based radars in Antarctica and in northern SwedenIntercomparison review of IPWV retrieved from INSAT-3DR sounder, GNSS and CAMS reanalysis dataSensitivity of Aeolus HLOS winds to temperature and pressure specification in the L2B processorAirborne lidar observations of wind, water vapor, and aerosol profiles during the NASA Aeolus calibration and validation (Cal/Val) test flight campaignImproved method of estimating temperatures at meteor peak heightsError analyses of a multistatic meteor radar system to obtain a three-dimensional spatial-resolution distributionValidation of wind measurements of two mesosphere–stratosphere–troposphere radars in northern Sweden and in AntarcticaPerformance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), EthiopiaA 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at CabauwUsing machine learning to model uncertainty for water vapor atmospheric motion vectorsValidation of pure rotational Raman temperature data from the Raman Lidar for Meteorological Observations (RALMO) at PayerneFlywheel calibration of a continuous-wave coherent Doppler wind lidarMonitoring the TROPOMI-SWIR module instrument stability using desert sitesValidation of the TROPOspheric Monitoring Instrument (TROPOMI) surface UV radiation productImprovement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var studyValidation of Aeolus wind products above the Atlantic OceanCommercial microwave links as a tool for operational rainfall monitoring in Northern ItalyInter-calibration of nine UV sensing instruments over Antarctica and Greenland since 1980Inter-calibrating SMMR brightness temperatures over continental surfacesValidating HY-2A CMR precipitable water vapor using ground-based and shipborne GNSS observationsRetrieval of lower-order moments of the drop size distribution using CSU-CHILL X-band polarimetric radar: a case studyEvaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data recordConsistency and structural uncertainty of multi-mission GPS radio occultation recordsFirst validation of Aeolus wind observations by airborne Doppler wind lidar measurementsIntercomparison of wind observations from the European Space Agency's Aeolus satellite mission and the ALADIN Airborne DemonstratorCalibration and validation of the Polarimetric Radio Occultation and Heavy Precipitation experiment aboard the PAZ satelliteAutomatic quality control of the Meteosat First Generation measurementsConcurrent satellite and ground-based lightning observations from the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency network Meteorage and the SAETTA Lightning Mapping Array (LMA) in the northwestern Mediterranean regionUsing ground radar overlaps to verify the retrieval of calibration bias estimates from spaceborne platformsA geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 2: Evaluation over open oceanOn the zero-level offset in the GOSAT TANSO-FTS O2 A band and the quality of solar-induced chlorophyll fluorescence (SIF): comparison of SIF between GOSAT and OCO-2Evaluation of GPM-DPR precipitation estimates with WegenerNet gauge dataA study of a two-dimensional scanned lunar image for Advanced Technology Microwave Sounder (ATMS) geometric calibrationMultistatic meteor radar observations of gravity-wave–tidal interaction over southern AustraliaA geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 1: Evaluation over land surfaces using measurements from OMI at 466 nmRetrieval of convective available potential energy from INSAT-3D measurements: comparison with radiosonde data and their spatial–temporal variationsLidar temperature series in the middle atmosphere as a reference data set – Part 2: Assessment of temperature observations from MLS/Aura and SABER/TIMED satellitesPotential of INSAT-3D sounder-derived total precipitable water product for weather forecastLidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidarsEnhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filterRainfall retrieval with commercial microwave links in São Paulo, BrazilEvaluating two methods of estimating error variances using simulated data sets with known errorsEstimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaignInter-channel uniformity of a microwave sounder in spaceFrom model to radar variables: a new forward polarimetric radar operator for COSMOEvaluating tropospheric humidity from GPS radio occultation, radiosonde, and AIRS from high-resolution time seriesReducing representativeness and sampling errors in radio occultation–radiosonde comparisonsEvaluating the lower-tropospheric COSMIC GPS radio occultation sounding quality over the Arctic
Susanna Hagelin, Roohollah Azad, Magnus Lindskog, Harald Schyberg, and Heiner Körnich
Atmos. Meas. Tech., 14, 5925–5938,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,
Evgenia Belova, Peter Voelger, Sheila Kirkwood, Susanna Hagelin, Magnus Lindskog, Heiner Körnich, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 14, 2813–2825,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Tim A. van Kempen, Filippo Oggionni, and Richard M. van Hees
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
Validation of the instrument stability of the TROPOMI-SWIR module is done by monitoring the a group of very stable and remote locations in the Saharan and Arabian deserts. These 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.
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Hans Gleisner, Kent B. Lauritsen, Johannes K. Nielsen, and Stig Syndergaard
Atmos. Meas. Tech., 13, 3081–3098,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Irene Crisologo and Maik Heistermann
Atmos. Meas. Tech., 13, 645–659,Short summary
Archives of radar observations often suffer from errors, one of which is calibration. However, it is possible to correct them after the fact by using satellite radars as a calibration reference. We propose improvements to this calibration method by considering factors that affect the data quality, such that poor quality data gets filtered out in the bias calculation by assigning weights. We also show that the bias can be interpolated in time even for days when there are no satellite data.
Zachary Fasnacht, Alexander Vasilkov, David Haffner, Wenhan Qin, Joanna Joiner, Nickolay Krotkov, Andrew M. Sayer, and Robert Spurr
Atmos. Meas. Tech., 12, 6749–6769,Short summary
The anisotropy of Earth's surface reflection plays an important role in satellite-based retrievals of cloud, aerosol, and trace gases. Most current ultraviolet and visible satellite retrievals utilize climatological surface reflectivity databases that do not account for surface anisotropy. The GLER concept was introduced to account for such features. Here we evaluate GLER for water surfaces by comparing with OMI measurements and show that it captures these surface anisotropy features.
Haruki Oshio, Yukio Yoshida, and Tsuneo Matsunaga
Atmos. Meas. Tech., 12, 6721–6735,Short summary
We investigate the radiance offset in the O2 A band of GOSAT spectrometer and quality of the offset-corrected solar-induced chlorophyll fluorescence (SIF). An analysis of temporal variation of the offset suggests that the radiometric sensitivity of the spectrometer changed after switching the optics path selector in January 2015. Comparisons at multiple spatial scales show good agreement between GOSAT SIF and OCO-2 SIF, which supports the consistency among the present satellite SIF data.
Martin Lasser, Sungmin O, and Ulrich Foelsche
Atmos. Meas. Tech., 12, 5055–5070,Short summary
This paper evaluates the rain rate estimates from the Global Precipitation Measurement (GPM) mission's radar instrument by comparing them to the data of the WegenerNet, a local-scale high-resolution network of meteorological stations. Our results show that the GPM-DPR estimates basically match with the WegenerNet measurements, but absolute quantities are biased.
Jun Zhou and Hu Yang
Atmos. Meas. Tech., 12, 4983–4992,Short summary
Evaluating the on-orbit geolocation accuracy of the ATMS is of great importance. The widely used Earth-target-dependent methods are crippled by the strong atmospheric absorption at sounding channels and cloud contamination at window channels. To solve these issues, this study developed a geolocation evaluation algorithm based on a unique 2-D lunar scan dataset captured by the ATMS during a NOAA-20 pitch-over maneuver operation. The results are validated by the coastline inflection point method.
Andrew John Spargo, Iain Murray Reid, and Andrew David MacKinnon
Atmos. Meas. Tech., 12, 4791–4812,Short summary
We simulate the ability of a recently installed multistation meteor detection radar to measure characteristics of turbulence in the Earth's lower ionosphere. After verifying that it performs reasonably well, we use the radar's data to study an interaction between turbulence and tidal effects. We performed the study because no one has yet applied a multistation radar to this problem before and because multistation radars like this are becoming increasingly common worldwide.
Wenhan Qin, Zachary Fasnacht, David Haffner, Alexander Vasilkov, Joanna Joiner, Nickolay Krotkov, Bradford Fisher, and Robert Spurr
Atmos. Meas. Tech., 12, 3997–4017,Short summary
Satellite observations depend on Sun and view angles due to anisotropy of the Earth's atmosphere and surface reflection. But most of the ultraviolet and visible cloud, aerosol, and trace-gas algorithms utilize surface reflectivity databases that do not account for surface anisotropy. We create a surface database using the GLER concept which adequately accounts for surface anisotropy, validate it with independent satellite data, and provide a simple implementation to the current algorithms.
Uriya Veerendra Murali Krishna, Subrata Kumar Das, Kizhathur Narasimhan Uma, and Govindan Pandithurai
Atmos. Meas. Tech., 12, 777–790,Short summary
Convective available potential energy (CAPE) is an indicator of the occurrence of extreme weather. For the first time over India, this study estimated CAPE from high spatial–temporal resolution measurements of the geostationary satellite, INSAT-3D. INSAT-3D estimates that CAPE reasonably represents the radiosonde CAPE. This study allows the atmospheric science community to select the best available dataset for their use in nowcasting and making severe weather warnings based on numerical models.
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, and Emily M. McCullough
Atmos. Meas. Tech., 11, 6703–6717,Short summary
We have compared 2433 nights of OHP lidar temperatures (2002–2018) to temperatures derived from the satellites SABER and MLS. We have found a winter stratopause cold bias in the satellite measurements with respect to the lidar (−6 K for SABER and −17 K for MLS), a summer mesospheric warm bias for SABER (6 K near 60 km), and a vertically structured bias for MLS (−4 to 4 K). We have corrected the satellite data based on the lidar-determined stratopause height and found a significant improvement.
Shailesh Parihar, Ashim Kumar Mitra, Mrutyunjay Mohapatra, and Rajjev Bhatla
Atmos. Meas. Tech., 11, 6003–6012,Short summary
This paper is based on operational work carried out at IMD, New Delhi using the INSAT-3D satellite-derived sounder product TPW for weather events such as rainfall and thunderstorms. The INSAT-3D TPW has been used by forecasters as well as many other users over the last 2 years. This work mainly brings out an in-depth validation with in situ ground measurement data as well as a GNSS system for its suitability in weather prediction. This paper can be utilized operationally for weather purposes.
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, Emily M. McCullough, Jean-François Mariscal, and Éric d'Almeida
Atmos. Meas. Tech., 11, 5531–5547,Short summary
The objective of this work is to minimize the errors at the highest altitudes of a lidar temperature profile which arise due to background estimation and a priori choice. The systematic method in this paper has the effect of cooling the temperatures at the top of a lidar profile by up to 20 K – bringing them into better agreement with satellite temperatures. Following the description of the algorithm is a 20-year cross-validation of two lidars which establishes the stability of the technique.
Irene Crisologo, Robert A. Warren, Kai Mühlbauer, and Maik Heistermann
Atmos. Meas. Tech., 11, 5223–5236,Short summary
The calibration of ground-based weather radar (GR) can be improved a posteriori by comparing observed GR reflectivity to well-established spaceborne radar platforms (SR), such as TRMM or GPM. Our study shows that the consistency between GR and SR reflectivity measurements can be enhanced by considering the quality of GR data from areas where signals may have been blocked due to the surrounding terrain, and provides an open-source toolset to carry out corresponding analyses.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476,Short summary
Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
Therese Rieckh and Richard Anthes
Atmos. Meas. Tech., 11, 4309–4325,Short summary
We compare the two-cornered hat (2CH) and three-cornered hat (3CH) method for estimating the error variances of two or more independent data sets using simulated data with various error correlations and biases. We assess the accuracy of the 3CH and 2CH estimates and examine the sensitivity of the estimated error variances to the degree of error correlation between the data sets as well as sample size. The 3CH method is less sensitive to these factors and hence more accurate.
Nicola Bodini, Julie K. Lundquist, and Rob K. Newsom
Atmos. Meas. Tech., 11, 4291–4308,Short summary
Turbulence within the atmospheric boundary layer is critically important to transfer heat, momentum, and moisture. Currently, improved turbulence parametrizations are crucially needed to refine the accuracy of model results at fine horizontal scales. In this study, we calculate turbulence dissipation rate from sonic anemometers and discuss a novel approach to derive turbulence dissipation from profiling lidar measurements.
Martin Burgdorf, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 4005–4014,Short summary
We analysed observations of the Moon with the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite in order to search for bias in the sounding channels. Significant bias had been detected in the past on the basis of simultaneous nadir overpasses. With the Moon providing a quite different reference flux than the on-board calibration target and Earth scenes, radio-frequency interference emerged as the best explanation for the anomalies of channel 20 of AMSU-B on NOAA-16.
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916,Short summary
This work presents a polarimetric forward operator for the COSMO weather prediction model. This tool is able to simulate radar observables from the state of the atmosphere simulated by the model, taking into account most physical aspects of radar beam propagation and backscattering. This operator was validated with a large dataset of radar observations from several instruments and it was shown that is able to simulate a realistic radar signature in liquid precipitation.
Therese Rieckh, Richard Anthes, William Randel, Shu-Peng Ho, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 3091–3109,Short summary
Water vapor is the most important tropospheric greenhouse gas and is also highly variable in space and time. We study the vertical structure and variability of tropospheric humidity using various observing techniques (GPS radio occultation, radiosondes, Atmospheric Infrared Sounder) and models. Time–height cross sections reveal seasonal biases for different pressure layers. We find that radio occultation humidity has high accuracy and can contribute valuable information in data assimilation.
Shay Gilpin, Therese Rieckh, and Richard Anthes
Atmos. Meas. Tech., 11, 2567–2582,Short summary
Comparing observational systems when observations are not taken at the exact same time or location can introduce sampling errors that can be come significant during error analysis. In this study, we develop two methods to reduce sampling errors: using ellipse distance constraints rather than circles and subtracting model background. We found that both the ellipses and subtracting model background from the observations reduce sampling errors caused by spatial and temporal differences.
Xiao Yu, Feiqin Xie, and Chi O. Ao
Atmos. Meas. Tech., 11, 2051–2066,Short summary
Atmospheric observations from GPS receiver satellites offer uniform spatial coverage over the Arctic. The GPS profiles sensing deep into the lowest 300 m of the atmosphere only reach 50–60 % in summer but over 70 % in other seasons. The profile uncertainty due to different data centers is within 0.07 % in refractivity, 0.72 K in temperature, and 0.05 g kg-1 in humidity below 10 km. A systematic negative bias of 1 % in refractivity below 2 km is only seen in the summer due to moisture impact.
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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.
A flexible machine-learning model was fit to explain the differences between estimates of water...