Special Issue "Satellite-Derived Wind Observations"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 July 2019).

Special Issue Editors

Mr. Christopher Velden
E-Mail Website
Guest Editor
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison 53706, Wisconsin, USA
Interests: developing satellite-based tools and algorithms for meteorological applications; tropical cyclones, severe weather
Mr. Steve Wanzong
E-Mail Website
Guest Editor
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison 53706, Wisconsin, USA
Interests: developing satellite-based tools and algorithms for meteorological applications

Special Issue Information

Dear Colleagues,

Tropospheric winds derived from meteorological satellites (atmospheric motion vectors, or AMVs) are an important contribution to the global observing system. As observing needs increase due to societal growth and sophistication of numerical models and data assimilation systems that use the observations, it is imperative for satellite data providers to advance the products. This Special issue of Remote Sensing will highlight how remote sensing from meteorological satellites is greatly contributing to the global tropospheric wind observing system and impacting meteorological applications/forecasts. Recent advancements are a result of progress made in terms of sensors’ radiometric, spatial, and temporal resolutions, together with new data processing methods, products, and applications.

The 14th International Winds Workshop (IWW14) was recently hosted at Jeju City, South Korea. This series of meetings brings together global AMV providers, researchers and users to discuss key scientific issues and developments. Intercomparison studies and collaborative projects are enabling a communal advancement of AMV observations and their use around the world. This special issue will highlight the proceedings of IWW14 but also the start of a new era for AMVs extracted from the advanced generation of geostationary satellites (Himawari, GOES-R, FY4 and preparation of GeoKOMPSAT and MTG-FCI). The high spatiotemporal resolution capabilities are enabling an increase in AMV production and better-quality products. Optimizing the use of these new AMV capabilities in global NWP, regional NWP and nowcasting is a topic of current research studies.

In addition to traditional AMVs, new and improved methods to extract ocean surface vector winds and wind profiles from Aeolus and IR sounders data (AIRS, IASI) are promising, and we encourage the publication of initial results in this dedicated volume. 

We are inviting submissions including, but not limited to:

  • high spatial and high temporal resolution AMV observations,
  • novel AMV height assignment methods,
  • synergetic use of multi-mission/satellite imagery to produce AMVs,
  • new tracking techniques,
  • producer intercomparison studies,
  • NWP assimilation and model impact studies,
  • mesoscale and nowcasting applications,
  • ocean surface vector wind retrievals,
  • tropospheric wind profiles from space
Mr. Christopher Velden
Mr. Steve Wanzong
Guest Editors

Manuscript Submission Information

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Keywords

  • Meteorological satellites
  • Tropospheric winds
  • Atmospheric motion vectors
  • Meteorological applications
  • Numerical weather prediction impacts

Published Papers (7 papers)

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Research

Open AccessArticle
2018 Atmospheric Motion Vector (AMV) Intercomparison Study
Remote Sens. 2019, 11(19), 2240; https://doi.org/10.3390/rs11192240 - 26 Sep 2019
Abstract
Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility [...] Read more.
Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessArticle
Concept Development and Risk Reduction for MISTiC Winds, A Micro-Satellite Constellation Approach for Vertically Resolved Wind and IR Sounding Observations in the Troposphere
Remote Sens. 2019, 11(18), 2169; https://doi.org/10.3390/rs11182169 - 18 Sep 2019
Abstract
MISTiC Winds is an instrument and constellation mission approach to simultaneously observe the global thermodynamic state and the vertically resolved horizontal wind field in the troposphere from LEO SSO. The instrument is a wide-field imaging spectrometer operated in the 4.05–5.75 μm range, with [...] Read more.
MISTiC Winds is an instrument and constellation mission approach to simultaneously observe the global thermodynamic state and the vertically resolved horizontal wind field in the troposphere from LEO SSO. The instrument is a wide-field imaging spectrometer operated in the 4.05–5.75 μm range, with the spectral resolution, sampling, radiometric sensitivity, and stability needed to provide temperature and water vapor soundings of the atmosphere, with 1 km vertical resolution in the troposphere-comparable to those of NASA’s atmospheric infrared sounder (AIRS). These instruments have much higher spatial resolution (<3 km at nadir) and finer spatial sampling than current hyperspectral sounders, allowing a sequence of such observations from several micro-satellites in an orbital plane with short time separation, from which atmospheric motion vector (AMV) winds are derived. AMVs for both cloud-motion and water vapor-motion, derived from hyperspectral imagery, will have improved velocity resolution relative to AMVs obtained from multi-spectral instruments operating in GEO. MISTiC’s extraordinarily small size, low mass (<15 kg), and minimal cooling requirements can be accommodated aboard an ESPA-class microsatellite. Low fabrication and launch costs enable this constellation to provide more frequent atmospheric observations than current-generation sounders provide, at much lower mission cost. Key technology and observation method risks have been reduced through recent laboratory and airborne (NASA ER2) testing funded under NASA’s Instrument Incubator Program and BAE Systems IR&D, and through an observing system simulation experiment performed by NASA GMAO. This approach would provide a valuable new capability for the study of the processes driving high-impact weather events, and critical high-resolution observations needed for future numerical weather prediction. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessCommunication
Winds of Change for Future Operational AMV at EUMETSAT
Remote Sens. 2019, 11(18), 2111; https://doi.org/10.3390/rs11182111 - 10 Sep 2019
Abstract
EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites, is one of the key contributors to global atmospheric motion vector (AMV) production around the world. Its current contribution includes geostationary satellites at 0.0 and 41.5 degrees east, and several products extracted from [...] Read more.
EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites, is one of the key contributors to global atmospheric motion vector (AMV) production around the world. Its current contribution includes geostationary satellites at 0.0 and 41.5 degrees east, and several products extracted from the Metop low-orbit satellites. These last ones mainly cover high-latitude regions completing the observations from the geostationary ring. In the upcoming years, EUMETSAT will launch a new generation of geostationary and low-orbit satellites. The imager instruments Flexible Combined Imager (FCI) and METImage will take over the nominal AMV production at EUMETSAT around 2022 and 2024. The enhanced characteristics of these new-generation instruments are expected to increase AMV production and to improve the quality of the products. This paper presents an overview of the current EUMETSAT AMV operational production, together with a roadmap of the preparation activities for the new generation of satellites. The characteristics of the upcoming AMV products are described and compared to the current operational AMV products. This paper also presents a recent investigation into AMV extraction using the Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) instrument, as well as the retrieval of wind profiles from infrared sounders. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessArticle
Joint 3D-Wind Retrievals with Stereoscopic Views from MODIS and GOES
Remote Sens. 2019, 11(18), 2100; https://doi.org/10.3390/rs11182100 - 09 Sep 2019
Abstract
Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere [...] Read more.
Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessArticle
Development and Intercomparison Study of an Atmospheric Motion Vector Retrieval Algorithm for GEO-KOMPSAT-2A
Remote Sens. 2019, 11(17), 2054; https://doi.org/10.3390/rs11172054 - 01 Sep 2019
Abstract
We derived an atmospheric motion vector (AMV) algorithm for the Geostationary Korea Multipurpose Satellite (GEO-KOMPSAT-2A; GK-2A) launched on 4 December 2018, using the Advanced Himawari Imager (AHI) onboard Himawari-8, which is very similar to the Advanced Meteorological Imager onboard GK-2A. This study clearly [...] Read more.
We derived an atmospheric motion vector (AMV) algorithm for the Geostationary Korea Multipurpose Satellite (GEO-KOMPSAT-2A; GK-2A) launched on 4 December 2018, using the Advanced Himawari Imager (AHI) onboard Himawari-8, which is very similar to the Advanced Meteorological Imager onboard GK-2A. This study clearly describes the main steps in our algorithm and optimizes it for the target box size and height assignment methods by comparing AMVs with numerical weather prediction (NWP) and rawinsonde profiles for July 2016 and January 2017. Target box size sensitivity tests were performed from 8 × 8 to 48 × 48 pixels for three infrared channels and from 16 × 16 to 96 × 96 pixels for one visible channel. The results show that the smaller box increases the speed, whereas the larger one slows the speed without quality control. The best target box sizes were found to be 16 × 16 for CH07, 08, and 13, and 48 × 48 pixels for CH03. Height assignment sensitivity tests were performed for several methods, such as the cross-correlation coefficient (CCC), equivalent blackbody temperature (EBBT), infrared/water vapor (IR/WV) intercept, and CO2 slicing methods for a cloudy target as well as normalized total contribution (NTC) and normalized total cumulative contribution (NTCC) for a clear-air target. For a cloudy target, the CCC method is influenced by the quality of the cloud’s top pressure. Better results were found when using EBBT and IR/WV intercept methods together rather than individually. Furthermore, CO2 slicing had the best statistics. For a clear-air target, the combined use of NTC and NTCC had the best statistics. Additionally, the mean vector difference, root-mean-square (RMS) vector difference, bias, and RMS error (RMSE) between GK-2A AMVs and NWP or rawinsonde were smaller by approximately 18.2% on average than in the case of the Communication, Ocean and Meteorology Satellite (COMS) AMVs. In addition, we verified the similarity between GK-2A and Meteosat Third Generation (MTG) AMVs using the AHI of Himawari-8 from 21 July 2016. This similarity can provide evidence that the GK-2A algorithm works properly because the GK-2A AMV algorithm borrows many methods of the MTG AMV algorithm for geostationary data and inversion layer corrections. The Pearson correlation coefficients in the speed, direction, and height of the prescribed GK-2A and MTG AMVs were larger than 0.97, and the corresponding bias/RMSE were0.07/2.19 m/s, 0.21/14.8°, and 2.61/62.9 hPa, respectively, considering common quality indicator with forecast (CQIF) > 80. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessArticle
NWCSAF High Resolution Winds (NWC/GEO-HRW) Stand-Alone Software for Calculation of Atmospheric Motion Vectors and Trajectories
Remote Sens. 2019, 11(17), 2032; https://doi.org/10.3390/rs11172032 - 29 Aug 2019
Cited by 1
Abstract
The High Resolution Winds (NWC/GEO-HRW) software is developed by the EUMETSAT Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting (NWCSAF). It is part of a stand-alone software package for the calculation of meteorological products with geostationary satellite data (NWC/GEO). [...] Read more.
The High Resolution Winds (NWC/GEO-HRW) software is developed by the EUMETSAT Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting (NWCSAF). It is part of a stand-alone software package for the calculation of meteorological products with geostationary satellite data (NWC/GEO). NWCSAF High Resolution Winds provides a detailed calculation of Atmospheric Motion Vectors (AMVs) and Trajectories, locally and in near real time, using as input geostationary satellite image data, NWP model data, and OSTIA sea surface temperature data. The whole NWC/GEO software package can be obtained after registration at the NWCSAF Helpdesk, www.nwcsaf.org, where users also find support and help for its use. NWC/GEO v2018.1 software version, available since autumn 2019, is able to process MSG, Himawari-8/9, GOES-N, and GOES-R satellite series images, so that AMVs and trajectories can be calculated all throughout the planet Earth with the same algorithm and quality. Considering other equivalent meteorological products, in the ‘2014 and 2018 AMV Intercomparison Studies’ NWCSAF High Resolution Winds compared very positively with six other AMV algorithms for both MSG and Himawari-8/9 satellites. Finally, the Coordination Group for Meteorological Satellites (CGMS) recognized in its ‘2012 Meeting Report’: (1) NWCSAF High Resolution Winds fulfills the requirements to be a portable stand-alone AMV calculation software due to its easy installation and usability. (2) It has been successfully adopted by some CGMS members and serves as an important tool for development. It is modular, well documented, and well suited as stand-alone AMV software. (3) Although alternatives exist as portable stand-alone AMV calculation software, they are not as advanced in terms of documentation and do not have an existing Helpdesk. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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Open AccessArticle
Development of Enhanced Vortex-Scale Atmospheric Motion Vectors for Hurricane Applications
Remote Sens. 2019, 11(17), 1981; https://doi.org/10.3390/rs11171981 - 22 Aug 2019
Abstract
Atmospheric motion vectors (AMVs) derived from geostationary meteorological satellites have long stood as an important observational contributor to analyses of global-scale tropospheric wind patterns. This paradigm is evolving as numerical weather prediction (NWP) models and associated data assimilation systems are at the point [...] Read more.
Atmospheric motion vectors (AMVs) derived from geostationary meteorological satellites have long stood as an important observational contributor to analyses of global-scale tropospheric wind patterns. This paradigm is evolving as numerical weather prediction (NWP) models and associated data assimilation systems are at the point of trying to better resolve finer scales. Understanding the physical processes that govern convectively-driven weather systems is usually hindered by a lack of observations on the scales necessary to adequately describe these events. Fortunately, satellite sensors and associated scanning strategies have improved and are now able to resolve convective-scale flow fields. Coupled with the increased availability of computing capacity and more sophisticated algorithms to track cloud motions, we are now poised to investigate the development and application of AMVs to convective-scale weather events. Our study explores this frontier using new-generation GOES-R Series imagery with a focus on hurricane applications. A proposed procedure for processing enhanced AMV datasets derived from multispectral geostationary satellite imagery for hurricane-scale analyses is described. We focus on the use of the recently available GOES-16 mesoscale domain sector rapid-scan (1-min) imagery, and emerging methods to optimally extract wind estimates (atmospheric motion vectors (AMVs)) from close-in-time sequences. It is shown that AMV datasets can be generated on spatiotemporal scales not only useful for global applications, but for mesoscale applications such as hurricanes as well. Full article
(This article belongs to the Special Issue Satellite-Derived Wind Observations)
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