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Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements. REMOTE SENSING 2022. [DOI: 10.3390/rs14133016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The space-borne microwave radiometers and scatterometers can effectively measure global sea surface winds under non-precipitation. However, the measurements in rainy conditions significantly degrade, which are usually flagged as poor quality or invalidated for some scientific purposes. This paper develops a combined active–passive wind vector retrieval model for rainy conditions based on the HY-2B radiometer and scatterometer measurements. In our model, the polarization ratio of brightness temperatures at 6.925 GHz (PR06) is used as an indicator to implicitly represent the rain effect. For wind speed retrieval, a statistical regression model is trained as a function of PR06 and brightness temperatures of the radiometer. Moreover, two new geophysical model functions, including rain effect, are developed for wind direction inversion. Comparisons between HY-2B retrieval results and ERA5 wind products indicate that the retrieval model performs well under all rainy conditions. The overall root mean squared errors (RMSEs) of wind speed and direction retrievals are 1.60 m/s and 20.60°, respectively. With an increase in the rain rate, the wind retrieval performance degrades slightly and still provides a reliable retrieval result.
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Ruf CS, Chew C, Lang T, Morris MG, Nave K, Ridley A, Balasubramaniam R. A New Paradigm in Earth Environmental Monitoring with the CYGNSS Small Satellite Constellation. Sci Rep 2018; 8:8782. [PMID: 29884899 PMCID: PMC5993737 DOI: 10.1038/s41598-018-27127-4] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 05/25/2018] [Indexed: 12/03/2022] Open
Abstract
A constellation of small, low-cost satellites is able to make scientifically valuable measurements of the Earth which can be used for weather forecasting, disaster monitoring, and climate studies. Eight CYGNSS satellites were launched into low Earth orbit on December 15, 2016. Each satellite carries a science radar receiver which measures GPS signals reflected from the Earth surface. The signals contain information about the surface, including wind speed over ocean, and soil moisture and flooding over land. The satellites are distributed around their orbit plane so that measurements can be made more often to capture extreme weather events. Innovative engineering approaches are used to reduce per satellite cost, increase the number in the constellation, and improve temporal sampling. These include the use of differential drag rather than propulsion to adjust the spacing between satellites and the use of existing GPS signals as the science radars' transmitter. Initial on-orbit results demonstrate the scientific utility of the CYGNSS observations, and suggest that a new paradigm in spaceborne Earth environmental monitoring is possible.
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Affiliation(s)
- Christopher S Ruf
- Climate and Space Dept., University of Michigan, Ann Arbor, MI, USA.
| | - Clara Chew
- University Corporation for Atmospheric Research, Boulder, CO, USA
| | - Timothy Lang
- NASA Marshall Space Flight Center, Huntsville, AL, USA
| | - Mary G Morris
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Kyle Nave
- Applied Defense Solutions, Columbia, MD, USA
| | - Aaron Ridley
- Climate and Space Dept., University of Michigan, Ann Arbor, MI, USA
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McCarty W, Chattopadhyay M, Conaty A. Evaluation of RapidScat Ocean Vector Winds for Data Assimilation and Reanalysis. MONTHLY WEATHER REVIEW 2018; 146:199-211. [PMID: 32747839 PMCID: PMC7398349 DOI: 10.1175/mwr-d-17-0117.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The RapidScat scatterometer was built as a low cost follow-on to the QuikSCAT mission. It flew on the International Space Station (ISS) and provided data from 3 October 2014 to 20 August 2016 and provided surface wind vectors retrieved from surface roughness estimates taken at multiple azimuth angles. These measurements were unique to the historical scatterometer record in that the ISS flies in a low inclination, non-sun-synchronous orbit. Scatterometry-derived wind vectors have been routinely assimilated in both forward processing and reanalysis systems run at the Global Modeling and Assimilation Office (GMAO). As the RapidScat retrievals were made available in near-real-time, they were assimilated in the forward processing system, and the methods to assimilate and evaluate these retrievals are described. Time series of data statistics are presented first for the near-real-time data assimilated in GMAO forward processing. Second, the full data products provided by the RapidScat team are compared passively to the MERRA-2 reanalysis. Both sets of results show that the root mean squared (RMS) difference of the observations and the GMAO model background fields increased over the course of the data record. Furthermore, the observations and the backgrounds are shown to be biased for both the zonal and meridional wind components. The retrievals are shown to have had a net forecast error reduction via the forecast sensitivity observation impact (FSOI) metric, which is a quantification of 24 hour forecast error reduction, though the impact became neutral as the signal to noise ratio of the instrument decreased over its lifespan.
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Affiliation(s)
- Will McCarty
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD
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A Novel Integrated Algorithm for Wind Vector Retrieval from Conically Scanning Scatterometers. REMOTE SENSING 2013. [DOI: 10.3390/rs5126180] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Harlan J, O'Brien JJ. Assimilation of scatterometer winds into surface pressure fields using a variational method. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/jd091id07p07816] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Quilfen Y, Chapron B, Elfouhaily T, Katsaros K, Tournadre J. Observation of tropical cyclones by high-resolution scatterometry. ACTA ACUST UNITED AC 1998. [DOI: 10.1029/97jc01911] [Citation(s) in RCA: 226] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Colton MC, Plant WJ, Keller WC, Geernaert GL. Tower-based measurements of normalized radar cross section from Lake Ontario: Evidence of wind stress dependence. ACTA ACUST UNITED AC 1995. [DOI: 10.1029/95jc00364] [Citation(s) in RCA: 27] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Schultz H. A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data. ACTA ACUST UNITED AC 1990. [DOI: 10.1029/jc095ic04p05291] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Pierson WJ. Examples of, reasons for, and consequences of the poor quality of wind data from ships for the marine boundary layer: Implications for remote sensing. ACTA ACUST UNITED AC 1990. [DOI: 10.1029/jc095ic08p13313] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Keller WC, Wismann V, Alpers W. Tower-based measurements of the ocean C band radar backscattering cross section. ACTA ACUST UNITED AC 1989. [DOI: 10.1029/jc094ic01p00924] [Citation(s) in RCA: 70] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Yu TW. A method for determining equivalent depths of the atmospheric boundary layer over the oceans. ACTA ACUST UNITED AC 1988. [DOI: 10.1029/jc093ic04p03655] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Liu WT. Moisture and latent heat flux variabilities in the tropical Pacific derived from satellite data. ACTA ACUST UNITED AC 1988. [DOI: 10.1029/jc093ic06p06749] [Citation(s) in RCA: 99] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Glazman RE, Pihos GG, Ip J. Scatterometer wind speed bias induced by the large-scale component of the wave field. ACTA ACUST UNITED AC 1988. [DOI: 10.1029/jc093ic02p01317] [Citation(s) in RCA: 27] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Donelan MA, Pierson WJ. Radar scattering and equilibrium ranges in wind-generated waves with application to scatterometry. ACTA ACUST UNITED AC 1987. [DOI: 10.1029/jc092ic05p04971] [Citation(s) in RCA: 520] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Chelton DB, Wentz FJ. Further development of an improved altimeter wind speed algorithm. ACTA ACUST UNITED AC 1986. [DOI: 10.1029/jc091ic12p14250] [Citation(s) in RCA: 57] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Woiceshyn PM, Wurtele MG, Boggs DH, McGoldrick LF, Peteherych S. The necessity for a new parameterization of an empirical model for wind/ocean scatterometry. ACTA ACUST UNITED AC 1986. [DOI: 10.1029/jc091ic02p02273] [Citation(s) in RCA: 59] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Wentz FJ, Mattox LA, Peteherych S. New algorithms for microwave measurements of ocean winds: Applications to Seasat and the special sensor microwave imager. ACTA ACUST UNITED AC 1986. [DOI: 10.1029/jc091ic02p02289] [Citation(s) in RCA: 92] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Pierson WJ, Sylvester WB, Donelan MA. Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts. ACTA ACUST UNITED AC 1986. [DOI: 10.1029/jc091ic02p02263] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Baker WE, Atlas R, Kalnay E, Halem M, Woiceshyn PM, Peteherych S, Edelmann D. Large-scale analysis and forecast experiments with wind data from the Seasat A scatterometer. ACTA ACUST UNITED AC 1984. [DOI: 10.1029/jd089id03p04927] [Citation(s) in RCA: 28] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Wentz FJ, Peteherych S, Thomas LA. A model function for ocean radar cross sections at 14.6 GHz. ACTA ACUST UNITED AC 1984. [DOI: 10.1029/jc089ic03p03689] [Citation(s) in RCA: 214] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Lame DB, Born GH. SEASAT measurement system evaluation: Achievements and limitations. ACTA ACUST UNITED AC 1982. [DOI: 10.1029/jc087ic05p03175] [Citation(s) in RCA: 37] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Wentz FJ, Cardone VJ, Fedor LS. Intercomparison of wind speeds inferred by the SASS, altimeter, and SMMR. ACTA ACUST UNITED AC 1982. [DOI: 10.1029/jc087ic05p03378] [Citation(s) in RCA: 37] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Moore RK, Birrer IJ, Bracalente EM, Dome GJ, Wentz FJ. Evaluation of atmospheric attenuation from SMMR brightness temperature for the SEASAT satellite scatterometer. ACTA ACUST UNITED AC 1982. [DOI: 10.1029/jc087ic05p03337] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Schroeder LC, Boggs DH, Dome G, Halberstam IM, Jones WL, Pierson WJ, Wentz FJ. The relationship between wind vector and normalized radar cross section used to derive SEASAT-A satellite scatterometer winds. ACTA ACUST UNITED AC 1982. [DOI: 10.1029/jc087ic05p03318] [Citation(s) in RCA: 163] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Brown RA, Cardone VJ, Guymer T, Hawkins J, Overland JE, Pierson WJ, Peteherych S, Wilkerson JC, Woiceshyn PM, Wurtele M. Surface wind analyses for SEASAT. ACTA ACUST UNITED AC 1982. [DOI: 10.1029/jc087ic05p03355] [Citation(s) in RCA: 33] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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