Neural network temperature and moisture retrieval algorithm validation for AIRS/AMSU and CrIS/ATMS

We present comprehensive validation results for the recently introduced neural network technique for retrieving vertical profiles of atmospheric temperature and water vapor from spaceborne microwave and hyperspectral infrared sounding instruments. This technique is currently in operational use as th...

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Vydáno v:Journal of geophysical research. Atmospheres Ročník 121; číslo 4; s. 1414 - 1430
Hlavní autoři: Milstein, Adam B., Blackwell, William J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Washington Blackwell Publishing Ltd 27.02.2016
Témata:
Accuracy
Advanced Microwave Sounding Unit
advanced microwave sounding unit (AMSU)
Advanced Technology Microwave Sounder (ATMS)
Algorithms
Atmospheric Infrared Sounder
Atmospheric Infrared Sounder (AIRS)
Atmospheric temperature
Climatology
Cross‐Track Infrared Sounder (CrIS)
Data sources
Flight
Geophysics
Global weather
Ground truth
Infrared instruments
Infrared tracking
Instruments
Mathematical models
Meteorological satellites
Microwave sounding
Moisture
neural network
Neural networks
Profiles
Radiosondes
Resolution
Retrieval
Satellites
Sounding
Technology
Temperature
Temperature effects
Training
validation
Vertical profiles
Water vapor
Water vapour
Weather
Weather forecasting
ISSN:2169-897X, 2169-8996
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Popis
Shrnutí:We present comprehensive validation results for the recently introduced neural network technique for retrieving vertical profiles of atmospheric temperature and water vapor from spaceborne microwave and hyperspectral infrared sounding instruments. This technique is currently in operational use as the first guess for the NASA Atmospheric Infrared Sounder (AIRS) Science Team Version 6 retrieval algorithm. The validation incorporates a variety of data sources, independent from the algorithm training set, as ground truth, including global numerical weather analyses generated by the European Center for Medium‐Range Weather Forecasts, synoptic radiosonde measurements, and radiosondes dedicated for validation. The results demonstrate significant performance improvements over the previous AIRS/advanced microwave sounding unit (AMSU) operational sounding retrievals in both retrieval error and also show comparable vertical resolution. We also present initial neural network retrieval results using measurements from the Cross‐Track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) currently flying on the Suomi National Polar‐orbiting Partnership satellite. Key Points We present validation results for neural network retrievals of temperature and water vapor We show accuracy and resolution performance for AIRS/AMSU and CrIS/ATMS Results demonstrate significant performance improvement over previous AIRS/AMSU retrieval version
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ISSN:2169-897X
2169-8996
DOI:10.1002/2015JD024008