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
On-line přístup:	Získat plný text
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