Evaluation of NASA GEOS‐ADAS Modeled Diurnal Warming Through Comparisons to SEVIRI and AMSR2 SST Observations. Issue 2 (23rd February 2018)

• Record Type: Journal Article
• Authors: Gentemann, C. L.; Akella, S.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 2(2018)
• Page Start: 1364
• Page End: 1375
• Publication Date: 2018-02-23
• Subjects: SEVIRI -- AMSR2 -- SST -- diurnal warming -- GEOS‐ADAS; Oceanography -- Periodicals; 551.4605
• DOI: 10.1002/2017JC013186
• Languages: English
• ISSNs: 2169-9275

Abstract

Abstract: An analysis of the ocean skin Sea Surface Temperature (SST) has been included in the Goddard Earth Observing System (GEOS) ‐ Atmospheric Data Assimilation System (ADAS), Version 5 (GEOS‐ADAS). This analysis is based on the GEOS atmospheric general circulation model (AGCM) that simulates near‐surface diurnal warming and cool skin effects. Analysis for the skin SST is performed along with the atmospheric state, including Advanced Very High Resolution Radiometer (AVHRR) satellite radiance observations as part of the data assimilation system. One month (September, 2015) of GEOS‐ADAS SSTs were compared to collocated satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and Advanced Microwave Scanning Radiometer 2 (AMSR2) SSTs to examine how the GEOS‐ADAS diurnal warming compares to the satellite measured warming. The spatial distribution of warming compares well to the satellite observed distributions. Specific diurnal events are analyzed to examine variability within a single day. The dependence of diurnal warming on wind speed, time of day, and daily average insolation is also examined. Overall the magnitude of GEOS‐ADAS warming is similar to the warming inferred from satellite retrievals, but several weaknesses in the GEOS‐AGCM simulated diurnal warming are identified and directly related back to specific features in the formulation of the diurnal warming model. Key Points: Modeled diurnal warming is compared to collocated satellite observed diurnal warming Overall the modeled warming is similar to the satellite warming in magnitude, spatial distribution, and variability Weaknesses in the modeled warming were directly related back to specific features in the formulation of the model