Evaluation of NASA GEOS‐ADAS Modeled Diurnal Warming Through Comparisons to SEVIRI and AMSR2 SST Observations

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.

Regional and Seasonal Variability of the Oceanic Thermal Skin Effect

“…The diurnal warming signals from observations and these schemes match fairly well for moderate U 10 around 6 m/s with the bias less than 0.1 K. The majority of U 10 measurements fall in the range from 4 to 10 m/s. Under light wind conditions, all of the three schemes show large errors, which may be attributed to the inappropriate assumptions for extending the vertical temperature profile from the surface to a fixed depth when the subsurface mixing is weak (Gentemann & Akella, 2018); the ZB05 scheme shows the largest bias. For U 10 > 10 m/s, the diurnal SST variability is small due to wind‐driven mixing, and all schemes predict very small wind‐speed dependence, but there is a spread in the asymptotic values.…”

Observational Needs of Sea Surface Temperature

“…This takes no account of the temperature gradient between the air-sea interface and in the upper 10 m and may introduce errors into forecasts (Beggs, 2010). New techniques apply cool-skin and warm-layer models on top of the standard ocean model configuration to predict the actual ocean skin temperature (Gentemann and Akella, 2018). Two-way airsea coupled weather prediction models have been developed, such as the ECMWF Integrated Forecasting System (IFS) 10 and the Met Office Unified Model Global Coupled Model 2.0 (Williams et al, 2015).…”

Diurnal Ocean Surface Warming Drives Convective Turbulence and Clouds in the Atmosphere

“…In the tropics, diurnal SST range (dSST) is strong under weak winds in areas of convergence and between storms. These conditions are most common in the eastern tropical Pacific intertropical convergence zone, in the convergence of Western Pacific summer monsoon westerlies and easterly trade winds, and during phases of suppressed precipitation of tropical intraseasonal variability (Clayson & Weitlich 2007; C. L. Gentemann & Akella 2018) such as the Madden Julian Oscillation (MJO).…”