SST Improvements in the NASA GMAO Weather Analysis and Prediction System

Akella, Santha

关键词: SEA SURFACE TEMPERATURE;    NUMERICAL WEATHER FORECASTING;    INFRARED RADIATION;    MICROWAVE RADIOMETERS;    WEATHER FORECASTING;    DIURNAL VARIATIONS;    SKIN TEMPERATURE (NON-BIOLOGICAL);    ATMOSPHERIC MODELS;    ASSIMILATION;    PREDICTION ANALYSIS TECHNIQUES;    DATA PROCESSING;   

RP-ID  :  GSFC-E-DAA-TN70167

美国|英语

来源: NASA Technical Reports Server

【 摘 要 】

It is well known that the sea surface temperature (SST) exhibits a diurnal cycle. Since January 2017, the NASA GMAO's Weather Analysis & Prediction System (https://gmao.gsfc.nasa.gov/weather_prediction/) includes a model for this diurnal cycle, a cool-skin layer and assimilates for skin SST. Data assimilation for the skin SST is carried out along with the 3-D state of the atmosphere, primarily using infrared radiance measurements, that are sensitive to the cool-skin and diurnal warming. In the context of Numerical Weather Prediction (NWP), this implies that the skin SST from our system is tightly coupled to the overlaying atmosphere and constrained by all the available atmospheric and surface-sensitive observations (in situ and satellite brightness temperatures). Comparisons of the SST diurnal cycle with other SST retrievals (SEVIRI (Spinning Enhanced Visible & InfraRed Imager) and AMSR-2 (Advanced Microwave Scanning Radiometer-2)) has shown mostly similar diurnal variation, however, the former decays at a faster rate. This poster presents our SST plus atmosphere assimilation methodology, and recent improvements to the skin SST model to address the known issues. Global, hourly estimates of the cool-skin and diurnal warm layer fields would be of interest to the SST retrieval community.