COWVR/TEMPEST Multisensor Satellite-Based Surface State Parameter Retrievals

被引:0
|
作者
May, Jackie C. [1 ]
Rowley, Clark [1 ]
机构
[1] US Naval Res Lab, Stennis Space Ctr, Ocean Sci Div, Bay St Louis, MS 39529 USA
关键词
Ocean temperature; Sea surface; Brightness temperature; Satellite broadcasting; Temperature measurement; Surface treatment; Cloud computing; Temperature sensors; Atmospheric measurements; Surface states; Compact Ocean Wind Vector Radiometer (COWVR); Naval Research Laboratory Ocean Surface Flux System (NFLUX); satellite retrievals; surface air temperature; surface specific humidity; Temporal Experiment for Storms and Tropical Systems (TEMPEST); AIR-SEA INTERACTION; GLOBAL OCEAN; TEMPERATURE; HUMIDITY; MICROWAVE; SYSTEM;
D O I
10.1109/JSTARS.2024.3520429
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Accurate estimates of essential climate variables, including ocean surface specific humidity (q(a)) and air temperature (T-a), at the air-sea interface are critical in understanding many atmospheric and oceanic processes and impacts and can be used to inform data-assimilative forecast systems about the coupled atmosphere-ocean state. To aid in addressing this scientific community need, the data processing component of the Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) uses multiple polynomial regression algorithms to produce single-sensor satellite-based swath-level estimates of surface state parameters and heat fluxes over the global ocean. This study extends the current NFLUX processing to include data processing from multiple sensors onboard the same platform. Specifically, we are combining satellite brightness temperature data from the Compact Ocean Wind Vector Radiometer (COWVR) and the Temporal Experiment for Storms and Tropical Systems (TEMPEST) to produce q(a) and T-a estimates. These combined surface estimates have error statistics comparable to current NFLUX satellite-based swath-level estimates from single sensors.
引用
收藏
页码:2444 / 2449
页数:6
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