Data used in "The role of in-situ ocean data assimilation in subseasonal forecasts of the tropical Pacific Ocean"
收藏DataCite Commons2022-10-31 更新2025-04-09 收录
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https://scholar.colorado.edu/concern/datasets/x633f252g
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资源简介:
The tropical Pacific plays an important role in modulating the global climate through its prevailing sea surface temperature spatial structure and dominant climate modes like ENSO, MJO, and their teleconnections. These modes of variability, including their oceanic anomalies, are considered to provide sources of prediction skill on subseasonal timescales in the tropics. Therefore, this study aims to examine how assimilating in-situ ocean observations influences the initial ocean state estimate and the subseasonal forecast. We analyze two subseasonal forecasts generated with European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) where the ocean states were initialized using two Observing System Experiment (OSE) reanalyses. We find that the initial SST differences between forecasts with and without assimilation of in-situ ocean observations grow with time, resulting in a reduced cold tongue bias when assimilating in-situ ocean observations. This growth of SST difference in the forecast is not attributable to surface heat fluxes, suggesting an important role of ocean processes on the evolution of SST difference. Two mechanisms related to air-sea coupling are considered to contribute to the SST difference evolution. One is a positive feedback between zonal SST gradient, pressure gradient, and surface wind. The other is the difference in Ekman suction and mixing at the equator due to the differences in surface wind speed. While the initial mixed layer depth (MLD) can be improved through ocean data assimilation, this improvement is not maintained in the forecasts. Instead, the MLD jumps at the beginning of the forecast and is overwhelmed by the shallow forecast model biases. These results emphasize how initialization and model biases in the surface and subsurface ocean state influence the air-sea interaction and thus the accuracy of subseasonal forecast in the tropical Pacific.
提供机构:
University of Colorado Boulder
创建时间:
2022-10-31



