Daily initialized coupled and uncoupled numerical weather prediction (NWP) forecasts from the global Met Office Unified Model (MetUM) are compared for the 2016 Indian summer monsoon. Three MetUM configurations are used: atmosphere only (ATM), coupled to a mixed‐layer ocean model (KPP), and coupled to a dynamical ocean model (NEMO). The analysis focuses on the impact of air–sea coupling, particularly in the Bay of Bengal (BoB), on NWP for monsoon rainfall. Seasonal‐mean biases in all three configurations are highly consistent and driven by errors in atmospheric processes. Rainfall is initially overestimated over India, but underestimated over the BoB, the latter associated with too much short‐wave radiation and too little cloud cover in MetUM. The excess short‐wave radiation (>40 W·m⁻² over the northwest BoB) is partially compensated by additional latent cooling, primarily due to overestimated surface wind speeds. In NEMO and KPP, coupling improves the timing of intraseasonal active and break phases over India, primarily the end of these phases, which are systematically too late in ATM. NEMO and KPP show a more realistic intraseasonal local phase relationship between sea surface temperature (SST) and rainfall throughout the BoB, but no configuration reproduces the observed significant lagged relationship between BoB SST and Indian rainfall. The lack of this relationship may be partly attributed to weak heat flux feedbacks to northern BoB SST, with the forecast short‐wave feedback having systematically the wrong sign (positive) compared to satellite radiation, and thus contributing to SST warming at all lead times. Based on these MetUM forecasts, there is a limited impact of coupling on NWP for monsoon rainfall, both for the mean rainfall and intraseasonal variability. Further research to improve NWP for monsoon rainfall should focus on reducing MetUM atmospheric systematical biases.

中文翻译：

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海气耦合对2016年印度夏季风预报及其季节内变化的影响

比较了2016年印度夏季风的全球气象局统一模型（MetUM）的每日初始化耦合和非耦合数值天气预报（NWP）预测。使用了三种MetUM配置：纯大气层（ATM），耦合到混合层海洋模型（KPP）和动态海洋模型（NEMO）。分析的重点是气海耦合，特别是在孟加拉湾（BoB），对季风降雨NWP的影响。这三种配置中的季节性均值偏差是高度一致的，并且受大气过程误差的影响。最初，印度的降雨被高估了，但BoB的估算却被低估了，后者与MetUM中的短波辐射过多和云量太少有关。多余的短波辐射（> 40  W · m⁻²主要是由于高估了地表风速，部分额外的潜在冷却措施部分补偿了西北BoB上空的温度）。在NEMO和KPP中，耦合改善了印度整个季节内活动和中断阶段的时间，主要是这些阶段的结束，这在ATM中系统地为时已晚。NEMO和KPP显示了整个BoB的海表温度（SST）与降雨之间的更现实的季节内局部相位关系，但是没有任何配置能够重现BoB SST与印度降雨之间的明显滞后关系。缺乏这种关系的部分原因可能是对北部BoB SST的热通量反馈较弱，与卫星辐射相比，预测的短波反馈在系统上具有错误的符号（正），从而导致所有提前期的SST变暖。根据这些MetUM预测，季风降雨对NWP的耦合影响有限，无论是平均降雨量还是季节内变异性。进一步改善季风降水NWP的研究应集中在减少MetUM大气系统偏差上。