[1] Two long-term simulations with the weather research and forecasting model are conducted to assess the contribution of land-atmosphere coupling to interannual variability of summer climate over East Asia. The control experiment (CTL) uses a fully coupled land surface model, while an additional experiment replaces soil moisture evolution at each time step with the climatology of CTL and thus removes the interannual variability of soil moisture. CTL is able to reproduce relatively well climatic means and interannual variability of summer climate over East Asia though some biases exist. It is found that land-atmosphere coupling plays a critical role in influencing summer climate variability, in particular over the climatic and ecological transition zones. Interactive soil moisture strongly amplifies daily mean temperature variability over the southern Siberia-northern Mongolia region, the region from northeast China to central China, and the eastern part of South Asia, accounting for half or more of the total variance. Soil moisture is found to exert substantially stronger impacts on daily maximum temperature variability than on daily mean temperature variability but generally has small effects on daily minimum temperature except for the eastern Tibetan Plateau and some other areas. Soil moisture makes a dominant contribution to precipitation variability over the climatic and ecological transition zones of the southern Siberia-northern Mongolia region and northern China and many areas of western China. While soil moisture-temperature coupling is largely determined by the ability of soil moisture to affect surface fluxes, soil moistureprecipitation coupling also depends on other physical processes, particularly moisture convection.

Climate extremes, such as extreme hot temperatures and heat waves, can have dramatic societal, economic, and ecological consequences. China has experienced remarkable interannual and decadal changes in hot extremes during the last several decades. However, the underlying mechanisms responsible for changes in the hot extremes over China have not been clearly identified. In this study, we investigate the role of land-atmosphere coupling for hot days and heat waves during summer over China using two long-term Weather Research and Forecasting model simulations with and without interactive soil moisture. Results indicate that land-atmosphere coupling mainly amplifies hot extremes over China. In particular, significant amplifying effects appear over most of eastern and southwestern China. Over these areas, land-atmosphere coupling generally accounts for 30%-70% of the numbers of hot days and heat waves. This study highlights the critical importance of land-atmosphere interactions for the occurrence of hot extremes over China. land-atmosphere coupling, hot extremes, regional climate modeling Citation:Zhang J Y, Wu L Y. Land-atmosphere coupling amplifies hot extremes over China.

[1] Soil moisture influences on daily maximum (T max ) and minimum (T min ) temperatures, and thus the diurnal temperature range (DTR) in summer, are statistically quantified across the contiguous Unites States using soil moisture from the Global Land Data Assimilation System and observational temperatures. A soil moisture feedback parameter is computed based on lagged covariance ratios. Over the zone from California through the Midwest to the Southeast, the soil moisture exhibits a negative feedback on DTR mainly through its damping effect on T max . In contrast, a positive feedback on DTR dominates Arizona and New Mexico as the soil moisture exerts a stronger negative forcing on T min relative to T max . The feedback-induced variability accounts for typically 10-20% of the total DTR variance over regions where strong feedbacks are identified. The results provide a useful benchmark for evaluating climate model simulations, although the employed data and method have limitations that should be recognized.

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In this study, we perform two regional climate simulations with the Weather Research and Forecasting model driven by outputs from the Community Climate System Model (CCSM-WRF) to investigate the role of soil moisture feedbacks in summer surface air temperature variability over East Asia for the period of 1976À2005. Strong soil moisture feedbacks on the daily mean and maximum temperatures identified by the CCSM-WRF model system mainly appear over the region from southern Siberia through eastern Mongolia to northeast China, the Tibetan Plateau, and most areas of central and east China, accounting for 30%À70% of the total variances. Meanwhile, the simulated soil moisture feedbacks on daily minimum temperature are shown to be much weaker than those on daily mean and maximum temperatures. The soil moisture-temperature feedbacks in the CCSM-WRF model system are generally well validated with those from two reanalysis products. The analysis of the physical processes shows that soil moisture feedback strength is mainly determined by the ability of soil moisture to influence the local surface heat fluxes and planetary boundary layer processes. The reasonable simulations of present soil moisture-temperature feedbacks indicate that the CCSM-WRF model system can be further applied to understand the role of soil moisture in influencing projected climate change over East Asia.

Two long-term regional climate model simulations with and without subsurface soil temperature feedbacks are performed to investigate the role of soil temperature-atmosphere coupling in influencing interannual variability of summer climate over East Asia. Results indicate that soil temperature-atmosphere coupling depends on climate regimes, mainly affecting summer climate variability over the arid/semi-arid regions. Over these areas, subsurface soil temperature feedbacks play an important role in amplifying summer surface air temperature variability, accounting for about 30-70% of total variance. The feedbacks on precipitation variability are weaker than those on surface air temperature variability over the arid/semi-arid regions, but are still significant over many areas of western part.

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[1] It is well known that the slowly varying oceanic processes provide the primary source for East Asian summer monsoon (EASM) predictability. However, the memory inherent in the land surface state is less well understood or applied toward the EASM prediction. Here we investigate the role of antecedent vegetation conditions over East Asia for the EASM variation and prediction using March, April, May, and spring mean satellite-sensed Normalized Difference Vegetation Index (NDVI) for the period of . Results show that May vegetation greenness on the southeastern Tibetan Plateau (TP) is most closely linked to the EASM, accounting for about half of the total EASM variance. May vegetation greenness on the southeastern TP has significant and positive correlations with summer rainfall over the southeastern TP, East Asian summer subtropical frontal region, and many areas of northern China. We further discuss the possible physical mechanism explaining our findings. It is proposed that increased TP vegetation greenness enhances surface thermal effects, which subsequently warm atmospheric temperature, as well as strengthen ascending motion, convergence at the lower layers and divergence at the higher layers, and summer monsoon circulation. Finally, a linear regression model is developed to predict the EASM strength by combination of El Niño-Southern Oscillation (ENSO) and the vegetation greenness. Hindcast for the period shows that the use of the southeastern TP vegetation information can highly improve the EASM prediction skill compared to that using ENSO alone.