China has been engaged in short-term climate prediction for nearly 70 years and was one of the earliest countries in the world to carry out short-term climate prediction and relevant researches. Since March 2021, the National Climate Center (NCC) of China has released officially the climate prediction for the next 15-30 days, months and seasons through its website. Short term climate forecasts are receiving increasing attention from society. In 2013, based on the operational prediction of short-term climate and the previous assessment methods, the Department of Forecasting and Networking of China Meteorological Administration issued a new method to assess operationally the short-term climate prediction. Using this new method, this paper analyzed the evaluation results for monthly climate prediction products during 1971-2020 released by the NCC. The results show that the prediction scores are lower in the winter half year than in the summer half year both for monthly temperature anomaly and precipitation anomaly percentage. The forecast skill of monthly temperature anomaly has been improved significantly in recent 50 years. The anomaly correlation coefficient between the forecast and observation of monthly temperature anomaly are positive in most parts of China throughout the year, except for December. The prediction level of monthly precipitation anomaly percentage in China in 50 years shows a trend of decreasing first and then increasing, especially in the past 30 years, it shows a relatively stable upward trend. The distribution of correlations between precipitation forecast and observation has three main patterns, which is much more complex than that of temperature, suggesting that the precipitation forecast is more challenging than temperature forecast.
In the context of global warming, soil moisture is a key factor affecting climate drought, crop growth, and environmental change. Using remote sensing technology to estimate soil moisture not only enhances drought early warning capabilities but also holds significant implications for agricultural development, ecological protection, and restoration. This article summarizes the currently used remote sensing data for soil moisture inversion and analyzes its development trends. It elaborates in detail on the principles, advantages, and disadvantages of each inversion method from optical and active-passive microwave perspectives, and further explores four main areas of soil moisture research: active-passive microwave, multisource data fusion, spatial scale conversion, and methods and model improvements. Finally, it outlines the evolutionary trends of remote sensing technology in the field of soil moisture inversion and presents a future outlook.