At present, high-resolution drought indices are scarce, and this problem has restricted the development of refined drought analysis to some extent. This study explored the possibility of calculating the standardized precipitation index (SPI) with short-term precipitation sequences in China, based on data from 2416 precipitation observation stations covering the time period from 1961 to 2019. The result shows that it is feasible for short-sequence stations to calculate SPI index, based on the spatial interpolation of the precipitation distribution parameters of the long-sequence station. Error analysis denoted that the SPI error was small in east China and large in west China, and the SPI was more accurate when the observation stations were denser. The SPI error of short-sequence sites was mostly less than 0.2 in most areas of eastern China and the consistency rate for the drought categories was larger than 80%, which was lower than the error using the 30-year precipitation samples. Further analysis showed that the estimation error of the distribution parameters $\beta$ and $q$ was the most important cause of SPI error. Two drought monitoring examples show that the SPI of more than 50,000 short-sequence sites can correctly express the spatial distribution of dry and wet and have refined spatial structure characteristics.

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting Lake basin. Afterwards, by means of the variance and autocorrelation coefficient that characterize the phenomenon of critical slowing down, the early-warning signals indicating the drought-flood state in the Dongting Lake basin are explored. The results show that an obvious drought-to-flood (flood-to-drought) event occurred around 1993 (2003) in the Dongting Lake basin in recent 60 years. The critical slowing down phenomena of the increases in the variance and autocorrelation coefficient, which are detected 5–10 years in advance, can be considered as early-warning signals indicating the drought-flood state transition. Through the studies on the drought-flood state and related early-warning signals for the Dongting Lake basin, the reliabilities of the variance and autocorrelation coefficient-based early-warning signals for abrupt changes are demonstrated. It is expected that the wide application of this method could provide important scientific and technological support for disaster prevention and mitigation in the Dongting Lake basin, and even in the middle and lower reaches of the Yangtze River.

Based on the U.S. Weather Research and Forecasting (WRF) numerical model, this study has developed the Northwest Mesoscale Numerical Prediction Service and Experimental System (NW-MNPS). Surface and sounding data assimilation has been introduced for this system. Effects of model vertical layers and land-use data replacement have been assessed. A year-long forecast validation and analysis have been performed. The following results have been obtained: (1) Data assimilation can improve the performance of regional numerical forecasting. (2) Compared to simulations with 40 vertical layers, simulations with 55 vertical layers are more accurate. The average absolute error and root-mean-square error of the 48 h surface element forecast decrease. The analysis of threat score (TS) and equitable threat score (ETS) shows that there are higher TS and ETS values for various precipitation intense levels, in particular for heavy rainfall when comparing a 55-vertical-layer test with a 40-vertical-layer test. (3) Updating the database to include vegetation coverage can more accurately reflect actual surface conditions. The updated land-use data reduce prediction errors in all domains of the NW-MNPS.

Synoptic circulation patterns over the midlatitudes play a pivotal role in regional precipitation changes; however, the synoptic circulation patterns over eastern Asia (35°–60° N, 105°–145° E) and their effects on extreme precipitation events in the North China Plain (NCP) and northeastern China (NEC) remain unclear. The summer daily 500 hPa geopotential height anomaly fields for 1979–2021 are classified into six synoptic circulation patterns using self-organizing map (SOM) cluster analysis. The SOM1 pattern, characterized by a high-pressure ridge over the north of eastern Asia and a trough near the Korean Peninsula, yields decreased precipitation in NEC. The SOM2 pattern reveals a robust high ridge over eastern Asia, resulting in a higher incidence of regional extreme precipitation events (REPEs) of approximately 24% in the NCP. Under the SOM3 pattern, the anomalous cyclonic circulation over eastern Asia leads to above-average precipitation in the NCP. The SOM4 pattern yields the highest incidence of REPEs in NEC, with the lowest incidence of REPEs in the NCP, as the anomalous cyclonic circulation over eastern Asia moves southeastward compared to the SOM3 pattern. The SOM5 pattern presenting an anticyclone–cyclone dipole reduces precipitation in the NCP and NEC, and the anticyclonic circulation near eastern China associated with the SOM6 pattern causes above-average precipitation in the NCP. On interannual time scales, the SOM2 pattern occurrence with an increasing trend tends to induce an increasing summer precipitation trend in the NCP. The SOM3 pattern occurrence is negatively correlated with the summer precipitation in NEC. Overall, classifying the synoptic circulation patterns helps to improve precipitation forecasting and provides insights into the synoptic circulation patterns dominating the occurrences of REPEs.

The hazard of ice accretion on overhead power circuits is significant, yet predicting it is very difficult. The key reason lies in the shortage of sufficient observational data on ice thickness, and previous studies have also rarely taken into account micro-terrain and micro-meteorological conditions. In response to the challenge of simulating overhead line icing, this study introduces a new icing simulation technique that fully considers the effects of micro-terrain and micro-meteorology. For this technique, typical micro-terrains of overhead line areas are first identified by using high-resolution elevation data, and the icing thickness characteristics in different micro-terrains are analyzed. Subsequently, icing thickness simulations for different micro-terrains are conducted. The results indicate that during the icing process, the icing thickness ranges from 5 mm to 8 mm under three types of micro-terrain, namely, “uplift type”, “alpine drainage divide type” and “canyon wind channel type”, whereas the icing thickness is less than 5 mm in the “flat type” of micro-terrain. This finding suggests that the first three micro-terrain types facilitate icing on overhead transmission lines due to the condensation and uplifting effects of water vapor caused by terrain. However, flat terrain lacks the conditions necessary for water vapor accumulation and thus is not easy to form icing. The results are advantageous for the deployment of overhead power lines in intricate terrain. It is advisable to steer clear of regions susceptible to icing, and endeavor to install circuits in level territories whenever feasible. In addition, the simulated icing thickness under different terrains is in good agreement with the observations. Specifically, the correlation coefficient between simulated and observed icing thickness is significant at the 0.99 confidence level, and the deviations between them are within 0.5 mm. This signifies that the forecasting methodologies employed are dependable and possess significant implications as a reference for disaster prevention and mitigation efforts.