SPATIO-TEMPORAL VARIATION CHARACTERISTICS OF EXTREMELY HEAVY PRECIPITATION FREQUENCY OVER SOUTH CHINA IN THE LAST 50 YEARS

This paper comprehensively studies the spatio-temporal characteristics of the frequency of extremely heavy precipitation events over South China by using the daily precipitation data of 110 stations during 1961 to 2008 and the extremely heavy precipitation thresholds determined for different stations by REOF, trend coefficients, linear trend, Mann-Kendall test and variance analysis. The results are shown as follows. The frequency distribution of extremely heavy precipitation is high in the middle of South China and low in the Guangdong coast and western Guangxi. There are three spatial distribution types of extremely heavy precipitation in South China. The consistent anomaly distribution is the main type. Distribution reversed between the east and the west and between the south and the north is also an important type. Extremely heavy precipitation events in South China mainly occurred in the summer-half of the year. Their frequency during this time accounts for 83.7% of the total frequency. In the 1960 s and 1980 s, extremely heavy precipitation events were less frequent while having an increasing trend from the late 1980 s. Their climatological tendency rates decrease in the central and rise in the other areas of South China, and on average the mean series also shows an upward but insignificant trend at all of the stations. South China's frequency of extremely heavy precipitation events can be divided into six major areas and each of them shows a different inter-annual trend and three of the representative stations experience abrupt changes by showing remarkable increases in terms of Mann-Kendall tests.

Recognition of Organizational Morphology of Mesoscale Convective Systems Using Himawari-8 Observations

The onset,evolution,and propagation processes of convective cells can be reflected by the organizational morphology of mesoscale convective systems(MCSs),which are key factors in determining the potential for heavy precipitation.This paper proposed a method for objectively classifying and segmenting MCSs using geosynchronous satellite observations.Validation of the product relative to the classification in radar composite reflectivity imagery indicates that the algorithm offers skill for discriminating between convective and stratiform areas and matched 65%of convective area identifications in radar imagery with a false alarm rate of 39%and an accuracy of 94%.A quantitative evaluation of the similarity between the structures of 50 MCSs randomly obtained from satellite and radar observations shows that the similarity was as high as 60%.For further testing,the organizational modes of the MCS that caused the heavy precipitation in Northwest China on August 21,2016(hereinafter known as the“0821”rainstorm)were identified.It was found that the MCS,accompanied by the“0821”rainstorm,successively exhibited modes of the isolated cell,squall line with parallel stratiform(PS)rain,and non-linear system during its life cycle.Among them,the PS mode might have played a key role in causing this flooding.These findings are in line with previous studies.

Improvement of an Extreme Heavy Rainfall Simulation Using Nudging Assimilation

From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging(GN) and spectral nudging(SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting(WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface(NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes,and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.

Study on Ensemble-Based Forecast of Extremely Heavy Rainfalls in China: Experiments for July 2011 Cases

According to the Anderson-Darling principle, a method for forecast of extremely heavy rainfall （abbre- viated as extreme rainfall/precipitation） was developed based on the ensemble forecast data of the T213 global ensemble prediction system （EPS） of the China Meteorological Administration （CMA）. Using the T213 forecast precipitation data during 2007-2010 and the observed rainfall data in June-August of 2001 2010, characteristics of the cumulative distribution functions （CDFs） of the observed and the T213 EPS forecast precipitation were analyzed. Accordingly, in the light of the continuous differences of the CDFs between model climate and EPS forecasts, a mathematical model of Extreme Precipitation Forecast Index （EPFI） was established and applied to forecast experiments of several extreme rainfall events in China during 17-31 July 2011. The results show that the EPFI has taken advantage of the tail information of the model climatic CDF and provided agreeable forecasts of extreme rainfalls. The EPFI based on the T213 EPS is useful for issuing early warnings of extreme rainfalls 3 7 days in advance. With extension of the forecast lead time, the EPFI becomes less skillful. The results also demonstrate that the rationality of the model climate CDF was of vital importance to the skill of EPFI.