Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The duration of dry periods is closely related to drought conditions and is used to evaluate the degree of drought. In this article, using the rotated empirical orthogonal function (REOF) and K‐medoids clustering methods and considering the spatial continuity, 500 stations in China are divided into 10 clusters to analyze the variation characteristics of consecutive dry days (CDDs) with different durations in spring. In Clusters 1–5 over the middle and lower reaches of the Yangtze River, South China, North China, and eastern and western Southwest China, the contribution percentage of short‐duration CDDs to total dry days decreases, while that of medium‐ and/or long‐duration CDDs increases, which leads to an increase in the total dry days and the duration of CDDs. In Clusters 6–8, the total dry days decrease, which are mainly contributed by the decreases in medium‐duration CDDs (for Cluster 6 over southern Northeast China) or long‐duration CDDs (for Clusters 7–8 over northern Northeast China and southern Xinjiang). The total dry days change little in Clusters 9–10 over eastern Northwest China and northern Xinjiang, which is attributed to the offset among the changes in the three‐type duration CDDs. In Clusters 6–10, the duration of CDDs shortens overall. The decadal changes of spring dry days in China exhibit remarkable regional differences. The total day days and three‐type duration CDDs in some clusters (1, 4, and 8) all have significant decadal changes, but they have not in Cluster 7. And the decadal change times also exhibit regional differences. The investigation of different‐duration CDDs in this study provides more information on droughts at different time scales in China.
The duration of dry periods is closely related to drought conditions and is used to evaluate the degree of drought. In this article, using the rotated empirical orthogonal function (REOF) and K‐medoids clustering methods and considering the spatial continuity, 500 stations in China are divided into 10 clusters to analyze the variation characteristics of consecutive dry days (CDDs) with different durations in spring. In Clusters 1–5 over the middle and lower reaches of the Yangtze River, South China, North China, and eastern and western Southwest China, the contribution percentage of short‐duration CDDs to total dry days decreases, while that of medium‐ and/or long‐duration CDDs increases, which leads to an increase in the total dry days and the duration of CDDs. In Clusters 6–8, the total dry days decrease, which are mainly contributed by the decreases in medium‐duration CDDs (for Cluster 6 over southern Northeast China) or long‐duration CDDs (for Clusters 7–8 over northern Northeast China and southern Xinjiang). The total dry days change little in Clusters 9–10 over eastern Northwest China and northern Xinjiang, which is attributed to the offset among the changes in the three‐type duration CDDs. In Clusters 6–10, the duration of CDDs shortens overall. The decadal changes of spring dry days in China exhibit remarkable regional differences. The total day days and three‐type duration CDDs in some clusters (1, 4, and 8) all have significant decadal changes, but they have not in Cluster 7. And the decadal change times also exhibit regional differences. The investigation of different‐duration CDDs in this study provides more information on droughts at different time scales in China.
ABSTRACT:In this study, we investigated changes in the precipitation characteristics for China from 1960 to 2012 based on a recent daily precipitation dataset of 666 climate stations and robust non-parametric trend detection techniques. We divided all precipitation events into four non-overlapping categories: light, moderate, heavy and very heavy based on percentile thresholds. We then established the trends for annual total and precipitation of different intensity categories, and examined their regional and seasonal variations. The results show that there was little change in annual total precipitation for entire China, but distinctive regional patterns existed. In general, precipitation increased in the west and decreased in east. Precipitation of different intensities, in general, changed in the same direction as the mean, but heavy and very heavy precipitation events had higher rates of change than mean precipitation. The exception was the southeast region, where despite the slight decrease in mean precipitation, heavy and very heavy precipitation still increased significantly. In addition, we used multiple regression models to explore the contribution of changes of frequency and intensity to total precipitation change, and the contributions of changes of precipitation at different intensities to total precipitation change. For western China, total precipitation change was associated more with frequency change, whereas in eastern China intensity contributed more. For precipitation amount, moderate, heavy and very heavy precipitations contributed to the total change, with little contribution from light precipitation change. For frequency, changes in light and moderate precipitation frequencies dominated the total change, with very little contributions from heavy and very heavy precipitation frequency changes. In addition, we examined the linkage between summer precipitation in eastern China and the East-Asian Summer Monsoon (EASM), found that the northern decrease and southern increase in summer precipitation was likely caused by the weakening of EASM over the study period.
This article presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in East China associated with variations of the East Asian summer monsoon (EASM) from 1979 to 2012. A high-quality daily precipitation data set covering 2076 observational stations in China is analysed. Based on the precipitation pattern analysis using empirical orthogonal functions and the regime shift detection method, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation, the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies to some extent during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport and contributes to the precipitation anomalies. In addition, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean through its effects on convective activity over the west Pacific that induces the cyclonic or anticyclonic anomaly over the South China and northwest Pacific.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.