scholarly journals Potential Predictability of Seasonal Extreme Precipitation Accumulation in China

2017 ◽  
Vol 18 (4) ◽  
pp. 1071-1080 ◽  
Author(s):  
Wenguang Wei ◽  
Zhongwei Yan ◽  
P. D. Jones
Keyword(s):  
Extreme Precipitation ◽  
Yangtze River ◽  
Large Scale ◽  
Southern China ◽  
Yangtze River Valley ◽  
River Valley ◽  
Northwestern China ◽  
Chain Model ◽  
The Yangtze River ◽  
Potential Predictability

Abstract The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960–2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes.

scholarly journals Estimation of the Potential Infestation Area of Newly-invaded Fall Armyworm Spodoptera Frugiperda in the Yangtze River Valley of China

Insects ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 298 ◽  
Author(s):  
Qiu-Lin Wu ◽  
Li-Mei He ◽  
Xiu-Jing Shen ◽  
Yu-Ying Jiang ◽  
Jie Liu ◽  
...  
Keyword(s):  
Yangtze River ◽  
Southern China ◽  
Meteorological Data ◽  
Fall Armyworm ◽  
Northern China ◽  
Yangtze River Valley ◽  
River Valley ◽  
Flight Behavior ◽  
The Yangtze River ◽  
Self Powered

The fall armyworm (FAW), native to the Americas, has rapidly invaded the whole of Southern China since January 2019. In addition, it can survive and breed in the key maize- and rice- growing area of the Yangtze River Valley. Furthermore, this pest is also likely to continue infiltrating other cropping regions in China, where food security is facing a severe threat. To understand the potential infestation area of newly-invaded FAW from the Yangtze River Valley, we simulated and predicted the possible flight pathways and range of the populations using a numerical trajectory modelling method combining meteorological data and self-powered flight behavior parameters of FAW. Our results indicate that the emigration of the first and second generations of newly-invaded FAW initiating from the Yangtze River Valley started on 20 May 2019 and ended on 30 July 2019. The spread of migratory FAW benefitted from transport on the southerly summer monsoon so that FAW emigrants from the Yangtze River Valley can reach northern China. The maize-cropping areas of Northeastern China, the Korean Peninsula and Japan are at a high risk. This study provides a basis for early warning and a broad picture of FAW migration from the Yangtze River Valley.

scholarly journals Holocene Environmental Archaeology of the Yangtze River Valley in China: A Review

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 302
Author(s):  
Li Wu ◽  
Shuguang Lu ◽  
Cheng Zhu ◽  
Chunmei Ma ◽  
Xiaoling Sun ◽  
...  
Keyword(s):  
Climate Change ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Valley ◽  
River Valley ◽  
Interactive Effects ◽  
Environmental Archaeology ◽  
The Yangtze River ◽  
The Past ◽  
Neolithic Cultures

The Yangtze River Valley is an important economic region and one of the cradles of human civilization. It is also the site of frequent floods, droughts, and other natural disasters. Conducting Holocene environmental archaeology research in this region is of great importance when studying the evolution of the relationship between humans and the environment and the interactive effects humans had on the environment from 10.0 to 3.0 ka BP, for which no written records exist. This review provides a comprehensive summary of materials that have been published over the past several decades concerning Holocene environmental archaeology in the Yangtze River Valley, to further understand large-scale regional Holocene environmental and cultural interaction within this area. The results show that: 1) in recent years, Holocene envi-ronmental archaeology research in the Yangtze River Valley has primarily taken paleoflood and sea-level change stratigraphical events to be the foundational threads for study. This began with research on the spatiotemporal distribution of archaeological sites, typical archaeological site stratigraphy, and research on background features concerning environmental evolution recorded by the regional natural sedimentary strata. 2) Significant progress has been made at the upper, middle, and lower reaches of the Yangtze River, indicating that Holocene environmental ar-chaeology research along the Yangtze River Valley is deepening and broadening. 3) Dramatic changes to Neolithic cultures that occurred approximately 4.0 ka BP were influenced by climate change and associated consequences, although the impacts differed on the various Neolithic cultures in the Yangtze River Valley. Local topography, regional climate, and varying survival strategies may have contributed to these differences. 4) Newly-published research pays particular attention to the sedimentary records of the past with resolutions as high as one year to several months, the degree to which humans altered the quality of their natural environment, and human adjustments to settlement and subsistence practices during periods of Holocene climate change. The application of technologies such as remote sensing, geographic information systems (GIS), and molecular biological analysis are also gradually being extended into the research field of Holocene environmental archaeology in the Yangtze River Valley.

scholarly journals Improving Seasonal Prediction of East Asian Summer Rainfall: Experiments with NESM3.0

2018 ◽  
Author(s):  
Young Min Yang ◽  
Bin Wang ◽  
Juan Li
Keyword(s):  
Interannual Variability ◽  
Yangtze River ◽  
Southern China ◽  
Yangtze River Valley ◽  
River Valley ◽  
Global Climate Models ◽  
The Yangtze River ◽  
Rainfall Prediction ◽  
Leading Mode ◽  
Seasonal March

It has been an outstanding challenge for global climate models to simulate and predict East Asia (EA) summer monsoon (EASM) rainfall. This study evaluates the dynamical hindcast skills with the newly developed Nanjing University of Information Science and Technology Earth System Model version 3.0 (NESM3.0). To improve the poor prediction of an earlier version of NESM3.0, we have modified convective parameterization schemes to suppress excessive deep convection and enhance insufficient shallow and stratiform clouds. The new version of NESM3.0 with modified parameterizations (MOD hereafter) yields significantly improved rainfall prediction in the northern and southern China but not over the Yangtze River Valley. The improved prediction is primarily attributed to the improvements in the predicted climatological summer mean rainfall and circulations, seasonal march of the subtropical rain belt, Nino 3.4 SST anomaly, and the rainfall anomalies associated with the development and decay of El Nino events. However, the MOD still has notable biases in the predicted leading mode of interannual variability of precipitation. The leading mode captures the dry (wet) anomalies over the South China Sea (northern EA) but misplaced precipitation anomalies over the Yangtze River Valley. The model can capture the interannual variation of the circulation indices very well, but the bias in the circulation-rainfall connection caused predicted rainfall errors. The results here suggest that over EA land regions, the skillful rainfall prediction relies on not only model’s capability in predicting better summer mean and seasonal march of rainfall and ENSO teleconnection with EASM, but also accurate prediction of the leading modes of interannual variability.

scholarly journals Improving Seasonal Prediction of East Asian Summer Rainfall Using NESM3.0: Preliminary Results

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 487 ◽  
Author(s):  
Young-Min Yang ◽  
Bin Wang ◽  
Juan Li
Keyword(s):  
East Asia ◽  
Interannual Variability ◽  
Yangtze River ◽  
Southern China ◽  
Yangtze River Valley ◽  
River Valley ◽  
Global Climate Models ◽  
The Yangtze River ◽  
Rainfall Prediction ◽  
Leading Mode

It has been an outstanding challenge for global climate models to simulate and predict East Asia summer monsoon (EASM) rainfall. This study evaluated the dynamical hindcast skills with the newly developed Nanjing University of Information Science and Technology Earth System Model version 3.0 (NESM3.0). To improve the poor prediction of an earlier version of NESM3.0, we modified convective parameterization schemes to suppress excessive deep convection and enhance insufficient shallow and stratiform clouds. The new version of NESM3.0 with modified parameterizations (MOD hereafter) yields improved rainfall prediction in the northern and southern China but not over the Yangtze River Valley. The improved prediction is primarily attributed to the improvements in the predicted climatological summer mean rainfall and circulations, Nino 3.4 SST anomaly, and the rainfall anomalies associated with the development and decay of El Nino events. However, the MOD still has biases in the predicted leading mode of interannual variability of precipitation. The leading mode captures the dry (wet) anomalies over the South China Sea (northern East Asia) but misplaces precipitation anomalies over the Yangtze River Valley. The model can capture the interannual variation of the circulation indices very well. The results here suggest that, over East Asia land regions, the skillful rainfall prediction relies on not only model’s capability in predicting better summer mean and ENSO teleconnection with EASM, but also accurate prediction of the leading modes of interannual variability.

scholarly journals Interdecadal Change in the Intensity of Interannual Variation of Spring Precipitation over Southern China and Possible Reasons

2019 ◽  
Vol 32 (18) ◽  
pp. 5865-5881 ◽  
Author(s):  
Chao Xu ◽  
Yunting Qiao ◽  
Maoqiu Jian
Keyword(s):  
South China ◽  
Yangtze River ◽  
Interannual Variation ◽  
Southern China ◽  
Yangtze River Valley ◽  
River Valley ◽  
Interdecadal Change ◽  
High Latitudes ◽  
The Yangtze River ◽  
Spring Precipitation

AbstractThe intensity of interannual variation of spring precipitation over southern China during 1979–2014 and possible reasons for it are investigated in this paper. There is a significant interdecadal change in the intensity of interannual variation of spring precipitation over southern China around 1995/96. The intensity of interannual variation of spring rainfall over South China is stronger during 1979–95 than that during 1996–2014. The possible reason may be the larger amplitude of the sea surface temperature anomaly (SSTA) in the western Pacific Ocean (WP) before 1995/96. The cooler (warmer) SSTA in WP may trigger an abnormal local anticyclone (cyclone) at lower levels. The anomalous southwesterly (northeasterly) flow at the northwestern flank of the WP anticyclone (cyclone) covers South China, transporting more (less) moisture to South China. Meanwhile, the anomalous winds converge (diverge) in South China at lower levels and diverge (converge) at upper levels, which causes the anomalous ascent (descent) to enhance (reduce) the precipitation over there. However, during 1996–2014, the intensity of interannual variation of spring rainfall over the middle and lower reaches of the Yangtze River valley becomes much stronger than that during 1979–95, which is related to the intensified interannual variation of the atmospheric circulation in the middle and high latitudes over Eurasia. The weak (strong) Siberian high and East Asian trough may reduce (enhance) the northerly wind from the middle and high latitudes. As a result, the middle and lower reaches of the Yangtze River valley are subjected to the anomalous southerly wind, favoring more (less) precipitation over there.

An evaluation of the effectiveness of known large-scale modes for predicting extreme Mei-yu precipitation over China using causality driven approach

2021 ◽  
Author(s):  
Kelvin Ng ◽  
Gregor Leckebusch ◽  
Kevin Hodges
Keyword(s):  
Extreme Precipitation ◽  
Yangtze River ◽  
Large Scale ◽  
Climate Models ◽  
Southern China ◽  
Yangtze River Valley ◽  
The Past ◽  
Network Discovery ◽  
South Asia High ◽  
The Relationship

<p>Record-breaking amount of Mei-yu rainfall around the Yangtze River has been observed in the 2020 Mei-yu season.  This shows the necessity and urgency of accurate prediction of extreme Mei-yu precipitation over China for the current and future climate.  Such information could further improve the decision and policy making in the region.  Many studies in the past have shown that large-scale modes, e.g. western north Pacific subtropical high and the south Asia high, play a role in controlling extreme Mei-yu precipitation over China. Although the spatial resolution of typical climate models might be too coarse to simulate extreme precipitation accurately, they are likely to simulate large-scale modes reasonably well.  One might be possible to construct a causally guided statistical model based on those known large-scale modes to predict extreme Mei-yu precipitation. </p><p>In this presentation, we show preliminary results of the relationship between known large-scale atmospheric and oceanic modes and extreme Mei-yu precipitation in the two regions of China, i.e. Yangtze River Valley and Southern China, using the causal network discovery approach.  The relationships between large-scale modes and extreme Mei-yu precipitation on different time scale are explored.  Implication of relationships in constructing statistical predictive model is also discussed.</p>

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