
The Possible Influence of Arctic Sea Ice on the Precipitation Distribution Pattern of July in East of Northwest China
Dai WANG, Jianling YANG, Wen ZHANG, Yang MA, Xin LI, Suyan WANG
The Possible Influence of Arctic Sea Ice on the Precipitation Distribution Pattern of July in East of Northwest China
Using the observed precipitation data of 154 meteorological stations in East of Northwest China, NCEP/NCAR atmosphere reanalysis and Arctic sea ice data from 1961 to 2020, the possible impacts and mechanisms of the key area Arctic sea ice on the main distribution mode of precipitation in July during the main flood season in East of Northwest China was analyzed using SVD and other climatic statistic methods.The results show that there are two mainly sea ice modes influencing the distribution pattern of precipitation anomaly in July in East of Northwest China.One is that when the sea ice density in the Barents Sea and the Kuril Islands is relatively small (large), and that in Davis Strait is relatively large (small), wave trains propagating southeastward from the Davis Strait and southwestward from the Sea of Okhotsk are stimulated, resulting in the anomaly field of "high in the west and low in the east" ("low in the west and high in the east") at the 500 hPa geopotential height anomaly field over the East of Northwest China, which leads to the regional precipitation anomaly exhibiting a "consistent less (more)" pattern.The other is that when the sea ice density in the eastern part of the Beaufort Sea is relatively small, the wave train from the Caspian Sea to the Okhotsk Sea is stimulated and matched with the positive geopotential height anomaly over South China, making the cold air path eastward and southward, as well as the subtropical high stronger, which together lead to the precipation characterized by "less in the north and more in the south", on the contrary, the pattern of precipitation anomaly is reversed.The prediction model, which is established with sea ice in key areas as the prediction factors derived by “SVD projection method”, has certain prediction ability for grasping the precipitation anomaly trend and the spatial distribution pattern of the main flood season in July in East of Northwest China, especially for the "regional consistent less type" and "north more and south less type".
East of Northwest China / precipitation in flood season / Arctic Sea ice / prediction model {{custom_keyword}} /
Fig.2 Hetero-correlation of SVD between spring sea ice density and precipitation in July over East of Northwest China.In Fig.2(a) and (c), the ①、 ②、 ③、 ④ indicates the first and second mode sea ice key areas, respectively图2 春季(3 -5月)北极海冰密集度场与7月西北地区东部降水场的SVD异性相关系数 图(a)(c)中①、 ②、 ③、 ④分别表示第一、 二模态海冰关键区 |
Fig.6 Distribution of correlation coefficients between rtime1 (a) and rtime2 (c) with 500 hPa geopotential height anomaly field respectively from 1991 to 2020 (contour represents correlation coefficient, the colore area represents passing 95% confidence level), and composite difference field of 500 hPa geopotential height anomaly (contour and color area, unit: gpm) in high and low value years of rtime1 (b) and rtime2 (d)图6 1991 -2020年右场第一模态时间系数(rtime1, a)、 右场第二模态时间系数(rtime2, c)分别与500 hPa位势高度距平场的相关系数分布(等值线代表相关系数, 彩色区域代表通过了95%置信度检验)及rtime1(b)、 rtime2(d)高、 低值年500 hPa位势高度距平合成差值场(等值线和彩色区域, 单位: gpm) |
Fig.7 The correlation between index 1 (a, c) and index 2 (d, f) with the 500 hPa potential height field (contour represents correlation coefficient, the colore area represents passing 95% confidence level) and flow function [isoline, red (blue) lines represent positive (negative) values] as well as the wave flux of the flow function (vector), and composite difference field of 500hPa geopotential height anomaly (contour and color area, unit: gpm) in high and low value years of index 1 (b) and index 2 (e) of July from 1991 to 2020图7 1991 -2020年指数1(a、 c)、 指数2(d、 f)分别与7月500 hPa位势高度场(等值线代表相关系数, 彩色区域代表通过95%置信度检验)和7月流函数[等值线, 红(蓝)色表示正(负)值]及流函数的波通量(矢量)的相关, 指数1(b)、 指数2(e)高、 低值年500 hPa位势高度距平合成差值场(等值线和彩色区域, 单位: gpm) |
Fig.8 Spatial distribution of anomaly symbol consistency rate (PC) by precipitation prediction model from 2011 to 2020.Unit: %图8 2011 -2020年降水模型预测的距平符号一致率(PC)空间分布(单位: %) |
Table 1 Capability test of precipitation prediction model from 2011 to 2020表1 2011 -2020年逐年降水模型预测水平检验 |
年份 | 2011 | 2012 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|
降水分布型 | 北少南多 | 北多南少 | 以少为主 | 一致少 | 北多南少 | 北多南少 | 一致多 | 不典型 | 北少南多 |
ACC | 0.17 | 0.51 | 0.56 | 0.31 | 0.22 | -0.01 | 0.04 | -0.02 | 0.07 |
PC/% | 52 | 40 | 81 | 92 | 60 | 65 | 42 | 70 | 54 |
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