西北偏濕背景下青海省夏季降水的統(tǒng)計(jì)降尺度方法研究

doi:10.12306/2020jms.0003

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西北偏濕背景下青海省夏季降水的統(tǒng)計(jì)降尺度方法研究
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                        10.12306/2020jms.0003
                    
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中圖分類號:P456
基金項(xiàng)目:國家重點(diǎn)研究計(jì)劃項(xiàng)目（2018YFC1505906）

A statistical downscaling method of summer precipitation prediction in Qinghai Province under the background of northwest partial humidity

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本文研制建立了一個預(yù)測青海省夏季降水的動力—統(tǒng)計(jì)相結(jié)合的組合降尺度預(yù)測方法（Hybrid Statistical Downscaling Prediction，HSDP），該方法綜合利用了氣候模式Climate Forecast System 2.0版本（CFSv2）實(shí)時預(yù)測的高可預(yù)報性環(huán)流信息及前期觀測的與青海夏季降水具有高相關(guān)性的氣候因子，采用年際增量方法，基于氣候變量的年際增量規(guī)律建立統(tǒng)計(jì)模型，從而實(shí)現(xiàn)對青海夏季降水進(jìn)行動力—統(tǒng)計(jì)相結(jié)合的氣候預(yù)測。根據(jù)全球氣候因子的年際增量與青海省夏季降水年際增量的相關(guān)系數(shù)，以及CFSv2預(yù)測產(chǎn)品對實(shí)況模擬能力的評估，選取以下關(guān)鍵區(qū)氣候變量的年際增量作為預(yù)測因子：（1） CFSv2模式預(yù)測當(dāng)年夏季包含貝加爾湖脊、烏拉爾山脊和新疆脊區(qū)域的500 hPa高度場；（2） CFSv2模式預(yù)測青藏高原以西200 hPa緯向風(fēng)場；（3）觀測資料中前1 a秋、冬季熱帶太平洋地區(qū)海表面溫度場；（4）觀測資料中前1 a秋、冬季西伯利亞地區(qū)的海平面氣壓場，對青海省夏季降水進(jìn)行統(tǒng)計(jì)降尺度預(yù)測。統(tǒng)計(jì)降尺度模型利用1983—2011年進(jìn)行建模，回報2012—2018年夏季青海省降水的空間分布和時間變化，并對該模型對1983—2011年的夏季青海省降水的回報能力進(jìn)行了交叉檢驗(yàn)。回報結(jié)果表明該統(tǒng)計(jì)降尺度模型對CFSv2的青海省夏季降水預(yù)測能力有顯著的提高，能夠很好地再現(xiàn)青海省夏季降水西北部的高原地區(qū)偏少，而在東南部偏多的特點(diǎn)。該模型預(yù)測所得2012—2018年夏季青海省降水的時間變化也與實(shí)況有著較高的相關(guān)系數(shù)（0.76），對于降水顯著偏少的年份（如2015年）和顯著偏多的年份（如2012、2018年）的降水預(yù)測都有很好的表現(xiàn)。對于建模時段的交叉檢驗(yàn)結(jié)果（相關(guān)系數(shù)為0.46，比模型回報結(jié)果與實(shí)況的相關(guān)系數(shù)0.48略低）表明，該模型具有較高的穩(wěn)定性和可靠性。

Abstract:

A Hybrid Statistical Downscaling Prediction method (HSDP) was developed to predict summer precipitation in Qinghai Province, which comprehensively used the highly predictable circulation information predicted in real time by climate forecast system 2.0 (CFSv2) and the climate factors with high correlation with summer precipitation in Qinghai Province, so as to realize the climate prediction of Qinghai summer precipitation by combining dynamic and statistical methods. According to the correlation coefficient between the interannual increment of global climate factors and summer precipitation in Qinghai Province, and the evaluation of CFSv2 prediction products on the ability of actual simulation, this paper selects the interannual increment of climate variables in the following key areas as the prediction factors: (1) CFSv2 model predicts the 500 hPa height field in summer, including the Baikal Lake Ridge, Oral Ridge and Xinjiang Ridge regions; (2) CFSv2 model predicts the zonal wind field at 200 hPa in the west of the Tibetan Plateau; (3) the sea surface temperature field in autumn and winter of the previous year in the tropical Pacific region; (4) based on the observation data of the sea level pressure field in Siberia in autumn and winter of the previous year, the statistical downscaling prediction of summer precipitation in Qinghai Province was carried out. The statistical downscaling method is used to model the precipitation from 1983 to 2011, and the spatial distribution and temporal variation of the precipitation from 1983 to 2018 in Qinghai Province were hindcasted. Results show that the statistical downscaling model can significantly improve the prediction ability of CFSv2 for summer precipitation in Qinghai Province, and can well reproduce the characteristics of less precipitation in the Northwest Plateau and more precipitation in the Southeast of Qinghai Province. The temporal variation of summer precipitation in Qinghai Province from 2012 to 2018 predicted by the model also has a high correlation coefficient (0.76), which is good for the years with significantly less precipitation (such as 2015) and those with significantly more precipitation (such as 2012, 2018). The cross-checking results (the correlation coefficient is 0.46, which is slightly lower than the correlation coefficient of 0.48) show that the model has high stability and reliability.

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鄒晨曦,楊昭明,張培群.西北偏濕背景下青海省夏季降水的統(tǒng)計(jì)降尺度方法研究.氣象科學(xué),2021,41(3):374-385 ZOU Chenxi, YANG Zhaoming, ZHANG Peiqun. A statistical downscaling method of summer precipitation prediction in Qinghai Province under the background of northwest partial humidity. Journal of the Meteorological Sciences,2021,41(3):374-385

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收稿日期:2019-07-31
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