A study of the impacts of late spring Tibetan Plateau snow cover on Chinese early autumn precipitation

N U I S T Nanjing University of Information Science & Technology A study of the impacts of late spring Tibetan Plateau snow cover on Chinese early autumn precipitation JIANG Zhihong,HUO Fei,LIU Zhengyu Nanjing University of Information Science and Technology, Key Laboratory of Meteorological Disaster, Nanjing, China Feb.2014, WMO S2S

OUTLINE 1. Introduction 2. Data and methods 3. MCA analysis on the relationship between TP snow cover and precipitation 4. MRE analysis on the response of ASO precipitation to TP snow cover 5. Possible mechanism 6. Summary

Impacts of TP snow on Chinese precipitation Soil moisture TP snow East Asian Monsoon Persistence Boreal summer rainfall in central China has apositive correlation, whereas that in northern and southern China has a negative correlation, with the Tibetan Plateau snow depth in the previous winter spring.(chen et al.,2000;zhang and Tao,2002;Wu and Qian,2003;Zhao et al.,2007) The TPSC shows modulating effects on the ENSO teleconnections and in turn modify the ENSO EASM relationship(wu et al. 2012)

Impacts of TP snow on Chinese precipitation Soil moisture TP snow East Asian Monsoon Persistence The negative correlations between the surface heating of Tibet plateau and precipitation of southwestern China in autumn (Chen et al. 2001). Questions: A lot of researches about the relationship between TP snow and Chinese summer precipitation, how about that in other seasons? How to estimate the maximum atmospheric response to TP?

Assess atmospheric response to the surface forcing from observations Equilibrium feedback assessment (EFA) was introduced to estimate the stochastic atmospheric response to SST forcing. (Frankignoul et al. 1998) Generalized equilibrium feedback assessment (GEFA) was developed to calculate the contribution of different parts of SST basins to the atmospheric response. (Liu et al. 2008) Maximum response estimation (MRE) was devised to directly estimates the largest SST forced atmospheric modes. (Frankignoul et al. 2011)

Data Monthly geopotential height and zonal/meridional wind anomalies at different levels are from NCEP/NCAR reanalysis (Kistler et al. 2001). Snow cover is obtained from NESDIS. The snow cover data are binned into 2 latitude 2 longitude grids to reduce regional uncertainties. Monthly rainfall data at 160 stations in China All data in the period of 1984~2010. The ENSO signal is removed for all atmospheric variables by regression onto the Niño 3 (150 90W, 5S 5N)SST anomalies of preceding 1 month.

Methods Maximum Covariance Analysis (MCA) based on singular value decomposition (SVD), determines the atmospheric and oceanic patterns that maximize the covariance between the two fields.

MRE Generalized equilibrium feedback assessment H( t ) = BS( t) + N( t), H the atmospheric data matrix,n stochastic forcing,s snow forcing ( snow). The feedback matrix B B = C HS (τ )C SS (τ ) 1, (GEFA, Liu et al. 2008) Maximum response estimation (MRE Frankignoul et al. 2011) BS(t) = c i (t)p i, i ci(t) the principal components, pi orthogonal patterns. the largest response is obtained by calculating the main EOFs of BS(t)

Snow sst leads leads precipitation z850 [LAG (month)] precipitation leads snow 3 2 1 0 1 1200 1000 MCA analysis Squared covariance (SC) 4 1200 1200 1 5 1 1 1 6 JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ DJF z850 month The SC (Squared Covariance) of the first MCA mode between TP snow cover and precipitation (in China) anomalies at different lag time. 2 3 1000 1000 precipitation 1000 1200 1 1200 1000

sst leads z850 [LAG (month)] 3 1200 1000 1000 1200 1 2 1 0 1 1200 1000 2 3 4 1000 1000 1200 1200 5 1 1 1 1 6 1 JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ DJF z850 month 70 E 80 E 90 E 100 E 3 40 N 2 1 0 30 N 1 2 3 Heterogeneous precipitation covariance and homogeneous snow cover covariance for the first MCA mode between JJA precipitation and JFM TP snow cover.

70 E Lag 1 80 E 90 E 100 E 40 N 30 N 8~10月降水 70 E Lag 2 80 E 90 E 100 E 3 40 N 2 30 N 1 70 E Lag 3 80 E 90 E 100 E 0 40 N 1 30 N 2 3 70 E Lag 4 80 E 90 E 100 E 3 2 sst leads z850 [LAG (month)] 1200 1000 1 1 1200 1000 0 1 2 3 1200 1000 4 1000 1200 1 1 6 1 JFM FMA MAM AMJ MJJ 5 40 N 30 N 1000 1200 1 1 JJA JAS ASO SON OND NDJ z850 month DJF Heterogeneous precipitation covariance and homogeneous snow cover covariance for the first MCA mode between ASO precipitation and TP snow cover at different lags.

ASO Precipitation response E1=5% JAS TP snow forcing 70 E 80 E 90 E 100 E 1 40 N 0.5 0 30 N 0.5 1 First MRE mode between precipitation and TP snow cover in ASO at Lag 1. E1 indicates statistical significance level

ASO 850hPa atmospheric response E1=5% JAS TP snow forcing 70 E 80 E 90 E 100 E 1 40 N 0.5 0 30 N 0.5 1 First MRE mode between geopotential height (shading) / wind fields at 850 hpa and TP snow cover in ASO at Lag 1

An increased Tibetan Plateau snow increases land surface albedo, and excessive TP snow can modify the surface thermal conditions, which suppresses the land surface heating on TP(Wu and Qian,2003;Tao and Ding, 1981;Ye,1981;Zhang et al.,2004;flanner and Zender,2005;Lin and Wu,2011). Both observations and numerical experiments show that atmospheric heating induced by the rising TP temperatures is connected to two distinct Rossby wave (Wang et al. 2008). Can increased TP snow cover excite two Rossby wave trains?

(a)aso Z200 & wind(200hpa) Z850 & U850/V850 Response, E1=0% C A C 200hPa (b)aso Z850 & wind(850hpa) A C A 850hPa Correlation coefficients of 200 hpa, 850 hpa ASO geopotential height (wind) fields with respect to snow cover time series of first MCA mode. Dark shading denotes statistical significance at 90% level. Dashed arrow indicates Rossby wave trains

200hPa The stationary wavenumber 850hPa ASO total stationary Rossby wavenumber at 200hPa and 850hPa. Thick line with an arrowhead shows the possible waveguide

Summary MCA analysis shows a significant correlation between early autumn (ASO) Chinese precipitation and the preceding TP snow cover. Maximum response estimation and diagnostic analyses show that lead positive snow cover anomalies over western TP signifies enhanced ASO rainfall over Yangze River basin and south China, and reduced rainfall over southeast coastline of China. The possible mechanism is as follow: positive early spring snow cover anomalies in TP can persist to summer, and modify the surface thermal conditions, which results in two distinct Rossby wavetrains propagating downstream along the westerly jet and the lower southwesterly airflow. The southerly flow strengthens abundant moisture transport to Southern China, the northerly flow contributes the southward moving of synoptic disturbances from the north. Both conditions lead to more rainfall in central and southern China.

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