Spring snow depth changes and feedback to surface air temperature across the Tibetan Plateau from 1961 to 2013

2021 ◽  
Author(s):  
Xiaona Chen ◽  
Yaping Yang
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Snow Depth ◽  
Surface Air Temperature ◽  
The Tibetan Plateau

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

Dominant Interannual and Decadal Variability of Winter Surface Air Temperature over Asia and the Surrounding Oceans

2008 ◽  
Vol 21 (6) ◽  
pp. 1371-1386 ◽  
Author(s):  
Chihiro Miyazaki ◽  
Tetsuzo Yasunari
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Silk Road ◽  
Western Pacific ◽  
The Tibetan Plateau ◽  
The Third ◽  
The North ◽  
Atmospheric Wave ◽  
Fourth Mode

Abstract To clarify the interannual variability of winter surface air temperature (SAT) over Asia and the surrounding oceans, the authors applied principal component analysis to normalized monthly SATs. The first mode represents the Asian north–south dipole pattern with a node over the Tibetan Plateau. This component has close relationships to the Arctic Oscillation and cold surge variability around Southeast Asia, showing decadal oscillation with signal changes in 1988 and 1997. The second mode is the inner-Asian mode with a center to the north of the Tibetan Plateau. This component connects to fluctuations of not only the western Siberian high but also the Icelandic low, which is associated with the pattern of the polar vortex over Eurasia. A recent warming trend and possible relationship to solar activity are also shown. The modes of Asian SAT variability associated with ENSO are extracted as the north–south dipole mode over the tropical western Pacific and Japan (the third mode) and Silk Road mode (the fourth mode). The two independent modes appear to be caused by different sea surface temperature (SST) anomalies over the western Pacific and Indian Ocean and their associated atmospheric Rossby wave responses: the atmospheric wave trains over both the north and south of the Tibetan Plateau in the third mode, and the atmospheric wave train that propagates toward the Silk Road via Greenland in the fourth mode.

The AMV phase-dependence of the connection between February NAO and March surface air temperature over the Tibetan Plateau

2021 ◽  
Author(s):  
Jingyi Li ◽  
Fei Li ◽  
Shengping He ◽  
Huijun Wang ◽  
Yvan J Orsolini
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Rossby Wave ◽  
North Atlantic ◽  
Wave Train ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
The North ◽  
Rossby Wave Train ◽  
The North Atlantic

<p>The Tibetan Plateau (TP), referred to as the “Asian water tower”, contains one of the largest land ice masses on Earth. The local glacier shrinkage and frozen-water storage are strongly affected by variations in surface air temperature over the TP (TPSAT), especially in springtime. This study reveals a distinct out-of-phase connection between the February North Atlantic Oscillation (NAO) and March TPSAT, which is non-stationary and regulated by the warm phase of the Atlantic Multidecadal Variability (AMV+). The results show that during the AMV+, the negative phase of the NAO persists from February to March, and is accompanied by a quasi-stationary Rossby wave train trapped along a northward-shifted subtropical westerly jet stream across Eurasia, inducing an anomalous adiabatic descent that warms the TP. However, during the cold phase of the AMV, the negative NAO does not persist into March. The Rossby wave train propagates along the well-separated polar and subtropical westerly jets, and the NAO−TPSAT connection is broken. Further investigation suggests that the enhanced synoptic eddy and low-frequency flow (SELF) interaction over the North Atlantic in February and March during the AMV+, caused by the enhanced and southward-shifted storm track, help maintain the NAO anomaly pattern via positive eddy feedback. This study provides a new detailed perspective on the decadal variability of the North Atlantic−TP connections in late winter−early spring.</p>

scholarly journals Improved parameterization of snow albedo in WRF + Noah. Part II: Applicability to snow estimates for the Tibetan Plateau

2021 ◽  
Author(s):  
Lian Liu ◽  
Yaoming Ma ◽  
Massimo Menenti ◽  
Rongmingzhu Su ◽  
Nan Yao ◽  
...  
Keyword(s):  
Heat Flux ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Snow Depth ◽  
Sensible Heat Flux ◽  
Parameterization Scheme ◽  
The Tibetan Plateau ◽  
Sensible Heat ◽  
Snow Albedo

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land-atmosphere interactions estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the WRF and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates, by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged RMSE relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %) respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.

scholarly journals Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau

2021 ◽  
Vol 25 (9) ◽  
pp. 4967-4981
Author(s):  
Lian Liu ◽  
Yaoming Ma ◽  
Massimo Menenti ◽  
Rongmingzhu Su ◽  
Nan Yao ◽  
...  
Keyword(s):  
Heat Flux ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Snow Depth ◽  
Sensible Heat Flux ◽  
Weather Research And Forecasting ◽  
The Tibetan Plateau ◽  
Sensible Heat ◽  
Snow Albedo

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow-related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land–atmosphere interaction estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the Weather Research and Forecasting (WRF) and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged root mean square error (RMSE) relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %), respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.

scholarly journals A climatology of surface–air temperature difference over the Tibetan Plateau: Results from multi‐source reanalyses

2020 ◽  
Vol 40 (14) ◽  
pp. 6080-6094
Author(s):  
Xuejia Wang ◽  
Deliang Chen ◽  
Guojin Pang ◽  
Tinghai Ou ◽  
Meixue Yang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Temperature Difference ◽  
Surface Air Temperature ◽  
The Tibetan Plateau

scholarly journals Trends of Sampling Error in Surface Air Temperature on the Tibetan Plateau during Recent Decades

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Wei Hua ◽  
Tianci Huang ◽  
Zouxin Lin ◽  
Lihua Zhu ◽  
Xin Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Sampling Error ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Statistical Inferences ◽  
Increasing Trends ◽  
Climate Studies ◽  
Monthly Variations

Understanding errors in surface air temperature (SAT) data and related uncertainties is crucial for climate studies because of their impact on the accuracy of statistical inferences in scientific conclusions. In recent decades, considerable research has focused on the trends and evolution of SAT on the Tibetan Plateau (TP). However, assessment of the uncertainties in SAT change on the TP has not been done adequately, which is of considerable importance for climate research. Using station-observed SAT data from the TP, this study estimates long-term variations and trends of sampling error variances in gridded monthly SAT data over recent decades. Results revealed large sampling error variances in northern and western parts of the TP but small variances in eastern, southern, and central areas. The sampling error variances also exhibited strong monthly variations with maximum errors in winter and minimum values in summer. Furthermore, spatial distributions of the trends of seasonal and annual mean sampling error variances were found distributed unevenly with decreasing trends found mainly in central and southern parts of the TP and increasing trends in northeastern, southeastern, and northwestern areas. Additionally, differences were also found in the trends of seasonal and annual mean sampling error variances on various timescales.

scholarly journals Systematic bias of Tibetan Plateau snow cover in subseasonal-to-seasonal models

2020 ◽  
Author(s):  
Shuzhen Hu ◽  
Wenkai Li
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Air Temperature ◽  
Lead Time ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Systematic Bias ◽  
Forecast Lead Time ◽  
Systematic Biases ◽  
Tibetan Plateau Snow Cover

Abstract. Accurate subseasonal-to-seasonal (S2S) atmospheric forecasts and hydrological forecasts have considerable socioeconomic value. This study conducts a multimodel comparison of the Tibetan Plateau snow cover (TPSC) prediction skill using three models (ECMWF, NCEP and CMA) selected from the S2S project database to understand their performance in capturing TPSC variability. S2S models can skilfully forecast TPSC within a lead time of 2 weeks but show limited skill beyond 3 weeks. Compared with the observational snow cover analysis, all three models tend to overestimate the area of TPSC, especially during winter. Another remarkable issue regarding the TPSC forecast is the increasing TPSC with forecast lead time, which further increases the systematic positive biases of TPSC in the S2S models at longer forecast lead times. The underestimation of TPSC dissipation induces an increase in TPSC with forecast lead time in the models. Such systematic biases of TPSC influence the forecasted surface air temperature in the S2S models. The surface air temperature over the Tibetan Plateau becomes colder with increasing forecast lead time in the S2S models.

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