Precipitation Seasonality and Variability over the Tibetan Plateau as Resolved by the High Asia Reanalysis*

Abstract

Because of the scarcity of meteorological observations, the precipitation climate on the Tibetan Plateau and surrounding regions (TP) has been insufficiently documented so far. In this study, the characteristics and basic features of precipitation on the TP during an 11-yr period (2001-11) are described on monthly-to-annual time scales. For this purpose, a new high-resolution atmospheric dataset is analyzed, the High Asia Reanalysis (HAR), generated by dynamical downscaling of global analysis data using the Weather Research and Forecasting (WRF) model. The HAR precipitation data at 30-and 10-km resolutions are compared with both rain gauge observations and satellite-based precipitation estimates from the Tropical Rainfall Measurement Mission (TRMM). It is found that the HAR reproduces previously reported spatial patterns and seasonality of precipitation and that the highresolution data add value regarding snowfall retrieval, precipitation frequency, and orographic precipitation. It is demonstrated that this process-based approach, despite some unavoidable shortcomings, can improve the understanding of the processes that lead to precipitation on the TP. Analysis focuses on precipitation amounts, type, seasonality, and interannual variability. Special attention is given to the links between the observed patterns and regional atmospheric circulation. As an example of an application of the HAR, a new classification of glaciers on the TP according to their accumulation regimes is proposed, which illustrates the strong spatial variability of precipitation seasonality. Finally, directions for future research are identified based on the HAR, which has the potential to be a useful dataset for climate, glaciological, and hydrological impact studies.

Impact of debris cover on glacier ablation and atmosphere–glacier feedbacks in the Karakoram

“…The month of May is characterized by basin-mean accumulation (Fig. 4b), consistent with the findings of Maussion et al (2014) of the importance of spring precipitation in this region. On average, the melt season lasts from approximately mid-June until mid-September, over which period more than ∼ 90 % of grid cells categorized as debris-covered are exposed.…”

Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987–2016

“…As control data, we analyze Moderate Resolution Imaging Spectroradiometer (MODIS) percentage snow-covered area (product MOD10C1 V6, 2001(product MOD10C1 V6, -2016Hall and Riggs, 2016) and High Asia Refined Analysis (HAR) surface temperature (2000Maussion et al, 2014). While these datasets only cover a subset of our study period, they are among the few independent control datasets available across the entire study area.…”

“…Instead, we use HAR (Maussion et al, 2014) and MODIS (Hall and Riggs, 2016) data alongside a manually generated set of control dates for the snowmelt season, determined from the SWE, XPGR, and Tb 37V signals by the researchers. We visually identified major peaks (MXPGR), as well as the cessation of snowmelt, by inspection of the time series.…”

“…HAR provides surface temperature at hourly intervals from 2000 to 2014 at 30 km spatial resolution over the entire study area (Maussion et al, 2014). Using these data, we derive (1) the full-day average surface temperature, (2) the average daytime surface temperature, and (3) the daily surface temperature range at each MXPGR date (Fig.…”

“…This important water reserve is certain to be impacted by, and reflect changes in, the snowmelt regime of HMA, as the timing of precipitation has been shown to be an important factor in the response of glaciers to climate change (Maussion et al, 2014;Wang et al, 2017). While many regions have seen rapid glacier retreat (Bolch et al, 2012;Kääb et al, 2012Kääb et al, , 2015Scherler et al, 2011), there exist regions of glacier stability and even growth, such as the Karakoram (Hewitt, 2005;Gardelle et al, 2012) and Kunlun Shan (Gardner et al, 2013;Yao et al, 2012).…”