Qinglong You

Review of climate and cryospheric change in the Tibetan Plateau.

The Tibetan Plateau (TP), with an average elevation of over 4000 m asl and an area of approximately 2.5 × 10 6 km 2 , is the highest and most extensive highland in the world and has been called the ‘Third Pole’. The TP exerts a huge influence on regional and global climate through thermal and mechanical forcing mechanisms. Because the TP has the largest cryospheric extent outside the polar region and is the source region of all the large rivers in Asia, it is widely recognized to be the driving force for both regional environmental change and amplification of environmental changes on a global scale. Within China it is recognized as the ‘Asian water tower’. In this letter, we summarize the recent changes observed in climate elements and cryospheric indicators on the plateau before discussing current unresolved issues concerning climate change in the TP, including the temporal and spatial components of this change, and the consistency of change as represented by different data sources. Based on meteorological station data, reanalyses and remote sensing, the TP has shown significant warming during the last decades and will continue to warm in the future. While the warming is predominantly caused by increased greenhouse gas emissions, changes in cloud amount, snow-albedo feedback, the Asian brown clouds and land use changes also partly contribute. The cryosphere in the TP is undergoing rapid change, including glacier retreat, inconsistent snow cover change, increasing permafrost temperatures and degradation, and thickening of the active layer. Hydrological processes impacted by glacial retreat have received much attention in recent years. Future attention should be paid to additional perspectives on climate change in the TP, such as the variations of climate extremes, the reliability of reanalyses and more detailed comparisons of reanalyses with surface observations. Spatial issues include the identification of whether an elevational dependency and weekend effect exist, and the identification of spatial contrasts in temperature change, along with their causes. These issues are uncertain because of a lack of reliable data above 5000 m asl.

Inconsistencies of precipitation in the eastern and central Tibetan Plateau between surface adjusted data and reanalysis

The Tibetan Plateau (TP) is the source of many Asian river systems and serves as “the Asian water tower”. Precipitation variability is a strong component of both hydrological processes and energy cycles, and the study of precipitation in the TP is of great importance in the content of global warming. In this study, the annual and seasonal (spring: MAM; summer: JJA; autumn: SON; and winter: DJF) variations in precipitation are investigated in the eastern and central TP during 1961–2007, based on surface raw and adjusted observations as well as both NCEP/NCAR (1961–2007) and ERA-40 (1961–2001) reanalyses. The adjusted precipitation in the TP is higher than raw values on both the annual and seasonal basis due to adjustments of solid precipitation by a bias experiential model. At the annual spring and winter scales, the adjusted precipitation shows a significant increase calculated by the Mann–Kendall trend test. Compared with adjusted precipitation; both NCEP/NCAR and ERA-40 reanalyses capture the broad spatial distributions of mean annual and seasonal precipitation, but are less good at repeating the decadal variability. Both reanalyses show the drying phenomena in most regions and fail to represent the change patterns of precipitation observed by the adjusted observations. Both NCEP/NCAR and ERA-40 have larger inconsistencies which may be caused by the differences between actual and model topography. This suggests that it is crucial to use the adjusted precipitation in the climate research and reanalysis products should be paid more attention in the TP.

Present and projected degree days in China from observation, reanalysis and simulations

Abstract Degree days are usually defined as the accumulated daily mean temperature varying with the base temperature, and are one of the most important indicators of climate changes. In this study, the present-day and projected changes of four degree days indices from daily mean surface air temperature output simulated by Max Planck Institute, Earth Systems Model of low resolution (MPI-ESM-LR) model are evaluated with the high resolution gridded-observation dataset and two modern reanalyses in China. During 1979–2005, the heating degree days (HDD) and the numbers of HDD (NHDD) have decreased for observation, reanalyses (ERA-Interim and NCEP/NCAR) and model simulations (historical and decadal experiments), consistent with the increasing cooling degree days (CDD) and the numbers of CDD (NCDD). These changes reflect the general warming in China during the past decades. In most cases, ERA-Interim is closer to observation than NCEP/NCAR and model simulations. There are discrepancies between observation, reanalyses and model simulations in the spatial patterns and regional means. The decadal hindcast/forecast simulation performance of MPI-ESM-LR produce warmer than the observed mean temperature in China during the entire period, and the hindcasts forecast a trend lower than the observed. Under different representative concentration pathway (RCP) emissions scenarios, HDD and NHDD show significant decreases, and CDD and NCDD consistently increase during 2006–2100 under RCP8.5, RCP4.5 and RCP2.6, especially before the mid-21 century. More pronounced changes occur under RCP8.5, which is associated with a high rate of radiative forcing. The 20th century runs reflect the sensitivity to the initial conditions, and the uncertainties in terms of the inter-ensemble are small, whereas the long-term trend is well represented with no differences among ensembles.

A comparison of heat wave climatologies and trends in China based on multiple definitions

Heat waves (HWs) can have disastrous impacts on human activities and natural systems, and are one of the current foci of scientific research, particularly in the context of global warming. However, there is no standard definition of a HW, which makes assessment of temporal trends a challenge. In this study, based on daily mean, maximum and minimum temperature, and relative humidity datasets from China Meteorological Administration, the patterns, trends and variations of HW in China during 1961–2014 are investigated. Sixteen previously published HW indices (HIs) are calculated, which are divided into two types using relative and absolute threshold temperatures, respectively. During 1961–2014, both relative and absolute threshold HIs show the highest number of HW in Jianghua and South China, geographically consistent with the climate characteristics of China. The majority of HIs shows negative/positive trends of HW days before/after 1990 over the whole of China, but especially in Jianghua and South China, which reflects rapid warming since 1990. There are significant correlations among different HIs in the same type (both absolute and relative), but correlations are weak between relative and absolute threshold HIs. Because relative and absolute HIs show contrasting trends, the choice of HI is therefore critical for future analysis

Does a weekend effect in diurnal temperature range exist in the eastern and central Tibetan Plateau

The ‘weekend effect’ method (defined here as the average for Saturday through Monday minus the average for Wednesday through Friday) has been used to identify fingerprints of anthropogenic emissions. Based on daily maximum and minimum temperature series from the China Meteorological Administration homogenized dataset, the weekend effect in diurnal temperature range (DTR) at 71 stations with elevations above 2000 m asl in the eastern and central Tibetan Plateau (TP) during 1961–2004 is examined, and principal component analysis (PCA) is performed to cluster series into four subregions with similar weekend effect variability. The DTR demonstrates a much stronger negative weekend effect in autumn and shows larger positive values in winter, which provides a strong evidence of anthropogenic activity in this region, especially in the central TP. Analysis by topographic type and degree of urbanization shows a clear weekly cycle which cannot be explained by a microclimate effect. We hypothesize that the interaction with anthropogenic aerosols from local emissions and transported by atmospheric circulation may account for the weekly cycle in the TP. More caution should be paid to the driving mechanism of the weekend effect in the most remote and clear regions in the world.

Observed climatology and trend in relative humidity in the central and eastern Tibetan Plateau

Monthly surface relative humidity (RH) data for 71 stations in the Tibetan Plateau (TP) provided by the National Meteorological Information Center/China Meteorological Administration are compared with corresponding grid points from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR hereafter) reanalysis. Mean climatologies, interannual variabilities, and trends calculated by the Mann-Kendal method are analyzed during 1961–2013. The annual regional long-term mean surface RH is 55.3%, with a clear maximum in summer (66.4%) and minimum in winter (44.9%). Compared with observations, NCEP/NCAR overestimates RH in all seasons, especially in spring (18.2%) and winter (17.8%). Mean annual regional surface RH has decreased by −0.23% decade−1 and even more rapidly in summer (−0.60% decade−1) and autumn (−0.39% decade−1). The reduction of surface RH is also captured by the NCEP/NCAR reanalysis at the surface, 400, 500, and 600 hPa. A particularly sharp reduction of RH since the mid-1990s is evident in both data sets, in line with rapid warming over the plateau. This suggests that moisture supply to the plateau from the Arabian Sea and the Bay of Bengal is limited and that variability and trends of surface RH over the TP are not uniquely driven by the Clausius-Clapeyron relationship.

Spatiotemporal Temperature Variability over the Tibetan Plateau: Altitudinal Dependence Associated with the Global Warming Hiatus

AbstractThe recent slowdown in global warming has initiated a reanalysis of temperature data in some mountainous regions for understanding the consequences and impact that a hiatus has on the climate system. Spatiotemporal temperature variability is analyzed over the Tibetan Plateau because of its sensitivity to climate change with a station network updated to 2014, and its linkages to remote sensing–based variability of MODIS daytime and nighttime temperature are investigated. Results indicate the following: 1) Almost all stations have experienced a notable warming in the time interval 1961–2014, with most obvious warming in winter, which depends on the selected time intervals. 2) There is no clear shift from a predominant warming to a near stagnation during the most recent period (2001–present). 3) Uniform altitudinal dependence of temperature change trends could not be confirmed for all regions, time intervals, and seasons, but sometimes an altitude threshold around 3 km is apparent. 4) Most of the met...

Revisiting the Relationship between Observed Warming and Surface Pressure in the Tibetan Plateau

AbstractThe Tibetan Plateau (TP) has an average elevation of over 4000 m and with its surrounding mountains is regarded as Earth’s “third pole.” As a result of its size and height, climate change in the TP has its own unique characteristics that include a proposed positive correlation between the surface temperature and pressure. This study examines the trends and relationships between the surface pressure and temperature in the TP through the examination of monthly mean data from 71 stations during 1961–2013. On annual, seasonal, and monthly time scales, the TP exhibits a statistically significant warming trend that attains a rate of 0.30°C decade−1 for annual means over the period 1961–2013. The most pronounced warming occurs in winter, in agreement with previous studies, with evidence of acceleration in the rate after the mid-1980s and the global warming slowdown period. For the entire period of 1961–2013, the surface pressure in the TP has a positive trend of 0.08 hPa decade−1 on an annual basis, agai...

Simulation of temperature extremes in the Tibetan Plateau from CMIP5 models and comparison with gridded observations

Understanding changes in temperature extremes in a warmer climate is of great importance for society and for ecosystem functioning due to potentially severe impacts of such extreme events. In this study, temperature extremes defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) from CMIP5 models are evaluated by comparison with homogenized gridded observations at 0.5° resolution across the Tibetan Plateau (TP) for 1961–2005. Using statistical metrics, the models have been ranked in terms of their ability to reproduce similar patterns in extreme events to the observations. Four CMIP5 models have good performance (BNU-ESM, HadGEM2-ES, CCSM4, CanESM2) and are used to create an optimal model ensemble (OME). Most temperature extreme indices in the OME are closer to the observations than in an ensemble using all models. Best performance is given for threshold temperature indices and extreme/absolute value indices are slightly less well modelled. Thus the choice of model in the OME seems to have more influences on temperature extreme indices based on thresholds. There is no significant correlation between elevation and modelled bias of the extreme indices for both the optimal/all model ensembles. Furthermore, the minimum temperature (Tmin) is significanlty positive correlations with the longwave radiation and cloud variables, respectively, but the Tmax fails to find the correlation with the shortwave radiation and cloud variables. This suggests that the cloud–radiation differences influence the Tmin in each CMIP5 model to some extent, and result in the temperature extremes based on Tmin.