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.

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[1] Most climate models suggest amplification of global warming in high mountains, but observations are less clear. Using comprehensive, homogeneity-adjusted temperature records from over 1000 high elevation stations across the globe, we examine the causes of changing temperature trends with elevation, assessing the roles of free atmospheric change, topography (exposure and aspect), and cryospheric feedback. The data show that observed 20th century temperature trends are most rapid near the annual 0°C isotherm due to snow-ice feedback. Mountain summit and freely draining slope sites are dominated by free-air advection and thus have consistent trend magnitudes, with reduced inter-site variance in comparison with incised valley sites where local factors are more important. Thus, while there has been no simplistic elevational increase in warming rates, some generalizations can be made. Water resources and ecosystems near the 0°C isotherm in the extratropics are at increased risk from accelerated warming. The data also suggest that exposed mountain summits, away from the effects of urbanization and topographic sheltering, may provide a relatively unbiased record of the planet's climate.

[1] In complex terrain, air in contact with the ground becomes cooled from radiative energy loss on a calm clear night and, being denser than the free atmosphere at the same elevation, sinks to valley bottoms. Cold-air pooling (CAP) occurs where this cooled air collects on the landscape. This article focuses on identifying locations on a landscape subject to considerably lower minimum temperatures than the regional average during conditions of clear skies and weak synoptic-scale winds, providing a simple automated method to map locations where cold air is likely to pool. Digital elevation models of regions of complex terrain were used to derive surfaces of local slope, curvature, and percentile elevation relative to surrounding terrain. Each pixel was classified as prone to CAP, not prone to CAP, or exhibiting no signal, based on the criterion that CAP occurs in regions with flat slopes in local depressions or valleys (negative curvature and low percentile). Along-valley changes in the topographic amplification factor (TAF) were then calculated to determine whether the cold air in the valley was likely to drain or pool. Results were checked against distributed temperature measurements in Loch Vale, Rocky Mountain National Park, Colorado; in the Eastern Pyrenees, France; and in Yosemite National Park, Sierra Nevada, California. Using CAP classification to interpolate temperatures across complex terrain resulted in improvements in root-mean-square errors compared to more basic interpolation techniques at most sites within the three areas examined, with average error reductions of up to 3°C at individual sites and about 1°C averaged over all sites in the study areas.

[1] Trend magnitudes of 11 indices of temperature extremes at 71 stations with elevations above 2000 m a.s.l. in the eastern and central Tibetan Plateau (TP) during 1961 -2005 are examined. Most trends in extremes are consistent with general warming in the TP. There are no significant correlations between elevation and trend magnitude of temperature extremes with the exception of TXn (coldest day temperature) and TX10 (cold day frequency). Thus an enhanced sensitivity of temperature extremes at higher elevations in the eastern and central TP is not apparent in the context of recent warming in this region. Although previous work showed a correlation between elevation and mean temperature trends in the TP, this analysis fails to substantiate this relationship for extremes. Analysis of trend magnitudes by topographic type and degree of urbanization show both factors to have a strong influence in this dataset, which overrides that of elevation.

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[1] Surface and free-air temperature observations from the period 1948-2002 are compared for 1084 surface locations at high elevations (>500 m) on all continents. Mean monthly surface temperatures are obtained from two homogeneity adjusted data sets: Global Historical Climate Network (GHCN) and Climatic Research Unit (CRU). Free-air temperatures are interpolated both vertically and horizontally from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis R1 2.5°grids at given pressure levels. The compatibility of surface and free-air observations is assessed by examination of the interannual variability of both surface and free-air temperature anomalies and the surface/free-air temperature difference (DT). Correlations between monthly surface and free-air anomalies are high. The correlation is influenced by topography, valley bottom sites showing lower values, because of the influence of temporally sporadic boundary layer effects. The annual cycle of the derived surface/freeair temperature difference (DT) demonstrates physically realistic variability. Cluster analysis shows coherent DT regimes, which are spatially organized. Temporal trends in surface and free-air temperatures and DT are examined at each location for 1948-1998. Surface temperatures show stronger, more statistically robust and widespread warming than free-air temperatures. Thus DT is increasing significantly at the majority of sites (>70%). A sensitivity analysis of trend magnitudes shows some reliance on the time period used. DT trend variability is dominated by surface trend variability because free-air trends are weak, but it is possible that reanalysis trends are unrealistically small. Results are sensitive to topography, with mountaintop sites showing weaker DT increases than other sites (although still positive). There is no strong relationship between any trend magnitudes and elevation. Since DT change is dependent on location, it is clear that temperatures at mountain sites are changing in ways contrasting to free air.

Global warming has created a need for studies along climatic gradients to assess the effects of temperature on ecological processes. Altitudinal and latitudinal gradients are often used as such, usually in combination with air temperature data from the closest weather station recorded at 1.52 m above the ground. However, many ecological processes occur in, at, or right above the soil surface. To evaluate how representative the commonly used weather station data are for the microclimate relevant for soil surface biota, we compared weather station temperatures for an altitudinal (500900 m a.s.l.) and a latitudinal gradient (4968 degrees N) with data obtained by temperature sensors placed right below the soil surface at five sites along these gradients. The mean annual temperatures obtained from weather stations and adjusted using a lapse rate of -5.5 degrees C km-1 were between 3.8 degrees C lower and 1.6 degrees C higher than those recorded by the temperature sensors at the soil surface, depending on the position along the gradients. The monthly mean temperatures were up to 10 degrees C warmer or 5 degrees C colder at the soil surface. The within-site variation in accumulated temperature was as high as would be expected from a 300 m change in altitude or from a 4 degrees change in latitude or a climate change scenario corresponding to warming of 1.63.8 degrees C. Thus, these differences introduced by the decoupling are significant from a climate change perspective, and the results demonstrate the need for incorporating microclimatic variation when conducting studies along altitudinal or latitudinal gradients. We emphasize the need for using relevant temperature data in climate impact studies and further call for more studies describing the soil surface microclimate, which is crucial for much of the biota