On the basis of mean temperature, maximum temperature and minimum temperature from the updated China Homogenized Historical Temperature Data Sets, the recent warming in the Tibetan Plateau (TP) during 1961-2005 and global warming hiatus period are examined. During 1961During -2005, the mean temperature, maximum temperature and minimum temperature in the whole TP show a statistically increasing trend especially after the 1980s, with the annual rates of 0.27, 0.19 and 0.36 ∘ C decade −1 , respectively. The performance of 26 general circulation models (GCMs) available in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) is evaluated in the TP by comparison with the observations during 1961-2005. Most CMIP5 GCMs can capture the decadal variations of the observed mean temperature, maximum temperature and minimum temperature, and have significant positive correlations with observations (R > 0.5), with root mean squared error <1 ∘ C. This suggests that CMIP5 GCMs can reproduce the recent temperature evolution in the TP, but with cold biases. However, most CMIP5 GCMs underestimate the observed warming rates, especially the CNRM-CM5, GISS-E2-H and MRI-CGCM3 models. There are significant positive correlations between the trend magnitudes and the anomaly of the mean temperature, maximum temperature and minimum temperature, with correlations of 0.85, 0.86 and 0.87, respectively. The warming from the observations and CMIP5 mean in the TP is significant during the global hiatus period, consistent with decreasing snow cover and albedo in the region. This study suggests that positive snow/ice-albedo feedback processes may account for ongoing surface warming in the TP despite the pause in global mean surface warming.

Compared with observations, most of the datasets (NCEP1, NCEP2, CMAP1, CMAP2, ERA-Interim, ERA-40, GPCP, 20century, MERRA and CFSR) can both broadly capture the spatial distributions and identify temporal patterns and variabilities of mean precipitation. However, most multi-datasets overestimate precipitation especially in the SE where summer convection is dominant. There remain substantial disagreements and large discrepancies in precipitation trends due to differences in assimilation systems between datasets. Taylor diagrams are used to show the correlation coefficients, standard deviation, and root-meansquare difference of precipitation totals between interpolated observations and assimilated values on an annual and seasonal basis. Merged analysis data (CMAP1 and CMAP2) agree with observations more closely than reanalyses. Thus not all datasets are equally biased and choice of dataset is important.

Climate warming on the Tibetan Plateau (TP) potentially influences many climate parameters other than temperature including wind speed, cloudiness and precipitation. Temporal trends of surface wind speed at 71 stations above 2000 m above sea level in the TP are examined during 1980-2005. To uncover causes of observed trends in wind speed, relationships with surface temperature, a TP index and sunshine duration are also analysed. The TP index is calculated as the accumulated 500 hPa geopotential height above 5000 m over the region of 30°N-40°N, 75°E-105°E from NCEP/NCAR reanalysis. The annual mean wind speed patterns during 1980-2005 are similar to those in different seasons, with higher wind speeds in the northern and western parts of the TP. Highest mean wind speeds occur in spring and lowest in autumn. During 1980-2005, annual and seasonal mean wind speeds show statistically decreasing trends at most stations. The mean trend magnitude for annual mean wind speed is -0.24ms-1decade-1, with the maximum decline in spring (-0.29ms-1decade-1) and minimum in autumn (-0.19ms-1decade-1). Both annually and in different seasons, wind speed is significantly negatively correlated with mean temperature, minimum temperature, maximum temperature, and the TP index, but significantly positively correlated with sunshine duration. Wind speed trends fail to show a simple elevation dependency but speeds are positively correlated with meridional surface temperature/pressure gradients. Warming in the TP may weaken the latitudinal gradients of both regional temperature and surface pressure, thus altering the regional atmospheric circulation and accounting in part for the observed decline of wind speed. © 2013 Royal Meteorological Society

Spatial and temporal variabilities of long-term (1961-2013) diurnal temperature range (DTR) are examined in the Tibetan Plateau (TP) based on the 71 observational stations. The relative regional contributions to DTR in the TP are studied among maximum temperature, minimum temperature, total cloud cover (TCC), and atmospheric teleconnections. The regional annual mean DTR (average of the 71 stations) is 14.17 ∘ C, with a clear maximum in winter (16.35 ∘ C) and minimum in summer (12.62 ∘ C). During 1961-2013, the DTR in the TP declines before the 1980s and shows mute change afterwards, with an annual rate of −0.20 ∘ C decade −1 calculated by the Mann-Kendall method. The trend in DTR is primarily a consequence of greater warming in minimum temperature than maximum temperature. In summer, there are significant negative correlations between the TCC and DTR in the TP, suggesting that the decreases in the DTR are associated with variations of TCC in the region. The atmospheric circulation composite analysis between strongly positive and negative DTR in summer in the TP reveals that during the low DTR period the TP has more water vapour flux, stronger temperature advection, and strengthened southerly wind. This suggests that the atmospheric circulations have contributed to the trends in the DTR, but it is difficult to account for the specific contributions. Further investigations of the impact of global warming on the DTR in the TP are still required.

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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 À0.23% decade À1 and even more rapidly in summer (À0.60% decade À1 ) and autumn (À0.39% decade À1 ). 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.

The impact of assimilating Infrared Atmospheric Sounding Interferometer (IASI) radiance observations on the analyses and forecasts of Hurricane Maria (2011) and Typhoon Megi (2010) is assessed using Weather Research and Forecasting Data Assimilation (WRFDA). A cloud-detection scheme (McNally and Watts 2003) was implemented in WRFDA for cloud contamination detection for radiances measured by high spectral resolution infrared sounders. For both Hurricane Maria and Typhoon Megi, IASI radiances with channels around 15-lm CO 2 band had consistent positive impact on the forecast skills for track, minimum sea level pressure, and maximum wind speed. For Typhoon Megi, the error reduction appeared to be more pronounced for track than for minimum sea level pressure and maximum wind. The sensitivity experiments with 6.7-lm H 2 O band were also conducted. The 6.7-lm band also had some positive impact on the track and minimum sea level pressure. The improvement for maximum wind speed forecasts from the 6.7-lm band was evident, especially for the first 42 h. The 15-lm band consistently improved specific humidity forecast and we found improved temperature and horizontal wind forecast on most levels. Generally, assimilating the 6.7-lm band degraded forecasts, likely indicating the inefficiency of the current WRF model and/or data assimilation system for assimilating these channels. IASI radiance assimilation apparently improved depiction of dynamic and thermodynamic vortex structures.

Multiproxies suggest a tripole humidity pattern in Asia in the Medieval Climate Anomaly (MCA, 950–1250 A.D.) and Little Ice Age (LIA, 1500–1800 A.D.), with drier (wetter) conditions in arid central Asia (ACA), wetter (drier) conditions in North China, and drier (wetter) conditions in South China. However, the mechanisms behind this reconstructed humidity variation remain unclear. In this study, we investigate Asian humidity changes by using the last millennium simulations of the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3). The results indicate that only one out of nine PMIP3 models (Meteorological Research Institute Coupled ocean‐atmosphere General Circulation Model version 3) can well reproduce the reconstructed humidity pattern. This model indicates that the tripole humidity pattern is mainly caused by precipitation changes in spring and summer and is prominent in the past millennium on a multidecadal time scale. In spring, the reduction (increase) of precipitation in ACA and South China is attributed to the northward (southward) shift of the westerlies and a weakened (strengthened) western Pacific subtropical high in the MCA (LIA). In summer, precipitation over ACA decreases (increases) due to a local descending (ascending) motion, while abundant (deficient) precipitation over eastern China results from the enhanced (depressed) summer monsoon. Moreover, we suggest that a La Niña (El Niño)‐like condition may be the primary reason the tripole precipitation pattern was maintained in the MCA (LIA), although a warmer (colder) North Pacific and North Atlantic also play a role. The mechanisms must be further validated since most simulations fail to reproduce the reconstructed humidity condition in the MCA/LIA, making model‐model comparisons difficult.