Energy and Water Cycles in the Third Pole

As the most prominent and complicated terrain on the globe, the Tibetan Plateau (TP) is often called the “Roof of the World”, “Third Pole” or “Asian Water Tower”. The energy and water cycles in the Third Pole have great impacts on the atmospheric circulation, Asian monsoon system and global climate change. On the other hand, the TP and the surrounding higher elevation area are also experiencing evident and rapid environmental changes under the background of global warming. As the headwater area of major rivers in Asia, the TP’s environmental changes—such as glacial retreat, snow melting, lake expanding and permafrost degradation—pose potential long-term threats to water resources of the local and surrounding regions. To promote quantitative understanding of energy and water cycles of the TP, several field campaigns, including GAME/Tibet, CAMP/Tibet and TORP, have been carried out. A large amount of data have been collected to gain a better understanding of the atmospheric boundary layer structure, turbulent heat fluxes and their coupling with atmospheric circulation and hydrological processes. The focus of this reprint is to present recent advances in quantifying land–atmosphere interactions, the water cycle and its components, energy balance components, climate change and hydrological feedbacks by in situ measurements, remote sensing or numerical modelling approaches in the “Third Pole” region

Estimation of surface energy fluxes under complex terrain of Mt. Qomolangma over the Tibetan Plateau

Surface solar radiation is an important parameter in surface energy balance models and in estimation of evapotranspiration. This study developed a DEM based radiation model to estimate instantaneous clear sky solar radiation for surface energy balance system to obtain accurate energy absorbed by the mountain surface. Efforts to improve spatial accuracy of satellite based surface energy budget in mountainous regions were made in this work. Based on eight scenes of Landsat TM/ETM+ (Thematic Mapper/Enhanced Thematic Mapper+) data and observations around the Qomolangma region of the Tibetan Plateau, the topographical enhanced surface energy balance system (TESEBS) was tested for deriving net radiation, ground heat flux, sensible heat flux and latent heat flux distributions over the heterogeneous land surface. The land surface energy fluxes over the study area showed a wide range in accordance with the surface features and their thermodynamic states. The model was validated by observations at QOMS/CAS site in the research area with a reasonable accuracy. The mean bias of net radiation, sensible heat flux, ground heat flux and latent heat flux is lower than 23.6 W m−2. The surface solar radiation estimated by the DEM based radiation model developed by this study has a mean bias as low as −9.6 W m−2. TESEBS has a decreased mean bias of about 5.9 W m−2 and 3.4 W m−2 for sensible heat and latent heat flux, respectively, compared to the Surface Energy Balance System (SEBS)

Multi-physics ensemble snow modelling in the western Himalaya

Combining multiple data sources with multi-physics simulation frameworks offers new potential to extend snow model inter-comparison efforts to the Himalaya. As such, this study evaluates the sensitivity of simulated regional snow cover and runoff dynamics to different snowpack process representations. The evaluation is based on a spatially distributed version of the Factorial Snowpack Model (FSM) set up for the Astore catchment in the upper Indus basin. The FSM multi-physics model was driven by climate fields from the High Asia Refined Analysis (HAR) dynamical downscaling product. Ensemble performance was evaluated primarily using MODIS remote sensing of snow-covered area, albedo and land surface temperature. In line with previous snow model inter-comparisons, no single FSM configuration performs best in all of the years simulated. However, the results demonstrate that performance variation in this case is at least partly related to inaccuracies in the sequencing of inter-annual variation in HAR climate inputs, not just FSM model limitations. Ensemble spread is dominated by interactions between parameterisations of albedo, snowpack hydrology and atmospheric stability effects on turbulent heat fluxes. The resulting ensemble structure is similar in different years, which leads to systematic divergence in ablation and mass balance at high elevations. While ensemble spread and errors are notably lower when viewed as anomalies, FSM configurations show important differences in their absolute sensitivity to climate variation. Comparison with observations suggests that a subset of the ensemble should be retained for climate change projections, namely those members including prognostic albedo and liquid water retention, refreezing and drainage processes

Long-term variations in actual evapotranspiration over the Tibetan Plateau

Actual terrestrial evapotranspiration (ET$_{a}$) is a key parameter controlling land–atmosphere interaction processes and water cycle. However, spatial distribution and temporal changes in ET$_{a}$ over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ET$_{a}$ and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded root-mean-square errors ranging from 9.3 to 14.5 mm per month and correlation coefficients exceeding 0.9. The domain mean of annual ET$_{a}$ on the TP decreased slightly (−1.45 mm yr$^{-1}$, p90° E) but decreased significantly at a rate of −5.52 mm yr$^{-1}$ (p<0.05) in the western sector of the TP (long <90° E). In addition, the decreases in annual ET$_{a}$ were pronounced in the spring and summer seasons, while almost no trends were detected in the autumn and winter seasons. The mean annual ET$_{a}$ during 2001–2018 and over the whole TP was 496±23 mm. Thus, the total evapotranspiration from the terrestrial surface of the TP was 1238.3±57.6 km3 yr$^{-1}$. The estimated ET$_{a}$ product presented in this study is useful for an improved understanding of changes in energy and water cycle on the TP. The dataset is freely available at the Science Data Bank (https://doi.org/10.11922/sciencedb.t00000.00010; Han et al., 2020b) and at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.270995, Han et al., 2020a)

THE TIBETAN PLATEAU SURFACE ENERGY BUDGET AND ITS TELECONNECTION WITH THE EAST ASIAN SUMMER MONSOON: EVIDENCE FROM GROUND OBSERVATIONS, REMOTE SENSING, AND REANALYSIS DATASETS

Estimations from meteorological stations indicate that the surface sensible heat flux over the Tibetan Plateau has been decreasing continuously since the 1980s. Modeling studies suggest that such change is physically linked to the weakening of the East Asian summer monsoon through Rossby wave trains. However, the relationship between the surface energy budget over the entire Tibetan Plateau and the East Asian summer monsoon rainfall has rarely been examined. The objective of this study is to quantify the relationship between the surface energy budget over the Tibetan Plateau and the East Asian summer monsoon, using ground observations, remote sensing, and reanalysis datasets with three specific questions: What are the spatiotemporal characteristics of the surface radiation and energy budgets over the Tibetan Plateau in recent decades? How does the interannual variation of the surface radiation and energy budgets correlate to, respond to, and impact the observed regional surface and atmospheric anomalies? And can the changes of the surface energy budget component over the Tibetan Plateau explain the weakening of the East Asian summer monsoon and associated precipitation changes in China? To address those questions, I 1) develop a fused monthly surface radiation and energy budgets dataset over the Tibetan Plateau using ground and satellite observations and reanalysis datasets; 2) analyze the spatial distribution of the fused surface radiation and energy budgets, and assess its correlations with the observed surface and atmospheric conditions over the Tibetan Plateau; and 3) test the hypothesis of whether the Asian summer monsoon rainfall is under the impact of the spring sensible heat flux over the Tibetan Plateau through correlation analysis, regression analysis, Granger causality test, and composite analysis. The root mean square errors from cross validation are 18.9 Wm-2, 10.3 Wm-2, 14.3 Wm-2 for the fused monthly surface net radiation, latent heat flux, and sensible heat flux. The fused downward shortwave irradiance, sensible heat flux, and latent heat flux anomalies are consistent with those estimated from meteorological stations. The associations among the fused surface radiation and energy budgets and the related surface anomalies such as mean temperature, temperature range, snow cover, and Normalized Difference Vegetation Index in addition to the atmospheric anomalies such as cloud cover and water vapor show seasonal dependence over the Tibetan Plateau. The decreased late spring sensible heat flux, which is sustained throughout the summer, has been associated with suppressed summer rainfall in the north of China and the north of Indian and enhanced rainfall in the west of India. The mechanism of those associations is found through a lower-level Rossby wave train as a result of anomalous sensible heating over the Tibetan Plateau. The decreased late spring sensible heat flux has also been associated with dry weather in the Yangtze River basin through a descending motion to the east of the Tibetan Plateau. This dissertation is the first synthesized analysis of the surface radiation and energy budgets at a spatial scale covering the entire Tibetan Plateau over a temporal period of two decades. The results of this study could contribute to a better understanding of the land-atmosphere interactions over the Tibetan Plateau, and the role of the Tibetan Plateau sensible heating in regulating the strength of the Asian summer monsoon. This study demonstrates a linkage between the spring sensible heat over the Tibetan Plateau and the Asian summer monsoon rainfall that affect about one fourth of the world's population, which has implications that will benefit local agriculture practices, disaster management, and climate change mitigation

Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau

The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair; the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming

Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data

Abstract. The climate regime shift during the 1980s had a substantial impact on the terrestrial ecosystems and vegetation at different scales. However, the mechanisms driving vegetation changes, before and after the shift, remain unclear. In this study, we used a biophysical-dynamic vegetation model to estimate large-scale trends in terms of carbon fixation, vegetation growth, and expansion during the period 1958–2007, and to attribute these changes to environmental drivers including elevated atmospheric CO2 concentration (hereafter eCO2), global warming, and climate variability (hereafter CV). Simulated Leaf Area Index (LAI) and Gross Primary Product (GPP) were evaluated against observation-based data. Significant spatial correlations are found (correlations &gt; 0.87), along with regionally varying temporal correlations of 0.34–0.80 for LAI and 0.45–0.83 for GPP. More than 40 % of the global land area shows significant trends in LAI and GPP since the 1950s: 11.7 % and 19.3 % of land has consistently positive LAI and GPP trends, respectively; while 17.1 % and 20.1 % of land, saw LAI and GPP trends respectively, reverse during the 1980s. Vegetation fraction cover (FRAC) trends, representing vegetation expansion/shrinking, are found at the edges of semi-arid areas and polar areas. Overall, eCO2 consistently contributes to positive LAI and GPP trends in the tropics. Global warming is shown to mostly affected LAI, with positive effects in high latitudes and negative effects in subtropical semi-arid areas. CV is found to dominate the variability of FRAC, LAI, and GPP in the semi-humid and semi-arid areas. The eCO2 and global warming effects increased after the 1980s, while the CV effect reversed during the 1980s. In addition, plant competition is shown to have played an important role in determining which driver dominated the regional trends. This paper presents a new insight into ecosystem variability and changes in the varying climate since the 1950s

Numerical study on the response of the largest lake in China to climate change

Lakes are sensitive indicators of climate change. There are thousands of lakes on the Tibetan Plateau (TP), and more than 1200 of them have an area larger than 1&thinsp;km2; they respond quickly to climate change, but few observation data of lakes are available. Therefore, the thermal condition of the plateau lakes under the background of climate warming remains poorly understood. In this study, the China regional surface meteorological feature dataset developed by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS), MODIS lake surface temperature (LST) data and buoy observation data were used to evaluate the performance of lake model FLake, extended by simple parameterizations of the salinity effect, for brackish lake and to reveal the response of thermal conditions, radiation and heat balance of Qinghai Lake to the recent climate change. The results demonstrated that the FLake has good ability in capturing the seasonal variations in the lake surface temperature and the internal thermal structure of Qinghai Lake. The simulated lake surface temperature showed an increasing trend from 1979 to 2012, positively correlated with the air temperature and the downward longwave radiation while negatively correlated with the wind speed and downward shortwave radiation. The simulated internal thermodynamic structure revealed that Qinghai Lake is a dimictic lake with two overturn periods occurring in late spring and late autumn. The surface and mean water temperatures of the lake significantly increased from 1979 to 2012, while the bottom temperatures showed no significant trend, even decreasing slightly from 1989 to 2012. The warming was the strongest in winter for both the lake surface and air temperature. With the warming of the climate, the later ice-on and earlier ice-off trend was simulated in the lake, significantly influencing the interannual and seasonal variability in radiation and heat flux. The annual average net shortwave radiation and latent heat flux (LH) both increase obviously while the net longwave radiation and sensible heat flux (SH) decrease slightly. Earlier ice-off leads to more energy absorption mainly in the form of shortwave radiation during the thawing period, and later ice-on leads to more energy release in the form of longwave radiation, SH and LH during the ice formation period. Meanwhile, the lake–air temperature difference increased in both periods due to shortening ice duration.</p