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This paper aims to update our understanding of the carbon cycle in the Himalayas, the most intense collisional orogeny globally, by providing new insight into its impact on Cenozoic climate cooling through the use of isotopic variations in both organic and inorganic carbon and an isotopic mass balance model. Our results from 20 selected hot springs show that the relative contributions of dissolved carbon from the mantle, metamorphic decarbonization, aqueous dissolution, and soil organic matter are approximately 2%, 82%, 6%, and 10%, respectively. Approximately 87% ± 5% of CO2 generated in the deep crust precipitates as calcite, while approximately 5.5% ± 1% of this carbon is converted to biomass through microbial chemosynthesis at depths less than 2 km. Our random forests approach yielded a metamorphic carbon flux from the entire Himalayan orogenic belt of approximately 2.7 ∼ 4.5 × 1012 mol/yr. The minor CO2 released into the atmosphere (2.5 ∼ 4.2 × 1011 mol/yr) is comparable to the carbon consumption driven by Himalayan weathering. This paper provides new insights into deep carbon cycling, notably that approximately 93% of deeply sourced carbon is trapped in the shallow crust, rendering orogenic processes carbon neutral and possibly acting as one of the major triggers of long‐term climate cooling in the Cenozoic. Plain Language Summary: Large‐scale deep metamorphic decarbonization and CO2 release into the atmosphere during continental collision orogenesis worldwide have had significant impacts on Cenozoic global climate change. However, the carbon sources and sinks and the mechanisms underlying their impacts on climate change are not fully understood. This paper reports the chemistry of aqueous solutions, carbon isotopic compositions of dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC), and helium and carbon isotopic compositions of free gases from hot springs in southern Tibet. The carbon isotope fractionation model between gas and aqueous solutions revealed that the carbon released from depth underwent six different stages. Based on the random forests machine learning algorithm, we estimated the metamorphic carbon flux across the Himalayan orogenic belt. Furthermore, only a small fraction (7%) of deep carbon is eventually released into the atmosphere, and this volume is the same magnitude as the amount of carbon absorbed by silicate weathering on the Tibetan Plateau. This paper emphasizes that the carbon sequestration process in the upper crust may have resulted in nearly carbon‐neutral geological bodies in the Himalayan orogenic belt, thus playing a critical role in Cenozoic climate cooling. Key Points: Approximately 87% of deeply sourced carbon precipitates as calcite, while approximately 5.5% is sequestered as biomass in the shallow crustThe carbon flux across the Himalayan orogenic belt was estimated by the random forests approachCrustal thickening has attenuated long‐term deep carbon emissions from the Himalayas [ABSTRACT FROM AUTHOR]

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

The growth history of the Tibetan Plateau provides a valuable natural laboratory to understand tectonic processes of the India–Asia collision and their impact on and interactions with Asian and global climate change. However, both Tibetan Plateau growth and Asian paleoenvironments are generally poorly documented in pre-Pliocene times and reflect limited temporal coverage for different parts of the plateau. In this paper, the 238 m thick Cenozoic sediments in the Hongzhuang section of the Xunhua Basin were tested and analyzed via paleomagnetic and environmental magnetic methods. The formation age was determined, and the evolution history of the regional climate environment was analyzed. The magnetostratigraphy study shows that the sediments record a continuous sequence of geomagnetic polarity changes from C5ACn to C10r, which spans an interval of approximately 30~14.3 Ma from the early Oligocene to the middle Miocene. The magnetic susceptibility of the Hongzhuang section is basically similar to the deep-sea oxygen isotope fluctuation, indicating that the monsoon climate change indicated by the magnetic susceptibility is affected by global temperature. It is worth noting that at ~27 Ma and ~15 Ma, there is a negative correlation between magnetic susceptibility and deep-sea oxygen isotope, and magnetic susceptibility lags behind the increase in deep-sea oxygen isotope. Combined with the change in the sedimentary rate curve, we explain the asynchrony between the magnetic susceptibility and the deep-sea oxygen isotope around ~27 Ma and ~15 Ma. As the uplift of the plateau leads to the enhancement of the East Asian summer monsoon, the soil formation in the region is strengthened, resulting in an increase in magnetic susceptibility. At the same time, the rapid uplift of the plateau caused the erosion of the surrounding mountains to strengthen, and the input of near-source materials may promote the increase in magnetic susceptibility. [ABSTRACT FROM AUTHOR]

The alpine grassland ecosystem accounts for 53% of the Qinghai-Tibet Plateau (QTP) area, which is an important ecological protection barrier, but fragile and highly vulnerable to climate change. Therefore, continuous monitoring of the aboveground biomass (AGB) of grassland is necessary. Although many studies have mapped the spatial distribution of AGB over the QTP, the results vary widely due to the limited ground samples and mismatches with satellite pixel scales. This paper proposed a new algorithm using unmanned aerial vehicles (UAVs) as a bridge to re-estimate the grassland AGB over 20 the QTP from 2000 to 2019. The innovations were as follows: 1) In the aspect of ground data collection, the spatial scale matching among the traditional ground quadrat sampling, UAV photos, and MODIS pixels was fully considered. From 2015 to 2019, 906 pairs of ground-UAV sample data at the quadrat scale and 2,602 sets of UAV data matching the MODIS pixel scale were collected. A total of more than 37,000 UAV photos were captured at the height of 20 meters. Therefore, the ground validation samples was sufficient and scale matched. 2) In terms of model construction, the traditional quadrat scale 25 (0.25m2) was successfully upscaled to the MODIS pixel scale (6,2500 m2) based on the random forest method and stepwise upscaling scheme. Compared with previous studies, the scale matching of independent and dependent variables was realized, effectively reducing the impact of scale mismatch. At the pixel scale, the AGB value estimated by UAV had a more linear correlation with the MODIS vegetation indices than the traditional sampling method. The multi-year independent crossvalidation results showed that the constructed pixel scale AGB estimation had good robustness, with an average R2 of 0.83 30 and RMSE of 34.13 g/m2. Our dataset provides an important input parameter for a comprehensive understanding of the QTP in the process of global climate change. [ABSTRACT FROM AUTHOR]

Mountain glaciers are one of the most sensitive indicators of climate change. Reconstructing past glacier extents provides valuable insights into the climate change for specific regions where instrumental records are not enough and even absent. In the paper we mapped the outlines for 691 Little Ice Age (LIA) glaciers in terms of prominent moraines beyond contemporary glaciers in the Tanggula Mountains, central Tibetan Plateau (TP). Based on these glacier outlines, we reconstructed the ice thicknesses and surfaces for the LIA glaciers in the region. Accordingly, we calculated the equilibrium-line altitudes (ELAs) for contemporary and LIA glaciers. By comparing the ELAs between the contemporary and LIA glaciers, we estimated the LIA summer temperature decreases in different subregions of the Tanggula Mountains. Since the LIA, the ELA have risen by 35.6 ± 18.8 m, 26.1 ± 17.6 m, and 63.1 ± 38.6 m in the respective western, central, and eastern subregions of the Tanggula Mountains. Assuming no change in precipitation, the LIA summer temperature would decrease by 0.22 ± 0.12 °C, 0.14 ± 0.09 °C, and 0.34 ± 0.21 °C in the three subregions, respectively. Moreover, glaciers in the western, central, and eastern subregions have lost 13.3%, 23.9%, and 42.8% of their area, 15.4%, 25.3%, and 39.6% of their length, and 20.8%, 39.0%, and 61.0% of their volume, respectively. By compiling the LIA ELA data from previous studies, we also estimated the LIA summer temperature changes for other regions of the TP. The LIA ELA and summer temperature changes relative to the present showed a decreasing trend from the edges towards the interior on the TP. • LIA glaciers and summer climate were reconstructed at the Tanggula Mountains. • LIA summers were 0.22 ± 0.12 °C, 0.14 ± 0.09 °C, and 0.34 ± 0.21 °C cooler than present in three subregions. • Summer temperature change had a decreasing trend from the edges towards the interior on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The implementation of the "Belt and Road" strategy not only promotes the coordinated development of China's regional economy but also generates a large amount of greenhouse gas emissions. The research and policy recommendations on agricultural carbon emissions are of great significance for China toward engendering sustainable agricultural development and appreciably contributing to the alleviation of global climate change. In this paper, agricultural carbon emissions in the Belt and Road region of China from 2003-2018 are calculated, and its spatial-temporal characteristics are analyzed. Then, we modified the logarithmic mean Divisia index model from the original four factors to six to analyze the drivers of agricultural carbon emissions. The research results obtained are as follows: (1) Total carbon emission reached a peak of 26.6326 million tons in 2016, representing a 54.53% increase from the 17.2342 million tons in 2003. Moreover, it indicated a downward trend in 2017 and dropped by approximately 4% to 25.5685 million tons in 2018. (2) Spatially, agricultural carbon emission varies greatly, with the highest value recorded in Heilongjiang and the lowest in Tibet, thereby exhibiting the characteristics of "northwest>northeast>southwest>southeast." (3) Overall, the economic factor was the most important driving factor, whereas the subsidy factor was the strongest inhibiting factor for the growth of agricultural carbon emissions. Notably, the foreign trade factor had both promoting and inhibiting effects on it. [ABSTRACT FROM AUTHOR]

Studies of geochemical proxies, such as carbonate δ18O and TEX 86 , show that the Earth's climate has changed significantly during the Cretaceous Period. However, knowledge about the sea surface temperature (SST) history of the eastern Tethys is limited. Based on the calcareous nannofossil record of the Nirang section, Tethys Himalayas, this paper attempts to establish the biostratigraphic framework and SST evolution of the Cretaceous Period in the southern Tibet. A total of 131 species were identified from the studied succession. Twelve bioevents were recognized, allowing for early Albian to the early Campanian (CC8 to CC18 biozones) in the section. Meanwhile, a disconformity within 81–71 Ma was also identified. The SST evolution was analysed by the calcareous nannofossils modified temperature index (mTI), and the results reveal that the long-term SST changes in the Tethys Himalayas of southern Tibet experienced progressive warming from the early Albian to the early Turonian and the warm interval persisted until the early Campanian. Short-term warming and cooling events, e.g., rapid warming in the early and late Albian, subsequent cooling in the latest Albian and peak warmth at the Cenomanian–Turonian transition, are also recorded in the study area. The SST history of the Albian-Cenomanian in the eastern Tethys can be well correlated to the western Tethys (central Italy). However, the compilation of TEX 86 data indicates substantial global cooling during the Coniacian to Campanian. This study suggests that the northward drift of the Indian continent towards the equator is likely to be responsible for the sustained warmth in the Tethys Himalayas from the middle Turonian to the early Campanian. • Calcareous nannofossil biozones of Albian-early Campanian in Tethys Himalaya of southern Tibet is defined. • Based on mTI of nannofossils, long term history of Cretaceous palaeoclimate of eastern Tethys is reconstructed. • The SST history in Tethys Himalaya is controlled by changes of global palaeotemperature and regional palaeolatitude. [ABSTRACT FROM AUTHOR]

The tropopause plays an important role in climate change, particularly in Tibet with complex topography and climate change system. In this paper, the temperature and height of the Cold Point Tropopause (CPT) in Tibet are obtained and investigated from COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) GPS Radio Occultation (RO) during June 2006–Feb 2014, which are compared with Lapse Rate Tropopause (LRT) from Atmospheric Infrared Sounder (AIRS/NASA). Furthermore, the impact of Gravity waves (GW) potential energy ( E p ) on the CPT-Temperature, CPT-Height, and the variation of stratospheric water vapor with GW E p variations are presented. Generally the coldest CPT temperature is in June–July–August (JJA) with −76.5 °C, resulting less water vapor into the stratosphere above the cold points. The temperature of the cold point increases up to −69 °C during the winter over the Tibetan Plateau (25–40°N, 70–100°E) that leads to increase in water vapor above the cold points (10 hPa). Mean vertical fluctuations of temperature are calculated as well as the mean gravity wave potential energy E p for each month from June 2006 to Feb 2014. Monthly E p is calculated at 5°×5° grids between 17 km and 24 km in altitude for the Tibetan Plateau. The E p raises from 1.83 J/Kg to 3.4 J/Kg from summer to winter with mean E p of 2.5 J/Kg for the year. The results show that the gravity waves affect the CPT temperature and water vapor concentration in the stratosphere. Water vapor, CPT temperature and gravity wave ( E p ) have good correlation with each other above the cold points, and water vapor increases with increasing E p . [ABSTRACT FROM AUTHOR]

• LUE-VPM produced better quality NPP than MODIS products. • PAR produced from high-resolution DEM can be used in regional NPP modelling. • The MODIS NPP is statistical different with the in-situ measurements in Zeku implementation. Accurate estimation of grassland Net Primary Productivity (NPP) is one of the most important steps in monitoring and further analysing the status of the grassland ecosystem. However, the quality of regional or even global grassland NPP estimations are commonly limited by the two most important input datasets: Photosynthetic Active Radiation (PAR) and climatic data, which make the NPP estimate unrepresentative or even inaccurate. This paper uses a Light Use Efficiency with Vegetation Photosynthesis Model (LUE-VPM) to estimate the high-quality grassland NPP in Zeku. By using the PAR data derived from high resolution DEM products and the improved land surface temperature data, the NPP produced by LUE-VPM shows that it is statistically the same as in situ converted NPP with a p-value of t -test equalling 0.90 (the RMSE between the two is 97.77 gC/m2), while MODIS NPP in Zeku is statically different from the all the in-situ sampling results with a p-value of t-text smaller than 0.03. The results of this paper provided a better estimate than MODIS NPP, and LUE-VPM can be used for the high-quality regional grassland NPP estimation when the quality of PAR data and climatic data improved. [ABSTRACT FROM AUTHOR]

In this paper, we review evidence for a major biotic turnover across the Oligocene/Miocene in the Tibetan Plateau region. Based on the recent study of six well-preserved fossil sites from the Cenozoic Lunpola and Nima basins in the central Tibetan Plateau, we report a regional changeover from tropical/subtropical ecosystems in the Late Oligocene ecosystem (26–24 Ma) to a cooler, alpine biota of the Early Miocene (23–18 Ma). The Late Oligocene fossil biota, comprising of fish (climbing perch), insects and plants (palms), shows that the hinterland of the Tibetan Plateau was a warm lowland influenced by tropical humidity from the Indian Ocean. In the Early Miocene, the regional biota became transformed, with the evolution and diversification of the endemic primitive snow carp. Early Miocene vegetation was dominated by temperate broad-leaved forest with abundant conifers and herbs under a cool climate, and mammals included the hornless rhinoceros, Plesiaceratherium , a warm temperate taxon. This dramatic ecosystem change is due to a cooling linked to the uplift of Tibetan region, from a Late Oligocene paleo-elevation of no greater than 2300 m a.s.l. in the sedimentary basin to a paleo-elevation of about 3000 m a.s.l. Another factor was the Cenozoic global climatic deterioration toward to an ice-house world. • The Tibetan uplift had a profound impact on the evolution of terrestrial ecosystems. • The Oligocene subtropical ecosystem was replaced by a Miocene cooler biota in Tibet. • The Late Oligocene biota showed that the Tibetan hinterland was a warm lowland. • The Early Miocene biota eventually culminated in the present ecosystem of Tibet. • This dramatic ecosystem change is due to the cooling effect of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen's slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change. [ABSTRACT FROM AUTHOR]

Aboveground net primary productivity (ANPP) and rain-use efficiency (RUE) are important indicators in assessing the response of ecosystems to climate change. In this paper, the Changtang Plateau in the Tibetan Autonomous Region was selected as the study area to analyze the spatial and temporal changes of ANPP and RUE in grassland communities and their response to climate change. The results showed the following:(1) The spatial pattern of ANPP was closely related to rainfall on the Changtang Plateau. The average ANPP over the past 15 years increased gradually from the arid west to the humid east. A consistent pattern was exhibited in different grassland types and climate zones. (2) The RUE was higher at the east and west edges of the Changtang Plateau, especially in the arid west, but was lower in the center. From the perspective of different climatic zones, the average RUE in the southern Tibetan semiarid climate zone and the Ngari arid climate zone was significantly higher than that in other climate zones. However, the average RUE in different grassland types only varied from 0.07 to 0.09 g·m−2·mm−1. The spatial variation in RUE was more distinct in different climatic zones than in different grassland types. (3) Climate change influenced the interannual variation of ANPP and RUE, but the response of ANPP to rainfall showed a significant lag. The interannual change in RUE was negatively correlated with changes in precipitation. (4) In general, a greater area showed a significant increase rather than a decrease in ANPP on the Changtang Plateau, which meant that the grassland condition is improving. The temporal variation patterns of ANPP and RUE in different climate zones were consistent with the overall patterns on the Changtang Plateau, while the variation was not significant in different grassland types. [ABSTRACT FROM AUTHOR]