Third Pole Research Articles

Observed changes in the climate and snow dynamics of the Third Pole

The Third Pole (TP) is the world’s largest highland and has one of the biggest reservoirs of glacier ice mass and snow cover on the Earth. Three major Asian rivers (the Indus, Ganga and Brahmaputra) are nourished by the melting of glaciers and snow in Central Himalaya, which are inevitable for the socioeconomic sustainability and water security of South Asia. Here, we investigate the long-term (1980–2020) changes in snow depth and precipitation in TP, where major precipitation occurs in the form of rainfall in summer, and snowfall in winter and spring. The seasonal mean snow depth is deep (≥1 m) in winter and shallow (≤0.2 m) in summer. The average snowmelt and snow water equivalent are higher in the central and western Himalaya and Karakoram ranges in spring, which are the regions with most glaciers in TP. There is a significant positive trend in total precipitation, about 0.01–0.03 mm d−1 yr−1 in the central and eastern TP during the South Asian Summer Monsoon for the 1980–2020 period. Snowmelt is also increasing (>0.5 × 10−3 mm yr−1) in the western Himalaya during spring, which is consistent with the temperature rise (0.04–0.06 °C yr−1) there. In addition, there is a notable increase in the annual mean glacier melt (here, the water equivalent thickness) in TP (−1 to −5 cm w.e. yr−1), with its highest values in the eastern and central Himalaya (−3 to −5 cm w.e. yr−1), as estimated for the period 2003–2020. On top of these, by the end of the 21st century, the Coupled Model Intercomparison Project Phase 6 (CMIP6) projections show that there would be a significant decrease in snow depth and an increase in temperature of TP in all shared socioeconomic pathways (SSPs). Henceforth, the increasing trend in temperature and melting of snow/glaciers in TP would be a serious threat to the regional climate, water security and livelihood of the people of South Asia.

Hydrological Projections in the Third Pole Using Artificial Intelligence and an Observation‐Constrained Cryosphere‐Hydrology Model

AbstractThe water resources of the Third Pole (TP), highly sensitive to climate change and glacier melting, significantly impact the water and food security of millions in Asia. However, projecting future spatial‐temporal runoff changes for TP's mountainous basins remains a formidable challenge. Here, we've leveraged the long short‐term memory model (LSTM) to craft a grid‐scale artificial intelligence (AI) model named LSTM‐grid. This model has enabled the production of hydrological projections for the seven major river basins of TP. The LSTM‐grid model integrates monthly precipitation, air temperature, and total glacier mass changes (total_GMC) data at a 0.25‐degree model grid. Training the LSTM‐grid model employed gridded historical monthly runoff and evapotranspiration data sets generated by an observation‐constrained cryosphere‐hydrology model at the headwaters of seven TP river basins during 2000–2017. Our results demonstrate the LSTM grid's effectiveness and usefulness, exhibiting a Nash‐Sutcliffe Efficiency coefficient exceeding 0.92 during the verification periods (2013–2017). Moreover, river basins in the monsoon region exhibited a higher rate of runoff increase compared to those in the westerlies region. Intra‐annual projections indicated notable increases in spring runoff, especially in basins where glacier meltwater significantly contributes to runoff. Additionally, the LSTM‐grid model aptly captures the runoff changes before and after the turning points of glacier melting, highlighting the growing influence of precipitation on runoff after reaching the maximum total_GMC. Therefore, the LSTM‐grid model offers a fresh perspective for understanding the spatiotemporal distribution of water resources in high‐mountain glacial regions by tapping into AI's potential to drive scientific discovery and provide reliable data.

Regional sources of NH3, SO2 and CO in the Third Pole

The Third Pole (TP) is a high mountain region in the world, and is well-known for its pristine environment, but recent development activities in the region have degraded its air quality. Here, we investigate the spatial and temporal changes of the air pollutants ammonia (NH₃), sulphur dioxide (SO₂) and carbon monoxide (CO) in TP, and reveal their sources using satellite measurements and emission inventory. We observe a clear seasonal cycle of NH3 in TP, with high values in summer and low values in winter. The intense agriculture activities in the southern TP are the cause of high NH₃ (6–8 × 1016 molec./cm2) there. Similarly, CO shows a distinct seasonal cycle with high values in spring in the southeast TP due to biomass burning. In addition, the eastern boundary of TP in the Sichuan and Qinghai provinces also show high values of CO (about 1.5 × 1018 mol/cm2), primarily owing to the industrial activities. There is no seasonal cycle found for SO₂ distribution in TP, but relatively high values (8–10 mg/m2) are observed in its eastern boundary. The high-altitude pristine regions of inner TP are also getting polluted because of increased human activities in and around TP, as we estimate positive trends in CO (0.5–1.5 × 1016 mol/cm2/yr) there. In addition, positive trends are also found in NH₃ (0.025 × 1016 molec./cm2/yr) during 2008–2020 in most regions of TP and SO₂ (about 0.25–0.75 mg/m2/yr) in the Sichuan and Qinghai region during 2000–2020. As revealed by the emission inventory, there are high anthropogenic emissions of NH3, SO2 and CO within TP. There are emissions of pollutants from energy sectors, oil and refinery, agriculture waste burning and manure management within TP. These anthropogenic activities accelerate the ongoing development in TP, but severely erode its environment.

Different maximum precipitation altitudes and precipitation gradient characteristics of different basins in the Third Pole region

Investigation of maximum precipitation altitude (MPA) and precipitation gradients supports the understanding of vertical precipitation distribution in the mountains and obtaining accurate areal precipitation datasets. This study provided the MPAs and precipitation gradients of 524 subbasins based on Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and discussed the dominant factors for the spatial pattern of MPAs and precipitation gradients. The results show that the MPAs across all subbasins in the Third Pole (TP) have noticeable seasonal variation, with the highest mean MPAs in winter (3803.2 m) and lowest mean MPAs in summer (3646.8 m). At the spatial scale, the MPAs are located at lower altitudes in the Himalayas, western Kunlun and Hengduan Mountains (<1500 m); in the Tienshan Mountains and Pamir, the MPAs mainly lie at middle altitudes (2000–3500 m); and in the interior of the TP, Tanggula Mountains and Karakoram Mountains, the MPAs exist at higher altitudes (>4500 m). Additionally, the precipitation gradients had different characteristics above and below the MPAs. Below the MPAs, there is a positive annual mean precipitation gradient of 11.35 mm/100 m, and the larger positive precipitation gradients are mainly located in the Himalayas, Hengduan Mountains, and western Kunlun. Above the MPAs, there is a negative annual mean precipitation gradient of − 8.61 mm/100 m, and smaller negative precipitation gradients are mainly located in the Himalayas and western Tienshan Mountains. Further discussions indicated that MPAs and precipitation gradients have a positive correlation with wind speed but a negative correlation with water vapor flux, the angle between wind direction and the aspect of mountains (AWA). The maximum effect of wind and topography on precipitation occurs when the AWA is close to 0, and the precipitation gradients are the largest.

A gradual increase of aerosol pollution in the Third Pole during the past four decades: Implication for regional climate change

We analyse the long-term (1980–2020) changes in aerosols over the Third Pole (TP) and assess the changes in radiative forcing (RF) using satellite, ground-based and reanalysis data. The annual mean aerosol optical depth (AOD) varies from 0.06 to 0.24, with the highest values of around 0.2 in the north and southwest TP, which are dominated by dust from Taklimakan and Thar deserts, respectively. However, Organic Carbon (OC), Black Carbon (BC) and sulphate aerosols have significant contributions to the total AOD in the south and east TP. High amounts of dust are observed in spring and summer, but BC in winter. Trajectory analysis reveals that the air mass originated from East and South Asia carries BC and OC, whereas the air from South Asia, Central Asia and Middle East brings dust to TP. Significant positive trends in AOD is found in TP, with high values of about 0.002/yr in the eastern and southern TP. There is a gradual increase in BC and OC concentrations during 1980–2020, but the change from 2000 is phenomenal. The RF at the top of the atmosphere varies from -10 to 2 W/m2 in TP, and high positive RF of about 2 W/m2 is estimated in Pamir, Karakoram and Nyainquentanglha mountains, where the massive glacier mass exists. The RF has increased in much of TP during recent decades (2001–2020) with respect to previous decades (1981–2000), which can be due to the rise in BC and dust during the latter period. Therefore, the positive trend in BC and its associated change in RF can amplify the regional warming, and thus, the melting of glaciers or ice in TP. This is a great concern as it is directly connected to the water security of many South Asian countries.

Quantifying the snowfall variations in the Third Pole region from 1980 to 2020

Snowfall is critical in the mountainous cryosphere cycle and is vulnerable to climate change. Due to data-scarcity and strong surface heterogeneity, its information is not sufficiently revealed across the Third Pole (TP) under warming. Accordingly, this study investigated the spatiotemporal variability of snowfall and its entropy information across the TP from 1980 to 2020 based on a new high-accuracy snowfall dataset (TPHiS), which was estimated from a long-term high-resolution precipitation dataset for the TP (TPHiPr) and High Asia Refined analysis version 2 reanalysis data (HARv2) using a threshold temperature method. The results indicated that the correlation coefficient, mean bias, and root-mean-square error of the daily TPHiS were 0.77, 0.03 mm/daily, and 0.18 mm/daily, respectively, compared against in-situ observation, illustrating that this dataset performs better than other snowfall datasets. The annual mean snowfall measured 259.38 mm across the TP and experienced a slight negative trend (−0.77 mm/decade, p > 0.05). A significantly positive trend in annual snowfall was observed in the intersection of the West Kunlun, Karakoram, and Western Inner Tibet, with elevations over 5500 m. In contrast, a significantly negative trend prevailed in the Pamir, Hengduan Shan, and West and Central Himalaya intersections, especially at elevations varied from 3000 to 4500 m. Compared with other seasons, a significantly negative trend in snowfall was observed in summer (−1.94 mm/decade, p < 0.05). Change in snowfall frequency entropy was more significant than that in snowfall amount entropy. A significantly positive trend in light snowfall frequency dominated the augmentation in snowfall frequency, causing a negative trend in snowfall frequency entropy, while a substantial reduction in snowfall frequency associated with the decline in light snowfall frequency induced a positive trend in snowfall frequency entropy. The outcomes provide a finer snowfall dataset for regional cryospheric research and might inform sustainable water resource management in alpines.

Trends and variability of total column ozone in the Third Pole

The Hindu Kush Himalaya and Tien Shan Mountain regions together are called the Third Pole (TP) of Earth, which encompasses ecologically fragile regions of 12 Asian countries. It is the highest mountain chain with the largest reserve of fresh ice mass on the planet outside the northern and southern polar regions. The TP region is experiencing high rate of glacier melting due to climate change for the past few decades, and is a great concern for water security of South Asia. Since changes in ozone concentrations in the atmosphere affect public health, ecosystem dynamics and climate, it is imperative to monitor its temporal evolution in an ecologically sensitive region such as TP. Here, the spatiotemporal characteristics of total column ozone (TCO) in TP and 20 selected cities in and around TP are investigated using a combined long-term data made from the satellite measurements of Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME)-2B for the period 2005–2020. The spatial trends in TCO over TP are mostly negative in summer and autumn (from −0.2 DU/yr to −0.6 DU/yr), but positive in winter (up to +0.2 DU/yr). Among the selected 20 urban regions, the highest annual trend −0.42 ± 0.3 DU/yr and the lowest −0.01 ± 0.2 DU/yr are estimated in Xining and Chittagong, respectively. Analysis using a multiple regression model reveals that the ozone variability in TP is mostly driven by tropopause height with a contribution of 24.92%, Quasi-Biennial Oscillation (23.42%), aerosols (16.12%) and solar flux (15.34%). Our study suggests that the observed negative trend is mainly associated with human activities and climate change in TP, which would likely to enhance the surface temperature and thus, melting of glaciers in the region.

TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations

Abstract. Reliable precipitation data are highly necessary for geoscience research in the Third Pole (TP) region but still lacking, due to the complex terrain and high spatial variability of precipitation here. Accordingly, this study produces a long-term (1979–2020) high-resolution (1/30∘, daily) precipitation dataset (TPHiPr) for the TP by merging the atmospheric simulation-based ERA5_CNN with gauge observations from more than 9000 rain gauges, using the climatologically aided interpolation and random forest methods. Validation shows that TPHiPr is generally unbiased and has a root mean square error of 5.0 mm d−1, a correlation of 0.76 and a critical success index of 0.61 with respect to 197 independent rain gauges in the TP, demonstrating that this dataset is remarkably better than the widely used datasets, including the latest generation of reanalysis (ERA5-Land), the state-of-the-art satellite-based dataset (IMERG) and the multi-source merging datasets (MSWEP v2 and AERA5-Asia). Moreover, TPHiPr can better detect precipitation extremes compared with these widely used datasets. Overall, this study provides a new precipitation dataset with high accuracy for the TP, which may have broad applications in meteorological, hydrological and ecological studies. The produced dataset can be accessed via https://doi.org/10.11888/Atmos.tpdc.272763 (Yang and Jiang, 2022).

Towards Ensemble-Based Kilometer-Scale Climate Simulations over the Third Pole Region

The Tibetan Plateau and its surrounding mountains have an average elevation of 4,400 m and a glaciated area of $$\sim $$ 100,000 $$\hbox {km}^{2}$$ giving it the name “Third Pole (TP) region”. The TP is the headwater of many major rivers in Asia that provide fresh water to hundreds of millions of people. Climate change is altering the energy and water cycle of the TP at a record pace but the future of this region is highly uncertain due to major challenges in simulating weather and climate processes in this complex area. The Convection-Permitting Third Pole (CPTP) project is a Coordinated Regional Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) that aims to revolutionize our understanding of climate change impacts on the TP through ensemble-based, kilometer-scale climate modeling. Here we present the experimental design and first results from multi-model, multi-physics ensemble simulations of three case studies. The five participating modeling systems show high performance across a range of meteorological situations and are close to having ”observational quality” in simulating precipitation and near-surface temperature. This is partly due to the large differences between observational datasets in this region, which are the leading source of uncertainty in model evaluations. However, a systematic cold bias above 2000 m exists in most modeling systems. Model physics sensitivity tests performed with the Weather Research and Forecasting (WRF) model show that planetary boundary layer (PBL) physics and microphysics contribute equally to model uncertainties. Additionally, larger domains result in better model performance. We conclude by describing high-priority research needs and the next steps in the CPTP project.

Corrected ERA5 Precipitation by Machine Learning Significantly Improved Flow Simulations for the Third Pole Basins

Abstract Precipitation is one of the most important atmospheric inputs to hydrological models. However, existing precipitation datasets for the Third Pole (TP) basins show large discrepancies in precipitation magnitudes and spatiotemporal patterns, which poses a great challenge to hydrological simulations in the TP basins. In this study, a gridded (10 km × 10 km) daily precipitation dataset is constructed through a random-forest-based machine learning algorithm (RF algorithm) correction of the ERA5 precipitation estimates based on 940 gauges in 11 upper basins of TP for 1951–2020. The dataset is evaluated by gauge observations at point scale and is inversely evaluated by the Variable Infiltration Capacity (VIC) hydrological model linked with a glacier melt algorithm (VIC-Glacier). The corrected ERA5 (ERA5_cor) agrees well with gauge observations after eliminating the severe overestimation in the original ERA5 precipitation. The corrections greatly reduce the original ERA5 precipitation estimates by 10%–50% in 11 basins of the TP and present more details on precipitation spatial variability. The inverse hydrological model evaluation demonstrates the accuracy and rationality, and we provide an updated estimate of runoff components contribution to total runoff in seven upper basins in the TP based on the VIC-Glacier model simulations with the ERA5_cor precipitation. This study provides good precipitation estimates with high spatiotemporal resolution for 11 upper basins in the TP, which are expected to facilitate the hydrological modeling and prediction studies in this high mountainous region. Significance Statement The Third Pole (TP) is the source of water to the people living in the areas downstream. Precipitation is the key driver of the terrestrial hydrological cycle and the most important atmospheric input to land surface hydrological models. However, none of the current precipitation data are equally good for all the TP basins because of high variabilities in their magnitudes and spatiotemporal patterns, posing a great challenge to the hydrological simulation. Therefore, in this study, a gridded daily precipitation dataset (10 km × 10 km) is reconstructed through a random-forest-based machine learning algorithm correction of ERA5 precipitation estimates based on 940 gauges in 11 TP basins for 1951–2020. The data eliminate the severe overestimation of original ERA5 precipitation estimates and present more reasonable spatial variability, and also exhibit a high potential for hydrological application in the TP basins. This study provides long-term precipitation data for climate and hydrological studies and a reference for deriving precipitation in high mountainous regions with complex terrain and limited observations.

Westerly drives long-distance transport of radionuclides from nuclear events to glaciers in the Third Pole

Major nuclear bomb tests and nuclear power plant incidents release large amounts of radionuclides. This study investigates beta (β) activities of radionuclides from four ice cores in the Third Pole (TP) to understand the transport routes and related atmospheric processes affecting the radionuclides deposition in glaciers of the region. All the ice cores show three major β activity peaks in the ice layers corresponding to 1963, 1986, and 2011. The β activity peak in the 1963 ice layer is referred to as the well-known 1962 Nuclear Bomb Test. Beta activity peaks in 1986 and 2011 ice layers from the Chernobyl and Fukushima Nuclear Incidents (CNI, FNI). Hysplit forward and backward trajectory analyses suggest that the radionuclides were transported by the westerly into the stratosphere and then to the high elevation TP glaciers. In the FNI case, the radionuclides traveled over Japan, the Pacific Ocean, Europe, and central Asia before being deposited in the TP glaciers. Investigations of the atmospheric circulation confirm that the stronger northern branch of westerly is responsible for high radionuclides during the FNI in the TP. Less precipitation with water vapor flux component divergence after the FNI also contributed to the enriched radionuclides.

Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset

Abstract. Altitudinal precipitation gradient plays an important role in the interpolation of precipitation in the Third Pole (TP) region, where the topography is very complex but in situ data are very sparse. This study proves that the altitude dependence of precipitation in the TP can be reasonably reproduced by a high-resolution atmospheric simulation-based dataset called ERA5_CNN. The precipitation gradients, including both absolute (APGs) and relative gradients (RPGs), for 388 sub-basins of the TP above 2500 m a.s.l. are calculated based on the ERA5_CNN. Results show that most sub-basins have positive precipitation gradients, and negative gradients are mainly found along the Himalayas, the Hengduan Mountains and the western Kunlun. The annual APG and RPG averaged across all sub-basins of the TP are 0.05 mm d−1 × 100 m−1 and 4.25 % × 100 m−1, respectively. The values of the APG are large in wet seasons but small in dry seasons, while the RPG shows opposite variations. Further analyses demonstrate that the RPGs have negative correlations with relative humidity but positive correlations with wind speed, likely because dry air tends to reach saturation at high altitudes, while stronger wind can bring more humid air to high altitudes. In addition, we find that precipitation gradients tend to be positive at small spatial scales compared to those at large scales, mainly because local topography plays a vital role in determining precipitation distribution at small scales. These findings on the spatiotemporal variations of precipitation gradients provide useful information for interpolating precipitation in the TP region.

Flood Seasonality Over the Third Pole Region Modulated by Upper Level Moisture Transport

AbstractThe nexus between atmospheric moisture transport and basin‐scale flood response is still lacking over the Third Pole (TP) region, despite projected increases in extreme rainfall under a changing climate. Based on long‐term daily streamflow observations, we show that peaks‐over‐threshold floods over the Yarlung Zangbo River (YZR) basin show two temporal clusters, that is, July and late August, with the flood magnitudes of the second cluster larger than the first by 20%. These floods are resultant from a mixture of flood‐producing storms with contrasting storm motion and moisture transport pathways. A suite of coupled atmospheric‐hydrological modeling experiments further quantify the impacts of different moisture transport pathways on the space‐time rainfall structure and flood response. A 50% reduction of upper level moisture transport (i.e., through the upslope of the Himalayas) leads to decreased flood peak magnitudes by 30% at the basin outlet for the August 1998 floods over the YZR basin. Upper‐level moisture transport is associated with the notable low pressure over the central‐east India and westward extension of West Pacific Subtropical High that enhances convergence of water vapor fluxes from Bay of Bengal toward TP. The magnitude of impact can potentially alter the seasonal clustering of high‐flow events over TP. Our analyses contribute to improved characterization of flood risk over TP, and advances in flood frequency hydrology.

Contrasting Fate of Western Third Pole's Water Resources Under 21st Century Climate Change

AbstractSeasonal melting of glaciers and snow from the western Third Pole (TP) plays important role in sustaining water supplies downstream. However, the future water availability of the region, and even today's runoff regime, are both hotly debated and inadequately quantified. Here, we characterize the contemporary flow regimes and systematically assess the future evolution of total water availability, seasonal shifts, and dry and wet discharge extremes in four most meltwater‐dominated basins in the western TP, by using a process‐based, well‐established glacier‐hydrology model, well‐constrained historical reference climate data, and the ensemble of 22 global climate models with an advanced statistical downscaling and bias correction technique. We show that these basins face sharply diverging water futures under 21st century climate change. In RCP scenarios 4.5 and 8.5, increased precipitation and glacier runoff in the Upper Indus and Yarkant basins more than compensate for decreased winter snow accumulation, boosting annual and summer water availability through the end of the century. In contrast, the Amu and Syr Darya basins will become more reliant on rainfall runoff as glacier ice and seasonal snow decline. Syr Darya summer river‐flows, already low, will fall by 16%–30% by end‐of‐century, and striking increases in peak flood discharge (by &gt;60%), drought duration (by &gt;1 month) and drought intensity (by factor 4.6) will compound the considerable water‐sharing challenges on this major transboundary river.

Evaluation of Climate in CMIP6 Models over Two Third Pole Subregions with Contrasting Circulation Systems

AbstractReliable simulations of historical and future climate are critical to assessing ecological and hydrological responses over the Third Pole (TP). In this study, we evaluate the historical and future temperature and precipitation simulations of 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in southeastern TP (SETP) and the upstream of the Amu Darya and Syr Darya (UAS) regions, two typical TP subregions dominated by the Indian summer monsoon system and westerlies, respectively. Comparison against station observations suggests that CMIP6 models generally capture the intra-annual variability and spatial pattern of historical climate over both subregions. However, the wetting and cold biases observed in CMIP5 still persist in CMIP6; annual temperature is underestimated by most models and annual precipitation is overestimated by all models. Multi-model average cold biases in SETP and UAS are 1.18°C and 0.32°C, respectively, and wet biases in SETP and UAS are 119% and 46%, respectively. We further analyze climate projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Both SETP and UAS subregions are projected to experience significant warming in 2015–2100, with warming trends 34%–42% and 40%–50% higher than the global trend, respectively. Model projections suggest that the warming trend will slow down under SSP1-2.6 and SSP2-4.5 but further intensify under SSP5-8.5 in 2050–2100. Monsoon-dominated SETP is projected to experience a significant wetting trend stronger than UAS over the entire future period, especially in summer (cf. winter in westerlies-dominated UAS). Concurrently, a significant drying trend in summer is found in UAS during 2050–2100 under SSP5-8.5, suggesting the intensified uneven distributions of seasonal precipitation based on projections.

Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias &lt; 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

TP-River: Monitoring and Quantifying Total River Runoff from the Third Pole

AbstractMonitoring changes in river runoff at the Third Pole (TP) is important because rivers in this region support millions of inhabitants in Asia and are very sensitive to climate change. Under the influence of climate change and intensified cryospheric melt, river runoff has changed markedly at the TP, with significant effects on the spatial and temporal water resource distribution that threaten water supply and food security for people living downstream. Despite some in situ observations and discharge estimates from state-of-the-art remote sensing technology, the total river runoff (TRR) for the TP has never been reliably quantified, and its response to climate change remains unclear. As part of the Chinese Academy of Sciences’ “Pan-Third Pole Environment Study for a Green Silk Road,” the TP-River project aims to construct a comprehensive runoff observation network at mountain outlets (where rivers leave the mountains and enter the plains) for 13 major rivers in the TP region, thereby enabling TRR to be accurately quantified. The project also integrates discharge estimates from remote sensing and cryosphere–hydrology modeling to investigate long-term changes in TRR and the relationship between the TRR variations and westerly/monsoon. Based on recent efforts, the project provides the first estimate (656 ± 23 billion m3) of annual TRR for the 13 TP rivers in 2018. The annual river runoff at the mountain outlets varies widely between the different TP rivers, ranging from 2 to 176 billion m3, with higher values mainly corresponding to rivers in the Indian monsoon domain, rather than in the westerly domain.

Pristine atmospheric condition over the Third Pole: An insight from levoglucosan records

Expanding urbanization and agricultural intensification across neighboring South Asia and East Asia have substantially threatened atmospheric condition over the Third Pole (TP) during the past few decades. Whether the atmospheric condition over the TP is still as clean as a representative of the regional background draws great concern. In this work, great differences in levoglucosan concentration within/above the atmospheric boundary layer height are revealed. Levoglucosan results support the hypothesis that atmospheric pollutants in the mid-troposphere over the TP are mainly affected by long-range transport, although there are some local biomass burning emissions in residential areas. In addition, levoglucosan concentration in the mid-troposphere over the TP is at the same magnitude as marine and polar regions, but about 2–3 magnitudes lower than neighboring densely-populated Asian regions. With insights of levoglucosan records, this work therefore proves that the high-altitude TP still has largely pristine atmospheric conditions, and is one of the cleanest remote regions on the Earth.

A Complete Isotope (δ15N, δ18O, Δ17O) Investigation of Atmospherically Deposited Nitrate in Glacial‐Hydrologic Systems Across the Third Pole Region

AbstractThe Himalayas and Tibetan Plateau, identified as the Third Pole (TP), is a unique region because of its insertion into global environmental and climatic changes. Deposition of atmospheric nitrate in this region is one of the most important sources of reactive nitrogen to glacial‐hydrologic system and ecosystems. The isotopic composition of atmospherically deposited nitrate preserved in ice bodies plays a central role in delineating environmental and climatic changes, present, and past. Here, we provide an overview of the complete isotopic compositions (δ15N, δ18O, and Δ17O) of nitrate in aerosol, snow, ice, and water samples (n = 46) collected across the Southern, Southeastern, Central, and Northern TP to constrain complex nitrogen cycles of the atmosphere, cryosphere, hydrosphere, and, potentially, the biosphere. A large variability of snow nitrate isotopic compositions is observed across the TP at different spatial scales (from a single glacier to the entire plateau), likely due to the complex landscape and relevant physical and chemical processes across the TP. Large nitrate Δ17O values are observed in water samples collected from the Mt. Everest region, highlighting the considerable fraction (up to 45%) of atmospheric nitrate to the nitrate load in this Himalayan hydrologic system. Our work reveals the complex chemical, depositional, and postdepositional processes over the TP that are greater than previously thought and identifies further comprehensive investigations, which entail using nitrate isotopic compositions as an identifier for nitrate source apportionment in various ecosystems and understanding past atmospheric and climatic conditions in this region.

Contrasting precipitation gradient characteristics between westerlies and monsoon dominated upstream river basins in the Third Pole

Based on precipitation observations from 256 gauges in the westerly and monsoon dominated upstream river basins of the Third Pole (TP), this study determined the relationships between precipitation and elevation. The basins include the upper basins of the Yangtze, Yellow, Lancang, Nujiang, Yarlung Zangbo, Yarkant, Indus, Amu Darya, and Syr Darya. Using the ERA5 data, this work examined the possible reasons for the difference in the characteristics of precipitation gradient, i.e. analyzing the relationships between the total column water vapor (TCWV), convective available potential energy (CAPE), lifting condensation level (LCL) and elevation, respectively. The feasibility of orographic corrections of precipitation data or observation is validated with the improved VIC land surface hydrological model in two mountain basins in the TP. Mean annual precipitation from gauges generally show decreasing trends (17–128 mm/100 m) with increased elevation (2500–5500 m a.s. l.) in the monsoon dominated basins, i.e. upper Yangtze, Yellow, Lancang, Nujiang, and Yarlung Zangbo, while the orographic enhancements are observed at relatively smaller scales, such as, in the very source regions of the upper Lancang and Nujiang, and Rikaze sub-basin with areas of 11000−67740 km2. On the other hand, in the westerly dominated basins, mean annual precipitation tends to increase with elevation (5–64 mm/ 100 m) in the upper Yarkant, Indus, Amu Darya, and Syr Darya. The precipitation estimates from ERA5 show a good correspondence with the gauge data ( R =0.6−0.9, P