TPRD3km: An observation-constrained high-resolution runoff data for Third Pole transboundary rivers

The 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.

The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP’s precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies’ preparation for future environmental challenges. Some key issues for future TP studies are also discussed.

The 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.

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

The Third Pole (TP) region, encompassing the Tibetan Plateau and surrounding alpine ecosystems, experiences significant anthropogenic impacts despite its remote nature. Long-range atmospheric transport (LRAT) and local emissions introduce both commercially produced chemicals and unintentionally released contaminants into this vulnerable region. Among these chemicals, many organic pollutants have not been extensively monitored in the TP, yet pose potential risks to human health and the environment, thus constituting an emerging concern for the region. These substances are known as emerging organic contaminants (EOCs). The TP serves as a unique model for studying pollutant migration and fate. Research on EOCs in this region not only confirms the LRAT behaviors of these compounds but also enhances our understanding of their environmental interactions, providing a scientific basis for effective pollutant regulation. Here, we offer an up-to-date summary of the distributions of EOCs across various environmental matrices and biota within the TP. This review aims to illustrate their potential sources, transport pathways, environmental fate, as well as ecological and human risks they pose in this sentinel region. We emphasize that EOCs are transported from surrounding source regions to the TP via LRAT, with deposition significantly heightened by concurrent cold trapping and forest filter effects. Furthermore, the intensification of local anthropogenic activities, coupled with the rerelease of both EOCs and legacy POPs under the impacts of global warming, exacerbates their impact on TP ecosystems. Finally, we propose several key research priorities for the future, highlighting the need for long-term multimedia monitoring to elucidate distribution patterns, origins, and transport pathways of EOCs. We call for enhanced regional and international research programs to better understand the various biogeochemical and geophysical processes influenced by climate change and anthropogenic pressures.

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.

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.

The scarcity of in situ observation stations and the unreliability of long-term satellite data necessitate the use of reanalysis datasets to study elevation-dependent climate change (EDCC) in the third pole (TP) region. We analyzed elevation-dependent temperature and precipitation patterns over TP using the ECMWF Atmospheric Reanalysis Fifth Generation (ERA5), a global reanalysis product with coarse resolution, along with three high-resolution regional reanalysis datasets that cover our study domain: Indian Monsoon Data Assimilation and Analysis (IMDAA), High Asia Refined Analysis—Version 2 (HAR-v2), and Tibetan Plateau Regional Reanalysis (TPRR). Comparing the performance of the four reanalysis datasets in capturing EDCC over TP is crucial, as these datasets provide spatially and temporally consistent data at an optimum resolution that greatly aids EDCC research. Our study results reveal the following: (1) A positive elevation-dependent warming trend is observed across all four datasets in winter and autumn, with varying magnitudes of warming across the datasets. (2) All four datasets exhibit positive elevation-dependent wetting trends in all seasons, except autumn. These are primarily driven by pronounced drying trends at lower elevations and relatively minimal changes in precipitation trends at higher elevations. (3) ERA5 and IMDAA exhibit similar results in capturing elevation-dependent climate change, whereas the TPRR dataset reveals more extreme and unique features in temperature trends compared to the other three datasets. HAR-v2 shows smaller variations in temperature and precipitation trends across different elevations and seasons, in contrast to the other three datasets. While all reanalysis datasets indicate EDCC in the TP, their varying degrees of seasonal and spatial differences underscore the need for a careful evaluation before using them as reference data. Comparison of reanalysis datasets with available observational records, such as in situ measurements and satellite data, over overlapping spatial and temporal domains is essential to assess their quality. This evaluation can help identify the most suitable reanalysis dataset, or combination of datasets, to serve as reliable a reference even in regions or periods without observational data.

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.

Vegetation fires release a large fraction of light-absorbing components, which can contribute to the melting of snowpack and alpine glaciers. However, the relationship between variability in fire emissions and alpine glacier melting on the Third Pole (TP) remains poorly understood. This study provides evidence that carbon emissions from windward vegetation fires play a crucial role in comprehending glacier melting on the TP, particularly during the months of intense vegetation fires from March to May for monsoon-dominated glaciers and from June to October for westerlies-dominated glaciers. Furthermore, robust positive correlations (with p < 0.05) have been observed since 1997 across the TP between variations in glacier melting and fire carbon emissions during both annual periods and those intense fire months. In addition to climate warming, intensified fire carbon emissions could potentially accelerate the melting and mass loss of TP glaciers, especially during those traditionally nonmelting months. An urgent reassessment of the impact of fire carbon emissions on changes in TP glaciers is necessary, given that meltwater during traditionally nonmelting months can reshape freshwater resource supply patterns, and the projected increased wildfire risk in high mountainous regions in a rapidly warming climate.

Conventional calibration methods used in hydrological modelling are based on runoff observations at the basin outlet. However, calibration with only runoff often produces reasonable runoff but poor results for other hydrological variables. Multi-variable calibration with both runoff and remote sensing-based evapotranspiration (ET) is developed naturally, due to the importance of ET and its data availability. This study compares two main calibration schemes: (1) calibration with only runoff (Scheme I) and (2) multi-variable calibration with both runoff and remote sensing-based ET (Scheme II). ET data are obtained from three remote sensing-based ET datasets, namely Penman–Monteith–Leuning (PML), FLUXCOM, and the Global Land Evaporation Amsterdam Model (GLEAM). The aforementioned calibration schemes are applied to calibrate the parameters of the Distributed Hydrology Soil Vegetation Model (DHSVM) through ε-dominance non-dominated sorted genetic algorithm II (ε-NSGAII). The results show that all three ET datasets have good performance for areal ET in the study area. The DHSVM model calibrated based on Scheme I produces acceptable performance in runoff simulation (Kling–Gupta Efficiency, KGE = 0.87), but not for ET simulation (KGE &lt; 0.7). However, reasonable simulations can be achieved for both variables based on Scheme II. The KGE value of runoff simulation can reach 0.87(0.91), 0.72(0.85), and 0.75(0.86) in the calibration (validation) period based on Scheme II (PML), Scheme II (FLUXCOM), and Scheme II (GLEAM), respectively. Simultaneously, ET simulations are greatly improved both in the calibration and validation periods. Furthermore, incorporating ET data into all three Scheme II variants is able to improve the performance of extreme flow simulations (including extreme low flow and high flow). Based on the improvement of the three datasets in extreme flow simulations, PML can be utilized for multi-variable calibration in drought forecasting, and FLUXCOM and GLEAM are good choices for flood forecasting.

Carbon dynamics shift in changing cryosphere and hydrosphere of the Third Pole

The 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.

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.

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.