The of the Yellow River between its source and Hekou Town in Inner Mongolia is known as the Upper Yellow River Basin. It is the main source area of water resources in the Yellow River Basin, providing reliable water resources for 120 million people. Studying the hydrometeorological changes in the Upper Yellow River Basin is crucial for the development of human society. However, in the past, there has been limited research on hydrometeorological changes in the Upper Yellow River Basin. In order to clarify the four-dimensional spatiotemporal variation characteristics of hydrometeorological elements in the Upper Yellow River Basin, satellite and reanalysis hydrometeorological elements products need to be used. Unfortunately, there is currently a lack of precise evaluation studies on satellite and reanalysis hydrometeorological elements products in the Upper Yellow River Basin, and the geomorphic characteristics of this area have raised doubts about the accuracy of satellite and reanalysis hydrometeorological elements products. Thus, the evaluation study in the Upper Yellow River Basin is an important prerequisite for studying the four-dimensional spatiotemporal changes of hydrometeorological elements. When conducting evaluation study, we found that previous evaluation studies had a very confusing understanding of the spatiotemporal characteristics of datasets. Some papers even treated the spatiotemporal characteristics of evaluation metrics as the spatiotemporal characteristics of datasets. Therefore, we introduced a four-dimensional spacetime of both datasets and evaluation metrics to rectify the chaotic spatiotemporal view in the past. Our research results show that satellite and reanalysis hydrometeorological elements products have different abilities in describing the temporal and spatial distribution and change characteristics of hydrometeorological elements. The difference in the ability of satellite and reanalysis hydrometeorological elements products to describe temporal and spatial distribution and change characteristics requires us to select data at different temporal and spatial scales according to research needs when conducting hydrometeorological research, in order to ensure the credibility of the research results.

Long-term and large-scale reanalysis products of soil temperature and soil moisture are very important for understanding the hydrothermal regime in permafrost regions. However, it is necessary to evaluate the reliability of these products before using them. In this study, five in situ observed sites with different land cover types were collected to evaluate the performance of soil temperature and soil moisture in four reanalysis products from 2013 to 2014 in permafrost regions on the Qinghai-Tibetan Plateau (QTP). The four reanalysis products included three widely used products derived from the Climate Forecast System Reanalysis version 2 (CFSv2), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), and the Noah model driven by the Global Land Data Assimilation System (GLDAS-Noah), as well as a latest reanalysis product from the fifth-generation reanalysis product by the ECMWF (ERAS). The results showed that all of these products could capture temporal dynamics of soil temperature (R > 0.8) and soil moisture (R > 0.4) well. However, soil temperature was underestimated, and soil moisture was overestimated during the thawing period. The investigated results showed, those errors may mainly be caused by soil properties and forcing data. In addition, the mismatch of spatial scales between the reanalysis products and in situ observed sites, and parameterization schemes in the land surface models, such as soil thermal and hydraulic conductivity schemes, may also contributed partly causes of simulation errors. Overall, the statistical results showed that GLDAS-Noah product ranked at the top of the four products in simulating soil temperature, especially in the alpine desert, alpine swamp and alpine grassy meadow. And ERA-Interim product was superior to the other products in simulating soil moisture in permafrost regions on the QTP, especially in the alpine desert and alpine meadow. Additionally, we found that ERAS product was better than ERA-Interim product in simulating soil temperature, especially in topsoil, but it did not show superior performance in simulating soil moisture in permafrost regions of the QTP. This may be related to the different land surface models and soil texture between the two products.

Long-term and large-scale reanalysis products of soil temperature and soil moisture are very important for understanding the hydrothermal regime in permafrost regions. However, it is necessary to evaluate the reliability of these products before using them. In this study, five in situ observed sites with different land cover types were collected to evaluate the performance of soil temperature and soil moisture in four reanalysis products from 2013 to 2014 in permafrost regions on the Qinghai-Tibetan Plateau (QTP). The four reanalysis products included three widely used products derived from the Climate Forecast System Reanalysis version 2 (CFSv2), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), and the Noah model driven by the Global Land Data Assimilation System (GLDAS-Noah), as well as a latest reanalysis product from the fifth-generation reanalysis product by the ECMWF (ERAS). The results showed that all of these products could capture temporal dynamics of soil temperature (R > 0.8) and soil moisture (R > 0.4) well. However, soil temperature was underestimated, and soil moisture was overestimated during the thawing period. The investigated results showed, those errors may mainly be caused by soil properties and forcing data. In addition, the mismatch of spatial scales between the reanalysis products and in situ observed sites, and parameterization schemes in the land surface models, such as soil thermal and hydraulic conductivity schemes, may also contributed partly causes of simulation errors. Overall, the statistical results showed that GLDAS-Noah product ranked at the top of the four products in simulating soil temperature, especially in the alpine desert, alpine swamp and alpine grassy meadow. And ERA-Interim product was superior to the other products in simulating soil moisture in permafrost regions on the QTP, especially in the alpine desert and alpine meadow. Additionally, we found that ERAS product was better than ERA-Interim product in simulating soil temperature, especially in topsoil, but it did not show superior performance in simulating soil moisture in permafrost regions of the QTP. This may be related to the different land surface models and soil texture between the two products.

A change in soil temperature (ST) is a significant indicator of climate change, so understanding the variations in ST is required for studying the changes of the Qinghai-Tibet Plateau (QTP) permafrost. We investigated the performance of three reanalysis ST products at three soil depths (0-10 cm, 10-40 cm, and 40-100 cm) on the permafrost regions of the QTP: the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the second version of the National Centers for Environmental Prediction Climate Forecast System (CFSv2), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results indicate that all three reanalysis ST products underestimate observations with negative mean bias error values at all three soil layers. The MERRA-2 product performed best in the first and second soil layers, and the ERA-Interim product performed best in the third soil layer. The spatiotemporal changes of annual and seasonal STs on the QTP from 1980 to 2017 were investigated using Sen's slope estimator and the Mann-Kendall test. There was an increasing trend of ST in the deeper soil layer, which was less than that of the shallow soil layers in the spring and summer as well as annually. In contrast, the first-layer ST warming rate was significantly lower than that of the deeper soil layers in the autumn and winter. The significantly (P < 0.01) increasing trend of the annual ST indicates that the QTP has experienced climate warming during the past 38 years, which is one of the factors promoting permafrost degradation of the QTP.

Soil temperature is an important physical variable of soil and plays a key role in controlling the underground hydro-thermal processes in permafrost regions on the Qinghai-Tibetan Plateau (QTP). Daily soil temperatures were observed at five different vegetation cover sites (alpine wet meadow, alpine meadow, alpine steppe, alpine desert steppe and alpine desert) from 2012 to 2015 in permafrost regions on the QTP. The performance of three reanalysis soil temperature products (National Centers for Environmental Prediction Climate Forecast System and Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), and Global Land Data Assimilation System (GLDAS-NOAH)) at four depths (0-10, 10-40, 40-100 and 100-200 cm) was evaluated using the observation data. The results revealed that the CFSR soil temperature products had the best performance at most sites and that GLDAS-NOAH and Era-Interim had the poorest performance. However, the original CFSR soil temperature products underestimated the lowest temperatures. The calibration models for CFSR soil temperature products were established using the observed daily soil temperature from 2013 to 2015 and were validated with observed data from 2012. The results showed that the calibrated CFSv2 products were closer to the observations at different depths in the study sites. Moreover, we investigated the variations of seasonal and annual mean soil temperature from 1980 to 2015 at depths of 0-10, 10-40, 40-100 and 100-200 cm using the soil temperature calibration results. It was found that the soil temperatures at different depths all warmed fastest in spring, more slowly in winter and slowest in autumn at most sites. In addition, the average annual soil temperature exhibited significant warming trends in the permafrost regions on the QTP. The effect was largest with alpine desert steppe and smallest with alpine wet meadow, with statistically significant rates of 0.0599, 0.0468, 0.0438, 0.0282 and 0.0145 degrees C/year in alpine desert steppe, alpine desert, alpine steppe, alpine meadow and alpine wet meadow, respectively. This research provides a foundation for understanding the thermal properties of permafrost on the Qinghai-Tibetan Plateau under climate change.