Soil moisture and soil temperature, reflecting a synthetic climate regime, are vitally important for climate change assessments and adaption. As historical in situ measurements of soil states are extremely scarce and spatially uneven, reanalysis products play an increasingly important role in filling these gaps. The focus of this paper is on water-heat covariations in reanalysis products and a joint evaluation of soil moisture and soil temperature in five widely used atmospheric and land reanalyses is presented using in situ observations from 25 networks during various periods from 1979 to 2017. At the network scale, the five reanalyses show statistically significant correlations with observations, and the European Centre for Medium-Range Weather Forecasts ERA5 shows higher skills than the other four products and a significant improvement over its predecessor. The National Centers for Environmental Prediction Climate Forecast System Reanalysis performs better in terms of long-term trends. The most skilful signals in the five reanalyses are the seasonal cycles, with correlation coefficients of over 0.9. However, long-term trends are substantially weaker than the observed trends and still tend to perform poorly over the high latitudes during cold seasons. Soil temperature reanalyses show even better skills, with mean correlation coefficients over 0.9 between anomalies; ERA5 shows enhanced annual ranges toward the high latitudes and altitudes. A joint evaluation of soil temperature and soil moisture showed physically consistent water-heat covariations in the soil in conjunction with atmospheric fluxes during the growing season over the Northern Hemisphere. This report suggests a good future for reanalysis products and their potential role in land surface climate change assessments.
Afforestation‐induced changes in water resources have attracted worldwide attention. However, a clear picture of quantitative attribution of terrestrial water storage (TWS) variation from hydroclimatic and anthropogenic factors is still lacking. In this study, a quantitative analysis of TWS variation was conducted in the Yellow River basin of China under the Grain for Green project with consideration of irrigation. The results showed that the TWS has decreased (increased) more and more quickly (slowly) in the Loess Plateau (headwater region). The TWS increase corresponded to increased runoff and soil moisture in the headwaters, and the TWS depletion corresponded to decreased runoff and groundwater in the Loess Plateau and downstream regions. Regarding the TWS change (TWSC), it exhibited a negative trend across the basin. The increase in evapotranspiration (ET) dominated the basin‐averaged TWSC reduction, while the increase in ET was highly related to the increases in vegetation cover and irrigation water use. For spatial TWSC variations, the value of precipitation minus ET could account for most changes in TWSC, except for those in the headwater region and a region near the internally drained area. The increased vegetation coverage, which can affect multiple hydrological processes, played an important role in these two excluded regions. Importantly, the irrigation‐induced TWSC was considerable and varied with different irrigation water sources (i.e., surface water and groundwater). Overall, the impacts of afforestation and irrigation on TWS are sufficiently important. The research in this study can provide guidance for the water resource management during revegetation efforts.
Land‐atmosphere interactions play an important role in shaping regional climate and its variability. In land‐atmosphere coupling study, a fundamental challenge is data limitation, such as the sparsity of long‐term land observations and uncertainty in individual model simulations. This study produces a multisource combined land surface data set using a Bayesian model averaging method, for the assessment of land‐atmosphere coupling across China. We employ the newly produced soil moisture and evapotranspiration, together with satellite‐derived soil moisture and observation‐based evapotranspiration to assess spatiotemporal characteristics of the coupling with observed precipitation and temperature. We also define a coupling index to identify region‐specific regimes. The results have shown that strong coupling occurs over northern China, particularly in the transition zone between dry and wet climate. Here summer coupling is dominated by land evaporative water storage. Over the southern humid regions and regions at high altitudes, land‐atmosphere coupling in summer is characterized by an energy‐limited regime. Estimated coupling strengths vary with season and variable used. Precipitation‐related couplings are generally stronger in summer; temperature‐related couplings are stronger in summer in dry areas but stronger in winter in humid areas. These findings provide a multisource combined representation and cross validation of spatial and temporal characteristics of land‐atmosphere coupling across China. The implications are that northern China is a critical region for climate change/variability impact and adaptation assessment.
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