Soil moisture and temperature (SM and ST) have been identified for modeling of extreme weather and hydrological processes. The coarser resolution global analyses are limited in capturing realistic heterogeneity. This study focuses on evaluating regional land surface conditions developed from a high-resolution (4 km grid spacing) land data assimilation system (HRLDAS) over India from 2000 to 2013 against in situ and global analyses. Global analyses such as the European Space Agency Climate Change Initiative (ESACCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Climate Forecasting System (CFS), and Global Land Data Assimilation System (GLDAS) have been considered to assess the credibility of the regional analysis. The regional SM from the HRLDAS is superior to global and satellite products, particularly in the orography (altitude > 300 m) regions followed by the plane regions (altitude ≤ 300 m). The probability distribution function (PDF) indicates that the regional SM and satellite analysis exhibited less error (~ 0.02 m³ m⁻³ at ~ 28%) in the plane regions. The regional SM analysis in the orography regions is reliable (0.015 m³ m⁻³ at 28% frequency) with a high equitable threat score (~ 0.6) compared to other analyses. The HRLDAS is consistently superior for soil temperature (ST) to other global analyses. The mean diurnal variation of HRLDAS-ST is close to in situ observation. The HRLDAS performs better for spatial representation of SM and ST for different months and monsoon seasons. The improved representation of land conditions from the HRLDAS could provide a realistic distribution of latent and sensible heat fluxes when compared with other global products. This study demonstrates the value of high-resolution regional analyses and recommends usefulness in hydrological applications.

已经确定了土壤湿度和温度（SM和ST），可用于模拟极端天气和水文过程。较粗分辨率的全局分析在捕获现实的异质性方面受到限制。这项研究的重点是评估2000年至2013年间印度高分辨率（4 km网格间距）土地数据同化系统（HRLDAS）开发的区域地表条件，并进行就地和全球分析。已考虑使用欧洲航天局气候变化倡议（ESACCI），中分辨率成像光谱仪（MODIS），气候预测系统（CFS）和全球土地数据同化系统（GLDAS）等全球分析来评估区域分析的可信度。HRLDAS的区域SM优于全球和卫星产品，尤其是在地形方面（海拔> 300 m）区域，然后是平面区域（海拔≤300 m）。概率分布函数（PDF）表示区域SM和卫星分析显示的误差较小（〜0.02 m在平面区域中为³  m ^-3（〜28％）。地形区域的区域SM分析是可靠的（0.015 m ³  m ^-3频率为28％），与其他分析相比，具有较高的公平威胁得分（〜0.6）。HRLDAS的土壤温度（ST）始终优于其他全局分析。HRLDAS-ST的平均日变化接近于原位观察。对于不同月份和季风季节的SM和ST的空间表示，HRLDAS表现更好。与其他全球产品相比，HRLDAS对土地状况的改进表示可以提供潜热通量和感热通量的实际分布。这项研究证明了高分辨率区域分析的价值，并建议了在水文应用中的有用性。