Reliable and accurate temperature data acquisition is not only important for hydroclimate research but also crucial for the management of water resources and agriculture. Gridded data products (GDPs) offer an opportunity to estimate and monitor temperature indices at a range of spatiotemporal resolutions; however, their reliability must be quantified by spatiotemporal comparison against in situ records. Here, we present spatial and temporal assessments of temperature indices (T_max, T_min, T_mean, and DTR) products against the reference data during the period of 1979–2015 over Punjab Province, Pakistan. This region is considered as a center for agriculture and irrigated farming. Our study is the first spatiotemporal statistical evaluation of the performance and selection of potential GDPs over the study region and is based on statistical indicators, trend detection, and abrupt change analysis. Results revealed that the CRU temperature indices (T_max, T_min, T_mean, and DTR) outperformed the other GDPs as indicated by their higher CC and R² but lower bias and RMSE. Furthermore, trend and abrupt change analysis indicated the superior performances of the CRU T_min and T_mean products. However, the T_max and DTR products were less accurate for detecting trends and abrupt transitions in temperature. The tested GDPs as well as the reference data series indicate significant warming during the period of 1997–2001 over the study region. Differences between GDPs revealed discrepancies of 1-2°C when compared with different products within the same category and with reference data. The accuracy of all GDPs was particularly poor in the northern Punjab, where underestimates were greatest. This preliminary evaluation of the different GDPs will be useful for assessing inconsistencies and the capabilities of the products prior to their reliable utilization in hydrological and meteorological applications particularly over arid and semiarid regions.

中文翻译：

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温度数据产品的时空评估，用于检测巴基斯坦最大灌溉区的暖化趋势和突变

可靠，准确的温度数据采集不仅对水文气候研究很重要，而且对水资源和农业的管理也至关重要。网格数据产品（GDP）提供了机会，可以在一系列时空分辨率下估算和监视温度指数；但是，必须通过与原位记录进行时空比较来量化其可靠性。在这里，我们介绍温度指数的空间和时间评估（T _max，T _min，T _mean和DTR）产品与1979-2015年期间巴基斯坦旁遮普省的参考数据进行比较。该地区被认为是农业和灌溉农业的中心。我们的研究是对研究区域内潜在GDP的表现和选择进行的首次时空统计评估，它基于统计指标，趋势检测和突变分析。结果显示，CRU温度指数（T _max，T _min，T _mean和DTR）优于其他GDP，这是因为它们的CC和R ²较高，而偏差和RMSE较低。此外，趋势和突变分析表明CRU T的卓越性能_min和T_表示乘积。但是，T _max和DTR产品在检测趋势和温度突然变化时不太准确。测试的GDP以及参考数据系列表明，研究区域在1997年至2001年期间显着变暖。与同一类别内的不同产品和参考数据相比，GDP之间的差异显示出1-2°C的差异。在低估最大的旁遮普北部，所有GDP的准确性都特别差。对这些不同GDP的初步评估将有助于评估产品在水文和气象应用中（尤其是在干旱和半干旱地区）可靠使用之前的不一致性和功能。