ABSTRACT This study evaluates the 1981–2010 spatiotemporal differences in six available climate datasets (daily total precipitation and mean air temperature) over the Lower Nelson River Basin (LNRB) in ten of its sub-watersheds at seasonal and annual time scales. We find that the Australian National University spline interpolation (ANUSPLIN), and inverse distance weighted (IDW) interpolated observations from 14 Environment and Climate Change Canada (ECCC) meteorological stations show dry biases, whereas reanalysis products tend to overestimate precipitation across most of the basin. All datasets exhibit prominent disagreement in precipitation trends whereby the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and European Union Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI) show exceptional wetting trends, while the IDW and ANUSPLIN data manifest drying trends. Mean air temperature trends generally agree across most of the datasets; however, the North American Regional Reanalysis (NARR) and IDW show stronger warming relative to other datasets. Overall, analyses of the different climate datasets and their ensemble reveal that the choice of input dataset plays a crucial role in the accurate estimation of historical climatic conditions, particularly when assessing trends, for the LNRB. Using the ensemble has the distinct advantage of preserving the unique strengths of all datasets and affords the opportunity to estimate the uncertainty for hydrologic modelling and climate change impact studies.

中文翻译：

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加拿大马尼托巴省下纳尔逊河流域多个水文气候数据集的比对

摘要 本研究评估了 1981-2010 年六个可用气候数据集（每日总降水量和平均气温）在下纳尔逊河流域 (LNRB) 的 10 个子流域的季节性和年度时间尺度的时空差异。我们发现澳大利亚国立大学样条插值 (ANUSPLIN) 和来自 14 个加拿大环境和气候变化 (ECCC) 气象站的反距离加权 (IDW) 插值观测显示干偏差，而再分析产品往往高估了该盆地大部分地区的降水. 所有数据集在降水趋势方面都表现出明显的分歧，欧洲中期天气预报中心 (ECMWF) 中期再分析 (ERA-Interim) 和欧盟水和全球变化 (WATCH) 强迫数据 ERA-Interim (WFDEI) 显示出异常的润湿趋势，而 IDW 和 ANUSPLIN 数据表明干燥趋势。大多数数据集的平均气温趋势通常是一致的；然而，与其他数据集相比，北美区域再分析 (NARR) 和 IDW 显示出更强的变暖。总体而言，对不同气候数据集及其集合的分析表明，输入数据集的选择在准确估计 LNRB 的历史气候条件方面起着至关重要的作用，尤其是在评估趋势时。