Jahn Sally, Gaythorpe Katy A M, Wainwright Caroline M, Ferguson Neil M
MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London UK.
University of Leeds Leeds UK.
Geohealth. 2025 Jun 18;9(6):e2024GH001260. doi: 10.1029/2024GH001260. eCollection 2025 Jun.
Globally gridded precipitation products (GGPPs) are commonly used in impact assessments as substitutes for weather station data, each with unique strengths and limitations. Reanalysis products are among the most widely used for driving impact models, evaluating climate models, or bias-correcting and downscaling model outputs to generate climate change projections. However, they are often outperformed in accuracy by other GGPPs, particularly in tropical regions, including areas of the Global South. Therefore, we assessed the utility and suitability of GGPPs for climate and health research by examining how differences and uncertainties in these products affect area-level precipitation estimates, often used in health studies when epidemiological data are linked to administrative units. We compared reanalysis (ERA5/-Land) with satellite-based (CHIRPS, PERSIANN-CDR) and interpolated gauge-based products (CRUTS, GPCC), each a viable candidate to serve as reference climatology in climate change impact assessments. We focused on seasonal patterns, disease-related bioclimatic variables, and climate change-relevant indices, such as the number of wet or dry periods. Our findings revealed substantial variation in the accuracy of local precipitation estimates across GGPPs, with differences in maximum pixel precipitation values exceeding 75% between ERA5-Land and CHIRPS. These differences in GGPPs translated into area-level precipitation and, consequently, in vector carrying capacity estimates, demonstrating their impact on health assessments. Our analysis focused on Brazil and Colombia, two diverse countries differing for example, in orography, climate, and size. Each product was evaluated against national station data. Our results indicate that estimating tropical precipitation is particularly challenging for reanalysis, while CHIRPS demonstrated the best overall performance.
全球网格化降水产品（GGPPs）通常在影响评估中用作气象站数据的替代品，每种产品都有独特的优势和局限性。再分析产品是驱动影响模型、评估气候模型或对模型输出进行偏差校正和降尺度以生成气候变化预测时使用最广泛的产品之一。然而，它们在准确性方面往往不如其他GGPPs，特别是在热带地区，包括全球南方地区。因此，我们通过研究这些产品中的差异和不确定性如何影响区域层面的降水估计来评估GGPPs在气候和健康研究中的实用性和适用性，当流行病学数据与行政单位相关联时，区域层面的降水估计常用于健康研究。我们将再分析产品（ERA5/-Land）与基于卫星的产品（CHIRPS、PERSIANN-CDR）以及基于雨量计插值的产品（CRUTS、GPCC）进行了比较，每一种都是气候变化影响评估中作为参考气候学的可行候选产品。我们重点关注季节模式、与疾病相关的生物气候变量以及与气候变化相关的指数，如湿润或干燥期的数量。我们的研究结果表明，不同GGPPs在局部降水估计的准确性上存在很大差异，ERA5-Land和CHIRPS之间最大像素降水量值的差异超过75%。GGPPs中的这些差异转化为区域层面的降水，进而转化为病媒传播能力估计值，证明了它们对健康评估的影响。我们的分析重点是巴西和哥伦比亚这两个不同的国家，例如在地形、气候和面积方面存在差异。每种产品都根据国家气象站数据进行了评估。我们的结果表明，对再分析来说，估算热带地区的降水特别具有挑战性，而CHIRPS总体表现最佳。
