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首页> 外文期刊>Journal of hydrometeorology >Triple collocation of summer precipitation retrievals from SEVIRI over europe with gridded rain gauge and weather radar data
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Triple collocation of summer precipitation retrievals from SEVIRI over europe with gridded rain gauge and weather radar data

机译：利用网格化的雨量计和天气雷达数据，从欧洲SEVIRI提取夏季降水的三重组合

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摘要

Quantitative information on the spatial and temporal error structures in large-scale(regional or global) precipitation datasets is essential for hydrologic and climatic studies. A powerful tool to quantify error structures in large-scale datasets is triple collocation. In this paper, triple collocation is used to determine the spatial and temporal error characteristics of three precipitation datasets over Europe-that is, the precipitationproperties visibleear infrared(PP-VNIR) retrievals from the Spinning Enhanced Visible and Infrared Imager(SEVIRI) instrument on board Meteosat Second Generation(MSG), weather radar observations from the European integrated weather radar system, and gridded rain gauge observations from the datasets of the Global Precipitation Climatology Centre(GPCC) and the European Climate Assessment and Dataset(ECA&D) project. For these datasets the spatial and temporal error characteristics are evaluated and their performance is discussed. Finally, weather radar and PP-VNIR retrievals are used to evaluate the diurnal cycles of precipitation occurrence and intensity during daylight hours for different European climate regions. The results suggest that the triple collocation method provides realistic error estimates. The spatial and temporal error structures agree with the findings of earlier studies and reveal the strengths and weaknesses of the datasets, such as inhomogeneity of weather radar practices across Europe, the effect of sampling density in the gridded rain gauge dataset, and the sensitivity to retrieval assumptions in the PP-VNIR dataset. This study can help us in developing satisfactory strategies for combining various precipitation datasets-for example, for improved monitoring of diurnal variations or for detecting temporal trends in precipitation.
机译：关于大规模（区域或全球）降水数据集的时空误差结构的定量信息对于水文和气候研究至关重要。量化大型数据集中错误结构的强大工具是三重配置。本文使用三重搭配确定欧洲三个降水数据集的时空误差特征-即从旋转增强型可见光和红外成像仪（SEVIRI）仪器中获取的降水属性可见/近红外（PP-VNIR）搭载在Meteosat第二代（MSG）上，来自欧洲集成天气雷达系统的天气雷达观测以及来自全球降水气候中心（GPCC）和欧洲气候评估与数据集（ECA＆D）项目的数据集的栅格雨量计观测。对于这些数据集，评估了空间和时间误差特征，并讨论了它们的性能。最后，天气雷达和PP-VNIR检索用于评估欧洲不同气候区域白天白天降水发生的日周期和强度。结果表明三重配置方法提供了现实的误差估计。时空误差结构与早期研究的发现一致，并揭示了数据集的优缺点，例如欧洲各地天气雷达做法的不均匀性，栅格化雨量计数据集中采样密度的影响以及对检索的敏感性PP-VNIR数据集中的假设。这项研究可以帮助我们制定令人满意的策略来组合各种降水数据集，例如，用于改进对昼夜变化的监测或检测降水的时间趋势。

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