自 1961 年以来奥地利的日照网格--将观测站和卫星观测结合起来,建立一个多十年期气候监测数据集

IF 2.8 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Johann Hiebl, Quentin Bourgeois, Anna-Maria Tilg, Christoph Frei
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引用次数: 0

摘要

区域气候学和环境变化中的定量应用(如干旱和冰雪覆盖建模、数值模式中的云评估、太阳能潜力绘图)需要高空间分辨率和长达数十年的日照时间网格数据集。我们展示了一个新的网格数据集,该数据集以 1 公里的网格间距计算奥地利的相对(和衍生的绝对)日照时间,并以日时间分辨率追溯到 1961 年。数据集构建过程中遇到的挑战包括可用站点数据的一致性问题、长时间序列的稀缺性以及研究区域云量的高度变化。为了应对这些挑战,我们做出了特别努力,修正了台站序列中的明显断点,并采用了一种将台站数据与卫星数据相结合的分析方法。该方法利用在短时间内提炼出的统计模式,将数据源进行非同期合并,从而使卫星数据也能用于研究的早期阶段。分析得出的气场包含可信的中尺度结构,而这些结构仅靠观测站网络是无法解决的。分析结果平均解释了 47% 的站点日照时间空间差异。评估结果显示,系统性低估(-1.5%)的程度轻微,平均绝对误差为 9.2%。平均误差在冬季、高海拔地区和 20 世纪 90 年代前后较大。数据集存在条件偏差,在计算与日照有关的气候指数时,可能会导致相当大的系统误差(最多 15%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Daily sunshine grids for Austria since 1961 – combining station and satellite observations for a multi-decadal climate-monitoring dataset

Daily sunshine grids for Austria since 1961 – combining station and satellite observations for a multi-decadal climate-monitoring dataset

Grid datasets of sunshine duration at high spatial resolution and extending over many decades are required for quantitative applications in regional climatology and environmental change (e.g., modelling of droughts and snow/ice covers, evaluation of clouds in numerical models, mapping of solar energy potentials). We present a new gridded dataset of relative (and derived absolute) sunshine duration for Austria at a grid spacing of 1 km, extending back until 1961 at daily time resolution. Challenges in the dataset construction were consistency issues in the available station data, the scarcity of long time series, and the high variation of cloudiness in the study region. The challenges were addressed by special efforts to correct evident breaks in the station series and by adopting an analysis method, which combines station data with satellite data. The methodology merges the data sources non-contemporaneously, using statistical patterns distilled over a short period, which allowed involving satellite data even for the early part of the study period. The resulting fields contain plausible mesoscale structures, which could not be resolved by the station network alone. On average, the analyses explain 47% of the spatial variance in daily sunshine duration at the stations. Evaluation revealed a slight systematic underestimation (− 1.5%) and a mean absolute error of 9.2%. The average error is larger during winter, at high altitudes, and around the 1990s. The dataset exhibits a conditional bias, which can lead to considerable systematic errors (up to 15%) when calculating sunshine-related climate indices.

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来源期刊
Theoretical and Applied Climatology
Theoretical and Applied Climatology 地学-气象与大气科学
CiteScore
6.00
自引率
11.80%
发文量
376
审稿时长
4.3 months
期刊介绍: Theoretical and Applied Climatology covers the following topics: - climate modeling, climatic changes and climate forecasting, micro- to mesoclimate, applied meteorology as in agro- and forestmeteorology, biometeorology, building meteorology and atmospheric radiation problems as they relate to the biosphere - effects of anthropogenic and natural aerosols or gaseous trace constituents - hardware and software elements of meteorological measurements, including techniques of remote sensing
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