Dynamics of meteorological time series on the base of ground measurements and retrospective data from MERRA‐2 for Poland,International Journal of Climatology

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Dynamics of meteorological time series on the base of ground measurements and retrospective data from MERRA‐2 for Poland
International Journal of Climatology ( IF 3.5 ) Pub Date : 2020-08-06 , DOI: 10.1002/joc.6787
Magdalena Gos ₁ , Piotr Baranowski ₁ , Jaromir Krzyszczak ₁ , Adam Kieliszek ₂ , Krzysztof Siwek ₂

Affiliation

A comparison study has been performed to assess the dynamics of meteorological processes in Poland on the basis of meteorological time series of air pressure, air temperature and wind speed coming from 35 synoptic stations belonging to the Institute of Meteorology and Water Management—National Research Institute (IMGW‐PIB) and from the nearest grid points of the Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2) produced at NASA's Global Modelling and Assimilation Office from January 1, 2007 to October 31, 2016. Apart from comparative statistics, the differences in the multifractal properties of the time series were evaluated with the use of MultiFractal Detrended Fluctuation Analysis (MFDFA), both for hourly and daily data, showing a high degree of similarity between the MERRA‐2 and IMGW‐PIB series. For the air pressure and air temperature, not only were high determination coefficients (close to .99) between the time series coming from the two sources noticed, but there were also similarities with the MFDFA parameters. Lower correlations between the time series of the wind speed obtained from the two studied databases were observed, which was related to differences in the data structure and methodology of the measurements for specific IMGW‐PIB stations. Additionally, to verify data similarities coming from the IMGW‐PIB and MERRA‐2 databases, the correlations between specific multifractal parameters and the orography were estimated and compared. For the air pressure and temperature, a remarkably high correlation was found between the multifractal parameter α₀ and the height above sea level of the measurement site. An analysis of the source of multifractality was performed, indicating that, for all studied meteorological elements and both data sources, the long‐range correlations prevail.

中文翻译：

基于地面测量和MERRA-2波兰的回顾性数据的气象时间序列动态

对于气压和气温，不仅注意到来自两个来源的时间序列之间的高确定系数（接近.99），而且与MFDFA参数也存在相似之处。从两个研究的数据库获得的风速时间序列之间的相关性较低，这与特定IMGW-PIB站的数据结构和测量方法的差异有关。此外，为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高不仅注意到来自两个来源的时间序列之间的高确定系数（接近.99），而且与MFDFA参数也存在相似之处。从两个研究的数据库获得的风速时间序列之间的相关性较低，这与特定IMGW-PIB站的数据结构和测量方法的差异有关。此外，为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高不仅注意到来自两个来源的时间序列之间的高确定系数（接近.99），而且与MFDFA参数也存在相似之处。从两个研究的数据库获得的风速时间序列之间的相关性较低，这与特定IMGW-PIB站的数据结构和测量方法的差异有关。此外，为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高从两个研究的数据库获得的风速时间序列之间的相关性较低，这与特定IMGW-PIB站的数据结构和测量方法的差异有关。此外，为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定的多重分形参数和地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高从两个研究的数据库获得的风速时间序列之间的相关性较低，这与特定IMGW-PIB站的数据结构和测量方法的差异有关。此外，为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高为了验证来自IMGW-PIB和MERRA-2数据库的数据相似性，估计并比较了特定多重分形参数与地形之间的相关性。对于气压和温度，多重分形参数α之间的相关性非常高₀和测量地点的海拔高度。对多重分形的来源进行了分析，表明对于所有研究的气象要素和两个数据源，长期相关性均占优势。

更新日期：2020-08-06

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