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Variability and trends of mean maximum and mean minimum air temperature in Greece from ground-based observations and NCEP–NCAR reanalysis gridded data.

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Title: Variability and trends of mean maximum and mean minimum air temperature in Greece from ground-based observations and NCEP–NCAR reanalysis gridded data.
Authors: Nastos, P. T.1 (AUTHOR) nastos@geol.uoa.gr, Philandras, C. M.2 (AUTHOR), Kapsomenakis, J.1 (AUTHOR), Eleftheratos, K.1 (AUTHOR)
Source: International Journal of Remote Sensing. 11/10/2011, Vol. 32 Issue 21, p6177-6192. 16p. 2 Charts, 5 Graphs, 1 Map.
Subjects: Atmospheric temperature standard deviations, Temperature measurements, Maxima & minima, Meteorological stations, Mountains
Geographic Terms: Greece
Abstract: In this study, the variability and trends of the mean annual and seasonal maximum and minimum surface air temperature in Greece are examined, using monthly data sets of 26 meteorological stations from the Hellenic National Meteorological Service (HNMS) and gridded data from the National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis project for the period 1955–2001. NCEP–NCAR reanalysis data sets are created by assimilating climate observations from different sources, including ships, satellites, ground stations, radiosonde observations and radar. The general purpose of conducting reanalyses is to produce multi-year global state-of-the-art gridded representations of atmospheric states, generated by a constant model and a constant data-assimilation system. The trends of the mean extreme air temperatures were evaluated, using the Mann–Kendall criterion, and, in the process, factor analysis was applied to both the stations' and the NCEP–NCAR grid points time series. Regarding the mean maximum air temperature, the first main factor, which explains a high percentage of the total variance, presents a statistically significant (CL = 95%) negative trend only during the winter. The first main factor of the mean minimum air temperature manifests a statistically significant (CL = 95%) positive trend during the summer and the year, and a statistically significant (CL = 95%) negative trend in autumn and winter. These findings were compared to the respective ones of the NCEP–NCAR reanalysis data and significant differences in the spatial distribution and temporal variability of the extracted new factors were found. These differences between the two examined data sets could be attributed to topographical factors such orography and land–sea distribution, which could not be represented properly by the reanalysis model. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In this study, the variability and trends of the mean annual and seasonal maximum and minimum surface air temperature in Greece are examined, using monthly data sets of 26 meteorological stations from the Hellenic National Meteorological Service (HNMS) and gridded data from the National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis project for the period 1955–2001. NCEP–NCAR reanalysis data sets are created by assimilating climate observations from different sources, including ships, satellites, ground stations, radiosonde observations and radar. The general purpose of conducting reanalyses is to produce multi-year global state-of-the-art gridded representations of atmospheric states, generated by a constant model and a constant data-assimilation system. The trends of the mean extreme air temperatures were evaluated, using the Mann–Kendall criterion, and, in the process, factor analysis was applied to both the stations' and the NCEP–NCAR grid points time series. Regarding the mean maximum air temperature, the first main factor, which explains a high percentage of the total variance, presents a statistically significant (CL = 95%) negative trend only during the winter. The first main factor of the mean minimum air temperature manifests a statistically significant (CL = 95%) positive trend during the summer and the year, and a statistically significant (CL = 95%) negative trend in autumn and winter. These findings were compared to the respective ones of the NCEP–NCAR reanalysis data and significant differences in the spatial distribution and temporal variability of the extracted new factors were found. These differences between the two examined data sets could be attributed to topographical factors such orography and land–sea distribution, which could not be represented properly by the reanalysis model. [ABSTRACT FROM AUTHOR]
ISSN:01431161
DOI:10.1080/01431161.2010.507798