Abstract

The characteristics of near surface air temperature and wind field over the Southeastern Levantine (SEL) sub-basin during the period 1979–2018 were simulated. The simulation was carried out using a dynamical downscaling approach, which requires running a regional climate model system (RegCM-SVN6994) on the study domain, using lower-resolution climate data (i.e., the fifth generation of ECMWF atmospheric reanalysis of the global climate ERA5 datasets) as boundary conditions. The quality of the RegCM-SVN simulation was first verified by comparing its simulations with ERA5 for the studied region from 1979 to 2018, and then with the available five WMO weather stations from 2007 to 2018. The dynamical downscaling results proved that RegCM-SVN in its current configuration successfully simulated the observed surface air temperature and wind field. Moreover, RegCM-SVN was proved to provide similar or even better accuracy (during extreme events) than ERA5 in simulating both surface air temperature and wind speed. The simulated annual mean T2m by RegCM-SVN (from 1979 to 2018) was 20.9 °C, with a positive warming trend of 0.44 °C/decade over the study area. Moreover, the annual mean wind speed by RegCM-SVN was 4.17 m/s, demonstrating an annual negative trend of wind speed over 92% of the study area. Surface air temperatures over SEL mostly occurred within the range of 4–31 °C; however, surface wind speed rarely exceeded 10 m/s. During the study period, the seasonal features of T2m showed a general warming trend along the four seasons and showed a wind speed decreasing trend during spring and summer. The results of the RegCM-SVN simulation constitute useful information that could be utilized to fully describe the study area in terms of other atmospheric parameters.

Highlights

  • Simulated RegCM-SVN results of T2m and surface wind field for the study area were examined to evaluate the accuracy of RegCM-SVN simulation compared with the ERA5 database

  • The validation of RegCM-SVN results was first done against the ERA5 reanalysis during the period 1979–2018 and with observed data during the period 2007–2018

  • Validation processes indicated that RegCM-SVN successfully simulated the surface air temperature and wind field over the study area

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Summary

Data and Methods of Analysis

SEL is highly affected by the Siberian High and the Azores. Used with primary and secondary low-pressure systems. ERA5 hourly data on 38 different (1) tends to produce favorable conditions for the rainy season to develop that paired with pressure levels from to (https://cds.climate.copernicus.eu/cdsapp#!/dathe Mediterranean low-pressure system, as stated by Nastos and Zerefos [11]; and (2). Elevation with 30regional/local arc seconds climates and(a downscaling procedure is needed to provide more reliable data to policy x. Building an accurate dynamical downscaling system to simulate the climate of the study area would be extremely beneficial for a better understanding of its climatology. Regional climate model, Apache Subversion (RegCM-SVN), is used to simulate near surface air temperature (T2m) and surface wind field over SEL during the period from 1979 to 2018 to test the dynamical downscaling ability to describe the climate of the study area with a similar or even better accuracy than ERA5. As such, understanding the variabilities of T2m and wind speed (UV10 ) in this region is the main goal of this study for planning adaptation measures in different life sectors (e.g., agricultural and energy sectors), together with finding suitable regional climate policies to cope with climatic change issues

Data Used to Force RegCM-SVN
ERA5 Hourly Data on Single Levels from 1979 to 2018
WMO Observed Data from 2007 to 2018
RegCM-SVN Model
RegCM-SVN Verification Analyses
Seasonal Characteristics of Surface Air Temperature and Wind Speed
Spatial Verification
Verification analyses and ERA5
Verification Using Atmospheric Observations over the Five Studied Stations
20 C of the sector
Seasonal Characteristics of Surface Air Temperature and Wind Speed over SEL
Seasonal
Variability of SEL Surface Air Temperature and Surface Wind
Variability
Summary
Full Text
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