High-resolution grids of hourly meteorological variables for Germany

Abstract

We present a 1-km 2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down-and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km 2 . This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted.

A New Approach for Generating Human Biometeorological Information Based on Gridded High-Resolution Data (Basic Data of Test-Reference-Years)

“…The data used for the analyses is the so-called "basis dataset of the Test-Reference-Years" (TRY) from the German Meteorological Service [25]. This is a gridded dataset covering the German land surface and comprises the following 12 meteorological variables: air temperature (T a ), air pressure (P), dew point temperature (T d ), cloud cover (CC), relative humidity (RH), water vapour content (X), wind speed (v) and wind direction (WD), global (G) and direct radiation (SIS), and both surface down-welling (SDL) and up-welling longwave radiation (SOL).…”

“…This is a gridded dataset covering the German land surface and comprises the following 12 meteorological variables: air temperature (T a ), air pressure (P), dew point temperature (T d ), cloud cover (CC), relative humidity (RH), water vapour content (X), wind speed (v) and wind direction (WD), global (G) and direct radiation (SIS), and both surface down-welling (SDL) and up-welling longwave radiation (SOL). The dataset covers the years from 1995 to 2012 with a spatial resolution of 1 km 2 and a temporal resolution of one hour [25]. Different data sources were used to construct the gridded data.…”

“…Table 1. Meteorological variables and data sources used for the gridding procedure of basis dataset of TRY [25]. RCM, Regional Climate Model.…”

“…The gridding procedure was used with different methods of interpolation, depending on the data source, data density, and the climate variable. For more details about the data gridding process and interpolation see [25].…”

“…As a consequence of the high spatial and temporal resolution, the effect of the Urban Heat Island (UHI) has to be considered [25]. The UHI effect is reflected in the positive difference of air temperature between urban and rural areas.…”