Climate and climate change in the Austrian–Swiss region of the European Alps during the twentieth century according to Feddema

We present a 1-km² 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 km². 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. The Rhine River Valley, for example, exhibited more than 100 summer days in 2003, whereas in 1996, the number was low everywhere in Germany. The dataset is useful for applications in various climate-related studies, hazard management and for solar or wind energy applications and it is available via doi: 10.5676/DWD_CDC/TRY_Basis_v001.     

Observed and projected climate change in the European region during the twentieth and twenty-first centuries according to Feddema

Climate change in the European region during the twentieth and twenty-first centuries is analyzed according to Feddema’s method. Precipitation and air temperature data from the twentieth century are taken from the Climatic Research Unit, while data for the twenty-first century are taken from the ENSEMBLES climate change project. The latter were bias-corrected to ensure homogeneity across the twentieth and twenty-first centuries. Climate classes based on monthly and annual values of potential evapotranspiration, precipitation and their ratio, are defined for 30-year averages, from which trend and spatial agreement analysis are calculated. There are separate classes for annual values and for intra-annual variation. The results indicate that the change of annual climate characteristics will be much more intense in the twenty-first than it was in the twentieth century. The dominant process in the projections is warming, mostly via cold to cool (about 45% of grid points) in north Europe and cool to warm (about 8% of grid points) transformations. The second most important process is the drying of moderately moist classes affecting about 10% of the grid points in south Europe. Changes in intra-annual variability classes are more common than changes in the annual ones during the twentieth century. The chance of increase in intra-annual temperature variation from high to extreme is about 5% during the course of the twentieth century, and about 10% in the following century.     

Climate change in Hungary during the twentieth century according to Feddema

Theoretical and Applied Climatology - Climate change in Hungary during the twentieth century is analyzed using Feddema’s original scheme suitable for global scale applications (F-GS) and...     

Sensitivity of MM5-simulated planetary boundary layer height to soil dataset: comparison of soil and atmospheric effects

The effects of two soil datasets on planetary boundary layer (PBL) height are analyzed, using model simulations. Simulations are performed with the MM5 weather prediction system over the Carpathian Basin, with 6?km horizontal resolution, investigating three summer days, two autumn, and one winter day of similar synoptic conditions. Two soil datasets include that of the United States Department of Agriculture, which is globally used, and a regional Hungarian called Hungarian unsaturated soil database. It is shown that some hydraulic parameter values between the two datasets can differ up to 5–50%. These differences resulted in 10% deviations in the space–time-averaged PBL height (averaged over Hungary and over 12?h in the daytime period). Over smaller areas, these relative deviations could reach 25%. Daytime course changes in the PBL height for reference run conditions were significant (p?<?0.01) in ≈70% of the grid points covering Hungary. Ensemble runs using different atmospheric parameterizations and soil moisture initialization setups are also performed to analyze the sensitivity under changed conditions. In these cases, the sensitivity test showed that irrespective of the radiation and PBL scheme, the effect of different soil datasets on PBL height is roughly the same. PBL height is also sensitive to field capacity (Θ_f) and wilting point (Θ_w) changes. Θ_f changes seem to be more important for loamy sand, while Θ_w changes for the clay soil textural class.     

The climate of Carpathian Region in the 20th century based on the original and modified Holdridge life zone system

The Holdridge life zone system has already been used a number of times for analysing the effects of climate change on vegetation. But a criticism against the method was formulated that it cannot interpret the ecotones (e.g. forest steppe). Thus, in this paper transitional life zones were also determined in the model. Then, both the original and modified life zone systems were applied for the climatic fields of database CRU TS 1.2. Life zone maps were defined in the Carpathian Region (43.5–50.5° N, 15.5–28° E) for each of five 20-year periods between 1901 and 2000. We estimated correctness of the result maps with another vegetation map using Cohen’s Kappa statistic. Finally, temporal changes in horizontal and vertical distribution of life zones were investigated. The coverage of boreal region decreased with 59.46% during the last century, while the warm temperate region became almost two and a half larger (257.36%). The mean centres of those life zones, which were not related to mountains, shifted northward during the investigation period. In case of the most abundant life zone types, the average distribution elevation increased. Using the modified model, the potential distribution of forest steppe could be also identified.     

Sensitivity of simulated temperature,precipitation, and global radiation to different WRF configurations over the Carpathian Basin for regional climate applications

In this study, the Weather Research and Forecasting (WRF) model is used to produce short-term regional climate simulations with several configurations for the Carpathian Basin region. The goal is to evaluate the performance of the model and analyze its sensitivity to different physical and dynamical settings, and input data. Fifteen experiments were conducted with WRF at 10 km resolution for the year 2013. The simulations differ in terms of configuration options such as the parameterization schemes, the hydrostatic and non-hydrostatic dynamical cores, the initial and boundary conditions (ERA5 and ERA-Interim reanalyses), the number of vertical levels, and the length of the spin-up period. E-OBS dataset 2 m temperature, total precipitation, and global radiation are used for validation. Temperature underestimation reaches 4–7 °C for some experiments and can be reduced by certain physics scheme combinations. The cold bias in winter and spring is mainly caused by excessive snowfall and too persistent snow cover, as revealed by comparison with satellite-based observations and a test simulation without snow on the surface. Annual precipitation is overestimated by 0.6–3.8 mm day⁻¹, with biases mainly accumulating in the period driven by large-scale weather processes. Downward shortwave radiation is underestimated all year except in the months dominated by locally forced phenomena (May to August) when a positive bias prevails. The incorporation of downward shortwave radiation to the validation variables increased the understanding of underlying problems with the parameterization schemes and highlighted false model error compensations.