VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, ...process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques.
Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on).
Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value‐cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value‐cost.eu/validationportal.
The largest and most comprehensive to date intercomparison of statistical downscaling methods is presented, with a total of over 50 downscaling methods representative of the most common approaches and techniques. Overall, most of the downscaling methods greatly improve raw model biases and no approach is superior in general, due to the large method‐to‐method variability. The main factors influencing the results are the seasonal calibration of the methods and their stochastic nature, for biases in the mean and variance.
Data from two automatic stations in Lodz (one urban and one rural) for the period 1997-2002 are analyzed to reveal urban-rural contrasts of such parameters as air temperature, relative humidity, ...water vapour pressure and wind speed. Under favourable weather conditions the highest temperature differences between the urban and rural station exceeds 8 degrees C. Relative humidity is lower in the town, sometimes by more than 40%. Water vapour pressure differences can be either positive (up to 5 hPa) or negative (up to -4 hPa). Wind speed at the urban station is on average lower by about 34% in night and 39% during daytime. Regression analysis shows that for rural winds lower than 1.13 m s -1 urban winds can be stronger than rural speeds. Attention has also been paid to singularities in the course of the analyzed parameters over 24 hour periods. It is shown that the typical course of the urban heat island intensity under favourable conditions is similar in all season. Four stages of this course have been distinguished. Wind speed differences also seem to change in a typical way. Case studies show that humidity contrasts, unlike temperature, can evolve in different ways under fine weather conditions. Types of relative humidity evolution are proposed. PUBLICATION ABSTRACT
Various indices of hot weather frequency and intensity were analysed in the area of Poland in the period between 1951 and 2006. An increase of majority of them was shown in the whole year and all ...summer months but September, when significant decrease in all indices was apparent. The correlation of selected hot weather indices and precipitation totals in a month of hot weather event and the preceding months were also calculated to check if prolonged dry weather can constitute a forcing factor for hot event creation. Because significant correlations appear mainly in the cases when precipitation is for the same month as the hot weather index, it seems that in Poland the presence of high pressure systems is a more important factor of hot event creation than dry weather.
A study of the long-term changes of various climatic extremes was made jointly by a number of European countries. It was found that the changes in maximum and minimum temperatures follow, in broad ...terms, the corresponding well-documented mean temperature changes.
Primary goal of presented study is to classify the most frequent patterns of the upper tropospheric jet stream over Europe. Wind fields were grouped into separated classes with the help of the ...correlation-based Lund's technique. The treatment of vector fields with Lund's method was achieved by replacement linear Pearson coefficient with vector correlation coefficient. The outstanding features of the upper-level circulation and ground-based weather associated with each jet type were analysed. Finally, basic statistics of jet stream patterns (frequency, duration time, day-to-day changes of jet structure) as well as their trends were estimated. The analysis was conducted on the basis of mean daily wind components at 200 hPa level, air temperature at 850 hPa, sea-level pressure, vertical velocity and geopotential at 500 hPa level. Data set was extracted from the NCEP/NCAR Reanalysis. The warm half-year in the period 1950-2001 was taken into consideration. The first 15 most frequent jet types, including 60.8% of the sample, were selected. Three jet stream types (C, E and I) are associated with distinct temperature changes in western Europe. Another three types (B, F and O) cause significant thermal advection in eastern and central Europe. Seasonal differences in frequency and duration time of jet stream patterns are also observed. Meridional types (A, C and D) dominate in spring, while in summer, patterns with intensified zonal flow prevail (B, E and J). At last, it is worth noticing that the majority of selected jet types pronounce an increase in day-to-day changes of wind field, which may indicate slight enhancement of circulation dynamics in the upper troposphere. PUBLICATION ABSTRACT
A simple statistical model of daily precipitation based on the gamma distribution is applied to summer (JJA in Northern Hemisphere, DJF in Southern Hemisphere) data from eight countries: Canada, the ...United States, Mexico, the former Soviet Union, China, Australia, Norway, and Poland. These constitute more than 40% of the global land mass, and more than 80% of the extratropical land area. It is shown that the shape parameter of this distribution remains relatively stable, while the scale parameter is most variable spatially and temporally. This implies that the changes in mean monthly precipitation totals tend to have the most influence on the heavy precipitation rates in these countries. Observations show that in each country under consideration (except China), mean summer precipitation has increased by at least 5% in the past century. In the USA, Norway, and Australia the frequency of summer precipitation events has also increased, but there is little evidence of such increases in any of the countries considered during the past fifty years. A scenario is considered, whereby mean summer precipitation increases by 5% with no change in the number of days with precipitation or the shape parameter. When applied in the statistical model, the probability of daily precipitation exceeding 25.4 mm (1 inch) in northern countries (Canada, Norway, Russia, and Poland) or 50.8 mm (2 inches) in mid-latitude countries (the USA, Mexico, China, and Australia) increases by about 20% (nearly four times the increase in mean). The contribution of heavy rains (above these thresholds) to the total 5% increase of precipitation is disproportionally high (up to 50%), while heavy rain usually constitutes a significantly smaller fraction of the precipitation events and totals in extratropical regions (but up to 40% in the tropics, e.g., in southern Mexico). Scenarios with moderate changes in the number of days with precipitation coupled with changes in the scale parameter were also investigated and found to produce smaller increases in heavy rainfall but still support the above conclusions. These scenarios give changes in heavy rainfall which are comparable to those observed and are consistent with the greenhouse-gas-induced increases in heavy precipitation simulated by some climate models for the next century. In regions with adequate data coverage such as the eastern two-thirds of contiguous United States, Norway, eastern Australia, and the European part of the former USSR, the statistical model helps to explain the disproportionate high changes in heavy precipitation which have been observed.
The variability of minimum and maximum temperature and the daily temperature range (DTR) in Poland was analyzed on the basis of the data from 9 stations with different periods of data (the longest ...was 98 yr). The long-term changes of seasonal means as well as for all Julian days were determined. The increase in the minimum temperature was accompanied by a slighter increase in the maximum temperature and a decrease in the DTR. It was found that the DTR changes correlate well with cloudiness, and the extreme temperature changes are related to the NAO (North Atlantic Oscillation) intensity, especially during winter and spring. The analysis of intra-annual changes has shown that the strongest increase in the minimum and maximum temperatures occurs in mid- and late winter, but there are also periods with decreasing tendencies, i.e. late autumn, the beginning of winter and the beginning of summer. All temperature indices indicate the cooling in autumn.
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