Studies detecting trends in climate elements typically concentrate on their local significance, ignoring the question of whether the significant local trends may or may not have occurred as a result ...of chance. This paper fills this gap by examining several approaches to detecting statistical significance of trends defined on a grid (i.e., on a regional scale). To this end, we introduce a novel simple procedure of significance testing that is based on counting signs of local trends (sign test), and we compare it with five other approaches to testing collective significance of trends: counting, extended Mann–Kendall, Walker, false detection rate (FDR), and regression tests. Synthetic data are used to construct null distributions of trend statistics, to determine critical values of the tests, and to assess the performance of tests in terms of type-II error. For lower values of spatial and temporal autocorrelations, the sign test and extended Mann–Kendall test perform slightly better than the counting test; these three tests outperform the Walker, FDR, and regression tests by a wide margin. For high autocorrelations, which is a more realistic case, all tests become similar in their performance, with the exception of the regression test, which performs somewhat worse. Some tests cannot be used under specific conditions because of their construction: the Walker and FDR tests for high temporal autocorrelations, and the sign test under high spatial autocorrelations.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Future climate conditions for the Mediterranean region based on an ensemble of 16 Global Climate Models are expressed and mapped using three approaches, giving special attention to the intermodel ...uncertainty. (1) The scenarios of mean seasonal temperature and precipitation agree with the projections published previously by other authors. The results show an increase in temperature in all seasons and for all parts of the Mediterranean with good intermodel agreement. Precipitation is projected to decrease in all parts and all seasons (most significantly in summer) except for the northernmost parts in winter. The intermodel agreement for the precipitation changes is lower than for temperature. (2) Changes in drought conditions are represented using the Palmer Drought Severity Index and its intermediate Z-index product. The results indicate a significant decrease in soil moisture in all seasons, with the most significant decrease occurring in summer. The displayed changes exhibit high intermodel agreement. (3) The climate change scenarios are defined in terms of the changes in parameters of the stochastic daily weather generator calibrated with the modeled daily data; the emphasis is put on the parameters, which affect the diurnal and interdiurnal variability in weather series. These scenarios indicate a trend toward more extreme weather in the Mediterranean. Temperature maxima will increase not only because of an overall rise in temperature means, but partly (in some areas) because of increases in temperature variability and daily temperature range. Increased mean daily precipitation sums on wet days occurring in some seasons, and some parts of the Mediterranean may imply higher daily precipitation extremes, and decreased probability of wet day occurrence will imply longer drought spells all across the Mediterranean.
The impact of climate change could undermine the future grain production as a consequence of increased temperature and drought condition or improve the crop performance owing to the increased CO2 in ...the atmosphere. Wheat water demand and yield are strictly related to climate conditions of the area where the plants are cropped. In this study, we assessed the future trends of grain yield and water consumption in two European regions, Germany (Continental region) and Italy (Mediterranean region) in the light of the multiple sources of uncertainty related to climate and yield forecasts. Four crop models were set up under combinations of two European climate regions, five Global Circulation Models and two Representative CO2 Concentration Pathways, 486 ppm and 540 ppm in 2050. Yield and water use were assessed under rainfed and irrigated regimes, and the water footprint of green water and total water was estimated. Our results indicated that projected yields were comparable (Mediterranean area) or even improved (+9%; Continental area) in rainfed conditions in comparison to the current trend; and water supply enhanced crop performance (+22% in Germany and +19% in Italy, as mean). Crop water consumption (both green and blue) remained stable in future projections but the water footprint was 5% lower on average in Italy and 23% in Germany when compared to the baseline. Despite the uncertainty in future predictions related to the factors analysed, our result indicated that current wheat production and its water footprint could become more favourable under climate change.
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•An ensemble of crop models was applied to assess the wheat water footprint (WF) in two European climate areas;•The effects of 5 Global Circulation Models and 2 CO2 concentrations on rainfed and irrigated crops were assessed;•Grain yield would remain the same in Mediterranean area or even improved in Continental area;•Further improvements of WF would be expected under irrigated management.
The relationship between seasonal agricultural drought and detrended yields (within a period from 1961 to 2000) of selected crops was assessed in the conditions of the Czech Republic, which are to ...some extent representative of a wider area of Central Europe. Impact of water stress was analyzed using time series of yields for 8 crops (spring barley, winter wheat, grain maize, potato, winter rape, oats, winter rye and hay from permanent meadows) for 77 districts in the Czech Republic (average district area is 1025
km
2). Relative version of Palmer’s Z-index (rZ-index or rZ-i) was used as a tool for quantification of agricultural drought. The monthly values of the rZ-index for each individual district were calculated as the spatial average (only for the grids of arable land). The study showed that severe droughts (e.g., in 1981 and 2000) are linked with significant reduction in yields of the main cereals and majority of other crops through the most drought prone regions. We found a statistically significant correlation (
p
≤
0.05) between the sum of the rZ-index for the main growing period of each crop and the yield departures of spring barley within 81% (winter wheat in 57%, maize in 48%, potato in 89%, oats in 79%, winter rye in 52%, rape in 39%, hay in 79%) of the analyzed districts. This study also defined the crop-specific thresholds under which a soil moisture deficit (expressed in terms of rZ-index) leads to severe impact at the district level. This can be expressed as the sum of the monthly rZ-index during the period of high crop sensitivity to drought; for spring barley it is −5, winter wheat −5, maize −9, rape −12, winter rye −10, oat −4, potato −6 and for hay −3. The length of the sensitive period is also crop-specific and includes the months that are important for the yield formation. The results show that yields of spring barley (and spring crops in general) are significantly more affected by seasonal water stress than yields of winter crops and hay from permanent meadows. The study proved that a severe drought spell during the sensitive period of vegetative season does have a quantifiable negative effect, even within more humid regions. These results demonstrate that, at least in some areas of the CR (and probably most of Central Europe), drought is one of the key causes of interannual yield variability.
Stochastic weather generators have been increasingly used as downscaling tools for climate change impact assessments. In spite of their widespread use, their potential to simulate climate extremes – ...especially multivariate extremes – is largely unexplored. The aim of this study is to assess the ability of the Richardson type six-variate weather generator SiSi to simulate the frequency of various univariate as well as multivariate extremes with focus on extremes related to the non-normally distributed weather variables relative humidity and wind speed. A total of 83 sites with different elevation and proximity to each other – thereby defining a European, a country (Austria) and a local (catchment) scale – and diverse climates across Europe are selected. Results show that SiSi is able to simulate univariate and multivariate extremes generally and equally well in all climate zones. The results depend on the nature of the individual variables involved in the extreme events. Among all the extreme events, the weather generator has a tendency to underestimate the extremes related to minimum temperature. The first-order auto-regressive (AR(1)) model used for modeling non-precipitation variables assumes the distribution of variables to be Gaussian. This assumption has been enforced in this study by transforming each non-precipitation variable to a normal distribution, but nevertheless the weather generator consistently underestimates the cold extremes. This is due to the multimodal nature of the distribution of temperature. The AR(1) model is not able to reproduce the multimodality of the distributions. The performance of SiSi does not depend on the climate type of a region or the proximity of sites to one another, rather it depends on the characteristics of a variable at an individual location.
To better understand the impact of climate change at a given location, it is crucial to consider a wide range of climate models that are representative of the area. In this study, we emphasize the ...importance of the careful validation and selection of climate models most suitable for a particular region. This step is critical to enhance the relevance of climate change impact studies and consequently design appropriate and robust adaptation measures, particularly in agriculture, forestry and water resources management. We propose validation and selection methods for regional climate models that can help identify a smaller group of well-performing models using the Central European area and Czech Republic as examples. In the validation process, 7 out of 19 regional climate models performed poorly. Of the 12 well-performing models, a subset of 7 models was selected to represent the uncertainty in the entire ensemble, which could be used in subsequent studies. The methodology is sufficiently general and may be applied to other climate model ensembles.
The paper shows a large-scale shift in agroclimatic zones in the territory of the Czech Republic (CR) between 1961 and 2019. The method used for agroclimatic zoning took advantage of high-resolution ...(0.5 km × 0.5 km) daily climate data collected from 268 climatological and 787 rain-gauge stations. The climate information was combined with soil and terrain data at the same resolution. The set of seven agroclimatic indicators allowed us to estimate rates of changes in agroclimatic conditions over the 1961–2019 period, including changes in the air temperature regime, global radiation, drought, frost risks and snow cover occurrence. These indicators are relevant for all main crops and agroclimatic zoning and account for local soil and slope conditions. The study clearly highlights major shifts in the type and extent of agroclimatic zones between 1961–2000 and 2000–2019, which led to the occurrence of entirely new combinations of agroclimatic indicators.
Extended periods without precipitation, observed for example in central Europe including Germany during the seasons from 2018 to 2020, can lead to water deficit and yield and quality losses for grape ...and wine production. Irrigation infrastructure in these regions to possibly overcome negative effects is largely non-existent. Regional climate models project changes in precipitation amounts and patterns, indicating an increase in frequency of the occurrence of comparable situations in the future. In order to assess possible impacts of climate change on the water budget of grapevines, a water balance model was developed, which accounts for the large heterogeneity of vineyards with respect to their soil water storage capacity, evapotranspiration as a function of slope and aspect, and viticultural management practices. The model was fed with data from soil maps (soil type and plant-available water capacity), a digital elevation model, the European Union (EU) vineyard-register, observed weather data, and future weather data simulated by regional climate models and downscaled by a stochastic weather generator. This allowed conducting a risk assessment of the drought stress occurrence for the wine-producing regions Rheingau and Hessische Bergstraße in Germany on the scale of individual vineyard plots. The simulations showed that the risk for drought stress varies substantially between vineyard sites but might increase for steep-slope regions in the future. Possible adaptation measures depend highly on local conditions and are needed to make targeted use of water resources, while an intense interplay of different wine-industry stakeholders, research, knowledge transfer, and local authorities will be required.
The close relationship between the onset and severity of agricultural and hydrological drought is considered self-evident, yet relatively few studies have addressed the effects of applying ...agricultural drought adaptation to hydrological drought characteristics. The present study applies a model cascade capable of simultaneously considering the interactions between agricultural and hydrological droughts. The study area covers all river basins in the Czech Republic and includes the periods of 1956–2015 (baseline) and 2021–2080 (future). The model cascade was shown to explain 91% of the variability in the seasonal and annual accumulated runoff and allows for the analysis of increasing/maintaining/decreasing available water capacity (AWC) across the 133 defined basins with a total area of c. 78,000 km2. The study reports that the probability and extent of agricultural drought increased over the entire period with higher AWC scenario showing slower pace of such increase especially from April to June. The trends in the extent or severity of hydrological droughts were of low magnitude. The future climate has been projected through the use of ensembles of five global (CMIP5) and five regional (EURO-CORDEX) climate models. The results showed a significant increase in the duration of agricultural drought stress and in the area affected throughout the year, particularly in July–September. The hydrological drought response showed a marked difference between areas with a negative and positive climatic water balance, i.e., areas where long-term reference evapotranspiration exceeds long-term precipitation (negative climatic water balance) and where it does not (positive climatic water balance). The overall results indicate that increasing soil AWC would decrease the frequency and likely also impact of future agricultural droughts, especially during spring. This result would be especially true if the wetter winters predicted by some of the models materialized. Hydrological droughts at the country level are estimated to become more pronounced with increasing AWC, particularly in catchments with a negative climatic water balance.
•We analyzed the past and projected agricultural and hydrological droughts in 133 basins in the Czech Republic.•The area and severity of the agricultural drought during the growing season has increased since 1956.•The runoff and hydrological droughts have increased insignificantly since 1956 except for June.•The increase in the water holding capacity decreases area and severity of agricultural droughts but exacerbates hydrological ones.•Adaptation studies have to consider drought impacts simultaneously to avoid maladaptation.
ABSTRACT
The weather conditions from August 2011 to May 2012 produced an extreme drought in the eastern Czech Republic (Moravia), whereas the patterns were nearly normal in its western region ...(Bohemia). The Southern and Central Moravia regions, which represent the most important agricultural areas, were most affected by the drought. The precipitation totals for the studied period were 50–70% of the long‐term mean, which was calculated for 1961–2000. In autumn 2011, the total precipitation accounted for 10–30% of the long‐term mean for most of Moravia, increasing to 30–50% in spring 2012. Moreover, 7.5% of the Czech Republic experienced a 100‐year drought; 20% of the country experienced a 20‐year drought. According to the Palmer Drought Severity Index, the 2012 drought was classified as the worst in the past 130 years. The drought patterns were related to the prevailing high‐pressure systems over Central Europe and the occurrence of weather types with different precipitation amounts in Bohemia and Moravia. The most substantial drought effects occurred in the agricultural sector. A decrease in cereal yields was observed in the analysed production areas in Moravia, which was unprecedented in the past 52 years. Moreover, winter crops were affected more than spring crops. An increased risk of fire occurred due to the drought conditions; the largest forest fire in the past 15 years was recorded during this period. Furthermore, signs of hydrological drought were also reported in rivers. The 2011–2012 drought was compared with the significant droughts in 2000, 2003 and 2007. Austria and Slovakia, which neighbour the Czech Republic, experienced a similar drought. Global circulation model sensitivity experiments appear to indicate that droughts similar to this episode may be occurring at a recurrence interval of 20 years by the 2050s.
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