scholarly journals Evolution of Köppen-Geiger's climate classification in the Basque Country in the context of climate change

2021 ◽  
Author(s):  
Roberto Hernandez ◽  
Maialen Martija ◽  
Jose Daniel Gomez de Segura ◽  
Santiago Gaztelumendi
Keyword(s):  
Climate Change ◽  
Spatial Resolution ◽  
Climate Models ◽  
Basque Country ◽  
Delta Method ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Adaptation To Climate Change ◽  
Climate Classification

<p>The Köppen-Geiger system classifies climate into five main classes and thirty sub-types, based on threshold values and seasonality of monthly air temperature and precipitation. Its aim is to map empirically biome distributions around the world. In this paper, we analyze the evolution of this climate classification in the Basque Country for the historical period 1971-2000 and for three periods of future conditions: 2011-2040, 2041-2070, 2071-2100 projected by climate change scenarios.</p><p>The baseline data consists of high spatial resolution climate data available in the Basque Country. Different results from the KLIMATEK project on Adaptation to Climate Change are used (promoted by IHOBE -Basque Government-). These results have been generated for the RCP4.5 and RCP8.5 experiments, based on simulations carried out with regional climate models within the framework of the Euro-CORDEX project. Once the indicators were obtained at a spatial resolution of 12km x 12km, they were also obtained at a resolution of 1km x 1km, using the delta method. This process is carried out for each of the Euro-CORDEX models, so that an averaged result is finally provided, together with a statistic on its dispersion.</p><p>The evolution of the Köppen-Geiger maps is accompanied by other bioclimatic indices (aridity/continentality) and diagrams, which reinforce the pre-diagnosis of future climate conditions in the Basque Country. In addition, the dispersion of the models used is taken into account in the analysis of results, showing the most and least unfavorable scenarios.</p><p>These indices are applicable in impact and vulnerability analysis studies in sectors such as agriculture and landscape. Although they have received less attention than other indices of climate extremes, they nevertheless reflect concepts that are relatively simple to understand by the general public and are therefore also useful in the task of disseminating the consequences of climate change.</p>

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Vol 11 (4) ◽  
pp. 995-1012
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Retrospective Analysis ◽  
Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Uncertainty Range ◽  
Future Warming ◽  
The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

scholarly journals Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey

2021 ◽  
pp. 1-13
Author(s):  
Hudaverdi Gurkan ◽  
Vakhtang Shelia ◽  
Nilgun Bayraktar ◽  
Y. Ersoy Yildirim ◽  
Nebi Yesilekin ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Adaptation To Climate Change ◽  
Impact Of Climate Change ◽  
The Impact

Abstract The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

scholarly journals CLIMATE CHANGE IMPACTS ON PROJECTED PV POWER POTENTIAL UNDER RCP 8.5 SCENARIO IN BURUNDI

2020 ◽  
Vol 8 (5) ◽  
pp. 1-14
Author(s):  
Marc Niyongendako ◽  
Agnidé Emmanuel Lawin ◽  
Célestin Manirakiza ◽  
Serge Dimitri Yikwé Buri Bazyomo ◽  
Batablinlè Lamboni
Keyword(s):  
Climate Change ◽  
Solar Irradiance ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Potential Change ◽  
Historical Period ◽  
Climate Data ◽  
Future Period ◽  
Near Future

This work focuses on analysis of climate change effects on Photovoltaic (PV) power output in the Eastern and Northeastern of Burundi. Monthly temperature data from meteorological stations and solar irradiance data provided by SoDa database were considered as observed dataset for the historical period 1981-2010. Projection climate data from eight Regional Climate Models of CORDEX for Africa were used over the near future period 2021-2050. The change in temperature and solar irradiance were analyzed and the effects of these climate changes were assessed to show their impacts on PV power potential. The results indicated increasing trends and change in temperature for about 2°C over this near future period. The solar irradiance change was revealed negative with a high interannual variation for all regions and the mean decrease ranges between 2 and 4 W/m². The findings revealed also a negative change in PV power potential close to zero for all regions with a high change occurred in NLL. Indeed, the contribution of each parameter to PV power potential change was negative all over regions. However, the projected climate change does not predict a huge PV power potential change by 2050. Therefore, Burundi may invest in producing electricity energy from PV systems.

scholarly journals Climate change and hydrological extremes in Belgian catchments

2010 ◽  
Vol 7 (4) ◽  
pp. 5033-5078 ◽  
Author(s):  
P. Baguis ◽  
E. Roulin ◽  
P. Willems ◽  
V. Ntegeka
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Hydrological Regime ◽  
Climate Change Impacts ◽  
Delta Method ◽  
Climate Change Signal ◽  
Climate Change Scenarios ◽  
Hydrological Extremes ◽  
Current Century

Abstract. In this study we focus our attention on the climate change impacts on the hydrological balance in Belgium. There are two main rivers in the country, the Scheldt and the Meuse, supplied with water almost exclusively by precipitation. With the climate change projected by climate models for the end of the current century, one would expect that the hydrological regime of the rivers may be affected mainly through the changes in precipitation patterns and the increased potential evapotranspiration (PET) due to increased temperature throughout the year. We examine the hydrology of two important tributaries of the rivers Scheldt and Meuse, the Gete and the Ourthe, respectively. Our analysis is based on simulations with the SCHEME hydrological model and on climate change data from the European PRUDENCE project. Two emission scenarios are considered, the SRES A2 and B2 scenarios, and the perturbation (or delta) method is used in order to assess the climate change signal at monthly time scale and provide appropriate input time series for the hydrological simulations. The ensemble of climate change scenarios used allows us to estimate the combined model and scenario uncertainty in the streamflow calculations, inherent to this kind of analysis. In this context, we also analyze extreme river flows using two probability distribution families, allowing us to quantify the shift of the extremes under climate change conditions.

scholarly journals Future drought analysis using SPI and EDDI to consider climate change in South Korea

2020 ◽  
Vol 20 (8) ◽  
pp. 3266-3280
Author(s):  
Jeongeun Won ◽  
Sangdan Kim
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Evaporative Demand ◽  
The Standardized Precipitation Index ◽  
The Impact

Abstract Prediction of drought is important for efficient water management, as the occurrence of droughts affects large areas over a long period. According to various climate change scenarios, it is reported that in the future, Korea's climate is likely to increase in temperature with increasing rainfall. This increase in temperature will have a big impact on evapotranspiration. The occurrence of drought begins mainly with two causes: lack of rainfall or an increase in evapotranspiration. Therefore, in this study, the impact of climate change on future droughts is revealed through the Standardized Precipitation Index (SPI) and the Evaporative Demand Drought Index (EDDI). These two drought indices with different characteristics are used to examine the trend of future drought, and a drought Severity-Duration-Frequency (SDF) curve was derived to quantitatively analyze the depth of future drought. Future droughts are projected by applying future climate data generated from various climate models.

scholarly journals Winter Wheat Adaptation to Climate Change in Turkey

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 689
Author(s):  
Yuksel Kaya
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Grain Yield ◽  
Spring Wheat ◽  
Control Treatment ◽  
Climate Change Scenarios ◽  
Combined Effects ◽  
Adaptation To Climate Change ◽  
Wheat Genotypes ◽  
Plant Characteristics

Climate change scenarios reveal that Turkey’s wheat production area is under the combined effects of heat and drought stresses. The adverse effects of climate change have just begun to be experienced in Turkey’s spring and the winter wheat zones. However, climate change is likely to affect the winter wheat zone more severely. Fortunately, there is a fast, repeatable, reliable and relatively affordable way to predict climate change effects on winter wheat (e.g., testing winter wheat in the spring wheat zone). For this purpose, 36 wheat genotypes in total, consisting of 14 spring and 22 winter types, were tested under the field conditions of the Southeastern Anatolia Region, a representative of the spring wheat zone of Turkey, during the two cropping seasons (2017–2018 and 2019–2020). Simultaneous heat (>30 °C) and drought (<40 mm) stresses occurring in May and June during both growing seasons caused drastic losses in winter wheat grain yield and its components. Declines in plant characteristics of winter wheat genotypes, compared to those of spring wheat genotypes using as a control treatment, were determined as follows: 46.3% in grain yield, 23.7% in harvest index, 30.5% in grains per spike and 19.4% in thousand kernel weight, whereas an increase of 282.2% in spike sterility occurred. On the other hand, no substantial changes were observed in plant height (10 cm longer than that of spring wheat) and on days to heading (25 days more than that of spring wheat) of winter wheat genotypes. In general, taller winter wheat genotypes tended to lodge. Meanwhile, it became impossible to avoid the combined effects of heat and drought stresses during anthesis and grain filling periods because the time to heading of winter wheat genotypes could not be shortened significantly. In conclusion, our research findings showed that many winter wheat genotypes would not successfully adapt to climate change. It was determined that specific plant characteristics such as vernalization requirement, photoperiod sensitivity, long phenological duration (lack of earliness per se) and vulnerability to diseases prevailing in the spring wheat zone, made winter wheat difficult to adapt to climate change. The most important strategic step that can be taken to overcome these challenges is that Turkey’s wheat breeding program objectives should be harmonized with the climate change scenarios.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

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