Bias-corrected Regional Climate Models Research Articles

Evaluating climate models to analyze drought conditions in the western region of Bangladesh

Being susceptible to natural disasters, Bangladesh is one of the most disaster-prone countries. Among the various natural calamities, droughts are a frequent occurrence in the western region of the country. Hence, this study first compared the efficacy of five bias-corrected Regional Climate Models (RCMs) - MIROC, NOAA, MPI, IPSL, and CCCma - for the Western region of Bangladesh with observed monthly precipitation and subsequent SPI values. Various evaluation methods- RMSE, Taylor Diagram, Mann–Whitney U Test, and t-test, were applied to precipitation and SPI3 values for the historical base period. Through these analyses, the MIROC model exhibited the highest level of accuracy. Accordingly, future projections for short-term droughts (SPI-3) and their characteristics were conducted using the ensemble of top three climate model under the RCM 8.5 W/m2 scenario. Short-term droughts are anticipated to become less frequent and severe in the 2060s and 2080s compared to the 2020s. Nonetheless, North-West region is projected to be more drought-prone than South-West until 2100. This research shows the importance of evaluating the better-fitting RCMs for assessing historical droughts and making reliable projections for the future. The methodology and findings can be employed in evidence-based decision-making and applied in other drought-prone areas to understand future drought risks.

Impact of Climate Change on Extreme Rainfall Events and Pluvial Flooding Risk in the Vojvodina Region (North Serbia)

Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection.

Apparent contradiction in the projected climatic water balance for Austria: wetter conditions on average versus higher probability of meteorological droughts

Abstract. In this paper future changes of surface water availability in Austria are investigated. We use an ensemble of downscaled and bias-corrected regional climate model simulations of the EURO-CORDEX initiative under moderate mitigation (RCP4.5) and Paris Agreement (RCP2.6) emission scenarios. The climatic water balance and its components (rainfall, snow melt, glacier melt and atmospheric evaporative demand) are used as indicators of surface water availability, and we focus on different altitudinal classes (lowland, mountainous and high alpine) to depict a variety of processes in complex terrain. Apart from analysing the mean changes of these components, we also pursue a hazard risk approach by estimating future changes in return periods of meteorological drought events of a given magnitude as observed in the reference period. The results show, in general, wetter conditions over the course of the 21st century over Austria on an annual basis compared to the reference period 1981–2010 (e.g. RCP4.5 +107 mm, RCP2.6 +63 mm for the period 2071–2100). Considering seasonal differences, winter and spring are getting wetter due to an increase in precipitation and a higher fraction of rainfall as a consequence of rising temperatures. In summer only little changes in the mean of the climatic water balance conditions are visible across the model ensemble (e.g. RCP4.5 ±0 mm, RCP2.6 −2 mm for the period 2071–2100). On the contrary, by analysing changes in return periods of drought events, an increasing risk of moderate and extreme drought events during summer is apparent, a signal emerging within the climate system along with increasing warming.

Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT

Abstract The study is conducted to examine the climate change impact on rice Crop Water Requirement (CWR) and Net Irrigation Requirement (NIR) using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) coupled with the CROPWAT 8.0 model. The maximum temperature (Tmax), minimum temperature (Tmin), and rainfall projections for the baseline (years 1981–2015) and future (years 2030 and 2040) under Representative Concentration Pathway (RCP) 4.5 were derived from NEX-GDDP. To reduce the bias, linear scaling (LS) and the modified difference approach (MDA) were employed. Results show that LS performed better than the MDA along with improved statistical measures such as mean (μ), standard deviation (σ), and percent bias (Pbias), in the case of Tmax and Tmin (μ = 31.14 and 19.63 °C, σ = 5.75 and 6.78 °C, Pbias = 1.43 and 0.33%), followed by rainfall (μ = 2.67 mm, σ = 4.94 mm, and Pbias = 2.4%). The future climatic projections showed an increasing trend in both Tmax and Tmin, which are expected to increase by 1.7 °C by 2040. This would cause an increased range of 1.2 and 2% in 2030 and 2040, respectively. Due to a wide variation in effective rainfall (Peff), NIR could increase by 4 and 9% in 2030 and 2040, respectively. The above results may help formulate adaptation measures to alleviate the impacts of climate change on rice production.

Impact of Climate Change on Water Resources and Crop Production in Western Nepal: Implications and Adaptation Strategies

Irrigation-led farming system intensification and efficient use of ground and surface water resources are currently being championed as a crucial ingredient for achieving food security and reducing poverty in Nepal. The potential scope and sustainability of irrigation interventions under current and future climates however remains poorly understood. Potential adaptation options in Western Nepal were analyzed using bias-corrected Regional Climate Model (RCM) data and the Soil and Water Assessment Tool (SWAT) model. The RCM climate change scenario suggested that average annual rainfall will increase by about 4% with occurrence of increased number and intensity of rainfall events in the winter. RCM outputs also suggested that average annual maximum temperature could decrease by 1.4 °C, and average annual minimum temperature may increase by 0.3 °C from 2021 to 2050. Similarly, average monthly streamflow volume could increase by about 65% from March–April, although it could decrease by about 10% in June. Our results highlight the tight hydrological coupling of surface and groundwater. Farmers making use of surface water for irrigation in upstream subbasins may inadvertently cause a decrease in average water availability in downstream subbasins at approximately 14%, which may result in increased need to abstract groundwater to compensate for deficits. Well-designed irrigated crop rotations that fully utilize both surface and groundwater conversely may increase groundwater levels by an average of 45 mm from 2022 to 2050, suggesting that in particular subbasins the cultivation of two crops a year may not cause long-term groundwater depletion. Modeled crop yield for the winter and spring seasons were however lower under future climate change scenarios, even with sufficient irrigation application. Lower yields were associated with shortened growing periods and high temperature stress. Irrigation intensification appears to be feasible if both surface and groundwater resources are appropriately targeted and rationally used. Conjunctive irrigation planning is required for equitable and year-round irrigation supply as neither the streamflow nor groundwater can provide full and year-round irrigation for intensified cropping systems without causing the degradation of natural resources.

Towards a More Robust Evaluation of Climate Model and Hydrological Impact Uncertainties

The uncertainty of climate model projections is recognized as being large. This represents a challenge for decision makers as the simulation spread of a climate model ensemble can be large, and there might even be disagreement on the direction of the climate change signal among the members of the ensemble. This study quantifies changes in the hydrological projection uncertainty due to different approaches used to select a climate model ensemble. The study assesses 16 Euro-CORDEX Regional Climate Models (RCMs) that drive three different conceptualizations of the MIKE-SHE hydrological model for the Ahlergaarde catchment in western Denmark. The skills of the raw and bias-corrected RCMs to simulate historical precipitation are evaluated using sets of nine, six, and three metrics assessing means and extremes in a series of steps, and results in reduction of projection uncertainties. After each step, the overall lowest-performing model is removed from the ensemble and the standard deviation is estimated, only considering the members of the new ensemble. This is performed for nine steps. The uncertainty of raw RCM outputs is reduced the most for river discharge (5 th , 50 th and 95 th percentiles) when using the set of three metrics, which only assess precipitation means and one ‘moderate’ extreme metrics. In contrast, the uncertainty of bias-corrected RCMs is reduced the most when using all nine metrics, which evaluate means, ‘moderate’ extremes and high extremes. Similar results are obtained for groundwater head (GWH). For the last step of the method, the initial standard deviation of the raw outputs decreases up to 38% for GWH and 37% for river discharge. The corresponding decreases when evaluating the bias-corrected outputs are 63% and 42%. For the bias corrected outputs, the approach proposed here reduces the projected hydrological uncertainty and provides a stronger change signal for most of the months. Thisanalysis provides an insight on how different approaches used to select a climatemodel ensemble affect the uncertainty of the hydrological projections and, in this case,reduce the uncertainty of the future projections.

The Impact of Climate Change on Hydrological Processes of the Glacierized Watershed and Projections

Under the influence of climate change, the hydrological processes of glaciers have undergone significant changes, a fact which is seriously affecting agricultural production in the downstream region of the Tianshan Mountains, China. In order to explore the intrinsic relationship between climate change and hydrological elements, we proposed an “evaluation-driving-prediction” system to study it. First, we constructed a glacier-enhanced soil and water assessment tool model (GE-SWAT) and used a two-stage calibration method to optimize the model parameters. Next, a scenario analysis was used to evaluate the driving factors of historical runoff changes. Finally, we projected future runoff changes using bias-corrected regional climate model (RCM) outputs. The results of the case study on the Jinghe River Basin in the Tianshan Mountains show that from 1963 to 2016, total runoff increased by 13.3%, 17.7% of which was due to increasing precipitation and 1.8% of which was negated by rising temperatures. The glacier runoff increased by 14.5%, mainly due to the rising temperatures. A 3.4% reduction in snowmelt was caused by a lower snowfall/precipitation ratio, which significantly reduced the snowfall from June to August. The RCM projection indicated that the warming and humidification phenomenon in the study area will continue at least through to the mid-21st century. A consistent increase in glacier runoff and total runoff is projected, but the contribution rate of the glacier runoff will have little to no change under the RCP4.5 and RCP8.5 emission scenarios. Our research demonstrates the simulation performance of the GE-SWAT model in a basin with moderate glacier cover. This method is shown to be efficient in quantifying the impact of climate change on glacier hydrological processes and predicting future streamflow changes, providing a good research reference for similar regions.

Evaluation of four bias correction methods and random forest model for climate change projection in the Mara River Basin, East Africa

Abstract This study evaluates the performance of four bias correction methods based on CORDEX (coordinated regional climate downscaling experiment) domain six regional climate models (RCMs) at the Mara River Basin. A suitable bias correction method was considered to develop the future climate scenario. The performance of bias correction methods was evaluated by various statistical metrics based on the historical period and revealed that the distribution mapping (DM) techniques have strong performance under the different climatic conditions. The effectiveness of the DM method is found to be better at capturing the coefficient of variation and standard deviation of observed rainfall and temperature. Therefore, this study considers the future climate (2026–2095) from bias-corrected RCMs output using DM techniques. The results from bias-adjusted RCMs show an increase of rainfall (+118.3%) and temperature (+2.91) in the future climate under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. In addition, this study tested the random forest (RF) method to determine the capacity of each bias-corrected RCMs for reproducing the future rainfall and temperature under the RCP 4.5 and RCP 8.5 scenario. The results demonstrate that the RF can reproduce the climate variable with its average correlation (R2) of 0.93 for rainfall and 0.95 for temperature.

High-Resolution Ensemble Projection of Mean and Extreme Precipitation Over China Based on Multiple Bias-Corrected RCM Simulations

In this study, we used the cumulative distribution function transform to conduct a bias correction for simulations from different regional climate models (RCMs) driven by one global climate model (HadGEM2-ES). We divided the historical period into two time-frames, i.e., the calibration period and the validation period. These two periods are 1986–1998 and 1999–2011, respectively. We then choose the period from 1986 to 2005 as the calibration period. The data for the future 2006–2098 were revised and used to explore future climate change under the RCP8.5 scenario. The difference before and after bias correction were compared. The results show that the cumulative distribution function transform method can improve the simulation accuracy of RCM in terms of the average precipitation and seasonal precipitation can improve in north arid regions. For extreme precipitation and different rainfall levels, the root mean squared errors of most indexes are reduced by about 60–80% in China, and the correlation coefficients are close to 1. For future precipitation, the bias correction method could reduce the overestimation of RCM simulations, but cannot change trends of precipitation variation. Compared with the simulations before bias correction, the predicted future precipitation indicates some differences in different regions. After correction, the spread of the precipitation and the most extreme precipitation indexes was smaller than those before correction. The predicted future daily precipitation intensity was also smaller. The reduction of drought days in the arid areas is more than before the correction, and the increase days of R50 in the southern regions is larger than before the correction.

Local climate change projections and impact on the surface hydrology in the Vea catchment, West Africa

Abstract Water security has been a major challenge in the semi-arid area of West Africa including Northern Ghana, where climate change is projected to increase if appropriate measures are not taken. This study assessed rainfall and temperature projections and its impact on the water resources in the Vea catchment using an ensemble mean of four bias-corrected Regional Climate Models and Statistical Downscaling Model-Decision Centric (SDSM-DC) simulations. The ensemble mean of the bias-corrected climate simulations was used as input to an already calibrated and validated Soil and Water Assessment Tool (SWAT) model, to assess the impact of climate change on actual evapotranspiration (ET), surface runoff and water yield, relative to the baseline (1990–2017) period. The results showed that the mean annual temperature and actual ET would increase by 1.3 °C and 8.3%, respectively, for the period 2020–2049 under the medium CO2 emission (RCP4.5) scenario, indicating a trend towards a drier climate. The surface runoff and water yield are projected to decrease by 42.7 and 38.7%, respectively. The projected decrease in water yield requires better planning and management of the water resources in the catchment.

Past and future changes of the Austrian climate – Importance for tourism

The paper summarizes changes of the climate conditions in Austria impacting tourism as part of an extended literature review. The holistic approach of the study enabled to establish the physical links between emissions created by touristic activities and resultant climate responses. Since the end of the 19 th century, air temperature in Austria increased in all elevations by 1.8 °C (+20% compared to the global land areas). Depending on the scenario, a further increase of less than 2 °C (“Paris target”) to 4 °C (“worst-case scenario”; RCP 8.5) is expected until the year 2100, which means that the number of hot days either will stabilize at the current level (“Paris Target”) or current extreme years will become the new normal at the end of the century (“worst-case scenario”). Regarding snow, as the basic requirement for winter tourism, the natural snow cover duration and snow depth decreased especially in western and southern Austria. Depending on the elevation, a further decline of 10% to 40% (“Paris target”) and 50% to 90% (“worst-case scenario”), respectively, is projected until the year 2100. Sustained warming also reduces the time slots for technical snow production in all elevations. More frequent severe thunderstorms and related small-scale phenomena such as heavy precipitation, hail, squalls, small-scale floods and mudflow avalanches are to be expected to increase, especially in the worst-case scenario. Climate change effects emerge progressively in observation-based tourism-climate indicators and more sustained impacts are projected for the future. The magnitude of climate risks in the second half of the 21 st century can be substantially reduced by rapid, global climate mitigation and adaptation measures. Climatological boundary conditions in Austria have already changed and more profound, human induced changes are expected in future, further increasing impacts relevant for tourism in all seasons of the year. The following implications for tourism management can be deduced from this study: • Sector-specific, immediate and effective climate mitigation and adaptation measures are required to substantially reduce the magnitude of the major tourism relevant climate risks (recession of snow, ice and permafrost; heat stress; thunderstorms and related local extreme events; drought events) in the second half of the 21 st century. • Site- and sector-specific, tailored studies based on downscaled and bias-corrected regional climate model output should be performed to help analyze current and future business-related climate risks together with national climate service providers. • Systematic, coordinated and sector-specific awareness raising for climate change and its causes and impacts is needed to ensure acceptance and increase effectivity of mitigation and adaptation measures both for people working in tourism and the guests. • Targeted operational meteorological early warning systems need to be designed and locally implemented (heat stress; thunderstorms and related local extreme events).

The impact of land use on future water balance - A simple approach for analysing climate change effects

Regional climate change projections for Europe agree in predicting a statistically significant warming in all seasons. The most significant climate change effect is its impact on water cycle through altering precipitation patterns and evapotranspiration processes at multiple scales. The anticipated changes in the distribution and precipitation amounts together with continuously increasing temperatures may induce a higher rate of water consumption in plants, which can generate changes in soil moisture, groundwater, and the water cycle. Thus, climate change can cause changes in the water balance equations structure. A Thornthwaite-type monthly step water balance model was established to compare the water balance in three different surface land cover types: (i) a natural forested area; (ii) a parcel with mixed surface cover; (iii) an agricultural area. The key parameter of the model is the water storage capacity of the soil. Maximal rooting depth of the given area is also determinable during the calibration process using actual evapotranspiration (AET) and soil physical data. The locally calibrated model was employed for assessing future AET and soil moisture of selected land cover types using data from four bias-corrected regional climate models. The projections demonstrate increasing actual evapotranspiration values in each surface cover type at the end of the 21st century. Regarding the 10th percentile minimum soil moisture values, the forested area displayed an increasing trend, while the agricultural field and mixed parcel showed a strong decrease. The 30-year monthly means of evapotranspiration shows the maximum values in June and July, while the minimum soil moisture in September. Water stress analysis indicates water stress is expected to occur only in the agricultural field during the 21st century. The comparison of the three surface covers reveals that forest has the greatest soil water storage capacity due to the highest rooting depth. Thus, according to the projections for 21st century, less water stress is predicted to occur at the forested area compared to the other two surface covers which shows shallow rooting depth.

Assessing the impacts of climate change on hydrological regimes and fish EQR in two Danish catchments

Study regionTwo large-scale catchments in Denmark: Ringkøbing fiord and Mid-Zealand catchments. Study focusFuture changes in hydrological regime, extremes, groundwater levels and ecological quality ratio (EQR) for fish were assessed. Based on an ensemble of 17 bias-corrected regional climate models forced by the emission scenario RCP8.5, a dry, a medium and a wet model were identified for the future period 2071–2100. Changes in water balances for catchments, impacts on groundwater level and fish ecological quality ration (fish EQR) were evaluated. The impact changes were based on an integrated, transient, coupled groundwater and surface-water flow model, set up with a horizontal resolution of 200m × 200m for the two catchments. New hydrological insights for the regionStrengths and weaknesses of EQR assessments based on symbolic regression methods compared to expert assessments based on flow calendar and max flow changes in percent exceedance thresholds (Q95) were identified. While the modelled impact of climate change on monthly flow and flow calendar follows the same pattern at all monitoring stations, the impact on groundwater level and fish EQRs are more complex, and somewhat ambiguous across realisations and catchments.

Evaluation of the performance of bias-corrected CORDEX regional climate models in reproducing Baro–Akobo basin climate

The applicability of the regional climate model (RCMs) for catchment hydroclimate is obscured due to their systematic bias. As a result, bias correction has become an essential precondition for the study of climate change. This study aimed to evaluate the skill of seven rainfall and five maximum and minimum temperature RCM outputs against observed data in simulating the characteristics of climate at several locations over the Baro–Akobo basin in Ethiopia. The evaluation was performed based on raw and bias-corrected RCMs against observed for a long-term basis. Several statistical metrics were used to compare RCMs against observed using a pixel-to-point approach. In this finding, raw RCMs showed pronounced biases such as lower correlation and higher PBIAS in estimating rainfall and minimum temperature than maximum temperature. However, most RCMs after bias correction showed better performance in reproducing the magnitude and distribution of the mean monthly rainfall and temperature and improve all the statistical metrics. The Mann–Kendall trend test for observed and bias-corrected RCMs indicated a decreasing annual rainfall trend while the maximum and minimum temperature showed an increasing trend in most stations. In most statistical metrics, the ensemble mean resulted in better agreement with observation than individual models in most stations. In general, after bias correction, the ensemble adequately simulates the Baro–Akobo basin climate and can be used for evaluation of future climate projections in the region.

Modelling hydrological processes under climate change scenarios in the Jemma sub-basin of upper Blue Nile Basin, Ethiopia

This study examines the response of hydrological processes to different climate change scenarios in the Jemma sub-basin of the Blue Nile Basin. Future near-term (2021–2050) and long-term (2071–2100) climate scenarios were developed from six statistically bias corrected Regional Climate Models (RCMs) under two Representative Concentration Pathways (RCPs) scenarios: RCP4.5 and RCP8.5. The outputs of climate models were used as input to a calibrated and validated Soil and Water Assessment Tool (SWAT) model to assess the impact of climate change on the hydrology of the sub-basin. For a robust hydrologic representation, the SWAT model was calibrated and validated at three River gauging stations and provided an acceptable result. The climate scenarios developed from bias corrected RCMs projected an increase in temperature in all models and a decrease in rainfall in the ensemble mean of the models in the near-term and long-term climate scenarios. Climate change may cause a consistent decrease in surface runoff and total water yield and an increase in evapotranspiration under all climate scenarios. This study recommends water management structures which can conserve water for agriculture and other ecosystem services in the Jemma sub-basin and in other similar areas in Ethiopia.

Climate change impacts on the water and groundwater resources of the Lake Tana Basin, Ethiopia

AbstractClimate change impacts on the water cycle can severely affect regions that rely on groundwater to meet their water demands in the mid- to long-term. In the Lake Tana basin, Ethiopia, discharge regimes are dominated by groundwater. We assess the impacts of climate change on the groundwater contribution to streamflow (GWQ) and other major water balance components in two tributary catchments of Lake Tana. Based on an ensemble of 35 bias-corrected regional climate models and a hydrologic catchment model, likely changes under two representative concentration pathways (RCP4.5 and 8.5) are assessed. No or only slight changes in rainfall depth are expected, but the number of rainy days is expected to decrease. Compared to the baseline average, GWQ is projected to decrease whereas surface runoff is projected to increase. Hence, rainfall trends alone are not revealing future water availability and may even be misleading, if regions rely heavily on groundwater.

Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin.

The Upper Indus Basin (UIB) is a major source of supplying water to different areas because of snow and glaciers melt and is also enduring the regional impacts of global climate change. The expected changes in temperature, precipitation and snowmelt could be reasons for further escalation of the problem. Therefore, estimation of hydrological processes is critical for UIB. The objectives of this paper were to estimate the impacts of climate change on water resources and future projection for surface water under different climatic scenarios using soil and water assessment tool (SWAT). The methodology includes: (i) development of SWAT model using land cover, soil and meteorological data; (ii) calibration of the model using daily flow data from 1978 to 1993; (iii) model validation for the time 1994–2003; (iv) bias correction of regional climate model (RCM), and (v) utilization of bias-corrected RCM for future assessment under representative concentration pathways RCP4.5 and RCP8.5 for mid (2041–2070) and late century (2071–2100). The results of the study revealed a strong correlation between simulated and observed flow with R2 and Nash–Sutcliff efficiency (NSE) equal to 0.85 each for daily flow. For validation, R2 and NSE were found to be 0.84 and 0.80, respectively. Compared to baseline period (1976–2005), the result of RCM showed an increase in temperature ranging from 2.36°C to 3.50°C and 2.92°C to 5.23°C for RCP4.5 and RCP8.5 respectively, till the end of the twenty-first century. Likewise, the increase in annual average precipitation is 2.4% to 2.5% and 6.0% to 4.6% (mid to late century) under RCP4.5 and RCP8.5, respectively. The model simulation results for RCP4.5 showed increase in flow by 19.24% and 16.78% for mid and late century, respectively. For RCP8.5, the increase in flow is 20.13% and 15.86% during mid and late century, respectively. The model was more sensitive towards available moisture and snowmelt parameters. Thus, SWAT model could be used as effective tool for climate change valuation and for sustainable management of water resources in future.

Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland

We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021–2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070–2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the ‘low concentration’ RCP 4.5 scenario.

Nossana Spring (Northern Italy) under Climate Change: Projections of Future Discharge Rates and Water Availability

Nossana represents an important pre-Alpine karst spring for drinking supply, sustaining a water distribution system serving 300,000 people. The goal of this study was to project Nossana discharges and evaluate potential supply limits for four future periods (2021–2040, 2041–2060, 2061–2080, 2081–2100). Bias-corrected Regional Climate Models (RCMs), part of the EURO-CORDEX experiment and forced by three emission scenarios (RCP2.6, RCP4.5, RCP8.5), were evaluated, statistically downscaled, and used as input in a calibrated rainfall-runoff model ensemble. For each emission scenario, the calibrated model ensemble considered three RCMs and ten rainfall-runoff parameterizations. Projected ensemble mean discharges are lower than observations (3%–23%) for all RCPs, though they do not show a clear trend between the four time periods. Days characterized by discharges lower than actual water demand are projected to decrease, except for the RCP8.5 emission scenarios and the period 2081–2100. Conversely, the same consecutive days are expected to increase after 2060 for all emission scenarios. These results reflect the projected precipitation trend, characterized by longer, drier summer periods and wetter autumns in comparison to today’s climate. Also, they indicate a possible need for alternative drinking water resources. The proposed methodology was demonstrated to deliver useful quantitative information for water management in the mid- long-term period.

Simulating the Impacts of Climate Change on Sugarcane in Diverse Agro-climatic Zones of Northern India Using CANEGRO-Sugarcane Model

CANEGRO-Sugarcane model was used to assess the impact of climate change on sugarcane in different combinations of elevated temperature and CO2 concentrations. Additionally, we used dynamically downscaled bias-corrected regional climate model (RCM) data using RegCM4 under RCP4.5 scenario (2040–2060) to project the future change in sugarcane stalk fresh mass (SFM) and sucrose mass (SM). The results showed an increase in temperature, rainfall and solar radiation in the future projections at the study site. The SFM and SM were found to be vulnerable (3–25% decrease) by increasing temperature (1–4 °C), however, a higher concentration (2–14% increase) was observed for both SFM and SM under elevated CO2 levels (450–850 ppm). The combined effect of increased temperature and elevated CO2 had a beneficial effect on SFM but negative on SM (more for rainfed condition). Overall, SFM was projected to increase by 3–39% (rainfed) and 7–47% (irrigated) in 2040–2060 relative to 1971–2000 in diverse agro-climatic zones of the region. Similarly, SM was projected to decrease by 9–69% (rainfed) and 6–37% (irrigated). In general, water stress conditions combined with the projected increase in temperature adversely affected the sugarcane. The findings suggest the development of a efficient water use, heat-tolerant cane variety and improved farm management strategies in the near future to assist the sugar industry and to adapt to the changing climate in northern India. This is required in the greater perspective of decrease in sucrose mass in spite of double-fold increase in CO2.