Land suitability for viticulture under present and future climate conditions: Sardinia as a regional case study

Seasonal droughts are a common feature of the Iberian climate. They can have severe socioeconomic and ecological impacts – especially, when recurring in consecutive years. We investigate the recurrence of extreme drought events in the Iberian Peninsula (IP) for the past decades and in regional climate change projections. With this aim, we introduce and apply a new set of indices: the Recurrent Dry Year Index (RDYI) and the Consecutive Drought Year (CDY) Index. For the present climate, different gridded observational and reanalysis datasets at several spatial resolutions (10 to 25 km) are used. To analyse the potential impacts of climate change, we apply the indices to a large EURO-CORDEX multi-model ensemble with 12 km horizontal resolution consisting of 25 different global-to-regional model (GCM-RCM) chains for the historical period and future periods along the RCP8.5 scenario. Results show that the IP is regularly affected by extreme droughts under present climate conditions, with roughly three individual events per decade. Especially the southern and central parts of IP are exposed to recurrent events, which last between two and six years. Under different global warming levels (GWLs), results reveal a general tendency towards more severe drought conditions. Moreover, recurrent drought events are projected to occur more frequent and last longer (up to 14 years). While the ensemble mean responses are only moderate for a GWL of +2°C (compared to the pre-industrial average), recurrent drought conditions are strongly enhanced for the +3°C GWL. The climate change signals are robust for most of IP and the considered recurrent drought indices, with a larger model agreement for the +3°C GWL. For both present and future climate conditions, results show some sensitivity on the choice of index and dataset. We conclude that the new indices are suitable for the detection and evaluation of recurrent drought events under present and future climate conditions. With ongoing climate change, the Iberian Peninsula faces an increased risk of recurrent drought events. If global warming should exceed the +3°C threshold, the majority of models projects an almost permanent state of drought – with severe consequences for the Iberian population and ecosystems.

Future energy-optimised buildings — Addressing the impact of climate change on buildings

Green buildings (GBs) employ a wide range of passive and active energy-saving strategies to improve buildings’ energy performance. The suitability and performance of some of these strategies depend on outdoor climate conditions and may change over time due to global warming. Therefore, a GB may not retain its performance in the future. To address this issue and explore how much GB performance may be affected by climate change, this research aims to (1) evaluate the energy performance and thermal comfort of a GB and non-GB under present climate conditions; (2) predict the impact of climate change on these buildings, and (3) evaluate the climate resilience of a GB as opposed to a non-GB. To this end, a university GB and non-GB are simulated using DesignBuilder and calibrated with measured data. Future weather files based on Representative Concentration Pathways (RCPs) are used to predict climate conditions in the 2050s and 2090s. A comparison between the GB and non-GB revealed that the GB would save 15.1% and up to 21.9% of site energy under present and future climate conditions, respectively. It was also found that the thermal comfort level in the GB will remain significantly higher than in the non-GB in the future. The overheating issue in non-GBs will deteriorate in the future, with an increase of nearly 70% by the 2090s. The GB produces approximately 15% and up to 22% fewer GHG emissions than the non-GB under present and future climate conditions (RCP 8.5), respectively.

<p>We present findings from an analysis of weather regimes over the North Atlantic and Europe in present and future climate conditions. Weather regimes strongly influence the statistical distribution of surface weather variables. We use a recently developed, all-season North Atlantic - European weather regime classification with seven regimes. These regimes were originally identified in ERA-Interim reanalyses and, in this study, we investigate how they are represented in climate simulations using the CESM1 large ensemble for present-day and future (RCP8.5) climate conditions. With these regimes, the classification of the flow conditions in the considered region goes beyond the classical categorization according to the North Atlantic oscillation index; the weather regimes explicitly capture different flavors of strong zonal flows and the occurrence of blocking over Greenland, Scandinavia, and Central Europe, respectively. In ERA-Interim they explain 70% of the variability in geopotential height at 500 hPa year-round. Our analysis quantifies how well CESM1 represents the statistics of the weather regimes in present-day climate and how strongly their frequencies change in the future climate scenario. In addition, we identify statistical relationships between weather regimes and their resulting impacts on spatial patterns of surface variables such as precipitation. We compare those patterns and characteristics of the weather regimes identified in ERA-Interim to their characteristics in simulations of present and future climate conditions.</p><p>This analysis leads to insight into the representation of and changes in atmospheric circulation in one particular climate model, and, at the same time, it quantifies how well the climate model captures the observed link between surface weather and weather regimes. This approach contributes to improving our understanding of atmospheric circulation changes and their impact on a regional scale, and it may benefit the interpretation and communication of climate projections.</p>

This study aims to apply large-scale climate ensemble simulation data to evaluate the magnitude of extreme rainfall events. It was conducted on the basis of extreme rainfall that occurred in the Hiroshima region in 2018. This event recorded an extreme rainfall magnitude corresponding to a return period of 1,000 years at a 24-h rainfall duration; it is difficult to evaluate this magnitude with the concept of probability rainfall based on frequency analysis due to the short observation period. To overcome this limitation, the data for policy decision making for future (d4PDF) climate change database based on a large-scale climate ensemble simulation was used. These data provided 3,000 annual maximum daily rainfall values, which were used to empirically estimate the probability rainfall with a return period of 10-1,000 years based on a non-parametric approach without statistical methods. The estimated probability rainfall of the d4PDF was compared with the estimated probability obtained from the observed rainfall and frequency analysis. The difference between the two probability rainfall values was 3.53% for the return period of 50 years. However, as the return period increases, the error increases to more than 10%. This indicates that the estimation of the probability rainfall with a long-term return period using the observed data of a relatively short period may present uncertainties. Regarding the probability rainfall using d4PDF under present climate conditions, the Hiroshima event represented a return period of nearly 300 years. Meanwhile, for the probability rainfall using the d4PDF under future climate conditions, the Hiroshima event had a return period of nearly 100 years. Consequently, the magnitude of the probability rainfall increased in future climate conditions, and the probability of the occurrence of extreme rainfall corresponding to the Hiroshima event increased from 0.33% to 1%. Therefore, d4PDF can be used to quantitatively evaluate the magnitude of extreme rainfall events under present and future climate conditions.

Due to a strong urbanization in Belgium, a lot of areas can be considered as particularly vulnerable to heat waves due to the urban heat island (UHI) effect. However, little information exists on the interaction between the urban heat island effects during heat waves and their interactions under present and future conditions. The heat wave definition and heat stress index chosen in this study are based upon the warnings issued by the Public Health of Belgium for the Brussels Capital Region. For this study, regional simulations were performed using the limited area model ALARO, coupled with the Town Energy Balance scheme. The offline air quality simulations are calculated using the CHIMERE model. Results from our observations and climate simulations indicate that for the present climate conditions night time UHI is enhanced during heat waves which affects also urban and rural surface energy balance differently. The projected climate change under scenario A1B for 2050 leads to an increase of the number and duration of heat waves. More specifically, for rural (urban) areas, climate change increases the intensity of heat waves more during the day (night). We will also look more closely to the effect these changes have on air quality when taking the present and future climate scenarios under consideration. There is a significant increase in the number of days for which ozone concentrations exceed the warning threshold during heat waves. Besides the urban scale we will also investigate the impact of this configuration on air quality for the rural scale under present and future climate conditions.

One of the major tasks of climate models is the description of precipitation characteristics. Many complex physical mechanisms are involved, and the corresponding parameterizations lead to more important differences among models for both present climate and climate change conditions than what is obtained for temperature analysis. Extreme precipitation events are more scarce, and therefore, differences are even larger. These processes are very relevant for impact studies, both when dealing with heavy precipitation events and also with drought conditions or dry spell description. But studies focused on dry spell analysis have received much less attention, compared with the ones related to large precipitation conditions. Present climate conditions already indicate important risks related to aridity over many areas of the world, and they are projected to be increased for future climate conditions. One good example of a region with these kind of risks is the Iberian Peninsula, where agricultural and socioeconomic impacts of water supply deficits are already a very relevant feature. The modeling results indicate that future climate will increase the mean and largest dry periods over most of the Iberian Peninsula, with a gradient of increase that is larger on the south and smaller on the north, therefore increasing the latitudinal contrast with respect to present climate. Regional features over certain basins and coasts are reproduced by the regional models, but not for the global climate model. Thus, future climate conditions point to a more severe hydrological stresses over several regions in the Iberian Peninsula.

Abstract. Tropical cyclones (TCs) are projected to increase in intensity globally, impacting human lives; infrastructure; and important agricultural activities, such as banana production. Banana production is already impacted by TCs in several parts of the world, leading to price volatility and impacted livelihoods of banana producers. While many potential impacts on banana production have already been quantified on a local scale, it remains unclear how bananas could be impacted by TCs across the globe under present and future climate conditions. To address this, we first looked at the documented impacts of TCs on banana production from different places all around the world. Using spatially explicit data on banana-producing regions and future TC occurrence and magnitude, we then identified the spatial distribution and extent of areas where TCs could impact banana production. Our results suggest that considerable portions of global banana production are at risk of being impacted by TCs under present and future climate conditions, and we show this for different return periods. Globally, 24.3 % of all banana-producing areas are projected to suffer major or complete (>84 %) damage under current climate conditions, increasing to 26.5 % under future climate scenarios at the 100-year wind speed return period. The regions experiencing the most notable increases in majorly damaged area under future conditions are the Caribbean (9.3 %), the Middle East and North Africa (36 %), and Southeast Asia (21.9 %). The most profound decreases in majorly damaged area are found in Central America (−35.8 %) and East Asia (−7.6 %). The most substantial change in completely damaged area is observed in East Asia, Southeast Asia and Oceania. Additionally, we estimate that 30.1 % of global production under current conditions and 31.1 % under future conditions will be majorly or completely damaged at the 100-year return period. The regions predominantly affected in the future are Asia and the Caribbean, potentially experiencing substantial disruption in banana production. Our results therefore indicate that considerable efforts in climate adaptation are essential to ensure the stability of global banana supply chains.

In this study, we investigated the impacts of land use alterations from harvesting practices on the regional surface climate over the North China Plain. The surface climate responses after harvest in June in regions where double‐cropping is practiced were evaluated using observations and model simulations with the global climate model HadGEM2‐Atmosphere. Responses were modeled under both present and possible future climate conditions. In the model, double‐cropping was represented using the monthly varying fraction of vegetation. This contributed to an improvement in the model simulation over East Asia. Modeling results showed that the land surface was warmer and drier after harvest, and these simulation results were consistent with observations. The bare soil surface after harvest in June had biophysical impacts on the surface climate that were mediated by decreasing evapotranspiration and latent heat flux effects, which increased surface air temperatures and decreased surface humidity. An increase in shortwave radiation also contributed to the rise in temperatures. Under two Representative Concentration Pathways (RCP) scenarios for possible future climate conditions, land conversion induced additional warming in addition to greenhouse gases induced global warming. The RCP 8.5 and RCP 2.6 scenarios demonstrated a warming of 1.0°C and 1.4°C due to harvesting practices in June, respectively. The response magnitude was affected by the climate conditions in each RCP. Our results suggest that potential impacts of harvest on the local climate need to be considered in future projections of CO2‐induced warming on a regional scale.

Climate change and air quality research are closely related research areas that have often been investigated with different objectives. However, addressing both topics as a joint approach can lead to synergies and help to avoid counteracting effects, where mitigating one may exacerbate the other. The convergence of methods and approaches is necessary to consider on the one hand the climate trend and forcing in mitigation scenarios applied by the air quality community and on the other hand to better understand and describe the impact of short-lived climate pollutants on the regional climate.The project FOCI aims to analyse non-CO2 forcings on both climate and air quality and therefore requires a joint approach. A core task of the project is the application of regional climate and urban scale models driven by global earth system models to describe continental to urban scale air quality under present and future climate conditions. The results of these processes will be used to investigate possible mitigation and adaptation scenario options.The present and future anthropogenic emissions required for such model investigations need to be consistent with CMIP6 historical climate reconstruction and future scenario simulations. CMIP6 has been based on CEDS emissions that are therefore the necessary reference for FOCI activities. One critical aspect is that pollutants considered in CEDS do not include particulate matter (PM2.5 and PM10), but only its black carbon (BC) and organic carbon (OC) components. This is understandable considering the objective for which CEDS has been built, but it would cause a significant underestimation of particulate matter concentrations and raises the need to define a method to estimate the non-speciated PM2.5 and PM10 emissions from the available information.In order to derive PM emissions for CEDS we investigate a number of approaches based on the use of different proxies from the EDGAR database. In particular, we consider the feasibility of deriving PM2.5 from BC and OC as the main components of fine particulate matter. For emission sectors where BC and OC is not available in the emission inventories, we explore the possibility of using alternative proxies including NOx. By combining the different approaches we derive PM2.5 emissions for CEDS at a spatial grid resolution of 0.1 degree and compare these for each main emissions sector.These estimated dataset of consistent CEDS and particulate matter emissions are used in the FOCI project numerical models to describe continental to urban scale air quality under present climate conditions. We also discuss the implications of employing our approach to derive consistent emissions for particulate matter in conjunction with SSP emission data for projections to ultimately evaluate the impact of key radiative forcers on climate and societal systems.

Bangladesh is a highly disaster prone flat land country in south Asia. 80% of the disaster comes from cyclonic disaster around this area. To investigate the damage risk due to the cyclonic event around the Bay of Bengal associated with the cyclone track (CT) is an important issue. The present study has extensive analysis on generating a most favorable track along the Bay of Bengal from the MRI-AGCM cyclone track data. We have investigated present (1978-2003) and future (2075-2099) track data from the MRI-AGCM data set to ensure the synthetic track for the present and future climate conditions of Bangladesh. A k-mean clustering technique has been applied to investigate the synthetic track for the present and future climate condition. This work may insight the changes in cyclone track patterns in both the present and future climate conditions with the global warming scenario. This study has found that the Sundarbans and its adjacent areas are the risky coastline area of the landfall zone and for the global warming scenario it will be shifted to the Odisha area in India.

Abstract. Many studies have investigated potential climate change impacts on regional hydrology; less attention has been given to the components of uncertainty that affect these scenarios. This study quantifies uncertainties resulting from (i) General Circulation Models (GCMs), (ii) Regional Climate Models (RCMs), (iii) bias-correction of RCMs, and (iv) hydrological model parameterization using a multi-model framework. This consists of three GCMs, three RCMs, three bias-correction techniques, and sets of hydrological model parameters. The study is performed for the Lech watershed (~ 1000 km2), located in the Northern Limestone Alps, Austria. Bias-corrected climate data are used to drive the hydrological model HQsim to simulate runoff under present (1971–2000) and future (2070–2099) climate conditions. Hydrological model parameter uncertainty is assessed by Monte Carlo sampling. The model chain is found to perform well under present climate conditions. However, hydrological projections are associated with high uncertainty, mainly due to the choice of GCM and RCM. Uncertainty due to bias-correction is found to have greatest influence on projections of extreme river flows, and the choice of method(s) is an important consideration in snowmelt systems. Overall, hydrological model parameterization is least important. The study also demonstrates how an improved understanding of the physical processes governing future river flows can help focus attention on the scientifically tractable elements of the uncertainty.

<p>The climate of the city of Tønsberg in Norway is cold and humid. As a result, the brick-made historic buildings in this city are threatened by frost damage. Climate change is expected to affect the action of this degradation mechanism. In the current research, climate data resulting from the REMO2015 driven by the global model MPI-ESM-LR were used for periods 1960-69, 2010-2019, and 2060-69 representing the past, present, and future climate conditions. In addition, data from the ERA5 reanalysis for the present conditions, 2010-19, were used to assess the accuracy of the climate model data. Given the climate excitations, the freeze-thaw events were calculated according to two climate indices, i) the events of temperature decrease below 0<sup>o</sup>C and ii) by considering that freezing occurs below -3<sup>o</sup>C and thawing occurs above 1<sup>o</sup>C. Moreover, a material response-based index that takes into account the temperature and the moisture content of a 5mm layer in the exterior side of the wall assembly was calculated. Prior to its calculation proper hygrothermal simulations were performed. According to this index, the critical temperature and degree of saturation that characterize a freeze-thaw event are 0<sup>o</sup>C and 25%, respectively. From the climate model data and the first climate index, the 0<sup>o</sup>C crossings that were calculated are 400, 340, and 223 under the past, present, and future conditions, respectively. The respective number of the freeze-thaw events that were calculated by using the second climate index are 49, 31, and 27 which are significantly lower. From the data obtained from the ERA5 reanalysis, the number of freeze-thaw events that were calculated is 425 and 123 for the first and the second climate index, respectively. This difference is attributed to the underestimation of the air temperature in the climate model data, which results in a lower number of temperatures hovering around the examined thresholds during winter. The results of the material response-based index show a minor frost risk for the brick-made wall assemblies which is reduced through the years. The southeast-oriented walls were the ones with the highest exposure to driving rain and the greatest frost damage risk. For this orientation, the number of freeze-thaw events was 6, 3, and 2 under past, present, and future conditions, respectively. Moreover, according to the ERA5 reanalysis, only 1 freeze-thaw event was calculated. This is attributed to the fact that the climate model overestimates significantly the precipitation and the relative humidity compared to the ERA5 reanalysis. In conclusion, it is worth mentioning that both the climate-based and the material response-based indices define a decreasing trend of the frost damage risk of historic brick-made walls due to climate change. The use of the material response-based index is suggested for a more accurate assessment of the frost damage which can further support proper adaptation measures. Finally, the quality of the results can be improved by using climate data from more climate models and applying bias correction or morphing methodologies on the climate files to avoid systematic errors.</p>

River discharge forms a major freshwater input into the Arctic Ocean, and as such it has the potential to influence the oceanic circulation. As the hydrology of Arctic river basins is dominated by cryospheric processes such as snow accumulation and snowmelt, it may also be highly sensitive to a change in climate. Estimating the water balance of these river basins is therefore important, but it is complicated by the sparseness of observations and the large uncertainties related to the measurement of snowfalls. This study aims at simulating the water balance of the Barents Sea drainage basin in Northern Europe under present and future climate conditions. We used a regional climate model to drive a large-scale hydrological model of the area. Using simulated precipitation derived from a climate model led to an overestimation of the annual discharge in most river basins, but not in all. Under the B2 scenario of climate change, the model simulated a 25% increase in freshwater runoff, which is proportionally larger than the projected precipitation increase. As the snow season is 30–50 day shorter, the spring discharge peak is shifted by about 2–3 weeks, but the hydrological regime of the rivers remains dominated by snowmelt.

Linking sinuosity, a fairly recently developed metric, with high temperature extremes (HTEs) can be both useful and insightful to better understand the physical mechanisms behind HTEs. However, it is not clear whether there exists a relationship between the sinuosity changes and HTE changes in present and future climate conditions over southeastern China. In this paper, the anomalous characteristics of the atmospheric circulation are quantified by sinuosity. Three sinuosity metrics are used in this study: individual sinuosity (SIN), aggregate sinuosity (ASIN), and comprehensive sinuosity (CSIN). Furthermore, we examine the relationship between sinuosity changes and HTE changes in present and future climate conditions. ASIN is strongly correlated with surface air temperature (SAT). We find that the influence of individual sinuosity (SIN) at different latitudes on the SAT of southeastern China is different. The SIN of low (middle) latitude isohypses has significant positive (negative) correlations with the SAT of southeastern China. The SIN of high-latitude isohypses is rather limited and can therefore be ignored. The projected relationship between the sinuosity changes and HTE changes in the late 21st century suggests similar results. The change in SAT is related to the changes in climate variables over southeastern China in the future, and these changes increase with the increase in Z500 or V850 and the decrease in U500. Moreover, the frequencies of large (small) comprehensive sinuosity (CSIN) values at low (mid) latitudes will increase. At the end of the 21st century, Z500 isohypses at different latitudes will have an obvious poleward shift. Our results indicate that measuring the aggregate waviness of the midtropospheric flow (via sinuosity) can provide insight regarding HTEs, and the climate model output can be used to examine the future likelihood of increased HTE.