Greenhouse Gas Concentration Scenarios Research Articles

Očekivano toplinsko opterećenje Dubrovnika, Osijeka, Rijeke, Zadra i Zagreba prema projekcijama regionalnih klimatskih modela

This paper examines the expected future heat load in five Croatian cities: Dubrovnik, Zadar, Rijeka, Zagreb, and Osijek. The heat load is estimated by temperature-related climate indices and mean, maximum and minimum daily temperatures obtained by climate simulations using two different regional climate models (DHMZ-RegCM4 and SMHI-RCA4) with a horizontal resolution of 12.5 km, forced with two global climate models (EC-EARTH and MPI-ESM-MR/LR) for two different greenhouse gas concentration scenarios (RCP4.5 and RCP8.5). By comparing these variables for the period 2041–2070 with respect to the current climate (defined as that of the period 1991–2020), a significant increase in mean, maximum and minimum temperatures was observed in all analysed combinations of regional and global climate models for all analysed cities. Although there is a difference in results depending on the combination of regional and global models, the largest increase is mainly found in the warm part of the year (April-October), with the strongest warming of Dubrovnik and Rijeka. Due to similar trends in minimum and maximum temperatures, the trend in the daily temperature range is weak. Under warmer climate conditions, the number of days with a maximum air temperature above 25 °C increases in all considered cities (especially in Dubrovnik), as does the number of days with a minimum air temperature exceeding 20 °C (especially in Rijeka and Zadar). Furthermore, a reduction in the number of days with maximum and minimum temperatures below 0 °C is projected for all cities. Nevertheless, some differences are found between coastal and inland cities caused by local factors.

Soil moisture precipitation feedbacks in the Eastern European Alpine region in convection-permitting climate simulations.

A novel convection permitting modelling framework that combines a pseudo-global warming approach with continuously forced deep soil moisture from prescribed perturbation storylines is applied in the Eastern European Alpine region and parts of the Pannonian Basin to investigate soil moisture precipitation (SMP) feedbacks on summertime precipitation and the feedbacks' role under changed climate conditions. A set of 1-year convection-permitting (3 km horizontal grid spacing) soil moisture sensitivity simulations with the regional climate model of the Consortium for Small-Scale Modelling in Climate Mode are conducted. In order to account for global warming, end-of-the-century climate change effects from four global climate models, projecting the greenhouse gas concentration scenario RCP 8.5, are imprinted. The simulations reveal that (1) the locations of precipitation events are highly sensitive to soil moisture modifications while intensities and the internal structure of precipitation events are nearly unaffected and (2) high precipitation intensities are more likely in combinations with positive temporal but distinctive (either strong positive or strong negative) spatial SMP coupling. Low precipitation intensities are in favour of combinations of negative temporal and positive spatial coupling. The analyses suggest that soil moisture at a given time acts as a guiding field for the location of the next precipitation event. Interestingly, this behaviour is independent of climate change, although the coupling strength's increase is 1.5-1.7 times larger than expected from linear climate change scaling when climate becomes 50% dryer. Finally, it is found that (1) local deviations in the climate change signal of summertime precipitation in the range of up to ±40% are caused by uncertainty in deep soil moisture in the range of ±10% and (2) these local deviations in the climate change signal are dominated by soil moisture uncertainty in future climate conditions.

Climate of Syria Based on Cordex Simulations: Present and Future

AbstractRegional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional climate models from the Coordinated Regional Climate Downscaling Experiment programme integrated over the following three CORDEX domains: AFR, MNA and WAS. Four meteorological variables (temperature, precipitation, solar radiation and cloud cover) were evaluated over Syria at a grid spacing of 0.44°. The performance of five models in simulating the present climate characteristics (1989–2008) is evaluated with respect to the observations: CRU, ERA5 reanalysis and SARA and CLARA satellite data. We find that the mini-ensemble captures well the general spatial patterns and annual cycles of the selected variables. Anotheraim of this study was to assess the expected change of the mentioned four climate variables over Syria under the moderate emission scenario (RCP4.5) and the high emission scenario (RCP8.5) in the near future (2031–2050) and in the far future (2080–2099) with respect to the present climate (1989–2008). The simulations show a decreasing trend in cloud cover (between 6% and 10%) and precipitation (up to 9%) by mid and late century, regardless of the forcing scenarios. The simulations show a pronounced warming over Syria, which is expected to reach 6 °C by the end of the twenty-first century following the high greenhouse gas concentration scenario (RCP8.5). Furthermore, such an increase, combined with a decrease in precipitation, will shift Syria’s climate towards a more arid one.

Microplitis manilae Ashmead (Hymenoptera: Braconidae): Biology, Systematics, and Response to Climate Change through Ecological Niche Modelling

The parasitoid wasp Microplitis manilae Ashmead (Braconidae: Microgastrinae) is an important natural enemy of caterpillars and of a range of noctuids, including pest species of armyworms (Spodoptera spp.). Here, the wasp is redescribed and, for the first time, illustrated based on the holotype. An updated list of all the Microplitis species attacking the noctuid Spodoptera spp. along with a discussion on host-parasitoid-food plant associations is offered. Based on information about the actual distribution of M. manilae and a set of bioclimatic variables, the maximum entropy (MaxEnt) niche model and the quantum geographic information system (QGIS) were explored to predict the potential distribution of this wasp in a global context. The worldwide geographical distribution of potential climatic suitability of M. manilae at present and in three different periods in the future was simulated. The relative percent contribution score of environmental factors and the Jackknife test were combined to identify dominant bioclimatic variables and their appropriate values influencing the potential distribution of M. manilae. The results showed that under current climate conditions, the prediction of the maximum entropy model highly matches the actual distribution, and that the obtained value of simulation accuracy was very high. Likewise, the distribution of M. manilae was mainly affected by five bioclimatic variables, listed in order of importance as follows: precipitation during the wettest month (BIO13), annual precipitation (BIO12), annual mean temperature (BIO1), temperature seasonality (BIO4), and mean temperature during the warmest quarter (BIO10). In a global context, the suitable habitat of M. manilae would be mainly in tropical and subtropical countries. Furthermore, under the four greenhouse gas concentration scenarios (representative concentration pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in the future period of the 2070s, the areas with high, medium, and low suitability showed varying degrees of change from current conditions and are expected to expand in the future. This work provides theoretical backing for studies associated with the safeguarding of the environment and pest management.

Projected expansion of hottest climate zones over Africa during the mid and late 21st century

Projected shifts in thermal climate zones over Africa during the mid and late 21st century are assessed by employing the Thornthwaite thermal classification applied to 40 CMIP6 global climate models under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 forcing scenarios. The CMIP6 multimodel ensemble mean reproduces the observed pattern of thermal zones during the reference period, albeit with some discrepancies. The projections reveal a gradual expansion of the hottest thermal type consisting of a northward and southward displacement of torrid climate zones, with this effect intensifying as greenhouse gas (GHG) forcing increases and the time horizon moves from the mid to the end of the century. In particular, the Mediterranean region, almost all southern African countries, part of East Africa and most Madagascar predominantly warm in present-day conditions, are projected to face mostly hot climates in the mid—21st century and torrid by the end of the 21st century in the high-end forcing scenario. Generally, in the mid—21st century, torrid climates expand by up to ∼15%, 20% and 27% of total Africa’s land areas for the SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively, with these fractions increasing to ∼16%, 28% and 42% in the late 21st century. Therefore, at the end of the 21st century for the high-end GHG concentration scenario, the African continent will be covered by 81%–87% of torrid climate type, which will have enormous impacts on the sustainable development of African countries.

Risk analysis of impacts of climate change on changes in municipal wastewater production in wastewater reuse plans

ABSTRACT Long-term changes in municipal wastewater production may disrupt wastewater reuse plans. However, no model/method has been developed to quantify the risks of climate change impacts on changes in wastewater production under relevant uncertainties. Accordingly, this research proposed a hybrid algorithm to analyze these risks under greenhouse gas concentration scenarios. This algorithm included a fuzzy risk assessment model based on six risk components and a framework for quantification of these components, which increased the relative confidence of decision-makers about risk values by 10%. The results showed that ‘considering’ and ‘ignoring’ the adaptive capacity to climate change under Representative Concentration Pathway scenarios in the risk analysis process lead to two completely different interpretations of risk. The risk difference based on these two approaches for Tehran was 50%, which was due to the occurrence of 11%–22% of untreated excess wastewater beyond capacity of wastewater reuse system under the temperature increase of 1.29°C.

Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator

Abstract Since many new generation Earth system models (ESMs) have been suggested to overestimate future global warming, the latest report of the Intergovernmental Panel on Climate Change used the constrained range of global warming instead of that in the raw ensemble. However, it is not clear how the constraints of climate change projections potentially reduce the uncertainty of impact assessments. Here, we show that the climate-related uncertainty of the economic impact of climate change in the world can be constrained. By applying an impact emulator, we estimate the economic impacts in nine sectors based on 67 ESMs’ future climate change projections and find that the impacts in eight sectors are closely related to the recent past trend of global mean temperature, which is the metric used for the constraint of global warming projections. Observational constraints lower the upper bound of the aggregate economic impact simulated by the single emulator from 2.9% to 2.5% of the world gross domestic product (the relative reduction of variance is 31%) under the medium greenhouse gas concentration scenarios. Our results demonstrate how advances in climate science can contribute to reducing climate-related uncertainties in impact assessments, while we do not examine uncertainties of emulators and impact models.

Predicting distribution overlaps between Dendroctonus adjunctus Blandford 1897 and six Pinus species in Mexico under global climate change

Species that coexist nowadays will not necessarily match their distributions in the future due to different climate suitability. The aim of this study was to identify potential distribution areas where the bark beetle Dendroctonus adjunctus and six of its host tree species overlap under different climate change scenarios. Potential distribution maps were built with species presence data using the MaxLike R library. For each projection, we used WorldClim bioclimatic variables, current and future (2050, 2070) condition climate data, two greenhouse gas concentration scenarios (RCP 4.5, RCP 8.5), and three general circulation models. The results show that the projected current potential distribution area of the bark beetle extends over 216 000 km2. This potential distribution range spans across 28 of the 32 Mexican states, eight of which have not yet reported the insect's presence. Of the 72 overlapping maps that we made, the largest covers more than 118 000 km2 for Pinus duranguensis, while all future projections show a reduction in spatial coincidence. Given future climatic scenarios, D. adjunctus will probably reach higher altitudinal sites. The information contained in this study can be used to identify areas to prioritize monitoring, management, plant sanitation treatment, and reforestation strategies in Mexican pine forests.

The timing of unprecedented hydrological drought under climate change

Droughts that exceed the magnitudes of historical variation ranges could occur increasingly frequently under future climate conditions. However, the time of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and existing water resource management measures and estimate the time of the first emergence of unprecedented regional drought conditions centered on the low-flow season. The times are detected for several subcontinental-scale regions, and three regions, namely, Southwestern South America, Mediterranean Europe, and Northern Africa, exhibit particularly robust results under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. However, appropriate and prior adaptation measures are considered indispensable when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

Assessment of the Impact of Climate Change on Stream Flow: The Case of Little Ruaha Catchment, Rufiji Basin, Tanzania

Little Ruaha catchment has been recognized for its potential to support multi-projects including irrigated schemes, urban water supply and providing significant inflow to Mtera reservoir for hydropower generation and ultimately Julius Nyerere Hydropower Plant (JNHPP). Despite the potential, the catchment has experienced declining flows in the recent years. This study assessed the likely changes in streamflow due to future climate change in the Little Ruaha catchment for the period 2025-2060. General Circulation Model (GCM) datasets from ACCESS1.0, CNRM-CM5 and BCC-CSM1 models and RCP4.5 and RCP8.5 greenhouse gas concentration scenarios were selected as the representative scenarios. Impact of climate change on stream flows was assessed using the calibrated NAM hydrological model. The impact assessment results show that under the climate change scenario (2025–2060), the monthly maximum and minimum temperatures will increase in the range of 0.8 °C to 2 °C for both RCP4.5 and RCP8.5 scenarios. For the case of rainfall, average annual rainfall is expected to increase by about 10% compared to the baseline. However, the inter-annual variability of rainfall for the period between 2025 and 2060 shows the decreasing trend for RCP 8.5. The simulation results show that streamflow will decrease by about 30% and 6% for RCP4.5 and RCP8.5, respectively.
 Keywords: Hydrological modelling; climate change scenarios; hydrological impacts; Little Ruaha.

Emergent constraints on future precipitation changes.

Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT)1. Although many observational constraints on ΔT have been proposed, constraints on ΔP have not been well studied2-5 and are often complicated by the large influence of aerosols on precipitation4. Here we show that the upper bound (95th percentile) of ΔP (2051-2100 minus 1851-1900, percentage of the 1980-2014 mean) is lowered from 6.2 per cent to 5.2-5.7 per cent (minimum-maximum range of sensitivity analyses) under a medium greenhouse gas concentration scenario. Our results come from the Coupled Model Intercomparison Project phase 5 and phase 6 ensembles6-8, in which ΔP for 2051-2100 is well correlated with the global mean temperature trends during recent decades after 1980 when global anthropogenic aerosol emissions were nearly constant. ΔP is also significantly correlated with the recent past trends in precipitation when we exclude the tropical land areas with few rain-gauge observations. On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8-30 per cent. The observationally constrained ranges of ΔP should provide further reliable information for impact assessments.

Local mortality impacts due to future air pollution under climate change scenarios

The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1–5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM2.5 levels. PM2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM2.5 linking local population and mortality data with PM2.5–mortality relationships from the literature, and incorporating population projections under the SSPs. PM2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM2.5 attributable burdens mid-century. Our analysis of local PM2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.

Current and future plant invasions in protected areas: Does clonality matter?

AbstractAimProtected areas (PAs) play an important role in biodiversity conservation, but remain increasingly threatened by invasive alien plant species (IAPS) in conjunction with global climate change. The latter is modifying the distribution of the former, and the magnitude and direction of distributional changes are predicted to vary depending on species dispersal mode. Here, we address the question of whether clonality is expected to affect the future invasion pattern in PAs.LocationWorldwide.Time period1950–2100.Major taxa studied36 invasive alien plant species.MethodsWe used ensembles of three species distribution models (GLM, GAM and Maxent) based on >70,000 occurrence records to project the distribution of 36 of the world's most invasive clonal and non‐clonal plants in >20,000 PAs. Projections were based on three greenhouse gas concentration scenarios (low, medium and high) for 2080.ResultsClimate change showed little impact on the global invasion pattern in PAs, and clonality showed little effect when all biomes were processed in concert. However, we discerned that the future invasion risk of clonal IAPS markedly increased in biomes located at high elevation and high latitude compared with non‐clonal IAPS, while the risk decreased in lower‐elevation tropical and subtropical biomes where asexual reproduction may be a less successful trait. We also showed that invasion hot spots overlapped with biodiversity hot spots and two realms (i.e. Nearctic and Palearctic), which calls for bridging the gap between invasion and conservation sciences and for more concerted management strategies.Main conclusionsWe suggest that effective management of IAPS in PAs should consider in which biomes PAs are located as well as the reproductive traits of IAPS that are present or may become so.

A quantitative evaluation of the issue of drought definition: a source of disagreement in future drought assessments

Droughts are anticipated to intensify in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought indices, makes it difficult to compare drought assessments. This issue is widely known, but its relative importance has never been quantitatively evaluated in comparison to other sources of uncertainty. Here, encompassing three drought categories (meteorological, agricultural, and hydrological droughts) with four temporal scales of interest, we evaluated changes in the drought frequency using multi-model and multi-scenario simulations to identify areas where the definition issue could result in pronounced uncertainties and to what extent. We investigated the disagreement in the signs of changes between drought definitions and decomposed the variance into four main factors: drought definitions, greenhouse gas concentration scenarios, global climate models, and global water models, as well as their interactions. The results show that models were the primary sources of variance over 82% of the global land area. On the other hand, the drought definition was the dominant source of variance in the remaining 17%, especially in parts of northern high-latitudes. Our results highlight specific regions where differences in drought definitions result in a large spread among projections, including areas showing opposite signs of significant changes. At a global scale, 7% of the variance resulted independently from the definition issue, and that value increased to 44% when 1st and 2nd order interactions were considered. The quantitative results suggest that by clarifying hydrological processes or sectors of interest, one could avoid these uncertainties in drought assessments to obtain a clearer picture of future drought change.

Extreme Ground Snow Loads in Europe from 1951 to 2100

Lightweight roofs are extremely sensitive to extreme snow loads, as confirmed by recently occurring failures all over Europe. Obviously, the problem is further emphasized in warmer climatic areas, where low design values are generally foreseen for snow loads. Like other climatic actions, representative values of snow loads provided in structural codes are usually derived by means of suitable elaborations of extreme statistics, assuming climate stationarity over time. As climate change impacts are becoming more and more evident over time, that hypothesis is becoming controversial, so that suitable adaptation strategies aiming to define climate resilient design loads need to be implemented. In the paper, past and future trends of ground snow load in Europe are assessed for the period 1950–2100, starting from high-resolution climate simulations, recently issued by the CORDEX program. Maps of representative values of snow loads adopted for structural design, associated with an annual probability of exceedance p = 2%, are elaborated for Europe. Referring to the historical period, the obtained maps are critically compared with the current European maps based on observations. Factors of change maps, referred to subsequent time windows are presented considering RCP4.5 and RCP8.5 emission trajectories, corresponding to medium and maximum greenhouse gas concentration scenarios. Factors of change are thus evaluated considering suitably selected weather stations in Switzerland and Germany, for which high quality point measurements, sufficiently extended over time are available. Focusing on the investigated weather stations, the study demonstrates that climate models can appropriately reproduce historical trends and that a decrease of characteristic values of the snow loads is expected over time. However, it must be remarked that, if on one hand the mean value of the annual maxima tends to reduce, on the other hand, its standard deviation tends to increase, locally leading to an increase of the extreme values, which should be duly considered in the evaluation of structural reliability over time.

Local mortality impacts due to future air pollution under climate change scenarios in Mozambique, India, and Spain

BACKGROUND AND AIM: The health impacts of global climate change mitigation will affect local populations differently. We aimed to quantify the local health impacts due to fine particles (PM2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain METHODS: We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM2.5 levels. We used comparative risk assessment methods to estimate attributable premature deaths due to PM2.5 linking local population and mortality data with PM2.5–mortality relationships from the literature. We incorporated population projections under the SSPs in sensitivity analysis. RESULTS:PM2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and scenario-sensitivity varied across populations. Holding population change constant, variation in PM2.5 attributable deaths in 2050 across scenarios was small in Manhiça (min:103, max:116 deaths per 100,000) and Barcelona (min:73, max:115), compared to Vadu (min:154, max:264). Future attributable mortality burden of PM2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM2.5 attributable burdens mid-century CONCLUSIONS:Our analysis of local PM2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM2.5 mortality burden to SSPs was particularly evident in low- and midlle- income country settings due either to high air pollution levels or dynamic populations. KEYWORDS: climate change mitigation; shared socioeconomic pathways; air pollution; mortality, representative concentration pathways

Projecting Relative Sea Level Rise under Climate Change at the Phrachula Chomklao Fort Tide Gauge in the Upper Gulf of Thailand

This study aims to project future sea-level rise (SLR) at the Phrachula Chomklao Fort (PCF) tide gauge station in the Upper Gulf of Thailand (UGoT) using the outputs of 35 climate models under two greenhouse gas concentration scenarios: representative concentration pathway 4.5 (RCP4.5) and RCP8.5. The Linear Scaling method was found to be better than Variance Scaling and Quantile Mapping methods for removing biases in raw Global Circulation Models (GCMs) sea level data. Land subsidence, induced by excessive groundwater abstraction, was found to contribute significantly to SLR during the observed period the PCF gauging station; hence, the effects of land subsidence had to be removed from relative sea level before bias correction. The overall increase in SLR is projected to be 0.94–1.05 mm/year under RCP4.5 and 1.07–1.18 mm/year under RCP8.5 for the twenty-first century in the UGoT. The results suggest that future SLR due to climate change will not be as severe in the study region compared to average global projections. However, land subsidence can amplify future SLR. It is therefore important to regulate groundwater abstraction in the future so that SLR can be restricted. It is even more relevant in the UGoT as the raw water intake from the Chao Phraya River for municipal water supply to Bangkok is close to the estuary, and SLR in the future can pose additional challenges for the water utility.

Global warming and population change both heighten future risk of human displacement due to river floods

Every year, millions of people around the world are being displaced from their homes due to climate-related disasters. River flooding is responsible for a large part of this displacement. Previous studies have shown that river flood risk is expected to change as a result of global warming and its effects on the hydrological cycle. At the same time, future scenarios of socio-economic development imply substantial population increases in many of the areas that presently experience disaster-induced displacement. Here we show that both global warming and population change are projected to lead to substantial increases in flood-induced displacement risk over the coming decades. We use a global climate-hydrology-inundation modelling chain, including multiple alternative climate and hydrological models, to quantify the effect of global warming on displacement risk assuming either current or projected future population distributions. Keeping population fixed at present levels, we find roughly a 50% increase in global displacement risk for every degree of global warming. Adding projected population changes further exacerbates these increases globally and in most world regions, with the relative global flood displacement risk is increasing by roughly 350% at the end of the 21st century, compared to an increase of 150% without the contribution of population change. While the resolution of the global models is limited, the effect of global warming is robust across greenhouse gas concentration scenarios, climate models and hydrological models. These findings indicate a need for rapid action on both climate mitigation and adaptation agendas in order to reduce future risks to vulnerable populations.

Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators

Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems.The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by U.S. Fish and Wildlife Service natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.

Assessment of the European Climate Projections as Simulated by the Large EURO‐CORDEX Regional and Global Climate Model Ensemble

AbstractThis paper analyzes the ensemble of regional climate model (RCM) projections for Europe completed within the EURO‐CORDEX project. Projections are available for the two greenhouse gas concentration scenarios RCP2.6 (22 members) and RCP8.5 (55 members) at 0.11° resolution from 11 RCMs driven by eight global climate models (GCMs). The RCM ensemble results are compared with the driving CMIP5 global models but also with a subset of available last generation CMIP6 projections. Maximum warming is projected by all ensembles in Northern Europe in winter, along with a maximum precipitation increase there; in summer, maximum warming occurs in the Mediterranean and Southern European regions associated with a maximum precipitation decrease. The CMIP6 ensemble shows the largest signals, both for temperature and precipitation, along with the largest inter‐model spread. There is a high model consensus across the ensembles on an increase of extreme precipitation and drought frequency in the Mediterranean region. Extreme temperature indices show an increase of heat extremes and a decrease of cold extremes, with CMIP6 showing the highest values and EURO‐CORDEX the finest spatial details. This data set of unprecedented size and quality will provide the basis for impact assessment and climate service activities for the European region.