1000 resultados para Projected models


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The aim of this paper is to demonstrate the importance of changing temperature variability with climate change in assessments of future heat-related mortality. Previous studies have only considered changes in the mean temperature. Here we present estimates of heat-related mortality resulting from climate change for six cities: Boston, Budapest, Dallas, Lisbon, London and Sydney. They are based on climate change scenarios for the 2080s (2070-2099) and the temperature-mortality (t-m) models constructed and validated in Gosling et al. (2007). We propose a novel methodology for assessing the impacts of climate change on heat-related mortality that considers both changes in the mean and variability of the temperature distribution.

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Anthropogenic changes in precipitation pose a serious threat to society—particularly in regions such as the Middle East that already face serious water shortages. However, climate model projections of regional precipitation remain highly uncertain. Moreover, standard resolution climate models have particular difficulty representing precipitation in the Middle East, which is modulated by complex topography, inland water bodies and proximity to the Mediterranean Sea. Here we compare precipitation changes over the twenty-first century against both millennial variability during the Holocene and interannual variability in the present day. In order to assess the climate model and to make consistent comparisons, this study uses new regional climate model simulations of the past, present and future in conjunction with proxy and historical observations. We show that the pattern of precipitation change within Europe and the Middle East projected by the end of the twenty-first century has some similarities to that which occurred during the Holocene. In both cases, a poleward shift of the North Atlantic storm track and a weakening of the Mediterranean storm track appear to cause decreased winter rainfall in southern Europe and the Middle East and increased rainfall further north. In contrast, on an interannual time scale, anomalously dry seasons in the Middle East are associated with a strengthening and focusing of the storm track in the north Mediterranean and hence wet conditions throughout southern Europe.

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Projections of stratospheric ozone from a suite of chemistry-climate models (CCMs) have been analyzed. In addition to a reference simulation where anthropogenic halogenated ozone depleting substances (ODSs) and greenhouse gases (GHGs) vary with time, sensitivity simulations with either ODS or GHG concentrations fixed at 1960 levels were performed to disaggregate the drivers of projected ozone changes. These simulations were also used to assess the two distinct milestones of ozone returning to historical values (ozone return dates) and ozone no longer being influenced by ODSs (full ozone recovery). The date of ozone returning to historical values does not indicate complete recovery from ODSs in most cases, because GHG-induced changes accelerate or decelerate ozone changes in many regions. In the upper stratosphere where CO2-induced stratospheric cooling increases ozone, full ozone recovery is projected to not likely have occurred by 2100 even though ozone returns to its 1980 or even 1960 levels well before (~2025 and 2040, respectively). In contrast, in the tropical lower stratosphere ozone decreases continuously from 1960 to 2100 due to projected increases in tropical upwelling, while by around 2040 it is already very likely that full recovery from the effects of ODSs has occurred, although ODS concentrations are still elevated by this date. In the midlatitude lower stratosphere the evolution differs from that in the tropics, and rather than a steady decrease in ozone, first a decrease in ozone is simulated from 1960 to 2000, which is then followed by a steady increase through the 21st century. Ozone in the midlatitude lower stratosphere returns to 1980 levels by ~2045 in the Northern Hemisphere (NH) and by ~2055 in the Southern Hemisphere (SH), and full ozone recovery is likely reached by 2100 in both hemispheres. Overall, in all regions except the tropical lower stratosphere, full ozone recovery from ODSs occurs significantly later than the return of total column ozone to its 1980 level. The latest return of total column ozone is projected to occur over Antarctica (~2045–2060) whereas it is not likely that full ozone recovery is reached by the end of the 21st century in this region. Arctic total column ozone is projected to return to 1980 levels well before polar stratospheric halogen loading does so (~2025–2030 for total column ozone, cf. 2050–2070 for Cly+60×Bry) and it is likely that full recovery of total column ozone from the effects of ODSs has occurred by ~2035. In contrast to the Antarctic, by 2100 Arctic total column ozone is projected to be above 1960 levels, but not in the fixed GHG simulation, indicating that climate change plays a significant role.

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This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.

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In addition to projected increases in global mean sea level over the 21st century, model simulations suggest there will also be changes in the regional distribution of sea level relative to the global mean. There is a considerable spread in the projected patterns of these changes by current models, as shown by the recent Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (AR4). This spread has not reduced from that given by the Third Assessment models. Comparison with projections by ensembles of models based on a single structure supports an earlier suggestion that models of similar formulation give more similar patterns of sea level change. Analysing an AR4 ensemble of model projections under a business-as-usual scenario shows that steric changes (associated with subsurface ocean density changes) largely dominate the sea level pattern changes. The relative importance of subsurface temperature or salinity changes in contributing to this differs from region to region and, to an extent, from model-to-model. In general, thermosteric changes give the spatial variations in the Southern Ocean, halosteric changes dominate in the Arctic and strong compensation between thermosteric and halosteric changes characterises the Atlantic. The magnitude of sea level and component changes in the Atlantic appear to be linked to the amount of Atlantic meridional overturning circulation (MOC) weakening. When the MOC weakening is substantial, the Atlantic thermosteric patterns of change arise from a dominant role of ocean advective heat flux changes.

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During the 20th century, solar activity increased in magnitude to a so-called grand maximum. It is probable that this high level of solar activity is at or near its end. It is of great interest whether any future reduction in solar activity could have a significant impact on climate that could partially offset the projected anthropogenic warming. Observations and reconstructions of solar activity over the last 9000 years are used as a constraint on possible future variations to produce probability distributions of total solar irradiance over the next 100 years. Using this information, with a simple climate model, we present results of the potential implications for future projections of climate on decadal to multidecadal timescales. Using one of the most recent reconstructions of historic total solar irradiance, the likely reduction in the warming by 2100 is found to be between 0.06 and 0.1 K, a very small fraction of the projected anthropogenic warming. However, if past total solar irradiance variations are larger and climate models substantially underestimate the response to solar variations, then there is a potential for a reduction in solar activity to mitigate a small proportion of the future warming, a scenario we cannot totally rule out. While the Sun is not expected to provide substantial delays in the time to reach critical temperature thresholds, any small delays it might provide are likely to be greater for lower anthropogenic emissions scenarios than for higher-emissions scenarios.

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The final warming date of the polar vortex is a key component of Southern Hemisphere stratospheric and tropospheric variability in spring and summer. We examine the effect of external forcings on Southern Hemisphere final warming date, and the sensitivity of any projected changes to model representation of the stratosphere. Final warming date is calculated using a temperature-based diagnostic for ensembles of high- and low-top CMIP5 models, under the CMIP5 historical, RCP4.5, and RCP8.5 forcing scenarios. The final warming date in the models is generally too late in comparison with those from reanalyses: around two weeks too late in the low-top ensemble, and around one week too late in the high-top ensemble. Ensemble Empirical Mode Decomposition (EEMD) is used to analyse past and future change in final warming date. Both the low- and high-top ensemble show characteristic behaviour expected in response to changes in greenhouse gas and stratospheric ozone concentrations. In both ensembles, under both scenarios, an increase in final warming date is seen between 1850 and 2100, with the latest dates occurring in the early twenty-first century, associated with the minimum in stratospheric ozone concentrations in this period. However, this response is more pronounced in the high-top ensemble. The high-top models show a delay in final warming date in RCP8.5 that is not produced by the low-top models, which are shown to be less responsive to greenhouse gas forcing. This suggests that it may be necessary to use stratosphere resolving models to accurately predict Southern Hemisphere surface climate change.

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We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

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Projected changes in the extra-tropical wintertime storm tracks are investigated using the multi-model ensembles from both the third and fifth phases of the World Climate Research Programme's Coupled Model Intercomparison Project (CMIP3 and CMIP5). The aim is to characterize the magnitude of the storm track responses relative to their present-day year-to-year variability. For the experiments considered, the ‘middle-of-the-road’ scenarios in each CMIP, there are regions of the Northern Hemisphere where the responses of up to 40% of the models exceed half of the inter-annual variability, and for the Southern Hemisphere there are regions where up to 60% of the model responses exceed half of the inter-annual variability.

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The occurrence of destructive mesoscale ‘polar low’ cyclones in the subpolar North Atlantic is projected to decline under anthropogenic change, due to an increase in atmospheric static stability. This letter reports on the role of changes in ocean circulation in shaping the atmospheric stability. In particular, the Atlantic Meridional Overturning Circulation (AMOC) is projected to weaken in response to anthropogenic forcing, leading to a local minimum in warming in this region. The reduced warming is restricted to the lower troposphere, hence contributing to the increase in static stability. Linear correlation analysis of the CMIP3 climate model ensemble suggests that around half of the model uncertainty in the projected stability response arises from the varied response of the AMOC between models.

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Sea level change predicted by the CMIP5 atmosphere–ocean general circulation models (AOGCMs) is not spatially homogeneous. In particular, the sea level change in the North Atlantic is usually characterised by a meridional dipole pattern with higher sea level rise north of 40°N and lower to the south. The spread among models is also high in that region. Here we evaluate the role of surface buoyancy fluxes by carrying out simulations with the FAMOUS low-resolution AOGCM forced by surface freshwater and heat flux changes from CO2-forced climate change experiments with CMIP5 AOGCMs, and by a standard idealised surface freshwater flux applied in the North Atlantic. Both kinds of buoyancy flux change lead to the formation of the sea level dipole pattern, although the effect of the heat flux has a greater magnitude, and is the main cause of the spread of results among the CMIP5 models. By using passive tracers in FAMOUS to distinguish between additional and redistributed buoyancy, we show that the enhanced sea level rise north of 40°N is mainly due to the direct steric effect (the reduction of sea water density) caused by adding heat or freshwater locally. The surface buoyancy forcing also causes a weakening of the Atlantic meridional overturning circulation, and the consequent reduction of the northward ocean heat transport imposes a negative tendency on sea level rise, producing the reduced rise south of 40°N. However, unlike previous authors, we find that this indirect effect of buoyancy forcing is generally less important than the direct one, except in a narrow band along the east coast of the US, where it plays a major role and leads to sea level rise, as found by previous authors.

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Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Inter-comparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981-2010) to the future (2070-2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.

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We utilize energy budget diagnostics from the Coupled Model Intercomparison Project phase 5 (CMIP5) to evaluate the models' climate forcing since preindustrial times employing an established regression technique. The climate forcing evaluated this way, termed the adjusted forcing (AF), includes a rapid adjustment term associated with cloud changes and other tropospheric and land-surface changes. We estimate a 2010 total anthropogenic and natural AF from CMIP5 models of 1.9 ± 0.9 W m−2 (5–95% range). The projected AF of the Representative Concentration Pathway simulations are lower than their expected radiative forcing (RF) in 2095 but agree well with efficacy weighted forcings from integrated assessment models. The smaller AF, compared to RF, is likely due to cloud adjustment. Multimodel time series of temperature change and AF from 1850 to 2100 have large intermodel spreads throughout the period. The intermodel spread of temperature change is principally driven by forcing differences in the present day and climate feedback differences in 2095, although forcing differences are still important for model spread at 2095. We find no significant relationship between the equilibrium climate sensitivity (ECS) of a model and its 2003 AF, in contrast to that found in older models where higher ECS models generally had less forcing. Given the large present-day model spread, there is no indication of any tendency by modelling groups to adjust their aerosol forcing in order to produce observed trends. Instead, some CMIP5 models have a relatively large positive forcing and overestimate the observed temperature change.

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How tropical cyclone (TC) activity in the northwestern Pacific might change in a future climate is assessed using multidecadal Atmospheric Model Intercomparison Project (AMIP)-style and time-slice simulations with the ECMWF Integrated Forecast System (IFS) at 16-km and 125-km global resolution. Both models reproduce many aspects of the present-day TC climatology and variability well, although the 16-km IFS is far more skillful in simulating the full intensity distribution and genesis locations, including their changes in response to El Niño–Southern Oscillation. Both IFS models project a small change in TC frequency at the end of the twenty-first century related to distinct shifts in genesis locations. In the 16-km IFS, this shift is southward and is likely driven by the southeastward penetration of the monsoon trough/subtropical high circulation system and the southward shift in activity of the synoptic-scale tropical disturbances in response to the strengthening of deep convective activity over the central equatorial Pacific in a future climate. The 16-km IFS also projects about a 50% increase in the power dissipation index, mainly due to significant increases in the frequency of the more intense storms, which is comparable to the natural variability in the model. Based on composite analysis of large samples of supertyphoons, both the development rate and the peak intensities of these storms increase in a future climate, which is consistent with their tendency to develop more to the south, within an environment that is thermodynamically more favorable for faster development and higher intensities. Coherent changes in the vertical structure of supertyphoon composites show system-scale amplification of the primary and secondary circulations with signs of contraction, a deeper warm core, and an upward shift in the outflow layer and the frequency of the most intense updrafts. Considering the large differences in the projections of TC intensity change between the 16-km and 125-km IFS, this study further emphasizes the need for high-resolution modeling in assessing potential changes in TC activity.

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Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.