The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron

USGS Publications Warehouse

Kao, Yu-Chun; Madenjian, Charles P.; Bunnell, David B.; Lofgren, Brent M.; Perroud, Marjorie

2015-01-01

We used a bioenergetics modeling approach to investigate potential effects of climate change on the growth of two economically important native fishes: yellow perch (Perca flavescens), a cool-water fish, and lake whitefish (Coregonus clupeaformis), a cold-water fish, in deep and oligotrophic Lakes Michigan and Huron. For assessing potential changes in fish growth, we contrasted simulated fish growth in the projected future climate regime during the period 2043-2070 under different prey availability scenarios with the simulated growth during the baseline (historical reference) period 1964-1993. Results showed that effects of climate change on the growth of these two fishes are jointly controlled by behavioral thermoregulation and prey availability. With the ability of behavioral thermoregulation, temperatures experienced by yellow perch in the projected future climate regime increased more than those experienced by lake whitefish. Thus simulated future growth decreased more for yellow perch than for lake whitefish under scenarios where prey availability remains constant into the future. Under high prey availability scenarios, simulated future growth of these two fishes both increased but yellow perch could not maintain the baseline efficiency of converting prey consumption into body weight. We contended that thermal guild should not be the only factor used to predict effects of climate change on the growth of a fish, and that ecosystem responses to climate change should be also taken into account.

Impact of Climate Change on Projected Runoff from Mountain Snowpack of the King's Rivershed in California

NASA Astrophysics Data System (ADS)

Dialesandro, J.; Elias, E.; Rango, A.; Steele, C. M.

2016-12-01

The Central Valley of California, like most dryland agricultural areas in the Southwest United States, relies heavily on winter snowpack for water resources. Projections of future climate in the Sierra Mountains of California calls for a warmer climate regime that will impact the snowpack in the Sierra Mountains and thus the water supply for downstream agriculture and municipal uses within California's Central Valley. We simulate the impacts of two future time windows (2040-2069 and 2070-2099) and two future climate scenarios (RCP 4.5 and 8.5) on King's River using the Snowmelt Runoff Model. Snow depletion curves for 2010 are generated using MODIS and SRM parameters are adjusted until measured and simulated runoff reach acceptable agreement (R2 = .81). Future projections are based upon the multimodel mean of 20 CMIP5 models for seasonal future temperature and precipitation at high and low elevation points in the watershed from the multivariate adaptive constructed analogs (MACA) downscaled dataset. Changes in monthly inflow to Pineflat Reservoir, at the pour point of King's River watersheds, show a large decline in June and July inflow for all future climate simulations. Conversely, simulated spring inflow to Pineflat Reservoir is larger in the future. Impacts are most pronounced for end of the century (2070-2099), business as usual (RCP 8.5) simulation. Results are discussed with regard to implications for reservoir storage, groundwater recharge and creative solutions to cope with anticipated changes in runoff.

Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa

NASA Astrophysics Data System (ADS)

Graham, L. Phil; Andersson, Lotta; Horan, Mark; Kunz, Richard; Lumsden, Trevor; Schulze, Roland; Warburton, Michele; Wilk, Julie; Yang, Wei

This study used climate change projections from different regional approaches to assess hydrological effects on the Thukela River Basin in KwaZulu-Natal, South Africa. Projecting impacts of future climate change onto hydrological systems can be undertaken in different ways and a variety of effects can be expected. Although simulation results from global climate models (GCMs) are typically used to project future climate, different outcomes from these projections may be obtained depending on the GCMs themselves and how they are applied, including different ways of downscaling from global to regional scales. Projections of climate change from different downscaling methods, different global climate models and different future emissions scenarios were used as input to simulations in a hydrological model to assess climate change impacts on hydrology. A total of 10 hydrological change simulations were made, resulting in a matrix of hydrological response results. This matrix included results from dynamically downscaled climate change projections from the same regional climate model (RCM) using an ensemble of three GCMs and three global emissions scenarios, and from statistically downscaled projections using results from five GCMs with the same emissions scenario. Although the matrix of results does not provide complete and consistent coverage of potential uncertainties from the different methods, some robust results were identified. In some regards, the results were in agreement and consistent for the different simulations. For others, particularly rainfall, the simulations showed divergence. For example, all of the statistically downscaled simulations showed an annual increase in precipitation and corresponding increase in river runoff, while the RCM downscaled simulations showed both increases and decreases in runoff. According to the two projections that best represent runoff for the observed climate, increased runoff would generally be expected for this basin in the future. Dealing with such variability in results is not atypical for assessing climate change impacts in Africa and practitioners are faced with how to interpret them. This work highlights the need for additional, well-coordinated regional climate downscaling for the region to further define the range of uncertainties involved.

Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

NASA Astrophysics Data System (ADS)

Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

2017-12-01

Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Determing Credibility of Regional Simulations of Future Climate

NASA Astrophysics Data System (ADS)

Mearns, L. O.

2009-12-01

Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach is being attempted in the North American Climate Change Assessment Program (NARCCAP) whereby multiple global models are used to drive multiple regional models for the current period and the mid-21st century over the continent. Progress in this endeavor will be reported.

Hourly test reference weather data in the changing climate of Finland for building energy simulations.

PubMed

Jylhä, Kirsti; Ruosteenoja, Kimmo; Jokisalo, Juha; Pilli-Sihvola, Karoliina; Kalamees, Targo; Mäkelä, Hanna; Hyvönen, Reijo; Drebs, Achim

2015-09-01

Dynamic building energy simulations need hourly weather data as input. The same high temporal resolution is required for assessments of future heating and cooling energy demand. The data presented in this article concern current typical values and estimated future changes in outdoor air temperature, wind speed, relative humidity and global, diffuse and normal solar radiation components. Simulated annual and seasonal delivered energy consumptions for heating of spaces, heating of ventilation supply air and cooling of spaces in the current and future climatic conditions are also presented for an example house, with district heating and a mechanical space cooling system. We provide details on how the synthetic future weather files were created and utilised as input data for dynamic building energy simulations by the IDA Indoor Climate and Energy program and also for calculations of heating and cooling degree-day sums. The information supplied here is related to the research article titled "Energy demand for the heating and cooling of residential houses in Finland in a changing climate" [1].

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

2016-10-01

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

NASA Astrophysics Data System (ADS)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the results of the earlier decisions, as simulated by C-ROADS. Preliminary evaluations show that both exercises have the potential to provide powerful learning experiences. University students who played World Climate in a climate change course cited it as one of the course activities "promoting the most learning." Students' responses on anonymous surveys and open-ended questions revealed that the experience affected them at visceral, as well as intellectual levels. All of the students recommended that the exercise be continued in future years and many felt that it was the most important learning experience of the semester. Similarly, understanding of climate change and the dynamics of the climate improved for the majority of Future Climate participants, and 90% of participants stated that they were more likely to take action to address climate change on a personal level because of their experience.

Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900-2099

NASA Astrophysics Data System (ADS)

Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.

2001-12-01

Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.

Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

USGS Publications Warehouse

Shafer, S.L.; Atkins, J.; Bancroft, B.A.; Bartlein, P.J.; Lawler, J.J.; Smith, B.; Wilsey, C.B.

2012-01-01

The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

The future of the Devon Ice cap: results from climate and ice dynamics modelling

NASA Astrophysics Data System (ADS)

Mottram, Ruth; Rodehacke, Christian; Boberg, Fredrik

2017-04-01

The Devon Ice Cap is an example of a relatively well monitored small ice cap in the Canadian Arctic. Close to Greenland, it shows a similar surface mass balance signal to glaciers in western Greenland. Here we use high resolution (5km) simulations from HIRHAM5 to drive the PISM glacier model in order to model the present day and future prospects of this small Arctic ice cap. Observational data from the Devon Ice Cap in Arctic Canada is used to evaluate the surface mass balance (SMB) data output from the HIRHAM5 model for simulations forced with the ERA-Interim climate reanalysis data and the historical emissions scenario run by the EC-Earth global climate model. The RCP8.5 scenario simulated by EC-Earth is also downscaled by HIRHAM5 and this output is used to force the PISM model to simulate the likely future evolution of the Devon Ice Cap under a warming climate. We find that the Devon Ice Cap is likely to continue its present day retreat, though in the future increased precipitation partly offsets the enhanced melt rates caused by climate change.

Hazardous Convective Weather in the Central United States: Present and Future

NASA Astrophysics Data System (ADS)

Liu, C.; Ikeda, K.; Rasmussen, R.

2017-12-01

Two sets of 13-year continental-scale convection-permitting simulations were performed using the 4-km-resolution WRF model. They consist of a retrospective simulation, which downscales the ERA-Interim reanalysis during the period October 2000 - September 2013, and a future climate sensitivity simulation for the same period based on the perturbed reanalysis-derived boundary conditions with the CMIP5 ensemble-mean high-end emission scenario climate change. The evaluation of the retrospective simulation indicates that the model is able to realistically reproduce the main characteristics of deep precipitating convection observed in the current climate such as the spectra of convective population and propagating mesoscale convective systems (MCSs). It is also shown that severe convection and associated MCS will increase in frequency and intensity, implying a potential increase in high impact convective weather in a future warmer climate. In this study, the warm-season hazardous convective weather (i.e., tonadoes, hails and damaging gusty wind) in the central United states is examined using these 4-km downscaling simulations. First, a model-based proxy for hazardous convective weather is derived on the basis of a set of characteristic meteorological variables such as the model composite radar reflectivity, updraft helicity, vertical wind shear, and low-level wind. Second, the developed proxy is applied to the retrospective simulation for estimate of the model hazardous weather events during the historical period. Third, the simulated hazardous weather statistics are evaluated against the NOAA severe weather reports. Lastly, the proxy is applied to the future climate simulation for the projected change of hazardous convective weather in response to global warming. Preliminary results will be reported at the 2017 AGU session "High Resolution Climate Modeling".

The effect of future outdoor air pollution on human health and the contribution of climate change

NASA Astrophysics Data System (ADS)

Silva, R.; West, J. J.; Lamarque, J.; Shindell, D.; Collins, W.; Dalsoren, S. B.; Faluvegi, G. S.; Folberth, G.; Horowitz, L. W.; Nagashima, T.; Naik, V.; Rumbold, S.; Skeie, R.; Sudo, K.; Takemura, T.; Bergmann, D. J.; Cameron-Smith, P. J.; Cionni, I.; Doherty, R. M.; Eyring, V.; Josse, B.; MacKenzie, I. A.; Plummer, D.; Righi, M.; Stevenson, D. S.; Strode, S. A.; Szopa, S.; Zeng, G.

2013-12-01

At present, exposure to outdoor air pollution from ozone and fine particulate matter (PM2.5) causes over 2 million deaths per year, due to respiratory and cardiovascular diseases and lung cancer. Future ambient concentrations of ozone and PM2.5 will be affected by both air pollutant emissions and climate change. Here we estimate the potential impact of future outdoor air pollution on premature human mortality, and isolate the contribution of future climate change due to its effect on air quality. We use modeled present-day (2000) and future global ozone and PM2.5 concentrations from simulations with an ensemble of chemistry-climate models from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Future air pollution was modeled for global greenhouse gas and air pollutant emissions in the four IPCC AR5 Representative Concentration Pathway (RCP) scenarios, for 2030, 2050 and 2100. All model outputs are regridded to a common 0.5°x0.5° horizontal resolution. Future premature mortality is estimated for each RCP scenario and year based on changes in concentrations of ozone and PM2.5 relative to 2000. Using a health impact function, changes in concentrations for each RCP scenario are combined with future population and cause-specific baseline mortality rates as projected by a single independent scenario in which the global incidence of cardiopulmonary diseases is expected to increase. The effect of climate change is isolated by considering the difference between air pollutant concentrations from simulations with 2000 emissions and a future year climate and simulations with 2000 emissions and climate. Uncertainties in the results reflect the uncertainty in the concentration-response function and that associated with variability among models. Few previous studies have quantified the effects of future climate change on global human health via changes in air quality, and this is the first such study to use an ensemble of global models.

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future warming patterns linked to today’s climate variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Climate changes and wildfire alter vegetation of Yellowstone National Park, but forest cover persists

USGS Publications Warehouse

Clark, Jason A.; Loehman, Rachel A.; Keane, Robert E.

2017-01-01

We present landscape simulation results contrasting effects of changing climates on forest vegetation and fire regimes in Yellowstone National Park, USA, by mid-21st century. We simulated potential changes to fire dynamics and forest characteristics under three future climate projections representing a range of potential future conditions using the FireBGCv2 model. Under the future climate scenarios with moderate warming (>2°C) and moderate increases in precipitation (3–5%), model simulations resulted in 1.2–4.2 times more burned area, decreases in forest cover (10–44%), and reductions in basal area (14–60%). In these same scenarios, lodgepole pine (Pinus contorta) decreased in basal area (18–41%), while Douglas-fir (Pseudotsuga menziesii) basal area increased (21–58%). Conversely, mild warming (<2°C) coupled with greater increases in precipitation (12–13%) suggested an increase in forest cover and basal area by mid-century, with spruce and subalpine fir increasing in abundance. Overall, we found changes in forest tree species compositions were caused by the climate-mediated changes in fire regime (56–315% increase in annual area burned). Simulated changes in forest composition and fire regime under warming climates portray a landscape that shifts from lodgepole pine to Douglas-fir caused by the interaction between the magnitude and seasonality of future climate changes, by climate-induced changes in the frequency and intensity of wildfires, and by tree species response.

Selecting climate change scenarios using impact-relevant sensitivities

Treesearch

Julie A. Vano; John B. Kim; David E. Rupp; Philip W. Mote

2015-01-01

Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the...

Simulating post-wildfire forest trajectories under alternative climate and management scenarios

Treesearch

Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom

2014-01-01

Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...

Spatial heterogeneity in the timing of birch budburst in response to future climate warming in Ireland

NASA Astrophysics Data System (ADS)

Caffarra, Amelia; Zottele, Fabio; Gleeson, Emily; Donnelly, Alison

2014-05-01

In order to predict the impact of future climate warming on trees it is important to quantify the effect climate has on their development. Our understanding of the phenological response to environmental drivers has given rise to various mathematical models of the annual growth cycle of plants. These models simulate the timing of phenophases by quantifying the relationship between development and its triggers, typically temperature. In addition, other environmental variables have an important role in determining the timing of budburst. For example, photoperiod has been shown to have a strong influence on phenological events of a number of tree species, including Betula pubescens (birch). A recently developed model for birch (DORMPHOT), which integrates the effects of temperature and photoperiod on budburst, was applied to future temperature projections from a 19-member ensemble of regional climate simulations (on a 25 km grid) generated as part of the ENSEMBLES project, to simulate the timing of birch budburst in Ireland each year up to the end of the present century. Gridded temperature time series data from the climate simulations were used as input to the DORMPHOT model to simulate future budburst timing. The results showed an advancing trend in the timing of birch budburst over most regions in Ireland up to 2100. Interestingly, this trend appeared greater in the northeast of the country than in the southwest, where budburst is currently relatively early. These results could have implications for future forest planning, species distribution modeling, and the birch allergy season.

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

NASA Astrophysics Data System (ADS)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

High-resolution dynamical downscaling of the future Alpine climate

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph

2017-04-01

The Alpine region and Switzerland is a challenging area for simulating and analysing Global Climate Model (GCM) results. This is mostly due to the combination of a very complex topography and the still rather coarse horizontal resolution of current GCMs, in which not all of the many-scale processes that drive the local weather and climate can be resolved. In our study, the Weather Research and Forecasting (WRF) model is used to dynamically downscale a GCM simulation to a resolution as high as 2 km x 2 km. WRF is driven by initial and boundary conditions produced with the Community Earth System Model (CESM) for the recent past (control run) and until 2100 using the RCP8.5 climate scenario (future run). The control run downscaled with WRF covers the period 1976-2005, while the future run investigates a 20-year-slice simulated for the 2080-2099. We compare the control WRF-CESM simulations to an observational product provided by MeteoSwiss and an additional WRF simulation driven by the ERA-Interim reanalysis, to estimate the bias that is introduced by the extra modelling step of our framework. Several bias-correction methods are evaluated, including a quantile mapping technique, to ameliorate the bias in the control WRF-CESM simulation. In the next step of our study these corrections are applied to our future WRF-CESM run. The resulting downscaled and bias-corrected data is analysed for the properties of precipitation and wind speed in the future climate. Our special interest focuses on the absolute quantities simulated for these meteorological variables as these are used to identify extreme events, such as wind storms and situations that can lead to floods.

Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

NASA Astrophysics Data System (ADS)

Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

2015-12-01

An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

Revisiting historical climatic signals to better explore the future: prospects of water cycle changes in Central Sahel

NASA Astrophysics Data System (ADS)

Leauthaud, C.; Demarty, J.; Cappelaere, B.; Grippa, M.; Kergoat, L.; Velluet, C.; Guichard, F.; Mougin, E.; Chelbi, S.; Sultan, B.

2015-06-01

Rainfall and climatic conditions are the main drivers of natural and cultivated vegetation productivity in the semiarid region of Central Sahel. In a context of decreasing cultivable area per capita, understanding and predicting changes in the water cycle are crucial. Yet, it remains challenging to project future climatic conditions in West Africa since there is no consensus on the sign of future precipitation changes in simulations coming from climate models. The Sahel region has experienced severe climatic changes in the past 60 years that can provide a first basis to understand the response of the water cycle to non-stationary conditions in this part of the world. The objective of this study was to better understand the response of the water cycle to highly variable climatic regimes in Central Sahel using historical climate records and the coupling of a land surface energy and water model with a vegetation model that, when combined, simulated the Sahelian water, energy and vegetation cycles. To do so, we relied on a reconstructed long-term climate series in Niamey, Republic of Niger, in which three precipitation regimes can be distinguished with a relative deficit exceeding 25% for the driest period compared to the wettest period. Two temperature scenarios (+2 and +4 °C) consistent with future warming scenarios were superimposed to this climatic signal to generate six virtual future 20-year climate time series. Simulations by the two coupled models forced by these virtual scenarios showed a strong response of the water budget and its components to temperature and precipitation changes, including decreases in transpiration, runoff and drainage for all scenarios but those with highest precipitation. Such climatic changes also strongly impacted soil temperature and moisture. This study illustrates the potential of using the strong climatic variations recorded in the past decades to better understand potential future climate variations.

Assessment of CORDEX-South Asia experiments for monsoonal precipitation over Himalayan region for future climate

NASA Astrophysics Data System (ADS)

Choudhary, A.; Dimri, A. P.

2018-04-01

Precipitation is one of the important climatic indicators in the global climate system. Probable changes in monsoonal (June, July, August and September; hereafter JJAS) mean precipitation in the Himalayan region for three different greenhouse gas emission scenarios (i.e. representative concentration pathways or RCPs) and two future time slices (near and far) are estimated from a set of regional climate simulations performed under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. For each of the CORDEX-SA simulations and their ensemble, projections of near future (2020-2049) and far future (2070-2099) precipitation climatology with respect to corresponding present climate (1970-2005) over Himalayan region are presented. The variability existing over each of the future time slices is compared with the present climate variability to determine the future changes in inter annual fluctuations of monsoonal mean precipitation. The long-term (1970-2099) trend (mm/day/year) of monsoonal mean precipitation spatially distributed as well as averaged over Himalayan region is analyzed to detect any change across twenty-first century as well as to assess model uncertainty in simulating the precipitation changes over this period. The altitudinal distribution of difference in trend of future precipitation from present climate existing over each of the time slices is also studied to understand any elevation dependency of change in precipitation pattern. Except for a part of the Hindu-Kush area in western Himalayan region which shows drier condition, the CORDEX-SA experiments project in general wetter/drier conditions in near future for western/eastern Himalayan region, a scenario which gets further intensified in far future. Although, a gradually increasing precipitation trend is seen throughout the twenty-first century in carbon intensive scenarios, the distribution of trend with elevation presents a very complex picture with lower elevations showing a greater trend in far-future under RCP8.5 when compared with higher elevations.

Future Climate Change Impact Assessment of River Flows at Two Watersheds of Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ercan, A.; Ishida, K.; Kavvas, M. L.; Chen, Z. R.; Jang, S.; Amin, M. Z. M.; Shaaban, A. J.

2016-12-01

Impacts of climate change on the river flows under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate model and a physically-based hydrology model utilizing an ensemble of 15 different future climate realizations. Coarse resolution GCMs' future projections covering a wide range of emission scenarios were dynamically downscaled to 6 km resolution over the study area. Hydrologic simulations of the two selected watersheds were carried out at hillslope-scale and at hourly increments.

The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution

NASA Astrophysics Data System (ADS)

Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.

2012-12-01

Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately. These results will strengthen our understanding of the impacts of climate change today, and in future years considering different plausible scenarios.

Stress testing hydrologic models using bottom-up climate change assessment

NASA Astrophysics Data System (ADS)

Stephens, C.; Johnson, F.; Marshall, L. A.

2017-12-01

Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

Wintertime urban heat island modified by global climate change over Japan

NASA Astrophysics Data System (ADS)

Hara, M.

2015-12-01

Urban thermal environment change, especially, surface air temperature (SAT) rise in metropolitan areas, is one of the major recent issues in urban areas. The urban thermal environmental change affects not only human health such as heat stroke, but also increasing infectious disease due to spreading out virus vectors habitat and increase of industry and house energy consumption. The SAT rise is mostly caused by global climate change and urban heat island (hereafter UHI) by urbanization. The population in Tokyo metropolitan area is over 30 millions and the Tokyo metropolitan area is one of the biggest megacities in the world. The temperature rise due to urbanization seems comparable to the global climate change in the major megacities. It is important to project how the urbanization and the global climate change affect to the future change of urban thermal environment to plan the adaptation and mitigation policy. To predict future SAT change in urban scale, we should estimate future UHI modified by the global climate change. This study investigates change in UHI intensity (UHII) of major metropolitan areas in Japan by effects of the global climate change. We performed a series of climate simulations. Present climate simulations with and without urban process are conducted for ten seasons using a high-resolution numerical climate model, the Weather Research and Forecasting (WRF) model. Future climate projections with and without urban process are also conducted. The future projections are performed using the pseudo global warming method, assuming 2050s' initial and boundary conditions estimated by a GCM under the RCP scenario. Simulation results indicated that UHII would be enhanced more than 30% in Tokyo during the night due to the global climate change. The enhancement of urban heat island is mostly caused by change of lower atmospheric stability.

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Climate change impacts on extreme events in the United States: an uncertainty analysis

EPA Science Inventory

Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Evaluation of regional climate simulations for air quality modelling purposes

NASA Astrophysics Data System (ADS)

Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

2013-05-01

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

Climate-suitable planting as a strategy for maintaining forest productivity and functional diversity.

PubMed

Duveneck, Matthew J; Scheller, Robert M

2015-09-01

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass).

SIMULATING REGIONAL-SCALE AIR QUALITY WITH DYNAMIC CHANGES IN REGIONAL CLIMATE AND CHEMICAL BOUNDARY CONDITIONS

EPA Science Inventory

This poster compares air quality modeling simulations under current climate and a future (approximately 2050) climate scenario. Differences in predicted ozone episodes and daily average PM_2.5 concentrations are presented, along with vertical ozone profiles. Modeling ...

Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

NASA Astrophysics Data System (ADS)

Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D. A.; Brogaard, Sara; van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

2016-11-01

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.

Future efficiency of run of the river hydropower schemes based on climate change scenarios: case study in UK catchments

NASA Astrophysics Data System (ADS)

Pasten Zapata, Ernesto; Moggridge, Helen; Jones, Julie; Widmann, Martin

2017-04-01

Run-of-the-River (ROR) hydropower schemes are expected to be importantly affected by climate change as they rely in the availability of river flow to generate energy. As temperature and precipitation are expected to vary in the future, the hydrological cycle will also undergo changes. Therefore, climate models based on complex physical atmospheric interactions have been developed to simulate future climate scenarios considering the atmosphere's greenhouse gas concentrations. These scenarios are classified according to the Representative Concentration Pathways (RCP) that are generated according to the concentration of greenhouse gases. This study evaluates possible scenarios for selected ROR hydropower schemes within the UK, considering three different RCPs: 2.6, 4.5 and 8.5 W/m2 for 2100 relative to pre-industrial values. The study sites cover different climate, land cover, topographic and hydropower scheme characteristics representative of the UK's heterogeneity. Precipitation and temperature outputs from state-of-the-art Regional Climate Models (RCMs) from the Euro-CORDEX project are used as input for a HEC-HMS hydrological model to simulate the future river flow available. Both uncorrected and bias-corrected RCM simulations are analyzed. The results of this project provide an insight of the possible effects of climate change towards the generation of power from the ROR hydropower schemes according to the different RCP scenarios and contrasts the results obtained from uncorrected and bias-corrected RCMs. This analysis can aid on the adaptation to climate change as well as the planning of future ROR schemes in the region.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Impacts of a 2-Degree Rise in Global Temperatures upon Gas-Phase Air Pollutants in Europe

NASA Astrophysics Data System (ADS)

Watson, Laura; Josse, Béatrice; Marecal, Virginie; Lacressonnière, Gwendoline; Vautard, Robert; Gauss, Michael; Engardt, Magnuz; Nyiri, Agnes; Siour, Guillaume

2014-05-01

The 15th session of the Conference of Parties (COP 15) in 2009 ratified the Copenhagen Accord, which "recognises the scientific view that" global temperature rise should be held below 2 degrees C above pre-industrial levels in order to limit the impacts of climate change. Due to the fact that a 2-degree limit has been frequently referred to by policy makers in the context of the Copenhagen Accord and many other high-level policy statements, it is important that the impacts of this 2-degree increase in temperature are adequately analysed. To this end, the European Union sponsored the project IMPACT2C, which uses a multi-disciplinary international team to assess a wide variety of impacts of a 2-degree rise in global temperatures. For example, this future increase in temperature is expected to have a significant influence upon meteorological conditions such as temperature, precipitation, and wind direction and intensity; which will in turn affect the production, deposition, and distribution of air pollutants. For the first part of the air quality analysis within the IMPACT2C project, the impact of meteorological forcings on gas phase air pollutants over Europe was studied using four offline atmospheric chemistry transport models. Two sets of meteorological forcings were used for each model: reanalysis of past observation data and global climate model output. Anthropogenic emissions of ozone precursors for the year 2005 were used for all simulations in order to isolate the impact of meteorology and assess the robustness of the results across the different models. The differences between the simulations that use reanalysis of past observation data and the simulations that use global climate model output show how global climate models modify climate hindcasts by boundary conditions inputs: information that is necessary in order to interpret simulations of future climate. The baseline results were assessed by comparison with AirBase (Version 7) measurement data, and were then used as a reference for an analysis of future climate scenarios upon European air quality. The future scenarios included two types of emission data for the year 2050: one set of emission data corresponding to a current legislation scenario and another corresponding to a scenario with a maximum feasible reduction in emissions. The future scenarios were run for the time period that corresponds to a 2-degree increase in global temperatures; a time period that varies depending on which global climate model is used. In order to calculate the effect of climate change on emission reduction scenarios, the "climate penalty", the future simulations were compared to a simulation using the same future emissions but with current (2005) climate. Results show that climate change will have consequential impacts with regards to the production and geographical distribution of ozone and nitrogen oxides.

Comparing approaches for using climate projections in assessing water resources investments for systems with multiple stakeholder groups

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2015-04-01

Climate change has challenged conventional methods of planning water resources infrastructure investment, relying on stationarity of time-series data. It is not clear how to best use projections of future climatic conditions. Many-objective simulation-optimisation and trade-off analysis using evolutionary algorithms has been proposed as an approach to addressing complex planning problems with multiple conflicting objectives. The search for promising assets and policies can be carried out across a range of climate projections, to identify the configurations of infrastructure investment shown by model simulation to be robust under diverse future conditions. Climate projections can be used in different ways within a simulation model to represent the range of possible future conditions and understand how optimal investments vary according to the different hydrological conditions. We compare two approaches, optimising over an ensemble of different 20-year flow and PET timeseries projections, and separately for individual future scenarios built synthetically from the original ensemble. Comparing trade-off curves and surfaces generated by the two approaches helps understand the limits and benefits of optimising under different sets of conditions. The comparison is made for the Tana Basin in Kenya, where climate change combined with multiple conflicting objectives of water management and infrastructure investment mean decision-making is particularly challenging.

A first look at the influence of anthropogenic climate change on the future delivery of fluvial sediment to the Ganges-Brahmaputra-Meghna delta.

PubMed

Darby, Stephen E; Dunn, Frances E; Nicholls, Robert J; Rahman, Munsur; Riddy, Liam

2015-09-01

We employ a climate-driven hydrological water balance and sediment transport model (HydroTrend) to simulate future climate-driven sediment loads flowing into the Ganges-Brahmaputra-Meghna (GBM) mega-delta. The model was parameterised using high-quality topographic data and forced with daily temperature and precipitation data obtained from downscaled Regional Climate Model (RCM) simulations for the period 1971-2100. Three perturbed RCM model runs were selected to quantify the potential range of future climate conditions associated with the SRES A1B scenario. Fluvial sediment delivery rates to the GBM delta associated with these climate data sets are projected to increase under the influence of anthropogenic climate change, albeit with the magnitude of the increase varying across the two catchments. Of the two study basins, the Brahmaputra's fluvial sediment load is predicted to be more sensitive to future climate change. Specifically, by the middle part of the 21(st) century, our model results suggest that sediment loads increase (relative to the 1981-2000 baseline period) over a range of between 16% and 18% (depending on climate model run) for the Ganges, but by between 25% and 28% for the Brahmaputra. The simulated increase in sediment flux emanating from the two catchments further increases towards the end of the 21(st) century, reaching between 34% and 37% for the Ganges and between 52% and 60% for the Brahmaputra by the 2090s. The variability in these changes across the three climate change simulations is small compared to the changes, suggesting they represent a significant increase. The new data obtained in this study offer the first estimate of whether and how anthropogenic climate change may affect the delivery of fluvial sediment to the GBM delta, informing assessments of the future sustainability and resilience of one of the world's most vulnerable mega-deltas. Specifically, such significant increases in future sediment loads could increase the resilience of the delta to sea-level rise by giving greater potential for vertical accretion. However, these increased sediment fluxes may not be realised due to uncertainties in the monsoon related response to climate change or other human-induced changes in the catchment: this is a subject for further research.

Projected changes of the southwest Australian wave climate under two atmospheric greenhouse gas concentration pathways

NASA Astrophysics Data System (ADS)

Wandres, Moritz; Pattiaratchi, Charitha; Hemer, Mark A.

2017-09-01

Incident wave energy flux is responsible for sediment transport and coastal erosion in wave-dominated regions such as the southwestern Australian (SWA) coastal zone. To evaluate future wave climates under increased greenhouse gas concentration scenarios, past studies have forced global wave simulations with wind data sourced from global climate model (GCM) simulations. However, due to the generally coarse spatial resolution of global climate and wave simulations, the effects of changing offshore wave conditions and sea level rise on the nearshore wave climate are still relatively unknown. To address this gap of knowledge, we investigated the projected SWA offshore, shelf, and nearshore wave climate under two potential future greenhouse gas concentration trajectories (representative concentration pathways RCP4.5 and RCP8.5). This was achieved by downscaling an ensemble of global wave simulations, forced with winds from GCMs participating in the Coupled Model Inter-comparison Project (CMIP5), into two regional domains, using the Simulating WAves Nearshore (SWAN) wave model. The wave climate is modeled for a historical 20-year time slice (1986-2005) and a projected future 20-year time-slice (2081-2100) for both scenarios. Furthermore, we compare these scenarios to the effects of considering sea-level rise (SLR) alone (stationary wave climate), and to the effects of combined SLR and projected wind-wave change. Results indicated that the SWA shelf and nearshore wave climate is more sensitive to changes in offshore mean wave direction than offshore wave heights. Nearshore, wave energy flux was projected to increase by ∼10% in exposed areas and decrease by ∼10% in sheltered areas under both climate scenarios due to a change in wave directions, compared to an overall increase of 2-4% in offshore wave heights. With SLR, the annual mean wave energy flux was projected to increase by up to 20% in shallow water (< 30 m) as a result of decreased wave dissipation. In winter months, the longshore wave energy flux, which is responsible for littoral drift, is expected to increase by up to 39% (62%) under the RCP4.5 (RCP8.5) greenhouse gas concentration pathway with SLR. The study highlights the importance of using high-resolution wave simulations to evaluate future regional wave climates, since the coastal wave climate is more responsive to changes in wave direction and sea level than offshore wave heights.

Modelling the Holderness coast, eastern England: Past, present and future

NASA Astrophysics Data System (ADS)

Barkwith, A.; Limber, P. W.; Thomas, C. W.; Murray, A.; Jordan, H. M.; Ellis, M. A.

2012-12-01

The Holderness coast of eastern Yorkshire, England, is the most rapidly eroding coastline in Europe. Erosion can locally exceed 10 m in a single year and rates average 0.5 to 3 m yr-1, generally increasing from north to south. Pinned in the north by a chalk headland, the soft till coastline has a characteristic open spiral form terminated by a spit to the south. Erosion currently threatens local communities and infrastructure, including nationally important gas installations. Interventions to restrict local erosion usually result in enhanced erosion in adjacent, unprotected sections of coast, mirroring morphology seen on the large scale. We have initiated a modelling study to investigate the key controls on the form and evolution of this coastline, and its response to climate change, building on the Coastline Evolution Model (CEM) developed at Duke University, NC. We have adapted the CEM to permit an ensemble of simulations to be undertaken, based upon modified offshore wave climates, initial conditions and forcing factors. The CEM follows a standard 1d approach, where the cross-shore is collapsed into a single data point, allowing the planform shoreline shape and dynamics to be simulated. The model facilitates study of a coast with variable erosion rates, and enables simulation of coastline evolution when sediment is supplied from an eroding shoreface. Additionally, the CEM is adapted to use an observed two year, offshore wave climate data set as input. Initial work focussed on reconstruction of current coastline shape from an ensemble of hypothetical early Holocene shoreface positions and past wave climates. First order reconstruction of shoreline shape was achieved using several differing initial conditions and wave climates. For the majority of successful simulations, a steady state was noted for proceeding years, where erosion proceeds at an equal rate along the length of the coast south of the headland. Together with a sensitivity analysis, the derivation of the current coastline provided initial conditions for the second phase of the work: simulating the morphological response of the Holderness coastline to possible future changes in climate over the next century. An ensemble of future possible wave climate perturbations was generated from predictions of the likely response of the North Sea to future climate change over the next century, and applied linearly to the observed wave climate as each simulation progressed. The ensemble output was compared to a baseline simulation, run for a century under current wave climate, to assess the impact of predicted future climate on coastal erosion. Although this study does not currently take into account the changes in storm frequency, rises in sea level or the anthropogenic inputs that could influence the results, the initial output indicates erosional rates over the next century are likely to be retarded for the Holderness coastline under a changing climate.

Devon Ice cap's future: results from climate and ice dynamics modelling via surface mass balance modelling

NASA Astrophysics Data System (ADS)

Rodehacke, C. B.; Mottram, R.; Boberg, F.

2017-12-01

The Devon Ice Cap is an example of a relatively well monitored small ice cap in the Canadian Arctic. Close to Greenland, it shows a similar surface mass balance signal to glaciers in western Greenland. Here we various boundary conditions, ranging from ERA-Interim reanalysis data via global climate model high resolution (5km) output from the regional climate model HIRHAM5, to determine the surface mass balance of the Devon ice cap. These SMB estimates are used to drive the PISM glacier model in order to model the present day and future prospects of this small Arctic ice cap. Observational data from the Devon Ice Cap in Arctic Canada is used to evaluate the surface mass balance (SMB) data output from the HIRHAM5 model for simulations forced with the ERA-Interim climate reanalysis data and the historical emissions scenario run by the EC-Earth global climate model. The RCP8.5 scenario simulated by EC-Earth is also downscaled by HIRHAM5 and this output is used to force the PISM model to simulate the likely future evolution of the Devon Ice Cap under a warming climate. We find that the Devon Ice Cap is likely to continue its present day retreat, though in the future increased precipitation partly offsets the enhanced melt rates caused by climate change.

Precipitation Organization in a Warmer Climate

NASA Astrophysics Data System (ADS)

Rickenbach, T. M.; Nieto Ferreira, R.; Nissenbaum, M.

2014-12-01

This study will investigate changes in precipitation organization in a warmer climate using the Weather Research and Forecasting (WRF) model and CMIP-5 ensemble climate simulations. This work builds from an existing four-year NEXRAD radar-based precipitation climatology over the southeastern U.S. that uses a simple two-category framework of precipitation organization based on instantaneous precipitating feature size. The first category - mesoscale precipitation features (MPF) - dominates winter precipitation and is linked to the more predictable large-scale forcing provided by the extratropical cyclones. In contrast, the second category - isolated precipitation - dominates the summer season precipitation in the southern coastal and inland regions but is linked to less predictable mesoscale circulations and to local thermodynamics more crudely represented in climate models. Most climate modeling studies suggest that an accelerated water cycle in a warmer world will lead to an overall increase in precipitation, but few studies have addressed how precipitation organization may change regionally. To address this, WRF will simulate representative wintertime and summertime precipitation events in the Southeast US under the current and future climate. These events will be simulated in an environment resembling the future climate of the 2090s using the pseudo-global warming (PGW) approach based on an ensemble of temperature projections. The working hypothesis is that the higher water vapor content in the future simulation will result in an increase in the number of isolated convective systems, while MPFs will be more intense and longer-lasting. In the context of the seasonal climatology of MPF and isolated precipitation, these results have implications for assessing the predictability of future regional precipitation in the southeastern U.S.

Assessing the impact of future climate extremes on the US corn and soybean production

NASA Astrophysics Data System (ADS)

Jin, Z.

2015-12-01

Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.

Changing Characteristics of convective storms: Results from a continental-scale convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Prein, A. F.; Ikeda, K.; Liu, C.; Bullock, R.; Rasmussen, R.

2016-12-01

Convective storms are causing extremes such as flooding, landslides, and wind gusts and are related to the development of tornadoes and hail. Convective storms are also the dominant source of summer precipitation in most regions of the Contiguous United States. So far little is known about how convective storms might change due to global warming. This is mainly because of the coarse grid spacing of state-of-the-art climate models that are not able to resolve deep convection explicitly. Instead, coarse resolution models rely on convective parameterization schemes that are a major source of errors and uncertainties in climate change projections. Convection-permitting climate simulations, with grid-spacings smaller than 4 km, show significant improvements in the simulation of convective storms by representing deep convection explicitly. Here we use a pair of 13-year long current and future convection-permitting climate simulations that cover large parts of North America. We use the Method for Object-Based Diagnostic Evaluation (MODE) that incorporates the time dimension (MODE-TD) to analyze the model performance in reproducing storm features in the current climate and to investigate their potential future changes. We show that the model is able to accurately reproduce the main characteristics of convective storms in the present climate. The comparison with the future climate simulation shows that convective storms significantly increase in frequency, intensity, and size. Furthermore, they are projected to move slower which could result in a substantial increase in convective storm-related hazards such as flash floods, debris flows, and landslides. Some regions, such as the North Atlantic, might experience a regime shift that leads to significantly stronger storms that are unrepresented in the current climate.

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

Storylines of socio-economic and climatic drivers for land use and their hydrological impacts in alpine catchments - the STELLA project example

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Formayer, Herbert; Förster, Kristian; Marke, Thomas; Meißl, Gertraud; Schermer, Markus; Stotten, Friederike; Themessl, Matthias

2016-04-01

Future land use in Alpine catchments is controlled by the evolution of socio-economy and climate. Estimates of their coupled development should hence fulfill the principles of plausibility (be convincing) and consistency (be unambiguous). In the project STELLA, coupled future climate and land use scenarios are used as input in a hydrological modelling exercise with the physically-based, distributed water balance model WaSiM. The aim of the project is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The so-called „storylines" of future coupled climate and forest/land use management, policy, social cooperation, tourism and economy have jointly been developed in an inter- and transdisciplinary assessment with local actors. The climate background is given by simulations for the A1B (temperature conditions like today in Merano/Italy, 46.7°N) and RCP 8.5 (temperature conditions like today in Bologna/Italy, 44.5°N) emission scenarios. These two climate scenarios were combined with three potential socio-economic developments („local"/„glocal"/ „superglobal"), each in a positive and in a negative specification. From these twelve storylines of coupled climate/land use future, a set of four storylines was selected to be used in transient hydrological modelling experiments. Historical simulations of the water balance for the test site reveal the pattern of land use being the most prominent factor for the spatial distribution of its components. A new prototype for a snow-canopy interaction simulation module provides explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands in the catchment. This new canopy module will be used to model the coupled climate/land use future storylines for the Brixental. The aim is to quantify the effects of climate change and land use on the water balance and streamflow, both separately and in their respective combination.

Effectiveness and Tradeoffs between Portfolios of Adaptation Strategies Addressing Future Climate and Socioeconomic Uncertainties in California's Central Valley

NASA Astrophysics Data System (ADS)

Tansey, M. K.; Van Lienden, B.; Das, T.; Munevar, A.; Young, C. A.; Flores-Lopez, F.; Huntington, J. L.

2013-12-01

The Central Valley of California is one of the major agricultural areas in the United States. The Central Valley Project (CVP) is operated by the Bureau of Reclamation to serve multiple purposes including generating approximately 4.3 million gigawatt hours of hydropower and providing, on average, 5 million acre-feet of water per year to irrigate approximately 3 million acres of land in the Sacramento, San Joaquin, and Tulare Lake basins, 600,000 acre-feet per year of water for urban users, and 800,000 acre-feet of annual supplies for environmental purposes. The development of effective adaptation and mitigation strategies requires assessing multiple risks including potential climate changes as well as uncertainties in future socioeconomic conditions. In this study, a scenario-based analytical approach was employed by combining three potential 21st century socioeconomic futures with six representative climate and sea level change projections developed using a transient hybrid delta ensemble method from an archive of 112 bias corrected spatially downscaled CMIP3 global climate model simulations to form 18 future socioeconomic-climate scenarios. To better simulate the effects of climate changes on agricultural water demands, analyses of historical agricultural meteorological station records were employed to develop estimates of future changes in solar radiation and atmospheric humidity from the GCM simulated temperature and precipitation. Projected changes in atmospheric carbon dioxide were computed directly by weighting SRES emissions scenarios included in each representative climate projection. These results were used as inputs to a calibrated crop water use, growth and yield model to simulate the effects of climate changes on the evapotranspiration and yields of major crops grown in the Central Valley. Existing hydrologic, reservoir operations, water quality, hydropower, greenhouse gas (GHG) emissions and both urban and agricultural economic models were integrated into a suite of decision support tools to assess the impacts of future socioeconomic-climate uncertainties on key performance metrics for the CVP, State Water Project and other Central Valley water management systems under current regulatory requirements. Four thematic portfolios consisting of regional and local adaptation strategies including changes in reservoir operations, increased water conservation, storage and conveyance were developed and simulated to evaluate their potential effectiveness in meeting delivery reliability, water quality, environmental, hydropower, GHG, urban and agricultural economic performance criteria. The results indicate that the portfolios exhibit a considerable range of effectiveness depending on the socioeconomic-climate scenario. For most criteria, the portfolios were more sensitive to climate projections than socioeconomic assumptions. However, the results demonstrate that important tradeoffs occur between portfolios depending on the performance criteria considered.

Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.

PubMed

Dib, Alain E; Johnson, Chris E; Driscoll, Charles T; Fahey, Timothy J; Hayhoe, Katharine

2014-05-01

Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions. © 2013 John Wiley & Sons Ltd.

Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington

USGS Publications Warehouse

Mastin, Mark; Josberger, Edward

2014-01-01

Seasonally frozen ground occurs over approximately one‑third of the contiguous United States, causing increased winter runoff. Frozen ground generally rejects potential groundwater recharge. Nearly all recharge from precipitation in semi-arid regions such as the Columbia Plateau and the Snake River Plain in Idaho, Oregon, and Washington, occurs between October and March, when precipitation is most abundant and seasonally frozen ground is commonplace. The temporal and spatial distribution of frozen ground is expected to change as the climate warms. It is difficult to predict the distribution of frozen ground, however, because of the complex ways ground freezes and the way that snow cover thermally insulates soil, by keeping it frozen longer than it would be if it was not snow covered or, more commonly, keeping the soil thawed during freezing weather. A combination of satellite remote sensing and ground truth measurements was used with some success to investigate seasonally frozen ground at local to regional scales. The frozen-ground/snow-cover algorithm from the National Snow and Ice Data Center, combined with the 21-year record of passive microwave observations from the Special Sensor Microwave Imager onboard a Defense Meteorological Satellite Program satellite, provided a unique time series of frozen ground. Periodically repeating this methodology and analyzing for trends can be a means to monitor possible regional changes to frozen ground that could occur with a warming climate. The Precipitation-Runoff Modeling System watershed model constructed for the upper Crab Creek Basin in the Columbia Plateau and Reynolds Creek basin on the eastern side of the Snake River Plain simulated recharge and frozen ground for several future climate scenarios. Frozen ground was simulated with the Continuous Frozen Ground Index, which is influenced by air temperature and snow cover. Model simulation results showed a decreased occurrence of frozen ground that coincided with increased temperatures in the future climate scenarios. Snow cover decreased in the future climate scenarios coincident with the temperature increases. Although annual precipitation was greater in future climate scenarios, thereby increasing the amount of water available for recharge over current (baseline) simulations, actual evapotranspiration also increased and reduced the amount of water available for recharge over baseline simulations. The upper Crab Creek model shows no significant trend in the rates of recharge in future scenarios. In these scenarios, annual precipitation is greater than the baseline averages, offsetting the effects of greater evapotranspiration in future scenarios. In the Reynolds Creek Basin simulations, precipitation was held constant in future scenarios and recharge was reduced by 1.0 percent for simulations representing average conditions in 2040 and reduced by 4.3 percent for simulations representing average conditions in 2080. The focus of the results of future scenarios for the Reynolds Creek Basin was the spatial components of selected hydrologic variables for this 92 square mile mountainous basin with 3,600 feet of relief. Simulation results from the watershed model using the Continuous Frozen Ground Index provided a relative measure of change in frozen ground, but could not identify the within-soil processes that allow or reject available water to recharge aquifers. The model provided a means to estimate what might occur in the future under prescribed climate scenarios, but more detailed energy-balance models of frozen-ground hydrology are needed to accurately simulate recharge under seasonally frozen ground and provide a better understanding of how changes in climate may alter infiltration.

Implication of Agricultural Land Use Change on Regional Climate Projection

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes.

PubMed

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-11-01

Currently, the temperate forest biome cools the earth's climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (-10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems.

Cryospheric Research in China

DTIC Science & Technology

2015-03-30

marine monitoring for environment and security, using satellite Earth observation technologies), the WCRP/CliC Project (an international cooperative...BIOME4) to simulate the responses of biome distribution to future climate change in China. The simulation results suggest that regional climate

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0)contribution to CMIP6

DOE PAGES

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; ...

2016-10-18

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of futuremore » climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.« less

Simulating future climate and land-use impacts on at-risk species in parks and protected areas

EPA Science Inventory

Alpine and sagebrush ecosystems in the mountain west are under threat from climate change and development. The wolverine, fisher, greater sage-grouse,and pygmy rabbit are iconic at-risk species in the region. We explore the impacts of future climate and land-use change on these s...

Simulation of growth of Adirondack conifers in relation to global climate change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Y.; Raynal, D.J.

1993-06-01

Several conifer species grown in plantations in the southeastern Adirondack mountains of New York were chosen to model tree growth. In the models, annual xylem growth was decomposed into several components that reflect various intrinsic or extrinsic factors. Growth signals indicative of climatic effects were used to construct response functions using both multivariate analysis and Kalman filter methods. Two models were used to simulate tree growth response to future CO[sub 2]-induced climate change projected by GCMs. The comparable results of both models indicate that different conifer species have individualistic growth responses to future climatic change. The response behaviors of treesmore » are affected greatly by local stand conditions. The results suggest possible changes in future growth and distributions of naturally occurring conifers in this region.« less

Modeling the potential persistence of various ecological systems under CMIP5 future climate and land use scenarios throughout California, USA

NASA Astrophysics Data System (ADS)

Baker, B.; Ferschweiler, K.; Bachelet, D. M.; Sleeter, B. M.

2016-12-01

California's geographic location, topographic complexity and latitudinal climatic gradient give rise to great biological and ecological diversity. However, increased land use pressure, altered seasonal weather patterns, and changes in temperature and precipitation regimes are having pronounced effects on ecosystems and the multitude of services they provide for an increasing population. As a result, natural resource managers are faced with formidable challenges to maintain these critical services. The goals of this project were to better understand how projected 21st century climate and land-use change scenarios may alter ecosystem dynamics, the spatial distribution of various vegetation types and land-use patterns, and to provide a coarse scale "triage map" of where land managers may want to concentrate efforts to reduce ecological stress in order to mitigate the potential impacts of a changing climate. We used the MC2 dynamic global vegetation model and the LUCAS state-and-transition simulation model to simulate the potential effects of future climate and land-use change on ecological processes for the state of California. Historical climate data were obtained from the PRISM dataset and nine CMIP5 climate models were run for the RCP 8.5 scenario. Climate projections were combined with a business-as-usual land-use scenario based on local-scale land use histories. For ease of discussion, results from five simulation runs (historic, hot-dry, hot-wet, warm-dry, and warm-wet) are presented. Results showed large changes in the extent of urban and agricultural lands. In addition, several simulated potential vegetation types persisted in situ under all four future scenarios, although alterations in total area, total ecosystem carbon, and forest vigor (NPP/LAI) were noted. As might be expected, the majority of the forested types that persisted occurred on public lands. However, more than 78% of the simulated subtropical mixed forest and 26% of temperate evergreen needleleaf forest types persisted on private lands under all four future scenarios. Result suggest that building collaborations across management borders could be valuable tool to guide natural resource management actions into the future.

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355

Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.

Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States

NASA Astrophysics Data System (ADS)

Rasmussen, K. L.; Prein, A. F.; Rasmussen, R. M.; Ikeda, K.; Liu, C.

2017-11-01

Novel high-resolution convection-permitting regional climate simulations over the US employing the pseudo-global warming approach are used to investigate changes in the convective population and thermodynamic environments in a future climate. Two continuous 13-year simulations were conducted using (1) ERA-Interim reanalysis and (2) ERA-Interim reanalysis plus a climate perturbation for the RCP8.5 scenario. The simulations adequately reproduce the observed precipitation diurnal cycle, indicating that they capture organized and propagating convection that most climate models cannot adequately represent. This study shows that weak to moderate convection will decrease and strong convection will increase in frequency in a future climate. Analysis of the thermodynamic environments supporting convection shows that both convective available potential energy (CAPE) and convective inhibition (CIN) increase downstream of the Rockies in a future climate. Previous studies suggest that CAPE will increase in a warming climate, however a corresponding increase in CIN acts as a balancing force to shift the convective population by suppressing weak to moderate convection and provides an environment where CAPE can build to extreme levels that may result in more frequent severe convection. An idealized investigation of fundamental changes in the thermodynamic environment was conducted by shifting a standard atmospheric profile by ± 5 °C. When temperature is increased, both CAPE and CIN increase in magnitude, while the opposite is true for decreased temperatures. Thus, even in the absence of synoptic and mesoscale variations, a warmer climate will provide more CAPE and CIN that will shift the convective population, likely impacting water and energy budgets on Earth.

Exploring the implication of climate process uncertainties within the Earth System Framework

NASA Astrophysics Data System (ADS)

Booth, B.; Lambert, F. H.; McNeal, D.; Harris, G.; Sexton, D.; Boulton, C.; Murphy, J.

2011-12-01

Uncertainties in the magnitude of future climate change have been a focus of a great deal of research. Much of the work with General Circulation Models has focused on the atmospheric response to changes in atmospheric composition, while other processes remain outside these frameworks. Here we introduce an ensemble of new simulations, based on an Earth System configuration of HadCM3C, designed to explored uncertainties in both physical (atmospheric, oceanic and aerosol physics) and carbon cycle processes, using perturbed parameter approaches previously used to explore atmospheric uncertainty. Framed in the context of the climate response to future changes in emissions, the resultant future projections represent significantly broader uncertainty than existing concentration driven GCM assessments. The systematic nature of the ensemble design enables interactions between components to be explored. For example, we show how metrics of physical processes (such as climate sensitivity) are also influenced carbon cycle parameters. The suggestion from this work is that carbon cycle processes represent a comparable contribution to uncertainty in future climate projections as contributions from atmospheric feedbacks more conventionally explored. The broad range of climate responses explored within these ensembles, rather than representing a reason for inaction, provide information on lower likelihood but high impact changes. For example while the majority of these simulations suggest that future Amazon forest extent is resilient to the projected climate changes, a small number simulate dramatic forest dieback. This ensemble represents a framework to examine these risks, breaking them down into physical processes (such as ocean temperature drivers of rainfall change) and vegetation processes (where uncertainties point towards requirements for new observational constraints).

Simulating the response of natural ecosystems and their fire regimes to climatic variability in Alaska.

Treesearch

D. Bachelet; J. Lenihan; R. Neilson; R. Drapek; T. Kittel

2005-01-01

The dynamic global vegetation model MC1 was used to examine climate, fire, and ecosystems interactions in Alaska under historical (1922-1996) and future (1997-2100) climate conditions. Projections show that by the end of the 21st century, 75%-90% of the area simulated as tundra in 1922 is replaced by boreal and temperate forest. From 1922 to 1996, simulation results...

WRF-Cordex simulations for Europe: mean and extreme precipitation for present and future climates

NASA Astrophysics Data System (ADS)

Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.

2013-04-01

The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2013-01-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model.

PubMed

King, David A; Bachelet, Dominique M; Symstad, Amy J

2013-12-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine-prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Climate change and fire effects on a prairie–woodland ecotone: projecting species range shifts with a dynamic global vegetation model

PubMed Central

King, David A; Bachelet, Dominique M; Symstad, Amy J

2013-01-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects. PMID:24455138

Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed

NASA Astrophysics Data System (ADS)

Jyrkama, M. I.; Sykes, J. F.

2004-05-01

The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.

The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

DOE PAGES

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

2016-11-16

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

NASA Technical Reports Server (NTRS)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.;

Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Simulating malaria transmission in the current and future climate of West Africa

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Bomblies, A.; Eltahir, E. A. B.

2015-12-01

Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. We present results of a highly detailed, spatially explicit mechanistic modelling study exploring the relationships between the environment and malaria in the current and future climate of West Africa. A mechanistic model of human immunity was incorporated into an existing agent-based model of malaria transmission, allowing us to move beyond entomological measures such as mosquito density and vectorial capacity to analyzing the prevalence of the malaria parasite within human populations. The result is a novel modelling tool that mechanistically simulates all of the key processes linking environment to malaria transmission. Simulations were conducted across climate zones in West Africa, linking temperature and rainfall to entomological and epidemiological variables with a focus on nonlinearities due to threshold effects and interannual variability. Comparisons to observations from the region confirmed that the model provides a reasonable representation of the entomological and epidemiological conditions in this region. We used the predictions of future climate from the most credible CMIP5 climate models to predict the change in frequency and severity of malaria epidemics in West Africa as a result of climate change.

The response of vegetation distribution, ecosystem productivity, and fire in California to future climate scenarios simulated by the MC1 dynamic vegetation dynamic.

Treesearch

James M. Lenihan; Dominique Bachelet; Raymond Drapek; Ronald P. Neilson

2006-01-01

The objective of this study was to dynamically simulate the response of vegetation distribution, carbon, and fire to three scenarios of future climate change for California using the MAPSS-CENTURY (MCI) dynamic general vegetation model. Under all three scenarios, Alpine/Subalpine Forest cover declined with increased growing season length and warmth, and increases in...

Climate change negotiation simulations for students: responses across gender and age.A case study: San Francisco State University World Climate Exercises

NASA Astrophysics Data System (ADS)

Rasheva, E. A.

2015-12-01

For decades, role-play and simulation exercises have been utilized for learning and policy decision making. While the power of Model UN simulations in building first-person experience and understanding of complex international issues is well known, the effectiveness of simulations for inspiring citizen engagement in scientific public-policy issues is little studied. My work hypothesizes that climate-change negotiation simulations can enhance students' scientific literacy and policy advocacy. It aims to determine how age and gender influence the responsiveness of students to such simulations. During the 2015 fall semester, I am conducting World Climate exercises for fellow graduate and undergraduate students at San Francisco State University. At the end of the exercise, I will have collected the responses to an anonymous questionnaire in which the participants indicate age and gender. The questionnaire asks participants to describe their hopes and fears for the future and to propose public and personal actions for achieving a strong climate change agreement. I am tracking differences to determine whether participants' age and gender correlate with particular patterns of feeling and thinking. My future research will aim to determine whether and how strongly the World Climate Exercise has affected participants' actual policy engagement. This work will also reflect on my experiences as a World Climate facilitator. I will describe the facilitation process and then discuss some of my observations from the sessions. I will specify the challenges I have encountered and suggest strategies that can strengthen the learning process. World Climate is a computer-simulation-based climate change negotiations role-playing exercise developed by Climate Interactive in partnership with the System Dynamics Group at the MIT Sloan School of Management.

Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099

USGS Publications Warehouse

Wood, Tamara M.; Wherry, Susan A.; Piccolroaz, Sebastiano; Girdner, Scott F

2016-05-04

The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

TECA: Petascale pattern recognition for climate science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabhat, .; Byna, Surendra; Vishwanath, Venkatram

Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less

From ENSEMBLES to CORDEX: exploring the progress for hydrological impact research for the upper Danube basin

NASA Astrophysics Data System (ADS)

Stanzel, Philipp; Kling, Harald

2017-04-01

EURO-CORDEX Regional Climate Model (RCM) data are available as result of the latest initiative of the climate modelling community to provide ever improved simulations of past and future climate in Europe. The spatial resolution of the climate models increased from 25 x 25 km in the previous coordinated initiative, ENSEMBLES, to 12 x 12 km in the CORDEX EUR-11 simulations. This higher spatial resolution might yield improved representation of the historic climate, especially in complex mountainous terrain, improving applicability in impact studies. CORDEX scenario simulations are based on Representative Concentration Pathways, while ENSEMBLES applied the SRES greenhouse gas emission scenarios. The new emission scenarios might lead to different projections of future climate. In this contribution we explore these two dimensions of development from ENSEMBLES to CORDEX - representation of the past and projections for the future - in the context of a hydrological climate change impact study for the Danube River. We replicated previous hydrological simulations that used ENSEMBLES data of 21 RCM simulations under SRES A1B emission scenario as meteorological input data (Kling et al. 2012), and now applied CORDEX EUR-11 data of 16 RCM simulations under RCP4.5 and RCP8.5 emission scenarios. The climate variables precipitation and temperature were used to drive a monthly hydrological model of the upper Danube basin upstream of Vienna (100,000 km2). RCM data was bias corrected and downscaled to the scale of hydrological model units. Results with CORDEX data were compared with results with ENSEMBLES data, analysing both the driving meteorological input and the resulting discharge projections. Results with CORDEX data show no general improvement in the accuracy of representing historic climatic features, despite the increase in spatial model resolution. The tendency of ENSEMBLES scenario projections of increasing precipitation in winter and decreasing precipitation in summer is reproduced with the CORDEX RCMs, albeit with slightly higher precipitation in the CORDEX data. The distinct pattern of future change in discharge seasonality - increasing winter discharge and decreasing summer discharge - is confirmed with the new CORDEX data, with a range of projections very similar to the range projected by the ENSEMBLES RCMs. References: Kling, H., Fuchs, M., Paulin, M. 2012. Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology 424-425, 264-277.

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations.

PubMed

Tang, Ying; Winkler, Julie; Zhong, Shiyuan; Bian, Xindi; Doubler, Dana; Yu, Lejiang; Walters, Claudia

2017-07-10

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereas current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. The choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.

Relative impacts of land use and climate change on summer precipitation in the Netherlands

NASA Astrophysics Data System (ADS)

Daniels, Emma; Lenderink, Geert; Hutjes, Ronald; Holtslag, Albert

2016-10-01

The effects of historic and future land use on precipitation in the Netherlands are investigated on 18 summer days with similar meteorological conditions. The days are selected with a circulation type classification and a clustering procedure to obtain a homogenous set of days that is expected to favor land impacts. Changes in precipitation are investigated in relation to the present-day climate and land use, and from the perspective of future climate and land use. To that end, the weather research and forecasting (WRF) model is used with land use maps for 1900, 2000, and 2040. In addition, a temperature perturbation of +1 °C assuming constant relative humidity is imposed as a surrogate climate change scenario. Decreases in precipitation of, respectively, 3-5 and 2-5 % are simulated following conversion of historic to present, and present to future, land use. The temperature perturbation under present land use conditions increases precipitation amounts by on average 7-8 % and amplifies precipitation intensity. However, when also considering future land use, the increase is reduced to 2-6 % on average, and no intensification of extreme precipitation is simulated. In all, the simulated effects of land use changes on precipitation in summer are smaller than the effects of climate change, but are not negligible.

NOAA's State Climate Summaries for the National Climate Assessment: A Sustained Assessment Product

NASA Astrophysics Data System (ADS)

Kunkel, K.; Champion, S.; Frankson, R.; Easterling, D. R.; Griffin, J.; Runkle, J. D.; Stevens, L. E.; Stewart, B. C.; Sun, L.; Veasey, S.

2016-12-01

A set of State Climate Summaries have been produced for all 50 U.S. states as part of the National Climate Assessment Sustained Assessment and represent a NOAA contribution to this process. Each summary includes information on observed and projected climate change conditions and impacts associated with future greenhouse gas emissions pathways. The summaries focus on the physical climate and coastal issues as a part of NOAA's mission. Core climate data and simulations used to produce these summaries have been previously published, and have been analyzed to represent a targeted synthesis of historical and plausible future climate conditions. As these are intended to be supplemental to major climate assessment development, the scope of the content remains true to a "summary" style document. Each state's Climate Summary includes its climatology and projections of future temperatures and precipitation, which are presented in order to provide a context for the assessment of future impacts. The climatological component focuses on temperature, precipitation, and noteworthy weather events specific to each state and relevant to the climate change discussion. Future climate scenarios are also briefly discussed, using well-known and consistent sets of climate model simulations based on two possible futures of greenhouse gas emissions. These future scenarios present an internally consistent climate picture for every state and are intended to inform the potential impacts of climate change. These 50 State Climate Summaries were produced by NOAA's National Centers for Environmental Information (NCEI) and the North Carolina State University Cooperative Institute for Climate and Satellites - NC (CICS-NC) with additional input provided by climate experts, including the NOAA Regional Climate Centers and State Climatologists. Each summary document also underwent a comprehensive and anonymous peer review. Each summary contains text, figures, and an interactive web presentation. A full suite of the comprehensive analyses and metadata are also available. The audience is targeted as both decision-makers and informed non-scientists. This presentation will discuss the scientific development for the project, demonstrate the suite of information, and provide examples of noteworthy figures from select states.

Changes in U.S. Regional-Scale Air Quality at 2030 Simulated Using RCP 6.0

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Recent improvements in air quality in the United States have been due to significant reductions in emissions of ozone and particulate matter (PM) precursors, and these downward emissions trends are expected to continue in the next few decades. To ensure that planned air quality regulations are robust under a range of possible future climates and to consider possible policy actions to mitigate climate change, it is important to characterize and understand the effects of climate change on air quality. Recent work by several research groups using global and regional models has demonstrated that there is a "climate penalty," in which climate change leads to increases in surface ozone levels in polluted continental regions. One approach to simulating future air quality at the regional scale is via dynamical downscaling, in which fields from a global climate model are used as input for a regional climate model, and these regional climate data are subsequently used for chemical transport modeling. However, recent studies using this approach have encountered problems with the downscaled regional climate fields, including unrealistic surface temperatures and misrepresentation of synoptic pressure patterns such as the Bermuda High. We developed a downscaling methodology and showed that it now reasonably simulates regional climate by evaluating it against historical data. In this work, regional climate simulations created by downscaling the NASA/GISS Model E2 global climate model are used as input for the Community Multiscale Air Quality (CMAQ) model. CMAQ simulations over the continental United States are conducted for two 11-year time slices, one representing current climate (1995-2005) and one following Representative Concentration Pathway 6.0 from 2025-2035. Anthropogenic emissions of ozone and PM precursors are held constant at year 2006 levels for both the current and future periods. In our presentation, we will examine the changes in ozone and PM concentrations, with particular focus on exceedances of the current U.S. air quality standards, and attempt to relate the changes in air quality to the projected changes in regional climate.

Simulated hydrologic response to climate change during the 21st century in New Hampshire

USGS Publications Warehouse

Bjerklie, David M.; Sturtevant, Luke P.

2018-01-24

The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.

Assessing recent and near-future changes in Southern California's groundwater storage from the perspective of regional climate modeling

NASA Astrophysics Data System (ADS)

De Sales, F.; Rother, D.

2017-12-01

Current climate change assessments project an increase in temperature throughout the western U.S. over the next century, while precipitation is projected to decrease in the Southwest. These assessments are based mainly on coarse spatial resolution general circulation model (GCM) simulations, which do not include groundwater (soil and aquifer) storage projections. However, water availability is a regionally variable resource and climate change impacts on groundwater distribution will probably differ regionally across the southwestern U.S. We have implemented a coupled atmosphere-biosphere-aquifer regional modelling system (WRF/SSiB2/SIMGM) to generate recent (2005-2017) and near-future (2018-2030) high-resolution groundwater projections for Southern California. These projections are obtained by dynamic downscaling data from the Global Operation Analysis (recent) and the NCAR Community Earth System Model CMIP5 global projections (near future), which supported the Intergovernmental Panel on Climate Change 5th Assessment Report. Near-future simulations include three representative concentration pathway (RCP) scenarios namely, RCP4.5, RCP6, and RCP8.5. The model can reasonably simulate the recent changes in Southern California's groundwater as indicated by a comparison to terrestrial water storage obtained from the Gravity Recovery and Climate Experiment dataset. In particular, the 2011-2017 drought is simulated well with total groundwater storages declining throughout the period, especially along the western portion of the domain, which includes the high-populated areas of western Los Angeles, San Diego, Ventura and Orange counties. In general, the near-future simulations show a decline in groundwater storage for the region. The largest changes are observed with the RCP8.5 emission pathway, towards to southeastern tier of the study area. In addition to groundwater, this downscaling experiment also generates high-resolution precipitation and temperature estimates, which can help policy makers in the development of strategies to alleviate potential water resource deficiencies in California in the near future.

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

NASA Astrophysics Data System (ADS)

Dudula, John; Randhir, Timothy O.

2016-10-01

Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

The evolution of the Brewer-Dobson Circulation from 1960-2100 in simulations with the Chemistry Climate Model EMAC

NASA Astrophysics Data System (ADS)

Oberländer, Sophie; Langematz, Ulrike; Kubin, Anne; Abalichin, Janna; Meul, Stefanie; Jöckel, Patrick; Brühl, Christoph

2010-05-01

First results of research performed within the new DFG Research Unit Stratospheric Change and its Role for Climate Prediction (SHARP) will be presented. SHARP investigates past and future changes in stratospheric dynamics and composition to improve the understanding of global climate change and the accuracy of climate change predictions. SHARP combines the efforts of eight German research institutes and expertise in state-of-the-art climate modelling and observations. Within the scope of the scientific sub-project SHARP-BDC (Brewer-Dobson-Circulation) the past and future evolution of the BDC in an atmosphere with changing composition will be analysed. Radiosonde data show an annual mean cooling of the tropical lower stratosphere over the past few decades (Thompson and Solomon, 2005). Several independent model simulations indicate an acceleration of the BDC due to higher greenhouse gas (GHG) concentrations with direct impact on the exchange of air masses between the troposphere and stratosphere (e.g., Butchart et al, 2006). In contrast, from balloon-born measurements no significant acceleration in the BDC could be identified (Engel et al, 2008). This disagreement between observations and model analyses motivates further studies. For the future, expected changes in planetary wave generation and propagation in an atmosphere with increasing GHG concentrations are a major source of uncertainty for predicting future levels of stratospheric composition. To analyse and interpret the past and future evolution of the BDC, results from a transient multi-decadal simulation with the Chemistry-Climate Model (CCM) EMAC will be presented. The model has been integrated from 1960 to 2100 following the SCN2d scenario recommendations of the SPARC CCMVal initiative for the temporal evolution of GHGs, ozone depleting substances and sea surface temperatures as well as sea ice. The role of increasing GHG concentrations for the BDC will be assessed by comparing the SCN2d-results with a ‘non-climate change' (NCC) simulation, in which greenhouse gases have been kept fixed at their 1960 concentrations.

Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution AGCM based on the RCP scenarios

NASA Astrophysics Data System (ADS)

Woo, Sumin; Singh, Gyan Prakash; Oh, Jai-Ho; Lee, Kyoung-Min

2018-05-01

Seasonal changes in precipitation characteristics over India were projected using a high-resolution (40-km) atmospheric general circulation model (AGCM) during the near- (2010-2039), mid- (2040-2069), and far- (2070-2099) futures. For the model evaluation, we simulated an Atmospheric Model Intercomparison Project-type present-day climate using AGCM with observed sea-surface temperature and sea-ice concentration. Based on this simulation, we have simulated the current climate from 1979 to 2009 and subsequently the future climate projection until 2100 using a CMCC-CM model from Coupled Model Intercomparison Project phase 5 models based on RCP4.5 and RCP8.5 scenarios. Using various observed precipitation data, the validation of the simulated precipitation indicates that the AGCM well-captured the high and low rain belts and also onset and withdrawal of monsoon in the present-day climate simulation. Future projections were performed for the above-mentioned time slices (near-, mid-, and far futures). The model projected an increase in summer precipitation from 7 to 18% under RCP4.5 and from 14 to 18% under RCP8.5 from the mid- to far futures. Projected summer precipitation from different time slices depicts an increase over northwest (NWI) and west-south peninsular India (SPI) and a reduction over northeast and north-central India. The model projected an eastward shift of monsoon trough around 2° longitude and expansion and intensification of Mascarene High and Tibetan High seems to be associated with projected precipitation. The model projected extreme precipitation events show an increase (20-50%) in rainy days over NWI and SPI. While a significant increase of about 20-50% is noticed in heavy rain events over SPI during the far future.

Future changes in summer mean and extreme precipitation frequency in Japan by d4PDF regional climate simulations

NASA Astrophysics Data System (ADS)

Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.

2017-12-01

Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Simulations of the Montréal urban heat island

NASA Astrophysics Data System (ADS)

Roberge, François; Sushama, Laxmi; Fanta, Gemechu

2017-04-01

The current population of Montreal is around 3.8 million and this number is projected to go up in the coming years to decades, which will lead to vast expansion of urban areas. It is well known that urban morphology impacts weather and climate, and therefore should be taken into consideration in urban planning. This is particularly important in the context of a changing climate, as the intensity and frequency of temperature extremes such as hot spells are projected to increase in future climate, and Urban Heat Island (UHI) can potentially raise already stressful temperatures during such events, which can have significant effects on human health and energy consumption. High-resolution regional climate model simulations can be utilized to understand better urban-weather/climate interactions in current and future climates, particularly the spatio-temporal characteristics of the Urban Heat Island and its impact on other weather/climate characteristics such as urban flows, precipitation etc. This paper will focus on two high-resolution (250 m) simulations performed with (1) the Canadian Land Surface Scheme (CLASS) and (2) CLASS and TEB (Town Energy Balance) model; TEB is a single layer urban canopy model and is used to model the urban fractions. The two simulations are performed over a domain covering Montreal for the 1960-2015 period, driven by atmospheric forcing data coming from a high-resolution Canadian Regional Climate Model (CRCM5) simulation, driven by ERA-Interim. The two simulations are compared to assess the impact of urban regions on selected surface fields and the simulation with both CLASS and TEB is then used to study the spatio-temporal characteristics of the UHI over the study domain. Some preliminary results from a coupled simulation, i.e. CRCM5+CLASS+TEB, for selected years, including extreme warm years, will also be presented.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

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.

Persistent cold air outbreaks over North America in a warming climate

DOE PAGES

Gao, Yang; Leung, L. Ruby; Lu, Jian; ...

2015-03-30

This study examines future changes of cold air outbreaks (CAO) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 as well as regional high resolution climate simulations. In the future, while robust decrease of CAO duration dominates in most regions, the magnitude of decrease over northwestern U.S. is much smaller than the surrounding regions. We identified statistically significant increases in sea level pressure during CAO events centering over Yukon, Alaska, and Gulf of Alaska that advects continental cold air to northwestern U.S., leading to blocking and CAO events. Changes in large scale circulationmore » contribute to about 50% of the enhanced sea level pressure anomaly conducive to CAO in northwestern U.S. in the future. High resolution regional simulations revealed potential contributions of increased existing snowpack to increased CAO in the near future over the Rocky Mountain, southwestern U.S., and Great Lakes areas through surface albedo effects, despite winter mean snow water equivalent decreases in the future. Overall, the multi-model projections emphasize that cold extremes do not completely disappear in a warming climate. Concomitant with the relatively smaller reduction in CAO events in northwestern U.S., the top 5 most extreme CAO events may still occur in the future, and wind chill warning will continue to have societal impacts in that region.« less

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak

2015-04-01

Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties.

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

NASA Astrophysics Data System (ADS)

Wu, Yenan; Zhong, Ping-an; Xu, Bin; Zhu, Feilin; Fu, Jisi

2017-06-01

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960-2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001-2010) and the predicting period (2011-2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2018-01-01

Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526

Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.

Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.

2012-09-01

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 10-90 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 degrees (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 timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside 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 uppper 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.

Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

2013-04-01

The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc. Nonetheless, according to the results of this work future ozone is conditioned by the dependence of biogenic emissions on the climatological patterns of variability. In this sense, ozone over Europe is mainly driven by the warming-induced increase in biogenic emitting activity (vegetation is kept invariable in the simulations, but estimations of these emissions strongly depends on shortwave radiation and temperature, which are substantially modified in climatic simulations). Moreover, one of the most important drivers for ozone increase is the decrease of cloudiness (related to stronger solar radiation) mostly over southern Europe at the first half of the XXI century. However, given the large uncertainty isoprene sensitivity to climate change and the large uncertainties associated to the cloudiness projections, these results should be carefully considered.

The importance of considering shifts in seasonal changes in discharges when predicting future phosphorus loads in streams

USGS Publications Warehouse

LaBeau, Meredith B.; Mayer, Alex S.; Griffis, Veronica; Watkins, David Jr.; Robertson, Dale M.; Gyawali, Rabi

2015-01-01

In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.

A Regional-Scale Evaluation on Environmental Stability Conditions for Convective Rain under Climate Change from Super-High-Resolution GCM Simulations

NASA Astrophysics Data System (ADS)

Takemi, T.; Nomura, S.; Oku, Y.; Ishikawa, H.

2011-12-01

Understanding and forecasting of convective rain due to intense thunderstorms, which develop under conditions both with and without significant synoptic-scale and/or mesoscale forcings, are critical in dealing with disaster prevention/mitigation and developing urban planning appropriate for disaster management. Thunderstorms rapidly develop even during the daytimes of fair weather conditions without any external forcings, and sometimes become strong enough to induce local-scale meteorological disasters such as torrential rain, flush flooding, high winds, and tornadoes/gusts. With the growing interests in climate change, future changes in the behavior of such convectively generated extreme events have gained scientific and societal interests. This study conducted the regional-scale evaluations on the environmental stability conditions for convective rain that develops under synoptically undisturbed, summertime conditions by using the outputs of super-high-resolution AGCM simulations, at a 20-km resolution, for the present, the near-future, and the future climates under global warming with IPCC A1B emission scenario. The GCM, MRI-AGCM3.2S, was developed by Meteorological Research Institute of Japan Meteorological Agency under the KAKUSHIN program funded by the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The climate simulation outputs that were used in this study corresponded to three 25-year periods: 1980-2004 for the present climate; 2020-2044 for the near-future climate; and 2075-2099 for the future climate. The Kanto Plain that includes the Tokyo metropolitan area was chosen as the study area, since the Tokyo metropolitan area is one of the largest metropolises in the world and is vulnerable to extreme weather events. Therefore, one of the purposes of this study was to examine how regional-scale evaluations are performed from the super-high-resolution GCM outputs. After verifying the usefulness of the GCM present-climate outputs with observations and operational mesoscale analyses, we examined, as another purpose of this study, the future changes in the environmental stability for convective rain. To diagnose the environmental conditions, some of the commonly used stability parameters and indices were examined. In the future climates, temperature lapse rate decreased in the lower troposphere, while water vapor mixing ratio increased throughout the deep troposphere. The changes in the temperature and moisture profiles resulted in the increase in both precipitable water vapor and convective available potential energy. These projected changes will be enhanced with the future period. Furthermore, the statistical analyses for the differences of the stability parameters between no-rain and rain days under the synoptically undisturbed condition in each simulated climate period indicated that the environmental conditions in terms of the stability parameters that distinguish no-rain and rain events are basically unchanged between the present and the future climates. This result suggests that the environmental characteristics favorable for afternoon rain events in the synoptically undisturbed environments will not change under global warming.

Reliability of regional climate simulations

NASA Astrophysics Data System (ADS)

Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.

2003-04-01

Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.

Seasonal variations of soil erosion in UK under climate change: simulations with the use of high-resolution regional climatic models

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Kendon, Elizabeth; Constantine, José Antonio; Schindewolf, Marcus; Hall, Ian

2017-04-01

Climate change is expected to have a significant impact on the hydrological cycle, twenty-first century climate change simulations for Great Britain forecast an increase of surface runoff and flooding frequency. Once quality and resolution of the simulated rainfall deeply influence the results, we adopted rainfall simulations issued of a high-resolution climate model recently carried out for extended periods (13 years for present-day and future periods 2100) at 1.5 km grid scale over the south of the United Kingdom (simulations, which for the future period use the Intergovernmental Panel on Climate Change RCP 8.5 scenario, Kendon et al., 2014). We simulated soil erosion with 3D soil erosion model Schmidt (1990) on two catchments of Great Britain: the Rother catchment (350 km2) in West Sussex, England, because it has reported some of the most erosive events observed during the last 50 years in the UK, and the Conwy catchment (628 Km2) in North Wales, which is extremely resilient to soil erosion because of the abundant natural vegetation. Estimation of changes in soil moisture, saturation deficit as well as vegetation cover at daily time step have been done with the Joint UK Land Environment Simulator (JULES) (Best et al, 2011). Our results confirm the Rother catchment is the most erosive, while the Conwy catchment is the more resilient to soil erosion. Sediment production is perceived increase in both cases for the end of the century (27% and 50%, respectively). Seasonal disaggregation of the results revels that, while the most part of soil erosion is produced in winter months (DJF), the higher soil erosion variability for future periods is observed in summer (JJA). This behaviour is supported by the rainfall simulation analyse which highlighted this dual behaviour in precipitations.

Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

PubMed

Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

2017-06-01

Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

Past and future changes in climate and hydrological indicators in the US Northeast

USGS Publications Warehouse

Hayhoe, K.; Wake, C.P.; Huntington, T.G.; Luo, L.; Schwartz, M.D.; Sheffield, J.; Wood, E.; Anderson, B.; Bradbury, J.; DeGaetano, A.; Troy, T.J.; Wolfe, D.

2007-01-01

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century. ?? Springer-Verlag 2006.

CERES-Maize model-based simulation of climate change impacts on maize yields and potential adaptive measures in Heilongjiang Province, China.

PubMed

Lin, Yumei; Wu, Wenxiang; Ge, Quansheng

2015-11-01

Climate change would cause negative impacts on future agricultural production and food security. Adaptive measures should be taken to mitigate the adverse effects. The objectives of this study were to simulate the potential effects of climate change on maize yields in Heilongjiang Province and to evaluate two selected typical household-level autonomous adaptive measures (cultivar changes and planting time adjustments) for mitigating the risks of climate change based on the CERES-Maize model. The results showed that flowering duration and maturity duration of maize would be shortened in the future climate and thus maize yield would reduce by 11-46% during 2011-2099 relative to 1981-2010. Increased CO2 concentration would not benefit maize production significantly. However, substituting local cultivars with later-maturing ones and delaying the planting date could increase yields as the climate changes. The results provide insight regarding the likely impacts of climate change on maize yields and the efficacy of selected adaptive measures by presenting evidence-based implications and mitigation strategies for the potential negative impacts of future climate change. © 2014 Society of Chemical Industry.

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

PubMed Central

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change. PMID:23593325

Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China.

PubMed

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems' response to global climate change. China's ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund-Potsdam-Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China's terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

NASA Astrophysics Data System (ADS)

Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

Using Paleo-climate Comparisons to Constrain Future Projections in CMIP5

NASA Technical Reports Server (NTRS)

Schmidt, G. A.; Annan, J D.; Bartlein, P. J.; Cook, B. I.; Guilyardi, E.; Hargreaves, J. C.; Harrison, S. P.; Kageyama, M.; LeGrande, A. N..; Konecky, B.;

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Projected Changes to Streamflow Characteristics in Quebec Basins as Simulated by the Canadian Regional Climate Model (CRCM4)

NASA Astrophysics Data System (ADS)

Huziy, O.; Sushama, L.; Khaliq, M.; Lehner, B.; Laprise, R.; Roy, R.

2011-12-01

According to the Intergovernmental Panel on Climate Change (IPCC, 2007), an intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high-latitudes, is expected in future climate. This will have an impact on mean and extreme flow characteristics, which need to be assessed for better development of adaptation strategies. Analysis of the mean and extreme streamflow characteristics for Quebec (North-eastern Canada) basins in current climate and their projected changes in future climate are assessed using a 10 member ensemble of current (1970 - 1999) and future (2041 - 2070) Canadian RCM (CRCM4) simulations. Validation of streamflow characteristics, performed by comparing modeled values with those observed, available from the Centre d'expertise hydrique du Quebec (CEHQ) shows that the model captures reasonably well the high flows. Results suggest increase in mean and 10 year return levels of 1 day high flows, which appear significant for most of the northern basins.

Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

2017-03-01

Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

Impact of Climate Change on Irrigation and Hydropower Potential: A Case of Upper Blue Nile Basin

NASA Astrophysics Data System (ADS)

Abdella, E. J.; Gosain, A. K.; Khosa, R.

2017-12-01

Due to the growing pressure in water resource and climate change there is great uncertainty in the availability of water for existing as well as proposed irrigation and hydropower projects in the Upper Blue Nile basin (longitude 34oE and 39oE and latitude 7oN and 12oN). This study quantitatively assessed the impact of climate change on the hydrological regime of the basin which intern affect water availability for different use including hydropower and irrigation. Ensemble of four bias corrected regional climate models (RCM) of CORDEX Africa domain and two scenarios (RCP 4.5 and RCP 8.5) were used to determine climate projections for future (2021-2050) period. The outputs from the climate models used to drive the calibrated Soil and Water Assessment Tool (SWAT) hydrologic model to simulate future runoff. The simulated discharge were used as input to a Water Evaluation and Planning (WEAP) water allocation model to determine the implication in hydropower and irrigation potential of the basin. The WEAP model was setup to simulate three scenarios which includes Current, Medium-term (by 2025) and Long-term (by 2050) Development scenario. The projected mean annual temperature of the basin are warmer than the baseline (1982 - 2005) average in the range of 1 to 1.4oC. Projected mean annual precipitation varies across the basin in the range of - 3% to 7%, much of the expected increase is in the highland region of the basin. The water use simulation indicate that the current annual average irrigation water demand in the basin is 1.29Bm3y-1 with 100% coverage. By 2025 and 2050, with the development of new schemes and changing climate, water demand for irrigation is estimated to increase by 2.5 Bm3y-1 and 3.4 Bm3y-1 with 99 % and 96% coverage respectively. Simulation for domestic water demand coverage for all scenarios shows that there will be 100% coverage for the two major cities in the basin. The hydropower generation simulation indicate that 98% of hydroelectricity potential could be produced if all planed dams are constructed. The results in this study demonstrate the general idea of future water availability for different purpose in the basin, but uncertainties still exist in the projected future climate and simulated runoff. Optimal operation of existing and proposed reservoirs is also crucial in the context of climate change.

Evaluation and projected changes of precipitation statistics in convection-permitting WRF climate simulations over Central Europe

NASA Astrophysics Data System (ADS)

Knist, Sebastian; Goergen, Klaus; Simmer, Clemens

2018-02-01

We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature-extreme precipitation scaling from the Clausius-Clapeyron (C-C) scaling rate of 7% K-1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature-extreme precipitation scaling curves in the future climate are projected to shift along the 7% K-1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C-C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.

Sorghum production under future climate in the Southwestern USA: model projections of yield, greenhouse gas emissions and soil C fluxes

NASA Astrophysics Data System (ADS)

Duval, B.; Ghimire, R.; Hartman, M. D.; Marsalis, M.

2016-12-01

Large tracts of semi-arid land in the Southwestern USA are relatively less important for food production than the US Corn Belt, and represent a promising area for expansion of biofuel/bioproduct crops. However, high temperatures, low available water and high solar radiation in the SW represent a challenge to suitable feedstock development, and future climate change scenarios predict that portions of the SW will experience increased temperature and temporal shifts in precipitation distribution. Sorghum (Sorghum bicolor) is a valuable forage crop with promise as a biofuel feedstock, given its high biomass under semi-arid conditions, relatively lower N fertilizer requirements compared to corn, and salinity tolerance. To evaluate the environmental impact of expanded sorghum cultivation under future climate in the SW USA, we used the DayCent model in concert with a suite of downscaled future weather projections to predict biogeochemical consequences (greenhouse gas flux and impacts on soil carbon) of sorghum cultivation in New Mexico. The model showed good correspondence with yield data from field trials including both dryland and irrigated sorghum (measured vs. modeled; r2 = 0.75). Simulation experiments tested the effect of dryland production versus irrigation, low N versus high N inputs and delayed fertilizer application. Nitrogen application timing and irrigation impacted yield and N2O emissions less than N rate and climate. Across N and irrigation treatments, future climate simulations resulted in 6% increased yield and 20% lower N2O emissions compared to current climate. Soil C pools declined under future climate. The greatest declines in soil C were from low N input sorghum simulations, regardless of irrigation (>20% declines in SOM in both cases), and requires further evaluation to determine if changing future climate is driving these declines, or if they are a function of prolonged sorghum-fallow rotations in the model. The relatively small gain in yield for irrigated sorghum, and strong control of N rate on N2O emissions suggests that a dryland sorghum bioproduct system could be environmentally sustainable in the Southwestern US with effective N management, and warrants further investigation in field trials.

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Ying; Winkler, Julie; Zhong, Shiyuan

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We also assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereasmore » current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. Furthemore, the choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.« less

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations

DOE PAGES

Tang, Ying; Winkler, Julie; Zhong, Shiyuan; ...

2017-07-10

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We also assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereasmore » current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. Furthemore, the choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.« less

Modelling recent and future climatic suitability for fasciolosis in Europe.

PubMed

Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana

2015-03-19

Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

PubMed Central

Guis, Helene; Caminade, Cyril; Calvete, Carlos; Morse, Andrew P.; Tran, Annelise; Baylis, Matthew

2012-01-01

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate's impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT's emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT's recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT's emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change's impact on the future of such diseases. PMID:21697167

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio-economic perspective). In our presentation we will show the cases of Peru and the Philippines, and discuss the implications for agriculture policies and risk management.

Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

NASA Astrophysics Data System (ADS)

Tsarouchi, Gina; Buytaert, Wouter

2018-02-01

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

Application of the coastal generalized ecosystem model (CGEM) to assess the impacts of a potential future climate scenario on northern Gulf of Mexico hypoxia

EPA Science Inventory

Mechanistic hypoxia models for the northern Gulf of Mexico are being used to guide policy goals for Mississippi River nutrient loading reductions. However, to date, these models have not examined the effects of both nutrient loads and future climate. Here, we simulate a future c...

Regional projections of North Indian climate for adaptation studies.

PubMed

Mathison, Camilla; Wiltshire, Andrew; Dimri, A P; Falloon, Pete; Jacob, Daniela; Kumar, Pankaj; Moors, Eddy; Ridley, Jeff; Siderius, Christian; Stoffel, Markus; Yasunari, T

2013-12-01

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes. Copyright © 2012 Elsevier B.V. All rights reserved.

The effect of measured and estimated soil hydraulic properties on simulated water regime in the analysis of grapevine adaptability to future climate

NASA Astrophysics Data System (ADS)

Bonfante, Antonello; Alfieri, Silvia Maria; Agrillo, Antonietta; Dragonetti, Giovanna; Mileti, Antonio; Monaco, Eugenia; De Lorenzi, Francesca

2013-04-01

In the last years many research works have been addressed to evaluate the impact of future climate on crop productivity and plant water use at different spatial scales (global, regional, field) by means of simulation models of agricultural crop systems. Most of these approaches use estimated soil hydraulic properties, through pedotransfer functions (PTF). This choice is related to soil data availability: soil data bases lack measured soil hydraulic properties, but generally they contain information that allow the application of PTF . Although the reliability of the predicted future climate scenarios cannot be immediately validated, we address to evaluate the effects of a simplification of the soil system by using PTF. Thus we compare simulations performed with measured soil hydraulic properties versus simulations carried out with estimated properties. The water regimes resulting from the two procedures are evaluated with respect to crop adaptability to future climate. In particular we will examine if the two procedures bring about different seasonal and spatial variations in the soil water regime patterns, and if these patterns influence adaptation options. The present case study uses the agro-hydrological model SWAP (soil-water-atmosphere and plant) and studies future adaptability of grapevine. The study area is a viticultural area of Southern Italy (Valle Telesina, BN) devoted to the production of high quality wines (DOC and DOCG), and characterized by a complex geomorphology and pedology. The future climate scenario (2021-2050) was constructed applying statistical downscaling techniques to GCMs scenarios. The moisture regime for 25 soils of the selected study area was calculated by means of SWAP model, using both measured and estimated soil hydraulic properties. In the simulation, the upper boundary conditions were derived from the regional climate scenarios. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were estimated on the basis of scientific literature and assumed to be generically representative of the species. From the output of the simulation runs, the relative evapotranspiration deficit (or Crop Water Stress Index - CWSI) of the soil units was calculated. Since CWSI is considered an important indicator of the qualitative grapevine responses, its pattern in both simulation procedures has been evaluated. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios.

PubMed

Ge, Xuezhen; He, Shanyong; Wang, Tao; Yan, Wei; Zong, Shixiang

2015-01-01

As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010) and future climate warming estimates based on simulated climate data for the 2020s (2011-2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.

Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios

PubMed Central

Ge, Xuezhen; He, Shanyong; Wang, Tao; Yan, Wei; Zong, Shixiang

2015-01-01

As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981–2010) and future climate warming estimates based on simulated climate data for the 2020s (2011–2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas. PMID:26496438

Impact of large-scale circulation changes in the North Atlantic sector on the current and future Mediterranean winter hydroclimate

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Kapnick, Sarah B.; Feser, Frauke

2018-03-01

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.

Future Change of Snow Water Equivalent over Japan

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Kimura, F.; Fujita, M.; Ma, X.

2012-12-01

Western side of Honshu Island and Hokkaido Island in Japan are ones of the heaviest snowfall areas in the world. Although a heavy snowfall often brings disaster, snow is one of the major sources for agriculture, industrial, and house-use in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 C in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of the global warming, which is caused by an increase in greenhouse gases. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities. We performed a series of numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. The precipitation, snow depth, and surface air temperature of the hindcast simulations show good agreement with the AMeDAS station data. In much-snow cases, The decreasing rate of maximum total snow water equivalent over Japan due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is the air temperature rise due to global climate change. The difference in the precipitation amount between the present and the future simulations is small.

Assessment of the Impact of Climate Change on the Water Balances and Flooding Conditions of Peninsular Malaysia watersheds by a Coupled Numerical Climate Model - Watershed Hydrology Model

NASA Astrophysics Data System (ADS)

Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.

2017-12-01

Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Biomes computed from simulated climatologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Claussen, M.; Esch, M.

1994-01-01

The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a differencemore » in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.« less

Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

2012-12-01

We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. Our study, the first application of a coupled Earth system model at regional scale and resolution over Africa, reveals that vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa.

Impacts of Future Climate and Emission Changes on U.S. Air Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Penrod, Ashley; Zhang, Yang; Wang, K.

2014-06-01

Changes in climate and emissions will affect future air quality. In this work, simulations of present (2001-2005) and future (2026-2030) regional air quality are conducted with the newly released CMAQ version 5.0 to examine the individual and combined impacts of simulated future climate and anthropogenic emission projections on air quality over the U.S. Current (2001-2005) meteorological and chemical predictions are evaluated against observational data to assess the model’s capability in reproducing the seasonal differences. Overall, WRF and CMAQ perform reasonably well. Increased temperatures (up to 3.18 °C) and decreased ventilation (up to 157 m in planetary boundary layer height) aremore » found in both future winter and summer, with more prominent changes in winter. Increases in future temperatures result in increased isoprene and terpene emissions in winter and summer, driving the increase in maximum 8-h average O3 (up to 5.0 ppb) over the eastern U.S. in winter while decreases in NOx emissions drive the decrease in O3 over most of the U.S. in summer. Future concentrations of PM2.5 in winter and summer and many of its components including organic matter in winter, ammonium and nitrate in summer, and sulfate in winter and summer, decrease due to decreases in primary anthropogenic emissions and the concentrations of secondary anthropogenic pollutants and increased precipitation in winter. Future winter and summer dry and wet deposition fluxes are spatially variable and increase with increasing surface resistance and precipitation (e.g., NH4+ and NO3- dry and wet deposition fluxes increase in winter over much of the U.S.), respectively, and decrease with a decrease in ambient particulate concentrations (e.g., SO42- dry and wet deposition fluxes decrease over the eastern U.S. in summer and winter). Sensitivity simulations show that anthropogenic emission projections dominate over changes in climate in their impacts on the U.S. air quality in the near future. Changes in some regions/species, however, are dominated by climate and/or both climate and anthropogenic emissions, especially in future years that are marked by meteorological conditions conducive to poor air quality.« less

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less

Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin

USGS Publications Warehouse

Hunt, Randall J.; Westenbroek, Stephen M.; Walker, John F.; Selbig, William R.; Regan, R. Steven; Leaf, Andrew T.; Saad, David A.

2016-08-23

Potential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

USGS Publications Warehouse

Bock, Andy

2017-03-16

Simulations of future climate suggest profiles of temperature and precipitation may differ significantly from those in the past. These changes in climate will likely lead to changes in the hydrologic cycle. As such, natural resource managers are in need of tools that can provide estimates of key components of the hydrologic cycle, uncertainty associated with the estimates, and limitations associated with the climate forcing data used to estimate these components. To help address this need, the U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) provides a user friendly interface to deliver hydrologic and meteorological variables for monthly historic and potential future climatic conditions across the continental United States.

Assessment of future impacts of potential climate change scenarios on aquifer recharge in continental Spain

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Collados-Lara, Antonio-Juan; Alcalá, Francisco J.

2017-04-01

This research proposes and applies a method to assess potential impacts of future climatic scenarios on aquifer rainfall recharge in wide and varied regions. The continental Spain territory was selected to show the application. The method requires to generate future series of climatic variables (precipitation, temperature) in the system to simulate them within a previously calibrated hydrological model for the historical data. In a previous work, Alcalá and Custodio (2014) used the atmospheric chloride mass balance (CMB) method for the spatial evaluation of average aquifer recharge by rainfall over the whole of continental Spain, by assuming long-term steady conditions of the balance variables. The distributed average CMB variables necessary to calculate recharge were estimated from available variable-length data series of variable quality and spatial coverage. The CMB variables were regionalized by ordinary kriging at the same 4976 nodes of a 10 km x 10 km grid. Two main sources of uncertainty affecting recharge estimates (given by the coefficient of variation, CV), induced by the inherent natural variability of the variables and from mapping were segregated. Based on these stationary results we define a simple empirical rainfall-recharge model. We consider that spatiotemporal variability of rainfall and temperature are the most important climatic feature and variables influencing potential aquifer recharge in natural regime. Changes in these variables can be important in the assessment of future potential impacts of climatic scenarios over spatiotemporal renewable groundwater resource. For instance, if temperature increases, actual evapotranspitration (EA) will increases reducing the available water for others groundwater balance components, including the recharge. For this reason, instead of defining an infiltration rate coefficient that relates precipitation (P) and recharge we propose to define a transformation function that allows estimating the spatial distribution of recharge (both average value and its uncertainty) from the difference in P and EA in each area. A complete analysis of potential short-term (2016-2045) future climate scenarios in continental Spain has been performed by considering different sources of uncertainty. It is based on the historical climatic data for the period 1976-2005 and the climatic models simulations (for the control [1976-2005] and future scenarios [2016-2045]) performed in the frame of the CORDEX EU project. The most pessimistic emission scenario (RCP8.5) has been considered. For the RCP8.5 scenario we have analyzed the time series generated by simulating with 5 Regional Climatic models (CCLM4-8-17, RCA4, HIRHAM5, RACMO22E, and WRF331F) nested to 4 different General Circulation Models (GCMs). Two different conceptual approaches (bias correction and delta change techniques) have been applied to generate potential future climate scenarios from these data. Different ensembles of obtained time series have been proposed to obtain more representative scenarios by considering all the simulations or only those providing better approximations to the historical statistics based on a multicriteria analysis. This was a step to analyze future potential impacts on the aquifer recharge by simulating them within a rainfall-recharge model. This research has been supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.

Direct and indirect effects of climate change on herbicide leaching--a regional scale assessment in Sweden.

PubMed

Steffens, Karin; Jarvis, Nicholas; Lewan, Elisabet; Lindström, Bodil; Kreuger, Jenny; Kjellström, Erik; Moeys, Julien

2015-05-01

Climate change is not only likely to improve conditions for crop production in Sweden, but also to increase weed pressure and the need for herbicides. This study aimed at assessing and contrasting the direct and indirect effects of climate change on herbicide leaching to groundwater in a major crop production region in south-west Sweden with the help of the regional pesticide fate and transport model MACRO-SE. We simulated 37 out of the 41 herbicides that are currently approved for use in Sweden on eight major crop types for the 24 most common soil types in the region. The results were aggregated accounting for the fractional coverage of the crop and the area sprayed with a particular herbicide. For simulations of the future, we used projections of five different climate models as model driving data and assessed three different future scenarios: (A) only changes in climate, (B) changes in climate and land-use (altered crop distribution), and (C) changes in climate, land-use, and an increase in herbicide use. The model successfully distinguished between leachable and non-leachable compounds (88% correctly classified) in a qualitative comparison against regional-scale monitoring data. Leaching was dominated by only a few herbicides and crops under current climate and agronomic conditions. The model simulations suggest that the direct effects of an increase in temperature, which enhances degradation, and precipitation which promotes leaching, cancel each other at a regional scale, resulting in a slight decrease in leachate concentrations in a future climate. However, the area at risk of groundwater contamination doubled when indirect effects of changes in land-use and herbicide use, were considered. We therefore concluded that it is important to consider the indirect effects of climate change alongside the direct effects and that effective mitigation strategies and strict regulation are required to secure future (drinking) water resources. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US.

PubMed

Hurteau, Matthew D

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010-2019), mid (2050-2059), and late (2090-2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8-48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US

PubMed Central

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010–2019), mid (2050–2059), and late (2090–2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8–48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink. PMID:28046079

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

A Review on Regional Convection-Permitting Climate Modeling: Demonstrations, Prospects, and Challenges

NASA Astrophysics Data System (ADS)

Prein, A. F.; Langhans, W.; Fosser, G.; Ferrone, A.; Ban, N.; Goergen, K.; Keller, M.; Tölle, M.; Gutjahr, O.; Feser, F.; Brisson, E.; Kollet, S. J.; Schmidli, J.; Van Lipzig, N. P. M.; Leung, L. R.

2015-12-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. We aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

PubMed

Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P. M.; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

River flood risk in Jakarta under scenarios of future change

NASA Astrophysics Data System (ADS)

Budiyono, Yus; Aerts, Jeroen C. J. H.; Tollenaar, Daniel; Ward, Philip J.

2016-03-01

Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the Damagescanner-Jakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability. We estimate baseline flood risk at USD 186 million p.a. Combining all future scenarios, we simulate a median increase in risk of +180 % by 2030. The single driver with the largest contribution to that increase is land subsidence (+126 %). We simulated the impacts of climate change by combining two scenarios of sea level rise with simulations of changes in 1-day extreme precipitation totals from five global climate models (GCMs) forced by the four Representative Concentration Pathways (RCPs). The results are highly uncertain; the median change in risk due to climate change alone by 2030 is a decrease by -46 %, but we simulate an increase in risk under 12 of the 40 GCM-RCP-sea level rise combinations. Hence, we developed probabilistic risk scenarios to account for this uncertainty. If land use change by 2030 takes places according to the official Jakarta Spatial Plan 2030, risk could be reduced by 12 %. However, if land use change in the future continues at the same rate as the last 30 years, large increases in flood risk will take place. Finally, we discuss the relevance of the results for flood risk management in Jakarta.

Modeling the effects of land use and climate change on riverine smallmouth bass

USGS Publications Warehouse

Peterson, J.T.; Kwak, T.J.

1999-01-01

Anthropogenic changes in temperature and stream flow, associated with watershed land use and climate change, are critical influences on the distribution and abundance of riverine fishes. To project the effects of changing land use and climate, we modeled a smallmouth bass (Micropterus dolomieu) population in a midwestern USA, large river- floodplain ecosystem under historical (1915-1925), present (1977-1990), and future (2060, influenced by climate change) temperature and flow regimes. The age-structured model included parameters for temperature and river discharge during critical seasonal periods, fish population dynamics, and fishing harvest. Model relationships were developed from empirical field data collected over a 13-yr period. Sensitivity analyses indicated that discharge during the spawning/rearing period had a greater effect on adult density and fishing yield than did spawning/rearing temperature or winter discharge. Simulations for 100 years projected a 139% greater mean fish density under a historical flow regime (64.9 fish/ha) than that estimated for the present (27.1 fish/ha) with a sustainable fishing harvest under both flow regimes. Simulations under future climate-change-induced temperature and flow regimes with present land use projected a 69% decrease in mean fish density (8.5 fish/ha) from present and an unstable population that went extinct during 56% of the simulations. However, when simulated under a future climate-altered temperature and flow regime with historical land use, the population increased by 66% (45.0 fish/ha) from present and sustained a harvest. Our findings suggest that land-use changes may be a greater detriment to riverine fishes than projected climate change and that the combined effects of both factors may lead to local species extinction. However, the negative effects of increased temperature and precipitation associated with future global warming could be mitigated by river channel, floodplain, and watershed restoration.

Historical and Future Black Carbon Deposition on the Three Ice Caps: Ice Core Measurements and Model Simulations from 1850 to 2100

NASA Technical Reports Server (NTRS)

Bauer, Susanne E.; Bausch, Alexandra; Nazarenko, Larissa; Tsigaridis, Kostas; Xu, Baiqing; Edwards. Ross; Bisiaux, Marion; McConnell, Joe

2013-01-01

Ice core measurements in conjunction with climate model simulations are of tremendous value when examining anthropogenic and natural aerosol loads and their role in past and future climates. Refractory black carbon (BC) records from the Arctic, the Antarctic, and the Himalayas are analyzed using three transient climate simulations performed with the Goddard Institute for Space Studies ModelE. Simulations differ in aerosol schemes (bulk aerosols vs. aerosol microphysics) and ocean couplings (fully coupled vs. prescribed ocean). Regional analyses for past (1850-2005) and future (2005-2100) carbonaceous aerosol simulations focus on the Antarctic, Greenland, and the Himalayas. Measurements from locations in the Antarctic show clean conditions with no detectable trend over the past 150 years. Historical atmospheric deposition of BC and sulfur in Greenland shows strong trends and is primarily influenced by emissions from early twentieth century agricultural and domestic practices. Models fail to reproduce observations of a sharp eightfold BC increase in Greenland at the beginning of the twentieth century that could be due to the only threefold increase in the North American emission inventory. BC deposition in Greenland is about 10 times greater than in Antarctica and 10 times less than in Tibet. The Himalayas show the most complicated transport patterns, due to the complex terrain and dynamical regimes of this region. Projections of future climate based on the four CMIP5 Representative Concentration Pathways indicate further dramatic advances of pollution to the Tibetan Plateau along with decreasing BC deposition fluxes in Greenland and the Antarctic.

High resolution global climate modelling; the UPSCALE project, a large simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

2014-01-01

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

2014-08-01

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

Future climate data from RCP 4.5 and occurrence of malaria in Korea.

PubMed

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-10-15

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001-2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

PubMed Central

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P.; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-01-01

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future. PMID:25321875

Forecasting European cold waves based on subsampling strategies of CMIP5 and Euro-CORDEX ensembles

NASA Astrophysics Data System (ADS)

Cordero-Llana, Laura; Braconnot, Pascale; Vautard, Robert; Vrac, Mathieu; Jezequel, Aglae

2016-04-01

Forecasting future extreme events under the present changing climate represents a difficult task. Currently there are a large number of ensembles of simulations for climate projections that take in account different models and scenarios. However, there is a need for reducing the size of the ensemble to make the interpretation of these simulations more manageable for impact studies or climate risk assessment. This can be achieved by developing subsampling strategies to identify a limited number of simulations that best represent the ensemble. In this study, cold waves are chosen to test different approaches for subsampling available simulations. The definition of cold waves depends on the criteria used, but they are generally defined using a minimum temperature threshold, the duration of the cold spell as well as their geographical extend. These climate indicators are not universal, highlighting the difficulty of directly comparing different studies. As part of the of the CLIPC European project, we use daily surface temperature data obtained from CMIP5 outputs as well as Euro-CORDEX simulations to predict future cold waves events in Europe. From these simulations a clustering method is applied to minimise the number of ensembles required. Furthermore, we analyse the different uncertainties that arise from the different model characteristics and definitions of climate indicators. Finally, we will test if the same subsampling strategy can be used for different climate indicators. This will facilitate the use of the subsampling results for a wide number of impact assessment studies.

Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century

NASA Astrophysics Data System (ADS)

Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

2016-12-01

Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.

Change of ocean circulation in the East Asian Marginal Seas under different climate conditions

NASA Astrophysics Data System (ADS)

Min, Hong Sik; Kim, Cheol-Ho; Kim, Young Ho

2010-05-01

Global climate models do not properly resolve an ocean environment in the East Asian Marginal Seas (EAMS), which is mainly due to a poor representation of the topography in continental shelf region and a coarse spatial resolution. To examine a possible change of ocean environment under global warming in the EAMS, therefore we used North Pacific Regional Ocean Model. The regional model was forced by atmospheric conditions extracted from the simulation results of the global climate models for the 21st century projected by the IPCC SRES A1B scenario as well as the 20th century. The North Pacific Regional Ocean model simulated a detailed pattern of temperature change in the EAMS showing locally different rising or falling trend under the future climate condition, while the global climate models simulated a simple pattern like an overall increase. Changes of circulation pattern in the EAMS such as an intrusion of warm water into the Yellow Sea as well as the Kuroshio were also well resolved. Annual variations in volume transports through the Taiwan Strait and the Korea Strait under the future condition were simulated to be different from those under present condition. Relative ratio of volume transport through the Soya Strait to the Tsugaru Strait also responded to the climate condition.

Future climate change impact assessment of watershed scale hydrologic processes in Peninsular Malaysia by a regional climate model coupled with a physically-based hydrology modelo.

PubMed

Amin, M Z M; Shaaban, A J; Ercan, A; Ishida, K; Kavvas, M L; Chen, Z Q; Jang, S

2017-01-01

Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model utilizing an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century was dynamically downscaled to 6km resolution over Peninsular Malaysia by a regional climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over Muda and Dungun watersheds. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions in the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant from April to May and from July to October at Muda watershed. Also, the increase in mean monthly flows is shown to be significant in November during 2030-2070 and from November to December during 2070-2100 at Dungun watershed. In other words, the impact of the expected climate change will be significant during the northeast and southwest monsoon seasons at Muda watershed and during the northeast monsoon season at Dungun watershed. Furthermore, the flood frequency analyses for both watersheds indicated an overall increasing trend in the second half of the 21st century. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)

NASA Astrophysics Data System (ADS)

Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.

2013-12-01

We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.

Downscaling Future Climate Change Projections for Water Resource Applications: A Case Study for Mesoamerica (Invited)

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Rowe, C. M.; Munoz-Arriola, F.

2013-12-01

Mesoamerica is a region that is potentially at severe risk due to future climate change. This is especially true for the water resources required for agriculture, human consumption, and hydroelectric power generation. Yet global climate models cannot properly resolve surface climate in the region, due to it's complex topography and nearness to oceans. Precipitation in particular is poorly handled. Further, Mesoamerica is hardly the only region worldwide for which these issues exist. To address this deficiency, a series of high-resolution (4-12 km) dynamical downscaling simulations of future climate change between now and 2060 have been made for Mesoamerica and the Caribbean. We used the Weather Research and Forecasting (WRF) regional climate model to downscale results from the NCAR CCSM4 CMIP5 RCP8.5 global simulation. The entire region is covered at 12 km horizontal spatial resolution, with as much as possible (especially in mountainous regions) at 4 km. We compare a control period (2006-2010) with 50 years into the future (2056-2060). Basic results for surface climate will be presented, as well as a developing strategy for explicitly employing these results in projecting the implications for water resources in the region. Connections will also be made to other regions around the globe that could benefit from this type of integrated modeling and analysis.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections.

PubMed

Caballero, Rodrigo; Huber, Matthew

2013-08-27

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow "Earth system" feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or "Charney" climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature.

Improving sea level simulation in Mediterranean regional climate models

NASA Astrophysics Data System (ADS)

Adloff, Fanny; Jordà, Gabriel; Somot, Samuel; Sevault, Florence; Arsouze, Thomas; Meyssignac, Benoit; Li, Laurent; Planton, Serge

2017-08-01

For now, the question about future sea level change in the Mediterranean remains a challenge. Previous climate modelling attempts to estimate future sea level change in the Mediterranean did not meet a consensus. The low resolution of CMIP-type models prevents an accurate representation of important small scales processes acting over the Mediterranean region. For this reason among others, the use of high resolution regional ocean modelling has been recommended in literature to address the question of ongoing and future Mediterranean sea level change in response to climate change or greenhouse gases emissions. Also, it has been shown that east Atlantic sea level variability is the dominant driver of the Mediterranean variability at interannual and interdecadal scales. However, up to now, long-term regional simulations of the Mediterranean Sea do not integrate the full sea level information from the Atlantic, which is a substantial shortcoming when analysing Mediterranean sea level response. In the present study we analyse different approaches followed by state-of-the-art regional climate models to simulate Mediterranean sea level variability. Additionally we present a new simulation which incorporates improved information of Atlantic sea level forcing at the lateral boundary. We evaluate the skills of the different simulations in the frame of long-term hindcast simulations spanning from 1980 to 2012 analysing sea level variability from seasonal to multidecadal scales. Results from the new simulation show a substantial improvement in the modelled Mediterranean sea level signal. This confirms that Mediterranean mean sea level is strongly influenced by the Atlantic conditions, and thus suggests that the quality of the information in the lateral boundary conditions (LBCs) is crucial for the good modelling of Mediterranean sea level. We also found that the regional differences inside the basin, that are induced by circulation changes, are model-dependent and thus not affected by the LBCs. Finally, we argue that a correct configuration of LBCs in the Atlantic should be used for future Mediterranean simulations, which cover hindcast period, but also for scenarios.

Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts ...

Simulating future climate change impacts on seed cotton yield in the Texas high plains using the CSM-CROPGRO cotton model

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts ...

Comparison of Global Cloud Fraction and TOA Radiation Budgets between the NASA GISS AR5 GCM Simulations and CERES-MODIS Observations

NASA Astrophysics Data System (ADS)

Stanfield, R. E.; Dong, X.; Xi, B.; Del Genio, A. D.; Minnis, P.; Doelling, D.; Loeb, N. G.

2011-12-01

To better advise policymakers, it is necessary for climate models to provide credible predictions of future climates. Meeting this goal requires climate models to successfully simulate the present and past climates. The past, current and future Earth climate has been simulated by the NASA GISS ModelE climate model and has been summarized by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, AR4, 2007). New simulations from the updated AR5 version of the NASA GISS ModelE GCM have been released to the public community and will be included in the IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, however, they have yet to be extensively validated against observations. To evaluate the GISS AR5 simulated global clouds and TOA radiation budgets, we have collected and processed the NASA CERES and MODIS observations during the period 2000-2005. In detail, the 1ox1o resolution monthly averaged SYN1 product has been used with combined observations from both Terra and Aqua satellites, and degraded to a 2ox2.5o grid box to match the GCM spatial resolution. These observations are temporally interpolated and fit to data from geostationary satellites to provide time continuity. The GISS AR5 products were downloaded from the CMIP5 (Coupled Model Intercomparison Project Phase 5) for the IPCC-AR5. Preliminary comparisons between GISS AR5 simulations and CERES-MODIS observations have shown that although their annual and seasonal mean CFs agree within a few percent, there are significant differences in several climatic regions. For example, the modeled CFs have positive biases in the Arctic, Antarctic, Tropics, and Sahara Desert, but negative biases over the southern middle latitudes (30-65 oS). The OLR, albedo and NET radiation comparisons are similar to the CF comparison.

Modeling climate change impacts on water trading.

PubMed

Luo, Bin; Maqsood, Imran; Gong, Yazhen

2010-04-01

This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

The uncertainty cascade in flood risk assessment under changing climatic conditions - the Biala Tarnowska case study

NASA Astrophysics Data System (ADS)

Doroszkiewicz, Joanna; Romanowicz, Renata

2016-04-01

Uncertainty in the results of the hydraulic model is not only associated with the limitations of that model and the shortcomings of data. An important factor that has a major impact on the uncertainty of the flood risk assessment in a changing climate conditions is associated with the uncertainty of future climate scenarios (IPCC WG I, 2013). Future climate projections provided by global climate models are used to generate future runoff required as an input to hydraulic models applied in the derivation of flood risk maps. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps. One of the aims of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the process, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-section. The study shows that the application of the simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Acknowledgements: This work was supported by the project CHIHE (Climate Change Impact on Hydrological Extremes), carried out in the Institute of Geophysics Polish Academy of Sciences, funded by Norway Grants (contract No. Pol-Nor/196243/80/2013). The hydro-meteorological observations were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

A Statistical Modeling Framework for Projecting Future Ambient Ozone and its Health Impact due to Climate Change

PubMed Central

Chang, Howard H.; Hao, Hua; Sarnat, Stefanie Ebelt

2014-01-01

The adverse health effects of ambient ozone are well established. Given the high sensitivity of ambient ozone concentrations to meteorological conditions, the impacts of future climate change on ozone concentrations and its associated health effects are of concern. We describe a statistical modeling framework for projecting future ozone levels and its health impacts under a changing climate. This is motivated by the continual effort to evaluate projection uncertainties to inform public health risk assessment. The proposed approach was applied to the 20-county Atlanta metropolitan area using regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program. Future ozone levels and ozone-related excesses in asthma emergency department (ED) visits were examined for the period 2041–2070. The computationally efficient approach allowed us to consider 8 sets of climate model outputs based on different combinations of 4 RCMs and 4 general circulation models. Compared to the historical period of 1999–2004, we found consistent projections across climate models of an average 11.5% higher ozone levels (range: 4.8%, 16.2%), and an average 8.3% (range: −7% to 24%) higher number of ozone exceedance days. Assuming no change in the at-risk population, this corresponds to excess ozone-related ED visits ranging from 267 to 466 visits per year. Health impact projection uncertainty was driven predominantly by uncertainty in the health effect association and climate model variability. Calibrating climate simulations with historical observations reduced differences in projections across climate models. PMID:24764746

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Vulnerability of northern prairie wetlands to climate change

USGS Publications Warehouse

Johnson, W.C.; Millett, B.V.; Gilmanov, T.; Voldseth, R.A.; Guntenspergen, G.R.; Naugle, D.E.

2005-01-01

The prairie pothole region (PPR) lies in the heart of North America and contains millions of glacially formed, depressional wetlands embedded in a landscape matrix of natural grassland and agriculture. These wetlands provide valuable ecosystem services and produce 50% to 80% of the continent's ducks. We explored the broad spatial and temporal patterns across the PPR between climate and wetland water levels and vegetation by applying a wetland simulation model (WETSIM) to 18 stations with 95-year weather records. Simulations suggest that the most productive habitat for breeding waterfowl would shift under a drier climate from the center of the PPR (the Dakotas and southeastern Saskatchewan) to the wetter eastern and northern fringes, areas currently less productive or where most wetlands have been drained. Unless these wetlands are protected and restored, there is little insurance for waterfowl against future climate warming. WETSIM can assist wetland managers in allocating restoration dollars in an uncertain climate future.

The response of land-falling tropical cyclone characteristics to projected climate change in northeast Australia

NASA Astrophysics Data System (ADS)

Parker, Chelsea L.; Bruyère, Cindy L.; Mooney, Priscilla A.; Lynch, Amanda H.

2018-01-01

Land-falling tropical cyclones along the Queensland coastline can result in serious and widespread damage. However, the effects of climate change on cyclone characteristics such as intensity, trajectory, rainfall, and especially translation speed and size are not well-understood. This study explores the relative change in the characteristics of three case studies by comparing the simulated tropical cyclones under current climate conditions with simulations of the same systems under future climate conditions. Simulations are performed with the Weather Research and Forecasting Model and environmental conditions for the future climate are obtained from the Community Earth System Model using a pseudo global warming technique. Results demonstrate a consistent response of increasing intensity through reduced central pressure (by up to 11 hPa), increased wind speeds (by 5-10% on average), and increased rainfall (by up to 27% for average hourly rainfall rates). The responses of other characteristics were variable and governed by either the location and trajectory of the current climate cyclone or the change in the steering flow. The cyclone that traveled furthest poleward encountered a larger climate perturbation, resulting in a larger proportional increase in size, rainfall rate, and wind speeds. The projected monthly average change in the 500 mb winds with climate change governed the alteration in the both the trajectory and translation speed for each case. The simulated changes have serious implications for damage to coastal settlements, infrastructure, and ecosystems through increased wind speeds, storm surge, rainfall, and potentially increased size of some systems.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

DOE PAGES

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia; ...

2015-05-27

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less

Water and nitrogen management effects on semiarid sorghum production and soil trace gas flux under future climate.

PubMed

Duval, Benjamin D; Ghimire, Rajan; Hartman, Melannie D; Marsalis, Mark A

2018-01-01

External inputs to agricultural systems can overcome latent soil and climate constraints on production, while contributing to greenhouse gas emissions from fertilizer and water management inefficiencies. Proper crop selection for a given region can lessen the need for irrigation and timing of N fertilizer application with crop N demand can potentially reduce N2O emissions and increase N use efficiency while reducing residual soil N and N leaching. However, increased variability in precipitation is an expectation of climate change and makes predicting biomass and gas flux responses to management more challenging. We used the DayCent model to test hypotheses about input intensity controls on sorghum (Sorghum bicolor (L.) Moench) productivity and greenhouse gas emissions in the southwestern United States under future climate. Sorghum had been previously parameterized for DayCent, but an inverse-modeling via parameter estimation method significantly improved model validation to field data. Aboveground production and N2O flux were more responsive to N additions than irrigation, but simulations with future climate produced lower values for sorghum than current climate. We found positive interactions between irrigation at increased N application for N2O and CO2 fluxes. Extremes in sorghum production under future climate were a function of biomass accumulation trajectories related to daily soil water and mineral N. Root C inputs correlated with soil organic C pools, but overall soil C declined at the decadal scale under current weather while modest gains were simulated under future weather. Scaling biomass and N2O fluxes by unit N and water input revealed that sorghum can be productive without irrigation, and the effect of irrigating crops is difficult to forecast when precipitation is variable within the growing season. These simulation results demonstrate the importance of understanding sorghum production and greenhouse gas emissions at daily scales when assessing annual and decadal-scale management decisions' effects on aspects of arid and semiarid agroecosystem biogeochemistry.

Chemistry-Climate Model Simulations of Twenty-First Century Stratospheric Climate and Circulation Changes

DTIC Science & Technology

2010-10-15

cycle under volcanically clean aerosol conditions. Those models that do not reproduce a quasi- biennial oscillation ( QBO ) also include a relaxation...forc- ing toward the observed QBO (Giorgetta and Bengtsson 1999) for the SCN2 simulations. Table 2 summarizes the simulations used in this study and any...However simulations from three of the models included a future solar forcing and two models included an artificial QBO forcing in the tropics (see

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

A linear regression model for predicting PNW estuarine temperatures in a changing climate

EPA Science Inventory

Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

Hydrologic resilience and Amazon productivity.

PubMed

Ahlström, Anders; Canadell, Josep G; Schurgers, Guy; Wu, Minchao; Berry, Joseph A; Guan, Kaiyu; Jackson, Robert B

2017-08-30

The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the system transitions between water and radiation limitation of evapotranspiration. The breakpoint appears to be fairly stable in the future, suggesting resilience of the Amazon to climate change. Changes in precipitation and land use are therefore more likely to govern biomass and vegetation structure in Amazonia.Earth system model simulations of future climate in the Amazon show little agreement. Here, the authors show that biases in internally generated climate explain most of this uncertainty and that the balance between water-saturated and water-limited evapotranspiration controls the Amazon resilience to climate change.

The Community Climate System Model.

NASA Astrophysics Data System (ADS)

Blackmon, Maurice; Boville, Byron; Bryan, Frank; Dickinson, Robert; Gent, Peter; Kiehl, Jeffrey; Moritz, Richard; Randall, David; Shukla, Jagadish; Solomon, Susan; Bonan, Gordon; Doney, Scott; Fung, Inez; Hack, James; Hunke, Elizabeth; Hurrell, James; Kutzbach, John; Meehl, Jerry; Otto-Bliesner, Bette; Saravanan, R.; Schneider, Edwin K.; Sloan, Lisa; Spall, Michael; Taylor, Karl; Tribbia, Joseph; Washington, Warren

2001-11-01

The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users. The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a flux coupler that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1% per year. In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several pro-jections of the climate of the twenty-first century. The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model. Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.

Projected changes in climate extremes over Qatar and the Arabian Gulf region

NASA Astrophysics Data System (ADS)

Kundeti, K.; Kanikicharla, K. K.; Al sulaiti, M.; Khulaifi, M.; Alboinin, N.; Kito, A.

2015-12-01

The climate of the State of Qatar and the adjacent region is dominated by subtropical dry, hot desert climate with low annual rainfall, very high temperatures in summer and a big difference between maximum and minimum temperatures, especially in the inland areas. The coastal areas are influenced by the Arabian Gulf, and have lower maximum, but higher minimum temperatures and a higher moisture percentage in the air. The global warming can have profound impact on the mean climate as well as extreme weather events over the Arabian Peninsula that may affect both natural and human systems significantly. Therefore, it is important to assess the future changes in the seasonal/annual mean of temperature and precipitation and also the extremes in temperature and wind events for a country like Qatar. This study assesses the performance of the Coupled Model Inter comparison Project Phase 5 (CMIP5) simulations in present and develops future climate scenarios. The changes in climate extremes are assessed for three future periods 2016-2035, 2046-2065 and 2080-2099 with respect to 1986-2005 (base line) under two RCPs (Representative Concentrate Pathways) - RCP4.5 and RCP8.5. We analyzed the projected changes in temperature and precipitation extremes using several indices including those that capture heat stress. The observations show an increase in warm extremes over many parts in this region that are generally well captured by the models. The results indicate a significant change in frequency and intensity of both temperature and precipitation extremes over many parts of this region which may have serious implications on human health, water resources and the onshore/offshore infrastructure in this region. Data from a high-resolution (20km) AGCM simulation from Meteorological Research Institute of Japan Meteorological Agency for the present (1979-2003) and a future time slice (2075-2099) corresponding to RCP8.5 have also been utilized to assess the impact of climate change on regional climate extremes as well. The scenarios generated with the high-resolution model simulation were compared with the coarse resolution CMIP5 model scenarios to identify region specific features that might be better resolved in the former simulation.

Introducing the Met Office 2.2-km Europe-wide convection-permitting regional climate simulations

NASA Astrophysics Data System (ADS)

Kendon, Elizabeth J.; Chan, Steven C.; Berthou, Segolene; Fosser, Giorgia; Roberts, Malcolm J.; Fowler, Hayley J.

2017-04-01

The Met Office is currently conducting Europe-wide 2.2-km convection-permitting model (CPM) simulations driven by ERA-Interim reanalysis and present/future-climate GCM simulations. Here, we present the preliminary results of these new European simulations examining daily and sub-daily precipitation outputs in comparison with observations across Europe, 12-km European and 1.5-km UK climate model simulations. As the simulations are not yet complete, we focus on diagnostics that are relatively robust with a limited amount of data; for instance, the diurnal cycle and the probability distribution of daily and sub-daily precipitation intensities. We will also present specific case studies that showcase the benefits of using continental-scale CPM simulations over previously-available small-domain CPM simulations.

Long-range climate impacts on crop yield and the implications of enacting global carbon mitigation policies

EPA Science Inventory

Research on climate impacts and agriculture over the past two decades has applied simulation models at a range of scales and future climate scenarios, finding that crop growth and yield responds to changing climate conditions, and that the impacts are regional and highly depende...

Assessing the effects of urbanization and climate change on groundwater management in China

NASA Astrophysics Data System (ADS)

Hua, S.; Zheng, C.

2017-12-01

Groundwater is expected to be more vulnerable in the future due to climate change coupled with rapid urbanization. Thus, protecting future groundwater resources under the impact of urbanization and climate change is necessary towards more sustainable groundwater resource development. This study is intended to shed lights on how water managers may plan for the adverse effects of urbanization and climate change on groundwater quality. A new approach is presented in which the groundwater vulnerability under future climate change scenarios is employed as a constraint to urban expansion. An original form of the Land Transformation Model (LTM) and a revised LTM simulation are applied to model the urbanization. The results indicated that there would be a notable and uneven urban growth between 2010 and 2050. Future groundwater vulnerability is expected to shift significantly under future climate change scenarios. The results of the revised LTM project more urban expansion in the central regions of China, while those of the original LTM project urban expansion in throughout China, although the two projections have the same areas of expansion. The urban expansion simulated by the original LTM follows the historical trend under the drivers of socioeconomic, political and geographic factors. However, the revised LTM drives the urban expansion to the regions with relatively lower groundwater vulnerability, in contrast to the historical trend. This study demonstrates that the integration of LTM and future groundwater vulnerability in the urban planning can better protect the groundwater resource and promote more sustainable socioeconomic development. The methodology developed in this study provides water managers and city planners a useful groundwater management tool for mitigating the risks associated with rapid urbanization and climate change.

Future Precipitation Extremes in China Under Climate Change and Their Possible Mechanisms by Regional Climate Model and Earth System Model Simulations

NASA Astrophysics Data System (ADS)

Qin, P.; Xie, Z.

2017-12-01

Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.

Extreme storm surge and wind wave climate scenario simulations at the Venetian littoral

NASA Astrophysics Data System (ADS)

Lionello, P.; Galati, M. B.; Elvini, E.

Scenario climate projections for extreme marine storms producing storm surges and wind waves are very important for the northern flat coast of the Adriatic Sea, where the area at risk includes a unique cultural and environmental heritage, and important economic activities. This study uses a shallow water model and a spectral wave model for computing the storm surge and the wind wave field, respectively, from the sea level pressure and wind fields that have been computed by the RegCM regional climate model. Simulations cover the period 1961-1990 for the present climate (control simulations) and the period 2071-2100 for the A2 and B2 scenarios. Generalized Extreme Value analysis is used for estimating values for the 10 and 100 year return times. The adequacy of these modeling tools for a reliable estimation of the climate change signal, without needing further downscaling is shown. However, this study has mainly a methodological value, because issues such as interdecadal variability and intermodel variability cannot be addressed, since the analysis is based on single model 30-year long simulations. The control simulation looks reasonably accurate for extreme value analysis, though it overestimates/underestimates the frequency of high/low surge and wind wave events with respect to observations. Scenario simulations suggest higher frequency of intense storms for the B2 scenario, but not for the A2. Likely, these differences are not the effect of climate change, but of climate multidecadal variability. Extreme storms are stronger in future scenarios, but differences are not statistically significant. Therefore this study does not provide convincing evidence for more stormy conditions in future scenarios.

Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

USGS Publications Warehouse

Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-02-24

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.

Future changes in drought characteristics over South Korea using multi regional climate models with the standardized precipitation index

NASA Astrophysics Data System (ADS)

Choi, Yeon-Woo; Ahn, Joong-Bae; Suh, Myoung-Seok; Cha, Dong-Hyun; Lee, Dong-Kyou; Hong, Song-You; Min, Seung-Ki; Park, Seong-Chan; Kang, Hyun-Suk

2016-05-01

In this study, the projection of future drought conditions is estimated over South Korea based on the latest and most advanced sets of regional climate model simulations under the Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios, within the context of the national downscaling project of the Republic of Korea. The five Regional Climate Models (RCMs) are used to produce climate-change simulations around the Korean Peninsula and to estimate the uncertainty associated with these simulations. The horizontal resolution of each RCM is 12.5 km and model simulations are available for historical (1981-2010) and future (2021-2100) periods under forcing from the RCP4.5 and RCP8.5 scenarios. To assess the characteristics of drought on multiple time scales in the future, we use Standardized Precipitation Indices for 1-month (SPI- 1), 6-month (SPI-6) and 12-month (SPI-12). The number of drought months in the future is shown to be characterized by strong variability, with both increasing and decreasing trends among the scenarios. In particular, the number of drought months over South Korea is projected to increase (decrease) for the period 2041-2070 in the RCP8.5 (RCP4.5) scenario and increase (decrease) for the period 2071-2100 in the RCP4.5 (RCP8.5) scenario. In addition, the percentage area under any drought condition is overall projected to gradually decrease over South Korea during the entire future period, with the exception of SPI-1 in the RCP4.5 scenario. Particularly, the drought areas for SPI-1 in the RCP4.5 scenario show weakly positive long-term trend. Otherwise, future changes in drought areas for SPI-6 and SPI-12 have a marked downward trend under the two RCP scenarios.

Climate change: Future rise in rain inequality

NASA Astrophysics Data System (ADS)

Biasutti, Michela

2013-05-01

Rainfall disparities are expected to intensify in response to anthropogenic climate change. Model simulations suggest that wet regions and seasons will get wetter, and that a warmer equator will get wetter too.

Precipitation forecast verification over Brazilian watersheds on present and future climate

NASA Astrophysics Data System (ADS)

Xavier, L.; Bruyere, C. L.; Rotunno, O.

2016-12-01

Evaluating the quality of precipitation forecast is an essential step for hydrological studies, among other applications, which is particularly relevant when taking into account climate change and the consequent likely modification of precipitation patterns. In this study we analyzed daily precipitation forecasts given by the global model CESM and the regional model WRF on present and future climate. For present runs, CESM data have been considered from 1980 to 2005, and WRF data from 1990 to 2000. CESM future runs were available for 3 RCP scenarios (4.5, 6.0 and 8.5), over 2005-2100 period; for WRF, future runs spanned 4 different 11-year periods (2020-2030, 2030-2040, 2050-2060 and 2080-2090). WRF simulations had been driven by bias-corrected forcings, and had been done on present climate for a 24 members ensemble created by varying the adopted parameterization schemes. On WRF future climate simulations, data from 3 members out of the original ensemble were available. Precipitation data have been spatially averaged over some large Brazilian watersheds (Amazon and subbasins, Tocantins, Sao Francisco, 4 of Parana`s subbasins) and have been evaluated for present climate against a gauge gridded dataset and ERA Interim data both spanning the 1980-2013 period. The evaluation was focused on the analysis of precipitation forecasts probabilities distribution. Taking into account daily and monthly mean precipitation aggregated on 3-month periods (DJF,MAM,JJA,SON), we adopted some skill measures, amongst them, the Perkins Skill Score (PSS). From the results we verified that on present climate WRF ensemble mean led to clearly better results when compared with CESM data for Amazon, Tocantins and Sao Francisco, but model was not as skillful to the other basins, which could be also been observed for future climate. PSS results from future runs showed that few changes would be observed over the different periods for the considered basins.

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models

NASA Technical Reports Server (NTRS)

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.;

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R.

2012-01-01

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feldman, D.R.; Algieri, C.A.; Ong, J.R.

2011-04-01

Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

Improved hydrological model parametrization for climate change impact assessment under data scarcity - The potential of field monitoring techniques and geostatistics.

PubMed

Meyer, Swen; Blaschek, Michael; Duttmann, Rainer; Ludwig, Ralf

2016-02-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources, agricultural productivity and drinking water supply. Current projections of future hydrological change, based on regional climate model results and subsequent hydrological modeling schemes, are very uncertain and poorly validated. The Rio Mannu di San Sperate Basin, located in Sardinia, Italy, is one test site of the CLIMB project. The Water Simulation Model (WaSiM) was set up to model current and future hydrological conditions. The availability of measured meteorological and hydrological data is poor as it is common for many Mediterranean catchments. In this study we conducted a soil sampling campaign in the Rio Mannu catchment. We tested different deterministic and hybrid geostatistical interpolation methods on soil textures and tested the performance of the applied models. We calculated a new soil texture map based on the best prediction method. The soil model in WaSiM was set up with the improved new soil information. The simulation results were compared to standard soil parametrization. WaSiMs was validated with spatial evapotranspiration rates using the triangle method (Jiang and Islam, 1999). WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. The climate change impact was assessed based on differences between reference and future time series. The simulated results show a reduction of all hydrological quantities in the future in the spring season. Furthermore simulation results reveal an earlier onset of dry conditions in the catchment. We show that a solid soil model setup based on short-term field measurements can improve long-term modeling results, which is especially important in ungauged catchments. Copyright © 2015 Elsevier B.V. All rights reserved.

Projected changes to short- and long-duration precipitation extremes over the Canadian Prairie Provinces

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-09-01

The effects of climate change on April-October short- and long-duration precipitation extremes over the Canadian Prairie Provinces were evaluated using a multi-Regional Climate Model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by the National Centre for Environmental Prediction (NCEP) reanalysis II product for the 1981-2000 period and those driven by four Atmosphere-Ocean General Circulation Models (AOGCMs) for the current 1971-2000 and future 2041-2070 periods (i.e. a total of 11 current-to-future period simulation pairs). A regional frequency analysis approach was used to develop 2-, 5-, 10-, 25-, and 50-year return values of precipitation extremes from NCEP and AOGCM-driven current and future period simulations that respectively were used to study the performance of RCMs and projected changes for selected return values at regional, grid-cell and local scales. Performance errors due to internal dynamics and physics of RCMs studied for the 1981-2000 period reveal considerable variation in the performance of the RCMs. However, the performance errors were found to be much smaller for RCM ensemble averages than for individual RCMs. Projected changes in future climate to selected regional return values of short-duration (e.g. 15- and 30-min) precipitation extremes and for longer return periods (e.g. 50-year) were found to be mostly larger than those to the longer duration (e.g. 24- and 48-h) extremes and short return periods (e.g. 2-year). Overall, projected changes in precipitation extremes were larger for southeastern regions followed by southern and northern regions and smaller for southwestern and western regions of the study area. The changes to return values were also found to be statistically significant for the majority of the RCM-AOGCM simulation pairs. These projections might be useful as a key input for the future planning of urban drainage infrastructure and development of strategic climate change adaptation measures.

SIMULATED RESPONSES OF THE GULF OF MEXICO HYPOXIA TO VARIATIONS IN CLIMATE AND ANTHROPOGENIC NUTRIENT LOADING. (R827785E02)

EPA Science Inventory

A mathematical model was used to simulate monthly responses of the Gulf of Mexico hypoxia to variations in climate and anthropogenic nutrient loading over a 45-year period. We examined six hypothetical future scenarios that are based on observed and projected changes in the Mi...

Evaluations of alternative methods for monitoring and estimating responses of salmon productivity in the North Pacific to future climatic change and other processes: A simulation study

EPA Science Inventory

Estimation of the relative influence of climate change, compared to other human activities, on dynamics of Pacific salmon (Oncorhynchus spp.) populations can help management agencies take appropriate management actions. We used empirically based simulation modelling of 48 sockeye...

Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological Model

NASA Astrophysics Data System (ADS)

Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten

2016-04-01

Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.

Water use efficiency and crop water balance of rainfed wheat in a semi-arid environment: sensitivity of future changes to projected climate changes and soil type

NASA Astrophysics Data System (ADS)

Yang, Yanmin; Liu, De Li; Anwar, Muhuddin Rajin; O'Leary, Garry; Macadam, Ian; Yang, Yonghui

2016-02-01

Wheat production is expected to be affected by climate change through changing components of the crop water balance such as rainfall, evapotranspiration (ET), runoff and drainage. We used the Agricultural Production Systems Simulator (APSIM)-wheat model to simulate the potential impact of climate change on field water balance, ET and water use efficiency (WUE) under the SRES A2 emissions scenario. We ran APSIM with daily climate data statistically downscaled from 18 Global Circulation Models (GCMs). Twelve soil types of varying plant available water holding capacity (PAWC) at six sites across semi-arid southeastern Australia were considered. Biases in the GCM-simulated climate data were bias-corrected against observations for the 1961-1999 baseline period. However, biases in the APSIM output data relative to APSIM simulations forced with climate observations remained. A secondary bias correction was therefore performed on the APSIM outputs. Bias-corrected APSIM outputs for a future period (2021-2040) were compared with APSIM outputs generated using observations for the baseline period to obtain future changes. The results show that effective rainfall was decreased over all sites due to decreased growing season rainfall. ET was decreased through reduced soil evaporation and crop transpiration. There were no significant changes in runoff at any site. The variation in deep drainage between sites was much greater than for runoff, ranging from less than a few millimetres at the drier sites to over 100 mm at the wetter. However, in general, the averaged drainage over different soil types were not significantly different between the baseline (1961-1999) and future period of 2021-2040 ( P > 0.05). For the wetter sites, the variations in the future changes in drainage and runoff between the 18 GCMs were larger than those of the drier sites. At the dry sites, the variation in drainage decreased as PAWC increased. Overall, water use efficiency based on transpiration (WUE_T) and ET (WUE_ET) increased by 1.1 to 1.6 and 0.7 to 1.3 kg ha-1 mm-1, respectively, over the baseline historical climate. Significant relationships between changes in wheat yield and PAWC were only seen at three sites. At the dry sites, the impact of a future climate under a soil of high PAWC was less than that under one of low PAWC. Conversely, the opposite response was seen at two wetter sites, highlighting the importance of PAWC and rainfall in determining the interactive response of crops to primary components of the water balance.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) river basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms,more » were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Here, our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserves more in-depth examination.« less

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

NASA Astrophysics Data System (ADS)

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim; Mei, Rui; Kabela, Erik D.; Gangrade, Sudershan; Naz, Bibi S.; Preston, Benjamin L.; Singh, Nagendra; Anantharaj, Valentine G.

2017-05-01

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) River Basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserve more in-depth examination.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

DOE PAGES

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim; ...

2017-04-13

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) river basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms,more » were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Here, our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserves more in-depth examination.« less

Identifying outdoor thermal risk areas and evaluation of future thermal comfort concerning shading orientation in a traditional settlement.

PubMed

Huang, Kuo-Tsang; Yang, Shing-Ru; Matzarakis, Andreas; Lin, Tzu-Ping

2018-06-01

The outdoor thermal environment is expected to be deteriorated under climate change. An approach of risk identification including assessment from aspects of thermal stress effect, people's exposure, and local's vulnerability were adopted to study a hot-and-humid traditional rural community located at Tainan, Taiwan. Layers of each aspect were either constructed by in-situ measurements or simulations. To evaluate the future thermal comfort changes by simulations, the prerequisite hourly climate data of three future time slices were produced. Prognostic simulation model, ENVI-met, in combination with diagnostic model, RayMan, were respectively used for identifying current spatial distribution of thermal stress and for assessing the future thermal comfort changes. High thermal risk area was identified by superimposing layers of hazard, exposure and vulnerability. It revealed that because of the tourists' vulnerability to adapt local climate and the inflexibleness of choosing visiting time, it exhibited a high thermal stress at the Main Courtyard where its thermal comfort conditions will be deteriorated due to climate change. Furthermore, the thermal comfort conditions in various shading orientation were analyzed based on the changing climate in three future time slices, i.e. 2011-2040, 2041-2070, and 2071-2100. The results show the area with shading in the East and West side is more comfort than in the North side. In hot season, shading in the West side contributes less PET increasing, especially in the afternoon period. The severest overheat problem (the physiological equivalent temperature, PET>40°C) at the Main Courtyard will increase from current 10% to 28% in 2071-2100 in terms of overheating occurrence frequency. The results of this study can be used as the guidelines for environment analysis before planning or redesign community. Copyright © 2018 Elsevier B.V. All rights reserved.

The Mediterranean surface wave climate inferred from future scenario simulations

NASA Astrophysics Data System (ADS)

Lionello, P.; Cogo, S.; Galati, M. B.; Sanna, A.

2008-09-01

This study is based on 30-year long simulations of the wind-wave field in the Mediterranean Sea carried out with the WAM model. Wave fields have been computed for the 2071-2100 period of the A2, B2 emission scenarios and for the 1961-1990 period of the present climate (REF). The wave model has been forced by the wind field computed by a regional climate model with 50 km resolution. The mean SWH (Significant Wave Height) field over large fraction of the Mediterranean sea is lower for the A2 scenario than for the present climate during winter, spring and autumn. During summer the A2 mean SWH field is also lower everywhere, except for two areas, those between Greece and Northern Africa and between Spain and Algeria, where it is significantly higher. All these changes are similar, though smaller and less significant, in the B2 scenario, except during winter in the north-western Mediterranean Sea, when the B2 mean SWH field is higher than in the REF simulation. Also extreme SWH values are smaller in future scenarios than in the present climate and such SWH change is larger for the A2 than for the B2 scenario. The only exception is the presence of higher SWH extremes in the central Mediterranean during summer for the A2 scenario. In general, changes of SWH, wind speed and atmospheric circulation are consistent, and results show milder marine storms in future scenarios than in the present climate.

Assessment of Climate Change Impacts on Agricultural Water Demands and Crop Yields in California's Central Valley

NASA Astrophysics Data System (ADS)

Tansey, M. K.; Flores-Lopez, F.; Young, C. A.; Huntington, J. L.

2012-12-01

Long term planning for the management of California's water resources requires assessment of the effects of future climate changes on both water supply and demand. Considerable progress has been made on the evaluation of the effects of future climate changes on water supplies but less information is available with regard to water demands. Uncertainty in future climate projections increases the difficulty of assessing climate impacts and evaluating long range adaptation strategies. Compounding the uncertainty in the future climate projections is the fact that most readily available downscaled climate projections lack sufficient meteorological information to compute evapotranspiration (ET) by the widely accepted ASCE Penman-Monteith (PM) method. This study addresses potential changes in future Central Valley water demands and crop yields by examining the effects of climate change on soil evaporation, plant transpiration, growth and yield for major types of crops grown in the Central Valley of California. Five representative climate scenarios based on 112 bias corrected spatially downscaled CMIP 3 GCM climate simulations were developed using the hybrid delta ensemble method to span a wide range future climate uncertainty. Analysis of historical California Irrigation Management Information System meteorological data was combined with several meteorological estimation methods to compute future solar radiation, wind speed and dew point temperatures corresponding to the GCM projected temperatures and precipitation. Future atmospheric CO2 concentrations corresponding to the 5 representative climate projections were developed based on weighting IPCC SRES emissions scenarios. The Land, Atmosphere, and Water Simulator (LAWS) model was used to compute ET and yield changes in the early, middle and late 21st century for 24 representative agricultural crops grown in the Sacramento, San Joaquin and Tulare Lake basins. Study results indicate that changes in ET and yield vary between crops due to plant specific sensitivities to temperature, solar radiation and the vapor pressure deficits. Shifts in the growth period to earlier in the year, shortened growth period for annual crops as well as extended fall growth can also exert important influences. Projected increases in CO2 concentrations in the late 21st century exert very significant influences on ET and yield for many crops. To characterize potential impacts and the range of uncertainty, changes in total agricultural water demands and yields were computed assuming that current crop types and acreages in 21 Central Valley regional planning areas remained constant throughout the 21st century for each of the 5 representative future climate scenarios.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections

PubMed Central

Caballero, Rodrigo; Huber, Matthew

2013-01-01

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow “Earth system” feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or “Charney” climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature. PMID:23918397

Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

NASA Astrophysics Data System (ADS)

Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

2018-01-01

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Climate model biases and statistical downscaling for application in hydrologic model

USDA-ARS?s Scientific Manuscript database

Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

Tailored scenarios for streamflow climate change impacts based on the perturbation of precipitation and evapotranspiration

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel

2015-04-01

It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.

Vegetation zones in changing climate

NASA Astrophysics Data System (ADS)

Belda, Michal; Holtanova, Eva; Halenka, Tomas; Kalvova, Jaroslava

2017-04-01

Climate patterns analysis can be performed for individual climate variables separately or the data can be aggregated using e.g. some kind of climate classification. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. Thus, the Köppen-Trewartha classification provides integrated assessment of temperature and precipitation together with their annual cycle as well. This way climate classifications also can be used as a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes. The Köppen-Trewartha classification is applied on full CMIP5 family of more than 40 GCM simulations and CRU dataset for comparison. This evaluation provides insight on the GCM performance and errors for simulations of the 20th century climate. Common regions are identified, such as Australia or Amazonia, where many state-of-the-art models perform inadequately. Moreover, the analysis of the CMIP5 ensemble for future under RCP 4.5 and RCP 8.5 is performed to assess the climate change for future. There are significant changes for some types in most models e.g. increase of savanna and decrease of tundra for the future climate. For some types significant shifts in latitude can be seen when studying their geographical location in selected continental areas, e.g. toward higher latitudes for boreal climate. Quite significant uncertainty can be seen for some types. For Europe, EuroCORDEX results for both 0.11 and 0.44 degree resolution are validated using Köppen-Trewartha types in comparison to E-OBS based classification. ERA-Interim driven simulations are compared to both present conditions of CMIP5 models as well as their downscaling by EuroCORDEX RCMs. Finally, the climate change signal assessment is provided using the individual climate types. In addition to the changes assessed similarly as for GCMs analysis in terms of the area of individual types, in the continental scale some shifts of boundaries between the selected types can be studied as well providing the information on climate change signal. The shift of the boundary between the boreal zone and continental temperate zone to the north is clearly seen in most simulations as well as eastern move of the boundary of the maritime and continental type of temperate zone. However, there can be quite clear problem with model biases in climate types association. When analysing climate types in Europe and their shifts under climate change using Köppen-Trewartha classification (KTC), for the temperate climate type there are subtypes defined following the continentality patterns, and we can see their generally meridionally located divide across Europe shifted to the east. There is a question whether this is realistic or rather due to the simplistic condition in KTC following the winter minimum temperature, while other continentality indices consider rather the amplitude of temperature during the year. This leads us to connect our analysis of climate change effects using climate classification to the more detailed analysis of continentality patterns development in Europe to provide better insight on the climate regimes and to verify the continentality conditions, their definitions and climate change effects on them. The comparison of several selected continentality indices is shown.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less

Fire and reduced vigor facilitate vegetation shifts: MC2 results for the conterminous US with CMIP5 climate futures

NASA Astrophysics Data System (ADS)

Bachelet, D. M.; Ferschweiler, K.; Baker, B.; Sleeter, B. M.

2016-12-01

Climate variability and a warming trend during the 21st century ensures fuel build-up and episodic catastrophic wildfires. We used downscaled (2.5 arcmin) CMIP5 climate futures from 20 models under RCP 8.5 to run the dynamic global vegetation model MC2 over the conterminous US and identify key drivers of land cover change. We show regional and temporal differences in the magnitude of projected C losses due to fire over the 21st century. We also look at the vigor (NPP/LAI) of forest lands and estimate the loss in C capture due to declines in production as well as the increase in heterotrophic respiration due to increased mortality. We compare simulated the carbon sequestration potential of terrestrial biomes and the risk of carbon losses through disturbance. We quantify uncertainty in model results by showing the distribution of possible future impacts under 20 futures. We explore the effects of land use and highlight the challenges we met to simulate credible transient management practices throughout the 20th century and into the future.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Integrated simulation of consumptive use and land subsidence in the Central Valley, California, for the past and for a future subject to urbanization and climate change

USGS Publications Warehouse

Hanson, Randall T.; Flint, Alan L.; Faunt, Claudia C.; Cayan, Daniel R.; Flint, Lorraine E.; Leake, Stanley A.; Schmid, Wolfgang

2010-01-01

Competition for water resources is growing throughout California, particularly in the Central Valley where about 20% of all groundwater used in the United States is consumed for agriculture and urban water supply. Continued agricultural use coupled with urban growth and potential climate change would result in continued depletion of groundwater storage and associated land subsidence throughout the Central Valley. For 1962-2003, an estimated 1,230 hectare meters (hm3) of water was withdrawn from fine-grained beds, resulting in more than three meters (m) of additional land subsidence locally. Linked physically-based, supply-constrained and emanddriven hydrologic models were used to simulate future hydrologic conditions under the A2 climate projection scenario that assumes continued "business as usual" greenhouse gas emissions. Results indicate an increased subsidence in the second half of the twenty-first century. Potential simulated land subsidence extends into urban areas and the eastern side of the valley where future surface-water deliveries may be depleted. 

Future changes of temperature and heat waves in Ontario, Canada

NASA Astrophysics Data System (ADS)

Li, Zhong; Huang, Guohe; Huang, Wendy; Lin, Qianguo; Liao, Renfei; Fan, Yurui

2018-05-01

Apparent changes in the temperature patterns in recent years brought many challenges to the province of Ontario, Canada. As the need for adapting to climate change challenges increases, the development of reliable climate projections becomes a crucial task. In this study, a regional climate modeling system, Providing Regional Climates for Impacts Studies (PRECIS), is used to simulate the temperature patterns in Ontario. Three PRECIS runs with a resolution of 25 km × 25 km are carried out to simulate the present (1961-1990) temperature variations. There is a good match between the simulated and observed data, which validates the performance of PRECIS in reproducing temperature changes in Ontario. Future changes of daily maximum, mean, and minimum temperatures during the period 2071-2100 are then projected under the IPCC SRES A2 and B2 emission scenarios using PRECIS. Spatial variations of annual mean temperature, mean diurnal range, and temperature seasonality are generated. Furthermore, heat waves defined based on the exceedance of local climatology and their temporal and spatial characteristics are analyzed. The results indicate that the highest temperature and the most intensive heat waves are most likely to occur at the Toronto-Windsor corridor in Southern Ontario. The Northern Ontario, in spite of the relatively low projected temperature, would be under the risk of long-lasting heat waves, and thus needs effective measures to enhance its climate resilience in the future. This study can assist the decision makers in better understanding the future temperature changes in Ontario and provide decision support for mitigating heat-related loss.

Impact of climate change upon vector born diseases in Europe and Africa using ENSEMBLES Regional Climate Models

NASA Astrophysics Data System (ADS)

Caminade, Cyril; Morse, Andy

2010-05-01

Climate variability is an important component in determining the incidence of a number of diseases with significant human/animal health and socioeconomic impacts. The most important diseases affecting health are vector-borne, such as malaria, Rift Valley Fever and including those that are tick borne, with over 3 billion of the world population at risk. Malaria alone is responsible for at least one million deaths annually, with 80% of malaria deaths occurring in sub-Saharan Africa. The climate has a large impact upon the incidence of vector-borne diseases; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the environmental conditions. A large ensemble of regional climate model simulations has been produced within the ENSEMBLES project framework for both the European and African continent. This work will present recent progress in human and animal disease modelling, based on high resolution climate observations and regional climate simulations. Preliminary results will be given as an illustration, including the impact of climate change upon bluetongue (disease affecting the cattle) over Europe and upon malaria and Rift Valley Fever over Africa. Malaria scenarios based on RCM ensemble simulations have been produced for West Africa. These simulations have been carried out using the Liverpool Malaria Model. Future projections highlight that the malaria incidence decreases at the northern edge of the Sahel and that the epidemic belt is shifted southward in autumn. This could lead to significant public health problems in the future as the demography is expected to dramatically rise over Africa for the 21st century.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

How Are MIS-5e And MIS-11 Different From Other Interglacials And the Future?

NASA Astrophysics Data System (ADS)

Yin, Q.; Berger, A.

2017-12-01

MIS-5e and MIS-11 appear in many proxy records as the warmest interglacials of the last million years although their astronomical configurations are very different. To investigate how they are different from other interglacials and between themselves, the climate of nine interglacials of the past 800,000 years has been simulated using both snapshot and transient experiments. These simulations allow to investigate the relative contributions of insolation and CO2 to the intensity and duration of each interglacial as well as the differences and similarities between the interglacials. The transient simulations which cover a large range of precession, obliquity and eccentricity allow to investigate the response of different climate variables and different regions to the three astronomical parameters. My presentation will focus on the characteristics of the climate forcing and response of MIS-5e and MIS-11 in comparison with the other intergalcials. Their duration and intensity at global and regional scales will be shown and the causes will be discussed. Unique features in astronomical forcing as well as in regional climate response are found in MIS-5e and MIS-11, which might help to understand why they appear to be among the warmest interglacials. The model results also show that the warm interval of MIS-11 is the longest, confirming its long duration as found in many proxy records. The long duration of MIS-11 is related to a particular combination of eccentricity, obliquity and precession as well as to its long-lasting high CO2 concentration. The differences between the seasonal behaviour of the past interglacials highlight the importance of seasonal climate reconstruction and therefore the necessity to obtain seasonal proxies. The simulated climate of MIS-5e and MIS-11 will also be compared with the climate of today and of the future to investigate the differences and similarities between the past warm conditions and the projected future warming. Part of the results are published in: Yin Q.Z. and Berger A., 2015. Interglacial analogues of the Holocene and its natural near future. Quaternary Science Reviews, 120, 28-46. Yin Q.Z. and Berger A., 2012. Individual contribution of insolation and CO2 to the interglacial climates of the past 800,000 years. Climate Dynamics 38:709-724.

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

NASA Technical Reports Server (NTRS)

Jones, M.R; Singels, A.; Ruane, A. C.

2015-01-01

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Can the combined use of an ensemble based modelling approach and the analysis of measured meteorological trends lead to increased confidence in climate change impact assessments?

NASA Astrophysics Data System (ADS)

Gädeke, Anne; Koch, Hagen; Pohle, Ina; Grünewald, Uwe

2014-05-01

In anthropogenically heavily impacted river catchments, such as the Lusatian river catchments of Spree and Schwarze Elster (Germany), the robust assessment of possible impacts of climate change on the regional water resources is of high relevance for the development and implementation of suitable climate change adaptation strategies. Large uncertainties inherent in future climate projections may, however, reduce the willingness of regional stakeholder to develop and implement suitable adaptation strategies to climate change. This study provides an overview of different possibilities to consider uncertainties in climate change impact assessments by means of (1) an ensemble based modelling approach and (2) the incorporation of measured and simulated meteorological trends. The ensemble based modelling approach consists of the meteorological output of four climate downscaling approaches (DAs) (two dynamical and two statistical DAs (113 realisations in total)), which drive different model configurations of two conceptually different hydrological models (HBV-light and WaSiM-ETH). As study area serve three near natural subcatchments of the Spree and Schwarze Elster river catchments. The objective of incorporating measured meteorological trends into the analysis was twofold: measured trends can (i) serve as a mean to validate the results of the DAs and (ii) be regarded as harbinger for the future direction of change. Moreover, regional stakeholders seem to have more trust in measurements than in modelling results. In order to evaluate the nature of the trends, both gradual (Mann-Kendall test) and step changes (Pettitt test) are considered as well as both temporal and spatial correlations in the data. The results of the ensemble based modelling chain show that depending on the type (dynamical or statistical) of DA used, opposing trends in precipitation, actual evapotranspiration and discharge are simulated in the scenario period (2031-2060). While the statistical DAs simulate a strong decrease in future long term annual precipitation, the dynamical DAs simulate a tendency towards increasing precipitation. The trend analysis suggests that precipitation has not changed significantly during the period 1961-2006. Therefore, the decrease simulated by the statistical DAs should be interpreted as a rather dry future projection. Concerning air temperature, measured and simulated trends agree on a positive trend. Also the uncertainty related to the hydrological model within the climate change modelling chain is comparably low when long-term averages are considered but increases significantly during extreme events. This proposed framework of combining an ensemble based modelling approach with measured trend analysis is a promising approach for regional stakeholders to gain more confidence into the final results of climate change impact assessments. However, climate change impact assessments will remain highly uncertain. Thus, flexible adaptation strategies need to be developed which should not only consider climate but also other aspects of global change.

Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance.

PubMed

Chang, Jinfeng; Ciais, Philippe; Viovy, Nicolas; Soussana, Jean-François; Klumpp, Katja; Sultan, Benjamin

2017-12-01

Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071-2100 is predicted to be 1-5.5 °C higher than that for 1971-2000. Climate change and elevated CO 2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change. Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO 2 . The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C. This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers' ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.

Modelling of groundwater recharge and drought statistics within the framework of a climate impact study in a Mediterranean catchment (Thau Lagoon, France)

NASA Astrophysics Data System (ADS)

Herrmann, Frank; Baghdadi, Nicolas; Deidda, Roberto; La Jeunesse, Isabelle; Ludwig, Ralf; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2014-05-01

According to current climate projections until the year 2100, Mediterranean countries are likely to be at high risk for decreasing groundwater recharge during the hydrological winter half year as well as increasing drought severity and duration during summer. Thus, the irrigation needs of agricultural land might increase during the vegetation period and will have to be covered regionally specific partially from groundwater resources. This issue seems to be equally important to be investigated compared to the possible future change of the river discharge regime under changed climate conditions. Within the framework of the EU-founded CLIMB project (Climate Induced Changes on the Hydrology of Mediterranean Basins) the water balance model mGROWA (Herrmann, 2013) was applied in order to simulate the water balance within the Thau Lagoon catchment (France) under present and possible future climate conditions. The model was originally developed in order to simulate actual evapotranspiration and runoff components (e.g. groundwater recharge) in daily time-steps and with high spatial resolution (50 m grid). Area-differentiated groundwater recharge and soil water content can be simulated consistently using mGROWA because of an integrated multi-layer soil water module. In the framework of CLIMB, this module has been extended by routines to calculate drought statistics. The mGROWA-model will be briefly introduced and its application to the Thau Lagoon catchment will be presented. At first water balance was simulated for the reference period (1995-2010) based on observed climate data. Special attention will be paid to the simulated temporal variable water content in the root zone and thus to percolation water fluxes and drought statistics. Second, a possible bandwidth of future groundwater recharge (until 2070) is forecasted using climate data from a Regional-Climate-Modell-ensemble (RCM; Deidda, 2013). Three of the four RCM-mGROWA combinations indicate decreasing groundwater recharge up to 25 mm/a until 2070 compared to the reference period 1971-2000, whereas one RCM-mGROWA combination projects a nearly constant level of groundwater recharge for the future. The calculated drought indices however indicate that the frequency and duration of droughts will increase until 2070. References: Deidda R., M. Marrocu, G. Caroletti, G. Pusceddu, A. Langousis, V. Lucarini, M. Puliga, and A. Speranza (2013), Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas, Hydrology and Earth System Sciences, 17, 5041-5059, doi:10.5194/hess-17-5041-2013 Herrmann, F., Chen, S., Heidt, L., Elbracht, J., Engel, N., Kunkel, R., Müller, U., Röhm, H., Vereecken, H., Wendland, F., 2013. Zeitlich und räumlich hochaufgelöste flächendifferenzierte Simulation des Landschaftswasserhaushalts in Niedersachsen mit dem Model mGROWA. Hydrologie und Wasserbewirtschaftung, 57(5): 206-224.

Simulating the effects of climate change on population connectivity of American marten (Martes americana) in the northern Rocky Mountains, USA

Treesearch

T. N. Wasserman; S. A. Cushman; A. S. Shirk; E. L. Landguth; J. S. Littell

2012-01-01

We utilize empirically derived estimates of landscape resistance to assess current landscape connectivity of American marten (Martes americana) in the northern Rocky Mountains, USA, and project how a warming climate may affect landscape resistance and population connectivity in the future. We evaluate the influences of five potential future temperature scenarios...

Surface temperatures of the Mid-Pliocene North Atlantic Ocean: Implications for future climate

USGS Publications Warehouse

Dowsett, Harry J.; Chandler, Mark A.; Robinson, Marci M.

2009-01-01

The Mid-Pliocene is the most recent interval in the Earth's history to have experienced warming of the magnitude predicted for the second half of the twenty-first century and is, therefore, a possible analogue for future climate conditions. With continents basically in their current positions and atmospheric CO2 similar to early twenty-first century values, the cause of Mid-Pliocene warmth remains elusive. Understanding the behaviour of the North Atlantic Ocean during the Mid-Pliocene is integral to evaluating future climate scenarios owing to its role in deep water formation and its sensitivity to climate change. Under the framework of the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) sea surface reconstruction, we synthesize Mid-Pliocene North Atlantic studies by PRISM members and others, describing each region of the North Atlantic in terms of palaeoceanography. We then relate Mid-Pliocene sea surface conditions to expectations of future warming. The results of the data and climate model comparisons suggest that the North Atlantic is more sensitive to climate change than is suggested by climate model simulations, raising the concern that estimates of future climate change are conservative.

Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050

EPA Science Inventory

The potential impact of global climate change on future air quality in the United States is investigated with global and regional-scale models. Regional climate model scenarios are developed by dynamically downscaling the outputs from a global chemistry and climate model and are...

Climate change and watershed mercury export: a multiple projection and model analysis

EPA Science Inventory

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. We apply an ensemble of watershed models to simulate and assess the responses of hydrological and total Hg (HgT) fluxes and concentrations to two climate change projections in the US Co...

Modeling Pacific Northwest carbon and water cycling using CARAIB Dynamic Vegetation Model

NASA Astrophysics Data System (ADS)

Dury, M.; Kim, J. B.; Still, C. J.; Francois, L. M.; Jiang, Y.

2015-12-01

While uncertainties remain regarding projected temperature and precipitation changes, climate warming is already affecting ecosystems in the Pacific Northwest (PNW). Decrease in ecosystem productivity as well as increase in mortality of some plant species induced by drought and disturbance have been reported. Here, we applied the process-based dynamic vegetation model CARAIB to PNW to simulate the response of water and carbon cycling to current and future climate change projections. The vegetation model has already been successfully applied to Europe to simulate plant physiological response to climate change. We calibrated CARAIB to PNW using global Plant Functional Types. For calibration, the model is driven with the gridded surface meteorological dataset UIdaho MACA METDATA with 1/24-degree (~4-km) resolution at a daily time step for the period 1979-2014. The model ability to reproduce the current spatial and temporal variations of carbon stocks and fluxes was evaluated using a variety of available datasets, including eddy covariance and satellite observations. We focused particularly on past severe drought and fire episodes. Then, we simulated future conditions using the UIdaho MACAv2-METDATA dataset, which includes downscaled CMIP5 projections from 28 GCMs for RCP4.5 and RCP8.5. We evaluated the future ecosystem carbon balance resulting from changes in drought frequency as well as in fire risk. We also simulated future productivity and drought-induced mortality of several key PNW tree species.

Realism of the Indian Ocean Dipole in CMIP5 models, and the Implication for Climate Projections

NASA Astrophysics Data System (ADS)

Weller, E.; Cai, W.; Cowan, T.

2012-12-01

An assessment of how well climate models simulate the Indian Ocean Dipole (IOD) is undertaken using coupled models that have partaken in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared to CMIP3 models, no substantial improvement is evident in the simulation of the IOD pattern and/or amplitude during its peak season in austral spring (September-October-November, or SON). The majority of CMIP5 models generate a larger variance of sea surface temperature (SST) in the Sumatra-Java upwelling region and an IOD amplitude that is far greater than what is observed. Although the relationship between precipitation and the tropical Indian Ocean SST is well simulated, future projections of SON rainfall changes over IOD-influenced regions are intrinsically linked to the IOD-rainfall teleconnection and IOD amplitude in the model present-day climate. The diversity of the simulated IOD amplitudes in CMIP5 (and CMIP3) models which tend to be overly large, results in a wide range of future modelled SON rainfall trends over IOD-influenced regions. Our results highlight the importance of realistically simulating the present-day IOD properties and the caveat that needs to be exercised in interpreting climate projections in the IOD-affected regions.

Statistical downscaling of GCM simulations to streamflow using relevance vector machine

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Mujumdar, P. P.

2008-01-01

General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario.

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE PAGES

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

2018-01-22

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA

USGS Publications Warehouse

Lauffenburger, Zachary H.; Gurdak, Jason J.; Hobza, Christopher M.; Woodward, Duane; Wolf, Cassandra

2018-01-01

Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.

How Novel are 21st Century Climates? A Global Assessment of Future Climates and their Analogs Back Through the Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.; Jackson, S. T.

2016-12-01

Climate change is a multivariate process, where changes in the environmental space of a location will likely drive biotic responses of the flora and fauna that inhabit the region. In the face of a rapidly changing climate it is important to understand what the future may hold for ecosystems. One method commonly applied to understand how dissimilar future climates will be relative to the modern period is no-analog analysis. This has been done for 21st century climates relative to the modern period, but has not been extended through the paleorecord. Using HadCM3, CCSM3 TraCE-21ka, PMIP3, PlioMIP2 and EoMIP climate simulations, we assess global and regional climatic novelty by identifying the closest analogs in these periods for both future (21st century) and modern climates. This baseline offers a full range climate space with significant overlap of modern and future projected climates, and allows us to assess both emergences and disappearances of analog climate conditions throughout the past. This extended baseline includes past glacial and interglacial climates, as well as past earth warm periods. Past earth warm periods such as the middle to late Pliocene and the early Eocene may be most similar to projections of future climate, so it is important to evaluate our understanding of these global climates. Here we calculate dissimilarity to quantify novelty and no-analog conditions using the Standardized Euclidian Distance, as well as the Mahalanobis distance. Our work shows that nearest climate analogs for the modern period, as well as future climates, existed and disappeared during past warm periods. These results suggest that though climate change may be regionally novel relative to the modern period for some locations, analogs do exist through the paleorecord which in some cases reduce novelty. Nevertheless, novelty remains high in some locations suggesting that some future climates may be unprecedented.

Modeling the Hydro-Climatic Effects of Land Cover / Land Use Changes in the Euphrates and Tigris Basin Under a Changing Climate

NASA Astrophysics Data System (ADS)

Yilmaz, Y.; Sen, O. L.; Turuncoglu, U. U.

2016-12-01

The Southeastern Anatolia Project (SAP) of Turkey is a multidimensional regional development project based on utilizing the waters of Euphrates and Tigris rivers by irrigating vast semi-arid lands and by producing hydroelectric power. Since the beginning of 90s, the irrigation schemes carried out within the scope of SAP have substantially altered the land cover / land use (LCLU) of the region. In this study, the individual and combined effects of anthropogenic LCLU changes through intensification of irrigation and climate change are investigated by use of a state-of-the-art regional climate model (RegCM4). For this purpose, model simulations with three reconstructed LCLU maps and two future climate change scenarios were conducted over a domain at a horizontal resolution of 48 km over Eastern Mediterranean and Black Sea region, and later on nested domain with 12 km resolution over Turkey. As forcing dataset for RegCM4 at the boundaries, a reanalysis data (NNRP) and outputs of a global circulation model (EC-EARTH) have been used. Model performance was assessed by using high resolution gridded CRU (Climatic Research Unit) data for the period between 1991 and 2008. The model suggests that LCLU changes have some effects on surface hydro-climatic variables in the region (e.g., temperatures are 0.4 0C and 0.8 0C cooler while precipitation amounts are more around 3% and 7%, evapotranspiration rates are higher 51% and 114%, specific humidity amounts are more around 8% and 17%, on annual basis, in simulations respectively with current and future land use maps compared to a simulation with pre-SAP land use conditions). The RCP 4.5 scenario simulation with the default land use map shows that precipitation and evapotranspiration amounts will increase in opposition to the simulation results of RCP 8.5 scenario. Preliminary results of the study indicate that current and future LCLU changes will affect the water balance of the basin. The riparian countries (Turkey, Iraq and Syria) have been facing a crucial water sharing problem. Considering the significant water loss through evapotranspiration has potential for shaping the future water resources management and policies in the region. Acknowledgment This study has been supported by TUBITAK (The Scientific and Technological Research Council of Turkey) under project number 114Y114.

An introduction to three-dimensional climate modeling

NASA Technical Reports Server (NTRS)

Washington, W. M.; Parkinson, C. L.

1986-01-01

The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

NASA Astrophysics Data System (ADS)

Gutowski, W. J.

2009-12-01

NARCCAP is a multi-institutional program that is investigating systematically the uncertainties in regional scale simulations of contemporary climate and projections of future climate. NARCCAP is supported by multiple federal agencies. NARCCAP is producing an ensemble of high-resolution climate-change scenarios by nesting multiple RCMs in reanalyses and multiple atmosphere-ocean GCM simulations of contemporary and future-scenario climates. The RCM domains cover the contiguous U.S., northern Mexico, and most of Canada. The simulation suite also includes time-slice, high resolution GCMs that use sea-surface temperatures from parent atmosphere-ocean GCMs. The baseline resolution of the RCMs and time-slice GCMs is 50 km. Simulations use three sources of boundary conditions: National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) AMIP-II Reanalysis, GCMs simulating contemporary climate and GCMs using the A2 SRES emission scenario for the twenty-first century. Simulations cover 1979-2004 and 2038-2060, with the first 3 years discarded for spin-up. The resulting RCM and time-slice simulations offer opportunity for extensive analysis of RCM simulations as well as a basis for multiple high-resolution climate scenarios for climate change impacts assessments. Geophysical statisticians are developing measures of uncertainty from the ensemble. To enable very high-resolution simulations of specific regions, both RCM and high-resolution time-slice simulations are saving output needed for further downscaling. All output is publically available to the climate analysis and the climate impacts assessment community, through an archiving and data-distribution plan. Some initial results show that the models closely reproduce ENSO-related precipitation variations in coastal California, where the correlation between the simulated and observed monthly time series exceeds 0.94 for all models. The strong El Nino events of 1982-83 and 1997-98 are well reproduced for the Pacific coastal region of the U.S. in all models. ENSO signals are less well reproduced in other regions. The models also produce well extreme monthly precipitation in coastal California and the Upper Midwest. Model performance tends to deteriorate from west to east across the domain, or roughly from the inflow boundary toward the outflow boundary. This deterioration with distance from the inflow boundary is ameliorated to some extent in models formulated such that large-scale information is included in the model solution, whether implemented by spectral nudging or by use of a perturbation form of the governing equations.

The Sensitivity of the North American Monsoon to Deglacial Climate Change in Proxies and Models

NASA Astrophysics Data System (ADS)

Bhattacharya, T.; Tierney, J. E.

2017-12-01

The North American Monsoon (NAM), which brings summer rainfall to the arid US Southwest and northwestern Mexico, remains one of the least understood monsoon systems. Model simulations produce divergent NAM responses to future anthropogenic warming, and many paleoclimatic records from the NAM region are more sensitive to winter rainfall than the summertime circulation. As a result, we have an incomplete understanding of NAM sensitivity to past and future global climate change. Our work seeks to improve understanding of NAM dynamics using new proxy records and model simulations. We have developed quantitative reconstructions of NAM strength since the LGM ( 21 ka BP) using leaf wax biomarkers (e.g. dD of n-acids) from marine sediment cores in the Gulf of California. We contrast these proxy records with idealized GCM simulations (i.e. CESM1.2) to diagnose the mechanisms behind NAM responses to LGM boundary conditions and abrupt deglacial climate events. Our results suggest that ice-sheet induced changes in atmospheric circulation acted in concert with local changes in Gulf of California SSTs to modulate the late glacial NAM. This work has important implications for our understanding of NAM dynamics, its relationship with other monsoon systems, and its sensitivity to past and future global climate change.

Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan.

PubMed

Dixit, Prakash N; Telleria, Roberto; Al Khatib, Amal N; Allouzi, Siham F

2018-01-01

Different aspects of climate change, such as increased temperature, changed rainfall and higher atmospheric CO 2 concentration, all have different effects on crop yields. Process-based crop models are the most widely used tools for estimating future crop yield responses to climate change. We applied APSIM crop simulation model in a dry Mediterranean climate with Jordan as sentinel site to assess impact of climate change on wheat production at decadal level considering two climate change scenarios of representative concentration pathways (RCP) viz., RCP4.5 and RCP8.5. Impact of climatic variables alone was negative on grain yield but this adverse effect was negated when elevated atmospheric CO 2 concentrations were also considered in the simulations. Crop cycle of wheat was reduced by a fortnight for RCP4.5 scenario and by a month for RCP8.5 scenario at the approach of end of the century. On an average, a grain yield increase of 5 to 11% in near future i.e., 2010s-2030s decades, 12 to 16% in mid future i.e., 2040s-2060s decades and 9 to 16% in end of century period can be expected for moderate climate change scenario (RCP4.5) and 6 to 15% in near future, 13 to 19% in mid future and 7 to 20% increase in end of century period for a drastic climate change scenario (RCP8.5) based on different soils. Positive impact of elevated CO 2 is more pronounced in soils with lower water holding capacity with moderate increase in temperatures. Elevated CO 2 had greater positive effect on transpiration use efficiency (TUE) than negative effect of elevated mean temperatures. The change in TUE was in near perfect direct relationship with elevated CO 2 levels (R 2 >0.99) and every 100-ppm atmospheric CO 2 increase resulted in TUE increase by 2kgha -1 mm -1 . Thereby, in this environment yield gains are expected in future and farmers can benefit from growing wheat. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of Projected Agricultural Climate Risk over the Contiguous US

NASA Astrophysics Data System (ADS)

Zhu, X.; Troy, T. J.; Devineni, N.

2017-12-01

Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

PubMed

Kara, Fatih; Yucel, Ismail

2015-09-01

This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.

Assessing the Global Climate Response to Freshwater Forcing from the Antarctic Ice Sheet Under Future Climate Scenarios

NASA Astrophysics Data System (ADS)

Rogstad, S.; Condron, A.; DeConto, R.; Pollard, D.

2017-12-01

Observational evidence indicates that the West Antarctic Ice Sheet (WAIS) is losing mass at an accelerating rate. Impacts to global climate resulting from changing ocean circulation patterns due to increased freshwater runoff from Antarctica in the future could have significant implications for global heat transport, but to-date this topic has not been investigated using complex numerical models with realistic freshwater forcing. Here, we present results from a high resolution fully coupled ocean-atmosphere model (CESM 1.2) forced with runoff from Antarctica prescribed from a high resolution regional ice sheet-ice shelf model. Results from the regional simulations indicate a potential freshwater contribution from Antarctica of up to 1 m equivalent sea level rise by the end of the century under RCP 8.5 indicating that a substantial input of freshwater into the Southern Ocean is possible. Our high resolution global simulations were performed under IPCC future climate scenarios RCP 4.5 and 8.5. We will present results showing the impact of WAIS collapse on global ocean circulation, sea ice, air temperature, and salinity in order to assess the potential for abrupt climate change triggered by WAIS collapse.

Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

2018-07-01

In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010-2040, 2040-2070 and 2070-2100 with respect to the control period of 1970-2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070-2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain.

Evaluation of high-resolution climate simulations for West Africa using COSMO-CLM

NASA Astrophysics Data System (ADS)

Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Laux, Patrick; Heinzeller, Dominikus; Kunstmann, Harald; Sarr, Abdoulaye; Thierno Gaye, Amadou

2017-04-01

The climate change modeling activities within the WASCAL program (West African Science Service Center on Climate Change and Adapted Land Use) concentrate on the provisioning of future climate change scenario data at high spatial and temporal resolution and quality in West Africa. Such information is highly required for impact studies in water resources and agriculture for the development of reliable climate change adaptation and mitigation strategies. In this study, we present a detailed evaluation of high simulation runs based on the regional climate model, COSMO model in CLimate Mode (COSMO-CLM). The model is applied over West Africa in a nested approach with two simulation domains at 0.44° and 0.11° resolution using reanalysis data from ERA-Interim (1979-2013). The models runs are compared to several state-of-the-art observational references (e.g., CRU, CHIRPS) including daily precipitation data provided by national meteorological services in West Africa. Special attention is paid to the reproduction of the dynamics of the West African Monsoon (WMA), its associated precipitation patterns and crucial agro-climatological indices such as the onset of the rainy season. In addition, first outcomes of the regional climate change simulations driven by MPI-ESM-LR are presented for a historical period (1980 to 2010) and two future periods (2020 to 2050, 2070 to 2100). The evaluation of the reanalysis runs shows that COSMO-CLM is able to reproduce the observed major climate characteristics including the West African Monsoon within the range of comparable RCM evaluations studies. However, substantial uncertainties remain, especially in the Sahel zone. The added value of the higher resolution of the nested run is reflected in a smaller bias in extreme precipitation statistics with respect to the reference data.

Future integrated aquifer vulnerability assessment considering land use / land cover and climate change using DRASTIC and SWAT

NASA Astrophysics Data System (ADS)

Jang, W.; Engel, B.; Chaubey, I.

2015-12-01

Climate change causes significant changes to temperature regimes and precipitation patterns across the world. Such alterations in climate pose serious risks for not only inland freshwater ecosystems but also groundwater systems, and may adversely affect numerous critical services they provide to humans. All groundwater results from precipitation, and precipitation is affected by climate change. Climate change is also influenced by land use / land cover (LULC) change and vice versa. According to Intergovernmental Panel on Climate Change (IPCC) reports, climate change is caused by global warming which is generated by the increase of greenhouse gas (GHG) emissions in the atmosphere. LULC change is a major driving factor causing an increase in GHG emissions. LULC change data (years 2006-2100) will be produced by the Land Transformation Model (LTM) which simulates spatial patterns of LULC change over time. MIROC5 (years 2006-2100) will be obtained considering GCMs and ensemble characteristics such as resolution and trend of temperature and precipitation which is a consistency check with observed data from local weather stations and historical data from GCMs output data. Thus, MIROC5 will be used to account for future climate change scenarios and relationship between future climate change and alteration of groundwater quality in this study. For efficient groundwater resources management, integrated aquifer vulnerability assessments (= intrinsic vulnerability + hazard potential assessment) are required. DRASTIC will be used to evaluate intrinsic vulnerability, and aquifer hazard potential will be evaluated by Soil and Water Assessment Tool (SWAT) which can simulate pollution potential from surface and transport properties of contaminants. Thus, for effective integrated aquifer vulnerability assessment for LULC and climate change in the Midwestern United States, future projected LULC and climate data from the LTM and GCMs will be incorporated with DRASTIC and SWAT. It is hypothesized that: 1) long-term future hydrology and water quality in surface and subsurface drainage areas will be influenced by LULC and climate change, and 2) this approach will be useful to identify specific areas contributing the most pollutants to aquifers due to LULC and climate change.

The Geographic Climate Information System Project (GEOCLIMA): Overview and preliminary results

NASA Astrophysics Data System (ADS)

Feidas, H.; Zanis, P.; Melas, D.; Vaitis, M.; Anadranistakis, E.; Symeonidis, P.; Pantelopoulos, S.

2012-04-01

The project GEOCLIMA aims at developing an integrated Geographic Information System (GIS) allowing the user to manage, analyze and visualize the information which is directly or indirectly related to climate and its future projections in Greece. The main components of the project are: a) collection and homogenization of climate and environmental related information, b) estimation of future climate change based on existing regional climate model (RCM) simulations as well as a supplementary high resolution (10 km x 10 km) simulation over the period 1961-2100 using RegCM3, c) compilation of an integrated uniform geographic database, and d) mapping of climate data, creation of digital thematic maps, and development of the integrated web GIS application. This paper provides an overview of the ongoing research efforts and preliminary results of the project. First, the trends in the annual and seasonal time series of precipitation and air temperature observations for all available stations in Greece are assessed. Then the set-up of the high resolution RCM simulation (10 km x 10 km) is discussed with respect to the selected convective scheme. Finally, the relationship of climatic variables with geophysical features over Greece such as altitude, location, distance from the sea, slope, aspect, distance from climatic barriers, land cover etc) is investigated, to support climate mapping. The research has been co-financed by the European Union (European Regional Development Fund) and Greek national funds through the Operational Program "Competitiveness and Entrepreneurship" of the National Strategic Reference Framework (NSRF) - Research Funding Program COOPERATION 2009.

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

PubMed

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Patterns of crop cover under future climates.

PubMed

Porfirio, Luciana L; Newth, David; Harman, Ian N; Finnigan, John J; Cai, Yiyong

2017-04-01

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

CMIP5-based global wave climate projections including the entire Arctic Ocean

NASA Astrophysics Data System (ADS)

Casas-Prat, M.; Wang, X. L.; Swart, N.

2018-03-01

This study presents simulations of the global ocean wave climate corresponding to the surface winds and sea ice concentrations as simulated by five CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models for the historical (1979-2005) and RCP8.5 scenario future (2081-2100) periods. To tackle the numerical complexities associated with the inclusion of the North Pole, the WAVEWATCH III (WW3) wave model was used with a customized unstructured Spherical Multi-Cell grid of ∼100 km offshore and ∼50 km along coastlines. The climate model simulated wind and sea ice data, and the corresponding WW3 simulated wave data, were evaluated against reanalysis and hindcast data. The results show that all the five sets of wave simulations projected lower waves in the North Atlantic, corresponding to decreased surface wind speeds there in the warmer climate. The selected CMIP5 models also consistently projected an increase in the surface wind speed in the Southern Hemisphere (SH) mid-high latitudes, which translates in an increase in the WW3 simulated significant wave height (Hs) there. The higher waves are accompanied with increased peak wave period and increased wave age in the East Pacific and Indian Oceans, and a significant counterclockwise rotation in the mean wave direction in the Southern Oceans. The latter is caused by more intense waves from the SH traveling equatorward and developing into swells. Future wave climate in the Arctic Ocean in summer is projected to be predominantly of mixed sea states, with the climatological mean of September maximum Hs ranging mostly 3-4 m. The new waves approaching Arctic coasts will be less fetch-limited as ice retreats since a predominantly southwards mean wave direction is projected in the surrounding seas.

[Simulating climate change effect on aboveground carbon sequestration rates of main broadleaved trees in the Xiaoxing'an Mountains area, Northeast China].

PubMed

Ma, Jun; Bu, Rencang; Deng, Hua-Wei; Hu, Yuan-Man; Qin, Qin; Han, Feng-Lin

2014-09-01

LANDIS Pro 7.0 model was used to simulate the dynamics of aboveground biomass of ten broadleaved tree species in the Xiao Xing' an Mountains area under current and various climate change scenarios from 2000 to 2200, and carbon content coefficients (CCCs) were coupled to cal- culate the aboveground carbon sequestration rates (ACSRs) of these species. The results showed that in the initial year of simulation, the biomasses and their proportions of Fraxinus mandshurica, Phellodendron amurense, Quercus mongolica, Ulmus propinqua, and Acer mono were relatively low, while those of Betula costata, Betula platyphylla, and Populus davidiana were higher. A trend of rise after decline occurred in ACSR for pioneer species in the mid and late periods of simulation years, but ACSRs for the other broadleaved tree species were considerably complex. The ACSRs of Q. mongolica and Tilla amurensis fluctuated in the ranges of -0.05-0.25 t · hm(-2) · 10 a(-1) and 0.16-1.29 t · hm(-2) · 10 a(-1) in simulation years, respectively. The ACSRs of F. mandshurica, U. propinqua, A. mono, and B. costata showed a trend of decline after rise in late simulation years. There were significant differences in ACSR for P. amurense and B. davurica among various climate change scenarios in the periods of 2050-2100 and 2150-2200, while no significant difference in ACSR for the other species would be detected. Difference of sensitivity of various species in ACSR for future climate scenarios in the Small Khingan Mountains area existed. However, the un- certainty of future climates would not yield significant difference in ACSR for most broadleaved tree species. Moreover, a time lag would exist in the process of climate change effects on temperate forest's ACSR.

Widespread, Very Heavy Precipitation Events in Contemporary and Scenario Summer Climates from NARCCAP Simulations

NASA Astrophysics Data System (ADS)

Kawazoe, S.; Gutowski, W. J., Jr.

2015-12-01

We analyze the ability of regional climate models (RCMs) to simulate very heavy daily precipitation and supporting processes for both contemporary and future-scenario simulations during summer (JJA). RCM output comes from North American Regional Climate Change Assessment Program (NARCCAP) simulations, which are all run at a spatial resolution of 50 km. Analysis focuses on the upper Mississippi basin for summer, between 1982-1998 for the contemporary climate, and 2052-2068 during the scenario climate. We also compare simulated precipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. Precipitation observations are from the University of Washington (UW) and the Climate Prediction Center (CPC) gridded dataset. Utilizing two observational datasets helps determine if any uncertainties arise from differences in precipitation gridding schemes. Reanalysis fields come from the North American Regional Reanalysis. The NARCCAP models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, while producing overly strong precipitation at high intensity thresholds. In the future-scenario climate, there is a decrease in frequency for light to moderate precipitation intensities, while an increase in frequency is seen for the higher intensity events. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". For widespread events, we analyze local and large scale environmental parameters, such as 2-m temperature and specific humidity, 500-hPa geopotential heights, Convective Available Potential Energy (CAPE), vertically integrated moisture flux convergence, among others, to compare atmospheric states and processes leading to such events in the models and observations. The results suggest that an analysis of atmospheric states supporting very heavy precipitation events is a more fruitful path for understanding and detecting changes than simply looking at precipitation itself.

Potential Impacts of Future Warming and Land Use Changes on Intra-Urban Heat Exposure in Houston, Texas

PubMed Central

Conlon, Kathryn; Monaghan, Andrew; Hayden, Mary; Wilhelmi, Olga

2016-01-01

Extreme heat events in the United States are projected to become more frequent and intense as a result of climate change. We investigated the individual and combined effects of land use and warming on the spatial and temporal distribution of daily minimum temperature (Tmin) and daily maximum heat index (HImax) during summer in Houston, Texas. Present-day (2010) and near-future (2040) parcel-level land use scenarios were embedded within 1-km resolution land surface model (LSM) simulations. For each land use scenario, LSM simulations were conducted for climatic scenarios representative of both the present-day and near-future periods. LSM simulations assuming present-day climate but 2040 land use patterns led to spatially heterogeneous temperature changes characterized by warmer conditions over most areas, with summer average increases of up to 1.5°C (Tmin) and 7.3°C (HImax) in some newly developed suburban areas compared to simulations using 2010 land use patterns. LSM simulations assuming present-day land use but a 1°C temperature increase above the urban canopy (consistent with warming projections for 2040) yielded more spatially homogeneous metropolitan-wide average increases of about 1°C (Tmin) and 2.5°C (HImax), respectively. LSM simulations assuming both land use and warming for 2040 led to summer average increases of up to 2.5°C (Tmin) and 8.3°C (HImax), with the largest increases in areas projected to be converted to residential, industrial and mixed-use types. Our results suggest that urbanization and climate change may significantly increase the average number of summer days that exceed current threshold temperatures for initiating a heat advisory for metropolitan Houston, potentially increasing population exposure to extreme heat. PMID:26863298

Future land-use change emissions: CO2, BVOC and wildfire

NASA Astrophysics Data System (ADS)

Arneth, A.; Knorr, W.; Hantson, S.; Anthoni, P.; Szogs, S.

2015-12-01

Historical land-use (LUC) change is known to have been a large source of CO2 emissions, mostly from deforestation: the equivalent of around 1/3 of today's CO2 in the atmosphere arises from LUC. And LUC will continue into the future, although the expected area change, the type of LUC (deforestation vs. afforestation/reforestation) and regions where the LUC will take place will differ greatly, depending on the future scenario. But LUC is not only of importance for projecting emissions of CO2. It also affects greatly emissions of biogenic volatile organic carbon, and from wildfires - all of which are important for the quantification of precursor substances relevant to air quality, and interactions with climate change. We show here that accounting for future socio-economic developments and LUC scenarios has the potential to override climate change and effects of CO2 fertilisation on fire and BVOC emission, regionally and in some cases also globally. Simulation experiments with the dynamic global vegetation model LPJ-GUESS will be performed, covering the 20th and 21st century, and assessing a rage of future population growth, LUC and climate change scenarios. For wildfire emissions, we find that burned area and emissions depend greatly on the type of population growth scenario, and on the distribution of urban vs rural population. BVOC emissions depend greatly on the amount and location of deforestation vs the region and magnitude of forest expansion in response to warming, such as through expansion of vegetation in the northern hemisphere, and via reforestation/afforestation. LUC so far has not been given sufficient attention for simulations of future air quality-climate interactions. In terms of terrestrial precursor emissions of atmospherically reactive substances our simulations clearly demonstrate the importance of including LUC in combination with vegetation that responds dynamically to changes in climate and atmospheric CO2 levels.

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

NASA Astrophysics Data System (ADS)

Takhsha, Maryam; Nikiéma, Oumarou; Lucas-Picher, Philippe; Laprise, René; Hernández-Díaz, Leticia; Winger, Katja

2017-10-01

As part of the CORDEX project, the fifth-generation Canadian Regional Climate Model (CRCM5) is used over the Arctic for climate simulations driven by reanalyses and by the MPI-ESM-MR coupled global climate model (CGCM) under the RCP8.5 scenario. The CRCM5 shows adequate skills capturing general features of mean sea level pressure (MSLP) for all seasons. Evaluating 2-m temperature (T2m) and precipitation is more problematic, because of inconsistencies between observational reference datasets over the Arctic that suffer of a sparse distribution of weather stations. In our study, we additionally investigated the effect of large-scale spectral nudging (SN) on the hindcast simulation driven by reanalyses. The analysis shows that SN is effective in reducing the spring MSLP bias, but otherwise it has little impact. We have also conducted another experiment in which the CGCM-simulated sea-surface temperature (SST) is empirically corrected and used as lower boundary conditions over the ocean for an atmosphere-only global simulation (AGCM), which in turn provides the atmospheric lateral boundary conditions to drive the CRCM5 simulation. This approach, so-called 3-step approach of dynamical downscaling (CGCM-AGCM-RCM), which had considerably improved the CRCM5 historical simulations over Africa, exhibits reduced impact over the Arctic domain. The most notable positive effect over the Arctic is a reduction of the T2m bias over the North Pacific Ocean and the North Atlantic Ocean in all seasons. Future projections using this method are compared with the results obtained with the traditional 2-step dynamical downscaling (CGCM-RCM) to assess the impact of correcting systematic biases of SST upon future-climate projections. The future projections are mostly similar for the two methods, except for precipitation.

Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

NASA Astrophysics Data System (ADS)

Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

2015-01-01

In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30 day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

Sustainability of irrigated crops under future climate: the interplay of irrigation strategies and cultivar responses

NASA Astrophysics Data System (ADS)

De Lorenzi, F.; Bonfante, A.; Alfieri, S.; Patanè, C.; Basile, A.; Di Tommasi, P.; Monaco, E.; Menenti, M.

2012-04-01

Climate evolution will cause significant changes in the quality and availability of water resources, affecting many sectors including food production, where available water resources for irrigation play a crucial role. Strategies focused on managing and conserving water are one way to deal with the impact; moreover concurring adaptation measurements will be needed to cope with the foreseen decline of water resource. This work deals with i) the impacts of climate change on water requirements of an horticultural crop, determined in an irrigated district in Southern Italy, ii) the possible irrigation scheduling options and their sustainability in the future, iii) the adaptation measurements that can be undertaken to protect production, relying on intra-specific biodiversity of agricultural crops. Two climate scenarios were considered: present climate (1961-90) and future climate (2021-2050), the former from climatic statistics, and the latter from statistical downscaling of general circulation models (AOGCM). Climatic data set consists of daily time series of maximum and minimum temperature, and rainfall on a grid with spatial resolution of 35 km. The analysis of climate scenarios showed that significant increases in summer maximum daily temperature could be expected in 2021-2050 period. Soil water regime was determined by means of a mechanistic model (SWAP) of water flow in the soil-plant-atmosphere system. Twenty? soil units were identified in the district (in Sele Plain, Campania Region) and simulations were performed accounting for hydro-pedological properties of different soil units. Parameters of a generic tomato crop, in a rotation typical of the area, were used in simulations. Soil water balance was simulated in the present and future climate, both with optimal water availability and under constrains that irrigation schemes will pose. Indicators of soil water availability were calculated, in terms of soil water or evapotranspiration deficit. For several tomato cultivars, quantitative yield response functions to water availability were determined through the re-analysis of experimental data, derived from scientific literature. Variety-specific threshold values of yield reduction in dependence of soil water and evapotranspiration deficit were determined. The spatial pattern of soil water availability indicators was calculated., for present and future climate scenarios and for different irrigation scheduling options. Cultivars' threshold values were matched with indicators' values in all soil units. The future adaptability of the crop in the area is thus evaluated, and adaptation options that exploit the intra-specific biodiversity of the crop are indicated. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008) Keywords: climate change, tomato, deficit irrigation, biodiversity

The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

Direct and indirect effects of climate change on projected future fire regimes in the western United States.

PubMed

Liu, Zhihua; Wimberly, Michael C

2016-01-15

We asked two research questions: (1) What are the relative effects of climate change and climate-driven vegetation shifts on different components of future fire regimes? (2) How does incorporating climate-driven vegetation change into future fire regime projections alter the results compared to projections based only on direct climate effects? We used the western United States (US) as study area to answer these questions. Future (2071-2100) fire regimes were projected using statistical models to predict spatial patterns of occurrence, size and spread for large fires (>400 ha) and a simulation experiment was conducted to compare the direct climatic effects and the indirect effects of climate-driven vegetation change on fire regimes. Results showed that vegetation change amplified climate-driven increases in fire frequency and size and had a larger overall effect on future total burned area in the western US than direct climate effects. Vegetation shifts, which were highly sensitive to precipitation pattern changes, were also a strong determinant of the future spatial pattern of burn rates and had different effects on fire in currently forested and grass/shrub areas. Our results showed that climate-driven vegetation change can exert strong localized effects on fire occurrence and size, which in turn drive regional changes in fire regimes. The effects of vegetation change for projections of the geographic patterns of future fire regimes may be at least as important as the direct effects of climate change, emphasizing that accounting for changing vegetation patterns in models of future climate-fire relationships is necessary to provide accurate projections at continental to global scales. Copyright © 2015 Elsevier B.V. All rights reserved.

Nonlinear climate sensitivity and its implications for future greenhouse warming.

PubMed

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-11-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing-referred to as specific equilibrium climate sensitivity ( S )-is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth's future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.

Nonlinear climate sensitivity and its implications for future greenhouse warming

PubMed Central

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-01-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections. PMID:28861462

Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

EPA Pesticide Factsheets

Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).

Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.

Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

NASA Astrophysics Data System (ADS)

Nicholls, S.; Mohr, K. I.

2014-12-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

Changes in Benefits of Flood Protection Standard under Climate Change

NASA Astrophysics Data System (ADS)

Lim, W. H.; Koirala, S.; Yamazaki, D.; Hirabayashi, Y.; Kanae, S.

2014-12-01

Understanding potential risk of river flooding under future climate scenarios might be helpful for developing risk management strategies (including mitigation, adaptation). Such analyses are typically performed at the macro scales (e.g., regional, global) where the climate model output could support (e.g., Hirabayashi et al., 2013, Arnell and Gosling, 2014). To understand the potential benefits of infrastructure upgrading as part of climate adaptation strategies, it is also informative to understand the potential impact of different flood protection standards (in terms of return periods) on global river flooding under climate change. In this study, we use a baseline period (forced by observed hydroclimate conditions) and CMIP5 model output (historic and future periods) to drive a global river routing model called CaMa-Flood (Yamazaki et al., 2011) and simulate the river water depth at a spatial resolution of 15 min x 15 min. From the simulated results of baseline period, we use the annual maxima river water depth to fit the Gumbel distribution and prepare the return period-flood risk relationship (involving population and GDP). From the simulated results of CMIP5 model, we also used the annual maxima river water depth to obtain the Gumbel distribution and then estimate the exceedance probability (historic and future periods). We apply the return period-flood risk relationship (above) to the exceedance probability and evaluate the potential risk of river flooding and changes in the benefits of flood protection standard (e.g., 100-year flood of the baseline period) from the past into the future (represented by the representative concentration pathways). In this presentation, we show our preliminary results. References: Arnell, N.W, Gosling, S., N., 2014. The impact of climate change on river flood risk at the global scale. Climatic Change 122: 127-140, doi: 10.1007/s10584-014-1084-5. Hirabayashi et al., 2013. Global flood risk under climate change. Nature Climate Change 3: 816-821, doi: 10.1038/nclimate1911. Yamazaki et al., 2011. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resources Research 47, W04501, doi: 10.1029/2010wr009726.

Simulating post-wildfire forest trajectories under alternative climate and management scenarios.

PubMed

Tarancón, Alicia Azpeleta; Fulé, Peter Z; Shive, Kristen L; Sieg, Carolyn H; Meador, Andrew Sánchez; Strom, Barbara

Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned multispecies forest of Arizona, USA. The incorporation of seven combinations of General Circulation Models (GCM) and emissions scenarios altered long-term (100 years) predictions of future forest condition compared to a No Climate Change (NCC) scenario, which forecast a gradual increase to high levels of forest density and carbon stock. In contrast, emissions scenarios that included continued high greenhouse gas releases led to near-complete deforestation by 2111. GCM-emissions scenario combinations that were less severe reduced forest structure and carbon stock relative to NCC. Fuel reduction treatments that had been applied prior to the severe wildfire did have persistent effects, especially under NCC, but were overwhelmed by increasingly severe climate change. We tested six management strategies aimed at sustaining future forests: prescribed burning at 5, 10, or 20-year intervals, thinning 40% or 60% of stand basal area, and no treatment. Severe climate change led to deforestation under all management regimes, but important differences emerged under the moderate scenarios: treatments that included regular prescribed burning fostered low density, wildfire-resistant forests composed of the naturally dominant species, ponderosa pine. Non-fire treatments under moderate climate change were forecast to become dense and susceptible to severe wildfire, with a shift to dominance by sprouting species. Current U.S. forest management requires modeling of future scenarios but does not mandate consideration of climate change effects. However, this study showed substantial differences in model outputs depending on climate and management actions. Managers should incorporate climate change into the process of analyzing the environmental effects of alternative actions.

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

NASA Astrophysics Data System (ADS)

Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John

2015-10-01

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

Germination responses to current and future temperatures of four seeder shrubs across a latitudinal gradient in western Iberia.

PubMed

Chamorro, Daniel; Luna, Belén; Moreno, José M

2017-01-01

Species differ in their temperature germination niche. Populations of a species may similarly differ across the distribution range of the species. Anticipating the impacts of climate variability and change requires understanding the differential sensitivity to germination temperature among and within species. Here we studied the germination responses of four hard-seeded Cistaceae seeders to a range of current and future temperatures. Seeds were collected at sites across the Iberian Peninsula and exposed or not exposed to a heat shock to break dormancy, then set to germinate under four temperature regimes. Temperatures were varied daily and seasonally, simulating the temperature range across the gradient, plus an increased temperature simulating future climate. Time to germination onset and cumulative germination at the end of each season were analyzed for the effects of temperature treatments, seasons, and local climate (temperature of the germination period, T gp ) at each site. T gp was a significant covariate of germination in all species but Cistus populifolius. Temperature treatments significantly affected Cistus ladanifer, C. salviifolius, and Halimium ocymoides. Germination occurred in simulated autumn conditions, with little germination occurring at later seasons, except in unheated seeds of H. ocymoides. Exposure to a heat shock changed the sensitivity to temperature treatments and the relationships with T gp . Germination responses to temperature differ not only among species but also within species across their latitudinal range. The responses were idiosyncratic and related to the local climate of the population. This germination variability complicates generalizing the impacts of climate variability and climate change. © 2017 Botanical Society of America.

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Merging Methods to Manage Uncertainty: Combining Simulation Modeling and Scenario Planning to Inform Resource Management Under Climate Change

NASA Astrophysics Data System (ADS)

Miller, B. W.; Schuurman, G. W.; Symstad, A.; Fisichelli, N. A.; Frid, L.

2017-12-01

Managing natural resources in this era of anthropogenic climate change is fraught with uncertainties around how ecosystems will respond to management actions and a changing climate. Scenario planning (oftentimes implemented as a qualitative, participatory exercise for exploring multiple possible futures) is a valuable tool for addressing this challenge. However, this approach may face limits in resolving responses of complex systems to altered climate and management conditions, and may not provide the scientific credibility that managers often require to support actions that depart from current practice. Quantitative information on projected climate changes and ecological responses is rapidly growing and evolving, but this information is often not at a scale or in a form that is `actionable' for resource managers. We describe a project that sought to create usable information for resource managers in the northern Great Plains by combining qualitative and quantitative methods. In particular, researchers, resource managers, and climate adaptation specialists co-produced a simulation model in conjunction with scenario planning workshops to inform natural resource management in southwest South Dakota. Scenario planning for a wide range of resources facilitated open-minded thinking about a set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives that could be implemented in the simulation. With stakeholder input throughout the process, we built a simulation of key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between herd sizes and vegetation composition, and between the short- versus long-term costs of invasive species management. It also identified impactful uncertainties related to the effects of fire and grazing on vegetation. Ultimately, this integrative and iterative approach yielded counter-intuitive and surprising findings, and resulted in a more tractable set of possible futures for resource management planning.

Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C earth system model

NASA Astrophysics Data System (ADS)

Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.

2012-06-01

The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in scrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during winter and spring); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during summer), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during winter and spring) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.

Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model

NASA Astrophysics Data System (ADS)

Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.

2012-11-01

The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in shrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during December-January and March-May); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during June-August), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during December-February and March-May) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.

Ensemble of regional climate model projections for Ireland

NASA Astrophysics Data System (ADS)

Nolan, Paul; McGrath, Ray

2016-04-01

The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season of over 35 days per year. Results show significant projected decreases in mean annual, spring and summer precipitation amounts by mid-century. The projected decreases are largest for summer, with "likely" reductions ranging from 0% to 20%. The frequencies of heavy precipitation events show notable increases (approximately 20%) during the winter and autumn months. The number of extended dry periods is projected to increase substantially during autumn and summer. Regional variations of projected precipitation change remain statistically elusive. The energy content of the wind is projected to significantly decrease for the future spring, summer and autumn months. Projected increases for winter were found to be statistically insignificant. The projected decreases were largest for summer, with "likely" values ranging from 3% to 15%. Results suggest that the tracks of intense storms are projected to extend further south over Ireland relative to those in the reference simulation. As extreme storm events are rare, the storm-tracking research needs to be extended. Future work will focus on analysing a larger ensemble, thus allowing a robust statistical analysis of extreme storm track projections.

Use of NARCCAP Model Projections to Develop a Future Typical Meteorological Year and Estimate the Impact of a Changing Climate on Building Energy Consumption

NASA Astrophysics Data System (ADS)

Patton, S. L.; Takle, E. S.; Passe, U.; Kalvelage, K.

2013-12-01

Current simulations of building energy consumption use weather input files based on the past thirty years of climate observations. These 20th century climate conditions may be inadequate when designing buildings meant to function well into the 21st century. An alternative is using model projections of climate change to estimate future risk to the built environment. In this study, model-projected changes in climate were combined with existing typical meteorological year data to create future typical meteorological year data. These data were then formatted for use in EnergyPlus simulation software to evaluate their potential impact on commercial building energy consumption. The modeled climate data were taken from the North American Regional Climate Change Assessment Program (NARCCAP). NARCCAP uses results of global climate models to drive regional climate models, also known as dynamical downscaling. This downscaling gives higher resolution results over specific locations, and the multiple global/regional climate model combinations provide a unique opportunity to quantify the uncertainty of climate change projections and their impacts. Our results show a projected decrease in heating energy consumption and a projected increase in cooling energy consumption for nine locations across the United States for all model combinations. Warmer locations may expect a decrease in heating load of around 30% to 45% and an increase in cooling load of around 25% to 35%. Colder locations may expect a decrease in heating load of around 15% to 25% and an increase in cooling load of around 40% to 70%. The change in net energy consumption is determined by the balance between the magnitudes of heating change and cooling change. Net energy consumption is projected to increase by an average of 5% for lower-latitude locations and decrease by an average of 5% for higher-latitude locations. With these projected annual and seasonal changes presenting strong evidence for the unsuitable nature of current building practices holding up under future climate change, we recommend using our methods and results to make modifications and adaptations to existing buildings and to aid in the design of future buildings.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.

Impact of revised and potential future albedo estimates on CCSM3 simulations of growing-season surface temperature fields for North America

Treesearch

Warren E. Heilman; David Y. Hollinger; Xiuping Li; Xindi Bain; Shiyuan. Zhong

2010-01-01

Recently published albedo research has resulted in improved growing-season albedo estimates for forest and grassland vegetation. The impact of these improved estimates on the ability of climate models to simulate growing-season surface temperature patterns is unknown. We have developed a set of current-climate surface temperature scenarios for North America using the...

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Hydro-climatic simulation of Spring Creek Basin under dynamic C02 atmospheric concentration

USDA-ARS?s Scientific Manuscript database

Climate factors monitoring have indicated that global atmospheric C02 concentration rose in the past, and further rise should be expected in the future as indicated by projections. SWAT is a hydro-climatic distributed model used to assess the efficiency of agricultural and land use best management p...

Potential influence of wildfire in modulating climate-induced forest redistribution in a central Rocky Mountain landscape

USGS Publications Warehouse

Campbell, John L.; Shinneman, Douglas

2017-01-01

IntroductionClimate change is expected to impose significant tension on the geographic distribution of tree species. Yet, tree species range shifts may be delayed by their long life spans, capacity to withstand long periods of physiological stress, and dispersal limitations. Wildfire could theoretically break this biological inertia by killing forest canopies and facilitating species redistribution under changing climate. We investigated the capacity of wildfire to modulate climate-induced tree redistribution across a montane landscape in the central Rocky Mountains under three climate scenarios (contemporary and two warmer future climates) and three wildfire scenarios (representing historical, suppressed, and future fire regimes).MethodsDistributions of four common tree species were projected over 90 years by pairing a climate niche model with a forest landscape simulation model that simulates species dispersal, establishment, and mortality under alternative disturbance regimes and climate scenarios.ResultsThree species (Douglas-fir, lodgepole pine, subalpine fir) declined in abundance over time, due to climate-driven contraction in area suitable for establishment, while one species (ponderosa pine) was unable to exploit climate-driven expansion of area suitable for establishment. Increased fire frequency accelerated declines in area occupied by Douglas-fir, lodgepole pine, and subalpine fir, and it maintained local abundance but not range expansion of ponderosa pine.ConclusionsWildfire may play a larger role in eliminating these conifer species along trailing edges of their distributions than facilitating establishment along leading edges, in part due to dispersal limitations and interspecific competition, and future populations may increasingly depend on persistence in locations unfavorable for their establishment.

The Land Use Model Intercomparison Project (LUMIP) Contribution to CMIP6: Rationale and Experimental Design

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Hurtt, G. C.; Arneth, A.; Brovkin, V.; Calvin, K. V.; Jones, A. D.; Jones, C.; Lawrence, P.; De Noblet-Ducoudré, N.; Pongratz, J.; Seneviratne, S. I.; Shevliakova, E.

2016-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and (3) Are there regional land-management strategies with promise to help mitigate against climate change? LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. Foci will include separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that CO2 fertilization is modulated by past and future land use. LUMIP involves three sets of activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for LUMIP experiments, and (3) definition of metrics that quantify model performance with respect to LULCC. LUMIP experiments are designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate. LUMIP also includes simulations that allow quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. We will present the experimental protocol in detail, explain the rationale, outlines plans for analysis, and describe a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types).

Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers

USGS Publications Warehouse

Kurylyk, Barret L.; MacQuarrie, Kerry T.B; Voss, Clifford I.

2014-01-01

Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze-thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow-dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater-sourced thermal refugia may significantly increase under the most extreme climate scenarios.

Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database.

PubMed

Arnbjerg-Nielsen, K; Funder, S G; Madsen, H

2015-01-01

Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year return periods, respectively. The results should be interpreted with caution as the best region to represent future conditions for Denmark is the coastal areas of Northern France, for which only little information is available with respect to present precipitation extremes.

[Simulating the effects of climate change and fire disturbance on aboveground biomass of boreal forests in the Great Xing'an Mountains, Northeast China].

PubMed

Luo, Xu; Wang, Yu Li; Zhang, Jin Quan

2018-03-01

Predicting the effects of climate warming and fire disturbance on forest aboveground biomass is a central task of studies in terrestrial ecosystem carbon cycle. The alteration of temperature, precipitation, and disturbance regimes induced by climate warming will affect the carbon dynamics of forest ecosystem. Boreal forest is an important forest type in China, the responses of which to climate warming and fire disturbance are increasingly obvious. In this study, we used a forest landscape model LANDIS PRO to simulate the effects of climate change on aboveground biomass of boreal forests in the Great Xing'an Mountains, and compared direct effects of climate warming and the effects of climate warming-induced fires on forest aboveground biomass. The results showed that the aboveground biomass in this area increased under climate warming scenarios and fire disturbance scenarios with increased intensity. Under the current climate and fire regime scenario, the aboveground biomass in this area was (97.14±5.78) t·hm -2 , and the value would increase up to (97.93±5.83) t·hm -2 under the B1F2 scenario. Under the A2F3 scenario, aboveground biomass at landscape scale was relatively higher at the simulated periods of year 100-150 and year 150-200, and the value were (100.02±3.76) t·hm -2 and (110.56±4.08) t·hm -2 , respectively. Compared to the current fire regime scenario, the predicted biomass at landscape scale was increased by (0.56±1.45) t·hm -2 under the CF2 scenario (fire intensity increased by 30%) at some simulated periods, and the aboveground biomass was reduced by (7.39±1.79) t·hm -2 in CF3 scenario (fire intensity increased by 230%) at the entire simulation period. There were significantly different responses between coniferous and broadleaved species under future climate warming scenarios, in that the simulated biomass for both Larix gmelinii and Betula platyphylla showed decreasing trend with climate change, whereas the simulated biomass for Pinus sylvestris var. mongolica, Picea koraiensis and Populus davidiana showed increasing trend at different degrees during the entire simulation period. There was a time lag for the direct effect of climate warming on biomass for coniferous and broadleaved species. The response time of coniferous species to climate warming was 25-30 years, which was longer than that for broadleaf species. The forest landscape in the Great Xing'an Mountains was sensitive to the interactive effect of climate warming (high CO 2 emissions) and high intensity fire disturbance. Future climate warming and high intensity forest fire disturbance would significantly change the composition and structure of forest ecosystem.

Future nutrient load scenarios for the Baltic Sea due to climate and lifestyle changes.

PubMed

Hägg, Hanna Eriksson; Lyon, Steve W; Wällstedt, Teresia; Mörth, Carl-Magnus; Claremar, Björn; Humborg, Christoph

2014-04-01

Dynamic model simulations of the future climate and projections of future lifestyles within the Baltic Sea Drainage Basin (BSDB) were considered in this study to estimate potential trends in future nutrient loads to the Baltic Sea. Total nitrogen and total phosphorus loads were estimated using a simple proxy based only on human population (to account for nutrient sources) and stream discharges (to account for nutrient transport). This population-discharge proxy provided a good estimate for nutrient loads across the seven sub-basins of the BSDB considered. All climate scenarios considered here produced increased nutrient loads to the Baltic Sea over the next 100 years. There was variation between the climate scenarios such that sub-basin and regional differences were seen in future nutrient runoff depending on the climate model and scenario considered. Regardless, the results of this study indicate that changes in lifestyle brought about through shifts in consumption and population potentially overshadow the climate effects on future nutrient runoff for the entire BSDB. Regionally, however, lifestyle changes appear relatively more important in the southern regions of the BSDB while climatic changes appear more important in the northern regions with regards to future increases in nutrient loads. From a whole-ecosystem management perspective of the BSDB, this implies that implementation of improved and targeted management practices can still bring about improved conditions in the Baltic Sea in the face of a warmer and wetter future climate.

Changes in the shoreline at Paradip Port, India in response to climate change

NASA Astrophysics Data System (ADS)

Gopikrishna, B.; Deo, M. C.

2018-02-01

One of the popular methods to predict shoreline shifts into the future involves use of a shoreline evolution model driven by the historical wave climate. It is however understood by now that historical wave conditions might substantially change in future in response to climate change induced by the global warming. The future shoreline changes as well as sediment transport therefore need to be determined with the help of future projections of wave climate. In this work this is done at the port of Paradip situated along the east coast of India. The high resolution wind resulting from a climate modelling experiment called: CORDEX, South Asia, was used to simulate waves over two time-slices of 25 years each in past and future. The wave simulations were carried out with the help of a numerical wave model. Thereafter, rates of longshore sediment transport as well as shoreline shifts were determined over past and future using a numerical shoreline model. It was found that at Paradip Port the net littoral drift per metre width of cross-shore might go up by 37% and so also the net accumulated drift over the entire cross-shore width by 71%. This could be caused by an increase in the mean significant wave height of around 32% and also by changes in the frequency and direction of waves. The intensification of waves in turn might result from an increase in the mean wind speed of around 19%. Similarly, the horizontal extent of the beach accretion and erosion at the port's southern breakwater might go up by 4 m and 8 m, respectively, from the current level in another 25 years. This study should be useful in framing future port management strategies.

Climate Envelope Modeling and Dispersal Simulations Show Little Risk of Range Extension of the Shipworm, Teredo navalis (L.), in the Baltic Sea

PubMed Central

Appelqvist, Christin; Al-Hamdani, Zyad K.; Jonsson, Per R.; Havenhand, Jon N.

2015-01-01

The shipworm, Teredo navalis, is absent from most of the Baltic Sea. In the last 20 years, increased frequency of T. navalis has been reported along the southern Baltic Sea coasts of Denmark, Germany, and Sweden, indicating possible range-extensions into previously unoccupied areas. We evaluated the effects of historical and projected near-future changes in salinity, temperature, and oxygen on the risk of spread of T. navalis in the Baltic. Specifically, we developed a simple, GIS-based, mechanistic climate envelope model to predict the spatial distribution of favourable conditions for adult reproduction and larval metamorphosis of T. navalis, based on published environmental tolerances to these factors. In addition, we used a high-resolution three-dimensional hydrographic model to simulate the probability of spread of T. navalis larvae within the study area. Climate envelope modeling showed that projected near-future climate change is not likely to change the overall distribution of T. navalis in the region, but will prolong the breeding season and increase the risk of shipworm establishment at the margins of the current range. Dispersal simulations indicated that the majority of larvae were philopatric, but those that spread over a wider area typically spread to areas unfavourable for their survival. Overall, therefore, we found no substantive evidence for climate-change related shifts in the distribution of T. navalis in the Baltic Sea, and no evidence for increased risk of spread in the near-future. PMID:25768305

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

USGS Publications Warehouse

Graves, D.; Maule, A.

2014-01-01

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead (Oncorhynchus mykiss), a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Assessing Climate Vulnerability and Resilience of a Major Water Resource System - Inverting the Paradigm for Specific Risk Quantification at Decision Making Points of Impact

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.; Skindlov, J. A.

2015-12-01

Water resource systems have provided vital support to transformative growth in the Southwest United States and the Phoenix, Arizona metropolitan area where the Salt River Project (SRP) currently satisfies 40% of the area's water demand from reservoir storage and groundwater. Large natural variability and expectations of climate changes have sensitized water management to risks posed by future periods of excess and drought. The conventional approach to impacts assessment has been downscaled climate model simulations translated through hydrologic models; but, scenario ranges enlarge as uncertainties propagate through sequential levels of modeling complexity. The research often does not reach the stage of specific impact assessments, rendering future projections frustratingly uncertain and unsuitable for complex decision-making. Alternatively, this study inverts the common approach by beginning with the threatened water system and proceeding backwards to the uncertain climate future. The methodology is built upon reservoir system response modeling to exhaustive time series of climate-driven net basin supply. A reservoir operations model, developed with SRP guidance, assesses cumulative response to inflow variability and change. Complete statistical analyses of long-term historical watershed climate and runoff data are employed for 10,000-year stochastic simulations, rendering the entire range of multi-year extremes with full probabilistic characterization. Sets of climate change projections are then translated by temperature sensitivity and precipitation elasticity into future inflow distributions that are comparatively assessed with the reservoir operations model. This approach provides specific risk assessments in pragmatic terms familiar to decision makers, interpretable within the context of long-range planning and revealing a clearer meaning of climate change projections for the region. As a transferable example achieving actionable findings, the approach can guide other communities confronting water resource planning challenges.

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Assessing climate-change risks to cultural and natural resources in the Yakima River Basin, Washington, USA

USGS Publications Warehouse

Hatten, James R.; Waste, Stephen M.; Maule, Alec G.

2014-01-01

We provide an overview of an interdisciplinary special issue that examines the influence of climate change on people and fish in the Yakima River Basin, USA. Jenni et al. (2013) addresses stakeholder-relevant climate change issues, such as water availability and uncertainty, with decision analysis tools. Montag et al. (2014) explores Yakama Tribal cultural values and well-being and their incorporation into the decision-making process. Graves and Maule (2012) simulates effects of climate change on stream temperatures under baseline conditions (1981–2005) and two future climate scenarios (increased air temperature of 1 °C and 2 °C). Hardiman and Mesa (2013) looks at the effects of increased stream temperatures on juvenile steelhead growth with a bioenergetics model. Finally, Hatten et al. (2013) examines how changes in stream flow will affect salmonids with a rule-based fish habitat model. Our simulations indicate that future summer will be a very challenging season for salmonids when low flows and high water temperatures can restrict movement, inhibit or alter growth, and decrease habitat. While some of our simulations indicate salmonids may benefit from warmer water temperatures and increased winter flows, the majority of simulations produced less habitat. The floodplain and tributary habitats we sampled are representative of the larger landscape, so it is likely that climate change will reduce salmonid habitat potential throughout particular areas of the basin. Management strategies are needed to minimize potential salmonid habitat bottlenecks that may result from climate change, such as keeping streams cool through riparian protection, stream restoration, and the reduction of water diversions. An investment in decision analysis and support technologies can help managers understand tradeoffs under different climate scenarios and possibly improve water and fish conservation over the next century.

An Analysis of the Potential Impact of Climate Change on Dengue Transmission in the Southeastern United States.

PubMed

Butterworth, Melinda K; Morin, Cory W; Comrie, Andrew C

2017-04-01

Dengue fever, caused by a mosquito-transmitted virus, is an increasing health concern in the Americas. Meteorological variables such as temperature and precipitation can affect disease distribution and abundance through biophysical impacts on the vector and on the virus. Such tightly coupled links may facilitate further spread of dengue fever under a changing climate. In the southeastern United States, the dengue vector is widely established and exists on the current fringe of dengue transmission. We assessed projected climate change-driven shifts in dengue transmission risk in this region. We used a dynamic mosquito population and virus transmission model driven by meteorological data to simulate Aedes aegypti populations and dengue cases in 23 locations in the southeastern United States under current climate conditions and future climate projections. We compared estimates for each location with simulations based on observed data from San Juan, Puerto Rico, where dengue is endemic. Our simulations based on current climate data suggest that dengue transmission at levels similar to those in San Juan is possible at several U.S. locations during the summer months, particularly in southern Florida and Texas. Simulations that include climate change projections suggest that conditions may become suitable for virus transmission in a larger number of locations and for a longer period of time during each year. However, in contrast with San Juan, U.S. locations would not sustain year-round dengue transmission according to our model. Our findings suggest that Dengue virus (DENV) transmission is limited by low winter temperatures in the mainland United States, which are likely to prevent its permanent establishment. Although future climate conditions may increase the length of the mosquito season in many locations, projected increases in dengue transmission are limited to the southernmost locations.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

The evaluation of the climate change effects on maize and fennel cultivation by means of an hydrological physically based model: the case study of an irrigated district of southern Italy

NASA Astrophysics Data System (ADS)

Bonfante, A.; Alfieri, M. S.; Basile, A.; De Lorenzi, F.; Fiorentino, N.; Menenti, M.

2012-04-01

The effect of climate change on irrigated agricultural systems will be different from area to area depending on some factors as: (i) water availability, (ii) crop water demand (iii) soil hydrological behavior and (iv) irrigation management strategy. The adaptation of irrigated crop systems to future climate change can be supported by physically based model which simulate the water and heat fluxes in the soil-vegetation-atmosphere system. The aim of this work is to evaluate the effects of climate change on the heat and water balance of a maize-fennel rotation. This was applied to a on-demand irrigation district of Southern Italy ("Destra Sele", Campania Region, 22.645 ha). Two climate scenarios were considered, current climate (1961-1990) and future climate (2021-2050), the latter constructed by applying statistical downscaling to GCMs scenarios. For each climate scenario the soil moisture regime of the selected study area was calculated by means of a simulation model of the soil-water-atmosphere system (SWAP). Synthetic indicators of the soil water regimes (e.g., crop water stress index - CWSI, available water content) have been calculated and impacts evaluated taking into account the yield response functions to water availability of different cultivars. Different irrigation delivering strategies were also simulated. The hydrological model SWAP was applied to the representative soils of the whole area (20 soil units) for which the soil hydraulic properties were derived by means of pedo-transfer function (HYPRES) tested and validated on the typical soils in the study area. Upper boundary conditions were derived from two climate scenarios, i.e. current and future. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were derived from field experiments, in the same area, where the SWAP model was calibrated and validated. The results obtained have shown a significant increase of CWSI in the future climate scenario, and some spatial patterns strongly influenced by the soils characteristics. Adaptability of different maize cultivars has been evaluated. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008) Keywords: Plant Adaptative capacity, SWAP, Climate changes, Maize, Fennel

A framework for evaluating statistical downscaling performance under changing climatic conditions (Invited)

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Balaji, V.; Lanzante, J.; Radhakrishnan, A.; Hayhoe, K.; Stoner, A. K.; Gaitan, C. F.

2013-12-01

Statistical downscaling (SD) methods may be viewed as generating a value-added product - a refinement of global climate model (GCM) output designed to add finer scale detail and to address GCM shortcomings via a process that gleans information from a combination of observations and GCM-simulated climate change responses. Making use of observational data sets and GCM simulations representing the same historical period, cross-validation techniques allow one to assess how well an SD method meets this goal. However, lacking observations of future, the extent to which a particular SD method's skill might degrade when applied to future climate projections cannot be assessed in the same manner. Here we illustrate and describe extensions to a 'perfect model' experimental design that seeks to quantify aspects of SD method performance both for a historical period (1979-2008) and for late 21st century climate projections. Examples highlighting cases in which downscaling performance deteriorates in future climate projections will be discussed. Also, results will be presented showing how synthetic datasets having known statistical properties may be used to further isolate factors responsible for degradations in SD method skill under changing climatic conditions. We will describe a set of input files used to conduct these analyses that are being made available to researchers who wish to utilize this experimental framework to evaluate SD methods they have developed. The gridded data sets cover a region centered on the contiguous 48 United States with a grid spacing of approximately 25km, have daily time resolution (e.g., maximum and minimum near-surface temperature and precipitation), and represent a total of 120 years of model simulations. This effort is consistent with the 2013 National Climate Predictions and Projections Platform Quantitative Evaluation of Downscaling Workshop goal of supporting a community approach to promote the informed use of downscaled climate projections.

Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions - A case study in an intensively-used Mediterranean catchment.

PubMed

Herrmann, Frank; Baghdadi, Nicolas; Blaschek, Michael; Deidda, Roberto; Duttmann, Rainer; La Jeunesse, Isabelle; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2016-02-01

We used observed climate data, an ensemble of four GCM-RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM-RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived. Copyright © 2015 Elsevier B.V. All rights reserved.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

A new framework for quantifying uncertainties in modelling studies for future climates - how more certain are CMIP5 precipitation and temperature simulations compared to CMIP3?

NASA Astrophysics Data System (ADS)

Sharma, A.; Woldemeskel, F. M.; Sivakumar, B.; Mehrotra, R.

2014-12-01

We outline a new framework for assessing uncertainties in model simulations, be they hydro-ecological simulations for known scenarios, or climate simulations for assumed scenarios representing the future. This framework is illustrated here using GCM projections for future climates for hydrologically relevant variables (precipitation and temperature), with the uncertainty segregated into three dominant components - model uncertainty, scenario uncertainty (representing greenhouse gas emission scenarios), and ensemble uncertainty (representing uncertain initial conditions and states). A novel uncertainty metric, the Square Root Error Variance (SREV), is used to quantify the uncertainties involved. The SREV requires: (1) Interpolating raw and corrected GCM outputs to a common grid; (2) Converting these to percentiles; (3) Estimating SREV for model, scenario, initial condition and total uncertainty at each percentile; and (4) Transforming SREV to a time series. The outcome is a spatially varying series of SREVs associated with each model that can be used to assess how uncertain the system is at each simulated point or time. This framework, while illustrated in a climate change context, is completely applicable for assessment of uncertainties any modelling framework may be subject to. The proposed method is applied to monthly precipitation and temperature from 6 CMIP3 and 13 CMIP5 GCMs across the world. For CMIP3, B1, A1B and A2 scenarios whereas for CMIP5, RCP2.6, RCP4.5 and RCP8.5 representing low, medium and high emissions are considered. For both CMIP3 and CMIP5, model structure is the largest source of uncertainty, which reduces significantly after correcting for biases. Scenario uncertainly increases, especially for temperature, in future due to divergence of the three emission scenarios analysed. While CMIP5 precipitation simulations exhibit a small reduction in total uncertainty over CMIP3, there is almost no reduction observed for temperature projections. Estimation of uncertainty in both space and time sheds lights on the spatial and temporal patterns of uncertainties in GCM outputs, providing an effective platform for risk-based assessments of any alternate plans or decisions that may be formulated using GCM simulations.

Particulate matter air pollution in Europe in a +2 °C warming world

NASA Astrophysics Data System (ADS)

Lacressonnière, Gwendoline; Watson, Laura; Gauss, Michael; Engardt, Magnuz; Andersson, Camilla; Beekmann, Matthias; Colette, Augustin; Foret, Gilles; Josse, Béatrice; Marécal, Virginie; Nyiri, Agnes; Siour, Guillaume; Sobolowski, Stefan; Vautard, Robert

2017-04-01

In the framework of the IMPACT2C project, we have evaluated the future European particulate matter concentrations under the influence of climate change and anthropogenic emission reductions. To do so, 30-year simulations for present and future scenarios were performed with an ensemble of four regional Chemical Transport Models. +2 °C scenarios were issued from different regional climate simulations belonging to the CORDEX experiment (RCP4.5 scenario). Comparing present day simulations to observations shows that these simulations meet the requested quality criteria even if some biases do exist. Also, we showed that using regional climate models instead of meteorological reanalysis was not critical for the quality of our simulations. Present day as well as future scenarios show the large variability between models associated with different meteorology and process parameterizations. Future projections of PM concentrations show a large reduction of PM10 and PM2.5 concentrations in a +2 °C climate over the European continent (especially over Benelux), which can be mostly attributed to emission reduction policies. Under a current legislation scenario, annual PM10 could be reduced by between 1.8 and 2.9 μg m-3 (14.1-20.4%). If maximum technologically feasible emission reductions were implemented, further reductions of 1.4-1.9 μg m-3 (18.6-20.9%) are highlighted. Changes due to a +2 °C warming, in isolation from emission changes, are in general much weaker (-1.1 to +0.4 μg m-3,-0.3 to +5.1% for annual PM10 averaged over the European domain). Even if large differences exist between models, we have determined that the decrease of PM over Europe associated with emission reduction is a robust result. The patterns of PM changes resulting from climate change (for example the increase of PM over Spain and southern France and the decrease of PM10 over eastern Europe) are also robustly predicted even if its amplitude remains weak compared to changes associated with emission reductions.

Future Changes in Cyclonic Wave Climate in the North Atlantic, with a Focus on the French West Indies

NASA Astrophysics Data System (ADS)

Belmadani, A.; Palany, P.; Dalphinet, A.; Pilon, R.; Chauvin, F.

2017-12-01

Tropical cyclones (TCs) are a major environmental hazard in numerous small islands such as the French West Indies (Guadeloupe, Martinique, St-Martin, St-Barthélémy). The intense associated winds, which can reach 300 km/h or more, can cause serious damage in the islands and their coastlines. In particular, the combined action of waves, currents and low atmospheric pressure leads to severe storm surge and coastal flooding. Here we report on future changes in cyclonic wave climate for the North Atlantic basin, as a preliminary step for downscaled projections over the French West Indies at sub-kilometer-scale resolution. A new configuration of the Météo-France ARPEGE atmospheric general circulation model on a stretched grid with increased resolution in the tropical North Atlantic ( 15 km) is able to reproduce the observed distribution of maximum surface winds, including extreme events corresponding to Category 5 hurricanes. Ensemble historical simulations (1985-2014, 5 members) and future projections with the IPCC (Intergovernmental Panel on Climate Change) RCP8.5 scenario (2051-2080, 5 members) are used to drive the MFWAM (Météo-France Wave Action Model) over the North Atlantic basin. A lower 50-km resolution grid is used to propagate distant mid-latitude swells into a higher 10-km resolution grid over the cyclonic basin. Wave model performance is evaluated over a few TC case studies including the Sep-Oct 2016 Category 5 Hurricane Matthew, using an operational version of ARPEGE at similar resolution to force MFWAM together with wave buoy data. The latter are also used to compute multi-year wave statistics, which then allow assessing the realism of the MFWAM historical runs. For each climate scenario and ensemble member, a simulation of the cyclonic season (July to mid-November) is performed every year. The simulated sea states over the North Atlantic cyclonic basin over 150 historical simulations are compared to their counterparts over 150 future simulations. Changes in cyclonic wave climate are discussed in the light of concurrent changes in TC activity, inferred from objective tracking of individual TCs.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

NASA Astrophysics Data System (ADS)

Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

2017-02-01

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs

NASA Astrophysics Data System (ADS)

Reshmidevi, T. V.; Nagesh Kumar, D.; Mehrotra, R.; Sharma, A.

2018-01-01

This work evaluates the impact of climate change on the water balance of a catchment in India. Rainfall and hydro-meteorological variables for current (20C3M scenario, 1981-2000) and two future time periods: mid of the 21st century (2046-2065) and end of the century (2081-2100) are simulated using Modified Markov Model-Kernel Density Estimation (MMM-KDE) and k-nearest neighbor downscaling models. Climate projections from an ensemble of 5 GCMs (MPI-ECHAM5, BCCR-BCM2.0, CSIRO-mk3.5, IPSL-CM4, and MRI-CGCM2) are used in this study. Hydrologic simulations for the current as well as future climate scenarios are carried out using Soil and Water Assessment Tool (SWAT) integrated with ArcGIS (ArcSWAT v.2009). The results show marginal reduction in runoff ratio, annual streamflow and groundwater recharge towards the end of the century. Increased temperature and evapotranspiration project an increase in the irrigation demand towards the end of the century. Rainfall projections for the future shows marginal increase in the annual average rainfall. Short and moderate wet spells are projected to decrease, whereas short and moderate dry spells are projected to increase in the future. Projected reduction in streamflow and groundwater recharge along with the increase in irrigation demand is likely to aggravate the water stress in the region under the future scenario.

Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

NASA Astrophysics Data System (ADS)

Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

2017-12-01

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2012-12-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of transient daily river flow and monthly groundwater levels projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b.

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2013-03-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

Climate Simulations of Past, Present and Future

NASA Technical Reports Server (NTRS)

Hansen, James E.

1999-01-01

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Climate Modeling and Causal Identification for Sea Ice Predictability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

The effects of climate change on storm surges around the United Kingdom.

PubMed

Lowe, J A; Gregory, J M

2005-06-15

Coastal flooding is often caused by extreme events, such as storm surges. In this study, improved physical models have been used to simulate the climate system and storm surges, and to predict the effect of increased atmospheric concentrations of greenhouse gases on the surges. In agreement with previous studies, this work indicates that the changes in atmospheric storminess and the higher time-average sea-level predicted for the end of the twenty-first century will lead to changes in the height of water levels measured relative to the present day tide. However, the details of these projections differ somewhat from earlier assessments. Uncertainty in projections of future extreme water levels arise from uncertainty in the amount and timing of future greenhouse gas emissions, uncertainty in the physical models used to simulate the climate system and from the natural variability of the system. The total uncertainty has not yet been reliably quantified and achieving this should be a priority for future research.

Major collapse of the South Pacific Convergence Zone in the future and its consequences on tropical cyclones.

NASA Astrophysics Data System (ADS)

Menkes, C.; Dutheil, C.; Bador, M.; Lengaigne, M.; Lefèvre, J.; Jourdain, N.; Jullien, S.; Vialard, J.; Peltier, A.

2017-12-01

The South Pacific convergence zone (SPCZ) is poorly represented in global climate models, with trademark biases such as the "double ITCZ" or related cold tongue biases. Such biases decrease our confidence in climate change projections for this region. We first show that WRF atmospheric simulations using a 1°x1° regional configuration capture the SPCZ mean state and interannual variability well over the 1980-2016 period. We then perform climate change experiments by adding the RCP8.5, 2080-2100 CMIP5 multi-model mean boundary anomalies to the present conditions. We find a 4° equatorward shift of the SPCZ west of 170°W, and associated 40% rainfall reduction in the southwestern Pacific. These results strongly contrast with previous studies based on CMIP5 simulations that suggest a much weaker southwestern Pacific drying ( 7%). Regional sensitivity experiments show that this CMIP5 weak response can be tracked to climatological CMIP5 SST biases, which weaken the humidity transport reduction in the south Pacific in the future and result in an underestimated projected drying of the southwest Pacific. Our experiments also point toward a large increase in the future SPCZ variability with increased frequency of zonal SPCZ events. Next we explore the fate of tropical cyclones by downscaling the previous models to 20 km. The seasonal and spatial distribution of TC genesis and occurrence are in good agreement with the observations albeit with weaker than observed annual numbers. Our reference simulation is able to simulate intense category 4 and 5 TCs. In the future climate, we show a drastic decrease in the number of TCs ( 75%), and the disappearance of the most intense (Cat 4-5) cyclones. Additional regional simulations using a completely different set of physical parameterizations yield very similar results for the SPCZ collapse, including the strong decrease of TC numbers ( 63%), underlining the robustness of our results.

Quantifying the consequences of changing hydroclimatic extremes on protection levels for the Rhine

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; Hegnauer, Mark; Buiteveld, Hendrik; Lammersen, Rita; van den Boogaard, Henk; Beersma, Jules

2017-04-01

The Dutch method for quantifying the magnitude and frequency of occurrence of discharge extremes in the Rhine basin and the potential influence of climate change hereon are presented. In the Netherlands flood protection design requires estimates of discharge extremes for return periods of 1000 up to 100,000 years. Observed discharge records are too short to derive such extreme return discharges, therefore extreme value assessment is based on very long synthetic discharge time-series generated with the Generator of Rainfall And Discharge Extremes (GRADE). The GRADE instrument consists of (1) a stochastic weather generator based on time series resampling of historical f rainfall and temperature and (2) a hydrological model optimized following the GLUE methodology and (3) a hydrodynamic model to simulate the propagation of flood waves based on the generated hydrological time-series. To assess the potential influence of climate change, the four KNMI'14 climate scenarios are applied. These four scenarios represent a large part of the uncertainty provided by the GCMs used for the IPCC 5th assessment report (the CMIP5 GCM simulations under different climate forcings) and are for this purpose tailored to the Rhine and Meuse river basins. To derive the probability distributions of extreme discharges under climate change the historical synthetic rainfall and temperature series simulated with the weather generator are transformed to the future following the KNMI'14 scenarios. For this transformation the Advanced Delta Change method, which allows that the changes in the extremes differ from those in the means, is used. Subsequently the hydrological model is forced with the historical and future (i.e. transformed) synthetic time-series after which the propagation of the flood waves is simulated with the hydrodynamic model to obtain the extreme discharge statistics both for current and future climate conditions. The study shows that both for 2050 and 2085 increases in discharge extremes for the river Rhine at Lobith are projected by all four KNMI'14 climate scenarios. This poses increased requirements for flood protection design in order to prepare for changing climate conditions.

Making decisions based on an imperfect ensemble of climate simulators: strategies and future directions

NASA Astrophysics Data System (ADS)

Sanderson, B. M.

2017-12-01

The CMIP ensembles represent the most comprehensive source of information available to decision-makers for climate adaptation, yet it is clear that there are fundamental limitations in our ability to treat the ensemble as an unbiased sample of possible future climate trajectories. There is considerable evidence that models are not independent, and increasing complexity and resolution combined with computational constraints prevent a thorough exploration of parametric uncertainty or internal variability. Although more data than ever is available for calibration, the optimization of each model is influenced by institutional priorities, historical precedent and available resources. The resulting ensemble thus represents a miscellany of climate simulators which defy traditional statistical interpretation. Models are in some cases interdependent, but are sufficiently complex that the degree of interdependency is conditional on the application. Configurations have been updated using available observations to some degree, but not in a consistent or easily identifiable fashion. This means that the ensemble cannot be viewed as a true posterior distribution updated by available data, but nor can observational data alone be used to assess individual model likelihood. We assess recent literature for combining projections from an imperfect ensemble of climate simulators. Beginning with our published methodology for addressing model interdependency and skill in the weighting scheme for the 4th US National Climate Assessment, we consider strategies for incorporating process-based constraints on future response, perturbed parameter experiments and multi-model output into an integrated framework. We focus on a number of guiding questions: Is the traditional framework of confidence in projections inferred from model agreement leading to biased or misleading conclusions? Can the benefits of upweighting skillful models be reconciled with the increased risk of truth lying outside the weighted ensemble distribution? If CMIP is an ensemble of partially informed best-guesses, can we infer anything about the parent distribution of all possible models of the climate system (and if not, are we implicitly under-representing the risk of a climate catastrophe outside of the envelope of CMIP simulations)?

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

USGS Publications Warehouse

Swain, Eric; Stefanova, Lydia; Smith, Thomas

2014-01-01

Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

Assessing the impacts of climate change on future water resources: a methodological approach based on equiratio CDF-matching and vine copula

NASA Astrophysics Data System (ADS)

Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

2016-04-01

In this study, the impacts of climate change on future river discharge are evaluated using equiratio CDF-matching and a stochastic copula-based evapotranspiration generator. In recent years, much effort has been dedicated to improve the performances of RCMs outputs, i.e. the downscaled precipitation and temperature, to use in regional studies. However, these outputs usually suffer from bias due to the fact that many important small-scale processes, e.g. the representations of clouds and convection, are not represented explicitly within the models. To solve this problem, several bias correction techniques are developed. In this study, an advanced quantile bias approach called equiratio cumulative distribution function matching (EQCDF) is applied for the outputs from three RCMs for central Belgium, i.e. daily precipitation, temperature and evapotranspiration, for the current (1961-1990) and future climate (2071-2100). The rescaled precipitation and temperature are then used to simulate evapotranspiration via a stochastic copula-based model in which the statistical dependence between evapotranspiration, temperature and precipitation is described by a three-dimensional vine copula. The simulated precipitation and stochastic evapotranspiration are then used to model discharge under present and future climate. To validate, the observations of daily precipitation, temperature and evapotranspiration during 1961 - 1990 in Uccle, Belgium are used. It is found that under current climate, the basic properties of discharge, e.g. mean and frequency distribution, are well modelled; however there is an overestimation of the extreme discharges with return periods higher than 10 years. For the future climate change, compared with historical events, a considerable increase of the discharge magnitude and the number of extreme events is estimated for the studied area in the time period of 2071-2100.

On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

NASA Astrophysics Data System (ADS)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.

Warmer and drier conditions and nitrogen fertilizer application altered methanotroph abundance and methane emissions in a vegetable soil.

PubMed

Ran, Yu; Xie, Jianli; Xu, Xiaoya; Li, Yong; Liu, Yapeng; Zhang, Qichun; Li, Zheng; Xu, Jianming; Di, Hongjie

2017-01-01

Methane (CH 4 ) is a potent greenhouse gas, and soil can both be a source and sink for atmospheric CH 4 . It is not clear how future climate change may affect soil CH 4 emissions and related microbial communities. The aim of this study was to determine the interactive effects of a simulated warmer and drier climate scenarios and the application of different nitrogen (N) sources (urea and manure) on CH 4 emissions and related microbial community abundance in a vegetable soil. Greenhouses were used to control simulated climate conditions which gave 2.99 °C warmer and 6.2% lower water content conditions. The field experiment was divided into two phases. At the beginning of phase II, half of the greenhouses were removed to study possible legacy effects of the simulated warmer and drier conditions. The responses in methanogen and methanotroph abundance to a simulated climate change scenario were determined using real-time PCR. The results showed that the simulated warmer and drier conditions in the greenhouses significantly decreased CH 4 emissions largely due to the lower soil moisture content. For the same reason, CH 4 emissions of treatments in phase I were much lower than the same treatments in phase II. The abundance of methanotrophs showed a more significant response than methanogens to the simulated climate change scenario, increasing under simulated drier conditions. Methanogenic community abundance remained low, except where manure was applied which provided a source of organic C that stimulated methanogen growth. Soil moisture content was a major driver for methanotroph abundance and strongly affected CH 4 emissions. The application of N source decreased CH 4 emissions probably because of increased methanotrophic activity. CH 4 emissions were positively correlated to methanogenic abundance and negatively correlated to methanotrophic abundance. These results demonstrate that projected future climate change conditions can have a feedback impact on CH 4 emissions from the soil by altering soil conditions (particularly soil moisture) and related microbial communities.

a New Framework for Characterising Simulated Droughts for Future Climates

NASA Astrophysics Data System (ADS)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross-Dependence across Multiple Time Scales: Implications for Downscaling, Journal of Climate, 29(10), 3519-3539. Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 50, 650-660, doi:10.1002/2013WR013845.

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Climate and human intervention effects on future fire activity and consequences for air pollution across the 21st century

NASA Astrophysics Data System (ADS)

Val Martin, M.; Pierce, J. R.; Heald, C. L.; Li, F.; Lawrence, D. M.; Wiedinmyer, C.; Tilmes, S.; Vitt, F.

2016-12-01

Emissions of aerosols and gases from fires have been shown to adversely affect air quality across the world. Fire activity is strongly related to climate and anthropogenic activities. Current fire projections for the 21st century seem very uncertain, ranging from increasing to declining depending on the climate, land cover change and population growth scenarios used. Here we present an analysis of the changes in future wildfire activity and consequences on air quality, with focus on PM2.5 and surface O3 over regions vulnerable to fire. We use the global Community Earth System Model (CESM) with a process-based fire model to simulate emissions from agriculture, peatland, deforestation and landscape fires for present-day and throughout the current century. We consider two future Representative Concentration Pathways climate scenarios combined with population density changes predicted from Shared Socio-economic Pathways to project climate and demographic effects on fire activity and further consequences for future air quality.

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

2016-10-01

We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Evolution of precipitation extremes in two large ensembles of climate simulations

NASA Astrophysics Data System (ADS)

Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

2017-04-01

Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

Future impacts of global warming and reforestation on drought patterns over West Africa

NASA Astrophysics Data System (ADS)

Diasso, Ulrich; Abiodun, Babatunde J.

2017-07-01

This study investigates how a large-scale reforestation in Savanna (8-12°N, 20°W-20°E) could affect drought patterns over West Africa in the future (2031-2060) under the RCP4.5 scenario. Simulations from two regional climate models (RegCM4 and WRF) were analyzed for the study. The study first evaluated the performance of both RCMs in simulating the present-day climate and then applied the models to investigate the future impacts of global warming and reforestation on the drought patterns. The simulated and observed droughts were characterized with the Standardized Precipitation and Evapotranspiration Index (SPEI), and the drought patterns were classified using a Self-organizing Map (SOM) technique. The models capture essential features in the seasonal rainfall and temperature fields (including the Saharan Heat Low), but struggle to reproduce the onset and retreat of the West African Monsoon as observed. Both RCMs project a warmer climate (about 1-2 °C) over West Africa in the future. They do not reach a consensus on future change in rainfall, but they agree on a future increase in frequency of severe droughts (by about 2 to 9 events per decade) over the region. They show that reforestation over the Savanna could reduce the future warming by 0.1 to 0.8 °C and increase the precipitation by 0.8 to 1.2 mm per day. However, the impact of reforestation on the frequency of severe droughts is twofold. While reforestation decreases the droughts frequency (by about 1-2 events per decade) over the Savanna and Guinea coast, it increases droughts frequency (by 1 event per decade) over the Sahel, especially in July to September. The results of this study have application in using reforestation to mitigate impacts of climate change in West Africa.

West African Monsoon dynamics in idealized simulations: the competitive roles of SST warming and CO2

NASA Astrophysics Data System (ADS)

Gaetani, Marco; Flamant, Cyrille; Hourdin, Frederic; Bastin, Sophie; Braconnot, Pascale; Bony, Sandrine

2015-04-01

The West African Monsoon (WAM) is affected by large climate variability at different timescales, from interannual to multidecadal, with strong environmental and socio-economic impacts associated to climate-related rainfall variability, especially in the Sahelian belt. State-of-the-art coupled climate models still show poor ability in correctly simulating the WAM past variability and also a large spread is observed in future climate projections. In this work, the July-to-September (JAS) WAM variability in the period 1979-2008 is studied in AMIP-like simulations (SST-forced) from CMIP5. The individual roles of global SST warming and CO2 concentration increasing are investigated through idealized experiments simulating a 4K warmer SST and a 4x CO2 concentration, respectively. Results show a dry response in Sahel to SST warming, with dryer conditions over western Sahel. On the contrary, wet conditions are observed when CO2 is increased, with the strongest response over central-eastern Sahel. The precipitation changes are associated to modifications in the regional atmospheric circulation: dry (wet) conditions are associated with reduced (increased) convergence in the lower troposphere, a southward (northward) shift of the African Easterly Jet, and a weaker (stronger) Tropical Easterly Jet. The co-variability between global SST and WAM precipitation is also investigated, highlighting a reorganization of the main co-variability modes. Namely, in the 4xCO2 simulation the influence of Tropical Pacific is dominant, while it is reduced in the 4K simulation, which also shows an increased coupling with the eastern Pacific and the Indian Ocean. The above results suggest a competitive action of SST warming and CO2 increasing on the WAM climate variability, with opposite effects on precipitation. The combination of the observed positive and negative response in precipitation, with wet conditions in central-eastern Sahel and dry conditions in western Sahel, is consistent with the future precipitation trends over West Africa resulting from CMIP5 coupled simulations. It is argued that the large spread in CMIP5 future projections may be related to the weight given to SST warming and direct CO2 effect by individual models. The capability of climate models in reproducing the SST-precipitation relationship appears to be crucial in this respect.

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

2011-01-01

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Forecasting carbon budget under climate change and CO 2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

2011-01-01

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO 2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO 2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km 2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr -1 during the last half of the 21 st century. An NPP increase of about 24 Mt C by the end of the 21 st century was estimated with the combined effects of increasing CO 2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr -1. NEP will increase to about 5 Mt C yr -1 by the end of the 21 st century with the increasing atmospheric CO 2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO 2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

How Unusual were Hurricane Harvey's Rains?

NASA Astrophysics Data System (ADS)

Emanuel, K.

2017-12-01

We apply an advanced technique for hurricane risk assessment to evaluate the probability of hurricane rainfall of Harvey's magnitude. The technique embeds a detailed computational hurricane model in the large-scale conditions represented by climate reanalyses and by climate models. We simulate 3700 hurricane events affecting the state of Texas, from each of three climate reanalyses spanning the period 1980-2016, and 2000 events from each of six climate models for each of two periods: the period 1981-2000 from historical simulations, and the period 2081-2100 from future simulations under Representative Concentration Pathway (RCP) 8.5. On the basis of these simulations, we estimate that hurricane rain of Harvey's magnitude in the state of Texas would have had an annual probability of 0.01 in the late twentieth century, and will have an annual probability of 0.18 by the end of this century, with remarkably small scatter among the six climate models downscaled. If the event frequency is changing linearly over time, this would yield an annual probability of 0.06 in 2017.

The use of perturbed physics ensembles and emulation in palaeoclimate reconstruction (Invited)

NASA Astrophysics Data System (ADS)

Edwards, T. L.; Rougier, J.; Collins, M.

2010-12-01

Climate is a coherent process, with correlations and dependencies across space, time, and climate variables. However, reconstructions of palaeoclimate traditionally consider individual pieces of information independently, rather than making use of this covariance structure. Such reconstructions are at risk of being unphysical or at least implausible. Climate simulators such as General Circulation Models (GCMs), on the other hand, contain climate system theory in the form of dynamical equations describing physical processes, but are imperfect and computationally expensive. These two datasets - pointwise palaeoclimate reconstructions and climate simulator evaluations - contain complementary information, and a statistical synthesis can produce a palaeoclimate reconstruction that combines them while not ignoring their limitations. We use an ensemble of simulators with perturbed parameterisations, to capture the uncertainty about the simulator variant, and our method also accounts for structural uncertainty. The resulting reconstruction contains a full expression of climate uncertainty, not just pointwise but also jointly over locations. Such joint information is crucial in determining spatially extensive features such as isotherms, or the location of the tree-line. A second outcome of the statistical analysis is a refined distribution for the simulator parameters. In this way, information from palaeoclimate observations can be used directly in quantifying uncertainty in future climate projections. The main challenge is the expense of running a large scale climate simulator: each evaluation of an atmosphere-ocean GCM takes several months of computing time. The solution is to interpret the ensemble of evaluations within an 'emulator', which is a statistical model of the simulator. This technique has been used fruitfully in the statistical field of Computer Models for two decades, and has recently been applied in estimating uncertainty in future climate predictions in the UKCP09 (http://ukclimateprojections.defra.gov.uk). But only in the last couple of years has it developed to the point where it can be applied to large-scale spatial fields. We construct an emulator for the mid-Holocene (6000 calendar years BP) temperature anomaly over North America, at the resolution of our simulator (2.5° latitude by 3.75° longitude). This allows us to explore the behaviour of simulator variants that we could not afford to evaluate directly. We introduce the technique of 'co-emulation' of two versions of the climate simulator: the coupled atmosphere-ocean model HadCM3, and an equivalent with a simplified ocean, HadSM3. Running two different versions of a simulator is a powerful tool for increasing the information yield from a fixed budget of computer time, but the results must be combined statistically to account for the reduced fidelity of the quicker version. Emulators provide the appropriate framework.

Cloud evaluation using satellite simulators and cloud changes for global nonhydrostatic simulations with NICAM

NASA Astrophysics Data System (ADS)

Satoh, M.; Noda, A. T.; Kodama, C.; Yamada, Y.; Hashino, T.

2012-12-01

Global cloud distributions and properties simulated by the global nonhydrostatic model, NICAM (Nonhydrostatic Icosahedral Atmospheric Model), are evaluated and their future changes are discussed. First, we evaluated the simulated cloud properties produced by a case study of the 3.5km mesh experiment of NICAM using the satellite simulator package (the Joint-simulator) with cloud microphysics oriented approach (Hashino et al. 2012). Then, we analyzed future cloud changes using various sets of simulations under the present and the future global warming conditions. The results show that the zonal averaged ice water path (IWP) generally decreases or marginally unchanged in the tropics, while IWP in the extra-tropics increases. The upper cloud fraction increases both in the tropics and in the extra-tropics in general. We further analyzed contributions of cloud systems such as cloud clusters, tropical cyclones (TCs), and storm-tracks to these changes. Probability distribution of the larger cloud clusters decreases, while that of the smaller ones increases, consistent with the decrease in the number of tropical cyclones in the future climate. Average liquid water path (LWP) and IWP associated with each tropical cyclone are diagnosed, and it is found that both the associated LWP and IWP increase under the warmer condition. Even though, since the number of the intensive cloud systems decrease, the average IWP decreases. It should be remarked that the change in TC tracks largely contribute to the change in the horizontal distribution of clouds. The NICAM simulations also show that the storm-tracks shift poleward, and the storms become less frequent and stronger in the extra-tropics, similar to the results of other general circulation models. Both LWP and IWP associated with the storms also increase in the warmer climate in the NICAM simulations. This results in increase in the upper clouds under the warmer climate condition, as described by Miura et al. (2005). References: Hashino, T., Satoh, M., Hagihara, Y., Kubota, T., Matsui, T., Nasuno, T., and Okamoto, H. (2012), Evaluating Global Cloud Distribution and Microphysics from the NICAM against CloudSat and CALIPSO, J. Geophys. Res., submitted. Miura, H., Tomita,H., Nasuno,T., Iga, S., Satoh,M., and Matsuno, T. (2005), A climate sensitivity test using a global cloud resolving model under an aqua planet condition, Geophys. Res. Lett., 32, L19717, doi:10.1029/2005GL023672.

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

NASA Technical Reports Server (NTRS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-01-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

NASA Astrophysics Data System (ADS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-02-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Greenland-Wide Seasonal Temperatures During the Last Deglaciation

NASA Astrophysics Data System (ADS)

Buizert, C.; Keisling, B. A.; Box, J. E.; He, F.; Carlson, A. E.; Sinclair, G.; DeConto, R. M.

2018-02-01

The sensitivity of the Greenland ice sheet to climate forcing is of key importance in assessing its contribution to past and future sea level rise. Surface mass loss occurs during summer, and accounting for temperature seasonality is critical in simulating ice sheet evolution and in interpreting glacial landforms and chronologies. Ice core records constrain the timing and magnitude of climate change but are largely limited to annual mean estimates from the ice sheet interior. Here we merge ice core reconstructions with transient climate model simulations to generate Greenland-wide and seasonally resolved surface air temperature fields during the last deglaciation. Greenland summer temperatures peak in the early Holocene, consistent with records of ice core melt layers. We perform deglacial Greenland ice sheet model simulations to demonstrate that accounting for realistic temperature seasonality decreases simulated glacial ice volume, expedites the deglacial margin retreat, mutes the impact of abrupt climate warming, and gives rise to a clear Holocene ice volume minimum.

Future Heat Waves in Paris Metropolitan Area

NASA Astrophysics Data System (ADS)

Beaulant, A.; Lemonsu, A.; Somot, S.; Masson, V.

2010-12-01

Cities are particularly vulnerable to heat waves, firstly because they concentrate the majority of the population and, secondly because the heat island that characterizes the urban climate exacerbates heat wave effects. This work is part of the interdisciplinary VURCA project (Vulnerability of cities to heat waves), which deals with the evolution of heat wave events in the context of global warming, urban vulnerability and adaptation strategies. The aim of this study is to analyse urban heat wave events in present climate (1950-2009) and their evolution in an enhanced greenhouse gazes future climate (2010-2100). We used daily observations of temperature from several stations covering Paris metropolitan area and climate projections following three different IPCC-SRES scenarios (B1, A1B, A2) and issued from several ENSEMBLES regional climate models. The heat wave definition is based on the indexes of the operational French warning system. A heat wave is detected within observed or simulated time-series by a heat wave peak, when the temperatures exceed the value of the 99.9th percentile. Its duration is determined by all adjacent days to this peak, for which the temperatures are not durably smaller than the 99.9th percentile value minus 2 °C. The 99.9th percentile threshold is inferred from quantile-quantile plots produced for each climate model in comparison with observations for the reference period 1950-2000. Heat waves have been extracted within observations and 12 climatic simulations. The number of heat wave events and cumulated HW days per year have been calculated, the maximum being seven heat waves cumulating more than 60 HW days in one year in the case of the A2 scenario and until 50 days in the case of the more moderate A1B scenario. From 2050, the occurrence of three or four HW events per year is becoming the norm all scenarios taken together. The evolution of heat wave features has been analysed, highlighting the large variability of the climatic simulations, but also an overall trend to an increase in frequency and duration but less significantly in intensity. Further work will be carried out in order to assess the sensitivity of the Paris urban climate to different future heat wave events. Synthetic HW events will be built from future HW features as duration and intensity, and will be simulated using a urban-weather model. Then, the impacts in terms of energy consumption and bioclimatic comfort will be analysed and adaptation strategies will be proposed.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena

2011-01-01

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Future summer mega-heatwave and record-breaking temperatures in a warmer France climate

NASA Astrophysics Data System (ADS)

Bador, Margot; Terray, Laurent; Boé, Julien; Somot, Samuel; Alias, Antoinette; Gibelin, Anne-Laure; Dubuisson, Brigitte

2017-07-01

This study focuses on future very hot summers associated with severe heatwaves and record-breaking temperatures in France. Daily temperature observations and a pair of historical and scenario (greenhouse gas radiative concentration pathway 8.5) simulations with the high-resolution (∼12.5 km) ALADIN regional climate model provide a robust framework to examine the spatial distribution of these extreme events and their 21st century evolution. Five regions are identified with an extreme event spatial clustering algorithm applied to observed temperatures. They are used to diagnose the 21st century heatwave spatial patterns. In the 2070s, we find a simulated mega-heatwave as severe as the 2003 observed heatwave relative to its contemporaneous climate. A 20-member initial condition ensemble is used to assess the sensitivity of this future heatwave to the internal variability in the regional climate model and to pre-existing land surface conditions. Even in a much warmer and drier climate in France, late spring dry land conditions may lead to a significant amplification of summer extreme temperatures and heatwave intensity through limitations in evapotranspiration. By 2100, the increase in summer temperature maxima exhibits a range from 6 °C to almost 13 °C in the five regions in France, relative to historical maxima. These projections are comparable with the estimates given by a large number of global climate models.

Changes of climate regimes during the last millennium and the twenty-first century simulated by the Community Earth System Model

NASA Astrophysics Data System (ADS)

Huang, Wei; Feng, Song; Liu, Chang; Chen, Jie; Chen, Jianhui; Chen, Fahu

2018-01-01

This study examines the shifts in terrestrial climate regimes using the Köppen-Trewartha (K-T) climate classification by analyzing the Community Earth System Model Last Millennium Ensemble (CESM-LME) simulations for the period 850-2005 and CESM Medium Ensemble (CESM-ME), CESM Large Ensemble (CESM-LE) and CESM with fixed aerosols Medium Ensemble (CESM-LE_FixA) simulations for the period 1920-2080. We compare K-T climate types from the Medieval Climate Anomaly (MCA) (950-1250) with the Little Ice Age (LIA) (1550-1850), from present day (PD) (1971-2000) with the last millennium (LM) (850-1850), and from the future (2050-2080) with the LM in order to place anthropogenic changes in the context of changes due to natural forcings occurring during the last millennium. For CESM-LME, we focused on the simulations with all forcings, though the impacts of individual forcings (e.g., solar activities, volcanic eruptions, greenhouse gases, aerosols and land use changes) were also analyzed. We found that the climate types changed slightly between the MCA and the LIA due to weak changes in temperature and precipitation. The climate type changes in PD relative to the last millennium have been largely driven by greenhouse gas-induced warming, but anthropogenic aerosols have also played an important role on regional scales. At the end of the twenty-first century, the anthropogenic forcing has a much greater effect on climate types than the PD. Following the reduction of aerosol emissions, the impact of greenhouse gases will further promote global warming in the future. Compared to precipitation, changes in climate types are dominated by greenhouse gas-induced warming. The large shift in climate types by the end of this century suggests possible wide-spread redistribution of surface vegetation and a significant change in species distributions.

On the generation of climate model ensembles

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

2014-10-01

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

Modeling the Effects of Drought Events on Forest Ecosystem Functioning Historically and Under Scenarios of Climate Change

NASA Astrophysics Data System (ADS)

Ren, J.; Hanan, E. J.; Kolden, C.; Abatzoglou, J. T.; Tague, C.; Liu, M.; Adam, J. C.

2017-12-01

Drought events have been increasing across the western United States in recent years. Many studies have shown that, in the context of climate change, droughts will continue to be stronger, more frequent, and prolonged in the future. However, the response of forest ecosystems to droughts, particularly multi-year droughts, is not well understood. The objectives of this study are to examine how drought events of varying characteristics (e.g. intensity, duration, frequency, etc.) have affected the functioning of forest ecosystems historically, and how changing drought characteristics (including multi-year droughts) may affect forest functioning in a future climate. We utilize the Regional Hydro-Ecological Simulation System (RHESSys) to simulate impacts of both historical droughts and scenarios of future droughts on forest ecosystems. RHESSys is a spatially-distributed and process-based model that captures the interactions between coupled biogeochemical and hydrologic cycles at catchment scales. Here our case study is the Trail Creek catchment of the Big Wood River basin in Idaho, the Northwestern USA. For historical simulations, we use the gridded meteorological data of 1979 to 2016; for future climate scenarios, we utilize downscaled data from GCMs that have been demonstrated to capture drought events in the Northwest of the USA. From these climate projections, we identify various types of drought in intensity and duration, including multi-year drought events. We evaluate the following responses of ecosystems to these events: 1) evapotranspiration and streamflow; 2) gross primary productivity; 3) the post-drought recovery of plant biomass; and 4) the forest functioning and recovery after multi-year droughts. This research is part of an integration project to examine the roles of drought, insect outbreak, and forest management activities on wildfire activity and its impacts. This project will provide improved information for forest managers and communities in the wild urban interface to adapt to climate change.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards bridging the gap between climate change projections and maize producers in South Africa

NASA Astrophysics Data System (ADS)

Landman, Willem A.; Engelbrecht, Francois; Hewitson, Bruce; Malherbe, Johan; van der Merwe, Jacobus

2018-05-01

Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral mid-summer maximum temperature simulations for southern Africa. The statistical model uses atmospheric thickness fields from a high-resolution (0.5° × 0.5°) reanalysis-forced simulation as predictors in order to develop a linear recalibration model which represents the relationship between atmospheric thickness fields and gridded maximum temperatures across the region. The regional climate model, the conformal-cubic atmospheric model (CCAM), projects maximum temperatures increases over southern Africa to be in the order of 4 °C under low mitigation towards the end of the century or even higher. The statistical recalibration model is able to replicate these increasing temperatures, and the atmospheric thickness-maximum temperature relationship is shown to be stable under future climate conditions. Since dry land crop yields are not explicitly simulated by climate models but are sensitive to maximum temperature extremes, the effect of projected maximum temperature change on dry land crops of the Witbank maize production district of South Africa, assuming other factors remain unchanged, is then assessed by employing a statistical approach similar to the one used for maximum temperature projections.

Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System Perspective

NASA Astrophysics Data System (ADS)

Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.

2017-12-01

Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.

The impact of future climate on historic interiors.

PubMed

Lankester, Paul; Brimblecombe, Peter

2012-02-15

The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.

Suitability of European climate for the Asian tiger mosquito Aedes albopictus: recent trends and future scenarios

PubMed Central

Caminade, Cyril; Medlock, Jolyon M.; Ducheyne, Els; McIntyre, K. Marie; Leach, Steve; Baylis, Matthew; Morse, Andrew P.

2012-01-01

The Asian tiger mosquito (Aedes albopictus) is an invasive species that has the potential to transmit infectious diseases such as dengue and chikungunya fever. Using high-resolution observations and regional climate model scenarios for the future, we investigated the suitability of Europe for A. albopictus using both recent climate and future climate conditions. The results show that southern France, northern Italy, the northern coast of Spain, the eastern coast of the Adriatic Sea and western Turkey were climatically suitable areas for the establishment of the mosquito during the 1960–1980s. Over the last two decades, climate conditions have become more suitable for the mosquito over central northwestern Europe (Benelux, western Germany) and the Balkans, while they have become less suitable over southern Spain. Similar trends are likely in the future, with an increased risk simulated over northern Europe and slightly decreased risk over southern Europe. These distribution shifts are related to wetter and warmer conditions favouring the overwintering of A. albopictus in the north, and drier and warmer summers that might limit its southward expansion. PMID:22535696

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

NASA Technical Reports Server (NTRS)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Storylines of combined land use and climatic drivers and their hydrological impacts in an alpine catchment (Brixental/Austria)

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Förster, Kristian; Meissl, Gertraud; Marke, Thomas; Schermer, Markus; Stotten, Rike; Formayer, Herbert; Themessl, Matthias

2017-04-01

We present a numerical modelling experiment with storylines of coupled land use and climate evolution as input in the physically-based, distributed water balance model WaSiM. The aim is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The climatic background is defined by simulations for the A1B and RCP 8.5 emission scenarios until 2050. These two climate projections were combined with three future land use developments for forest management, developed in an inter- and transdisciplinary assessment with local actors using plausible and consisent projections for forest management, policy, social cooperation, tourism and economy: (i) Ecological adaptation: The forest management consequently applies the political guidelines, and the forest cover is dominated by an ecological, place-adapted mixed cultivation with a harmonious age structure. (ii) Economical overexploitation and wildness: The increase in efficiency, cost reduction and short term results are in focus of the forest management. (iii) Withdrawal and wildness: Cultivation in general is decreasing, and the forest becomes vulnerable against natural hazards. A new module for snow-canopy interaction simulation, providing explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands, has been implemented in WaSiM. The new version of the model is used to model the coupled future climate/land use storylines for the Brixental. Results show the effects of climate change and land use on the water balance and streamflow in the catchment.

Expansion of the Lyme Disease Vector Ixodes scapularis in Canada inferred from CMIP5 Climate Projections

NASA Astrophysics Data System (ADS)

McPherson, Michelle Yvonne; García-García, Almudena; José Cuesta-Valero, Francisco; Beltrami, Hugo; Hansen-Ketchum, Patti; MacDougall, Donna; Hume Ogden, Nicholas

2017-04-01

A number of studies have assessed possible climate change impacts on the Lyme disease vector, Ixodes scapularis. However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R0) of I. scapularis to explore uncertainties in future R0 estimates. We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical and forecast future effects of climate change on the R0 of I. scapularis. As in previous studies, R0 of I. scapularis increased with a warming climate under future projected climate. Increases in the multi-model mean R0 values showed significant changes over time under all RCP scenarios, however; only the estimated R0 mean values between RCP6.0 and RCP8.5 showed statistically significant differences. Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement's goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. On-going planning is needed to inform and guide adaptation in light of the projected range of possible futures.

Contrasting fire responses to climate and management: insights from two Australian ecosystems.

PubMed

King, Karen J; Cary, Geoffrey J; Bradstock, Ross A; Marsden-Smedley, Jonathan B

2013-04-01

This study explores effects of climate change and fuel management on unplanned fire activity in ecosystems representing contrasting extremes of the moisture availability spectrum (mesic and arid). Simulation modelling examined unplanned fire activity (fire incidence and area burned, and the area burned by large fires) for alternate climate scenarios and prescribed burning levels in: (i) a cool, moist temperate forest and wet moorland ecosystem in south-west Tasmania (mesic); and (ii) a spinifex and mulga ecosystem in central Australia (arid). Contemporary fire activity in these case study systems is limited, respectively, by fuel availability and fuel amount. For future climates, unplanned fire incidence and area burned increased in the mesic landscape, but decreased in the arid landscape in accordance with predictions based on these limiting factors. Area burned by large fires (greater than the 95th percentile of historical, unplanned fire size) increased with future climates in the mesic landscape. Simulated prescribed burning was more effective in reducing unplanned fire activity in the mesic landscape. However, the inhibitory effects of prescribed burning are predicted to be outweighed by climate change in the mesic landscape, whereas in the arid landscape prescribed burning reinforced a predicted decline in fire under climate change. The potentially contrasting direction of future changes to fire will have fundamentally different consequences for biodiversity in these contrasting ecosystems, and these will need to be accommodated through contrasting, innovative management solutions. © 2012 Blackwell Publishing Ltd.

Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Yang; Leung, Lai-Yung R.; Lu, Jian

2014-03-16

This study compares climate simulations over the United States produced by a regional climate model with the driving global climate simulations as well as a large multi-model ensemble of global climate simulations to investigate robust changes in water availability (precipitation (P) – evapotranspiration (E)). A robust spring dry signal across multiple models is identified in the Southwest that results from a decrease in P and an increase in E in the future. In the boreal winter and summer, the prominent changes in P – E are associated with a north – south dipole pattern, while in spring, the prominent changesmore » in P – E appear as an east – west dipole pattern. The progression of the north – south and east – west dipole patterns through the seasons manifests clearly as a seasonal “clockwise” migration of wet/dry patterns, which is shown to be a robust feature of water availability changes in the US consistent across regional and global climate simulations.« less

Predicting the effects of climate change on population connectivity and genetic diversity of an imperiled freshwater mussel, Cumberlandia monodonta (Bivalvia: Margaritiferidae), in riverine systems.

PubMed

Inoue, Kentaro; Berg, David J

2017-01-01

In the face of global climate change, organisms may respond to temperature increases by shifting their ranges poleward or to higher altitudes. However, the direction of range shifts in riverine systems is less clear. Because rivers are dendritic networks, there is only one dispersal route from any given location to another. Thus, range shifts are only possible if branches are connected by suitable habitat, and stream-dwelling organisms can disperse through these branches. We used Cumberlandia monodonta (Bivalvia: Unionoida: Margaritiferidae) as a model species to investigate the effects of climate change on population connectivity because a majority of contemporary populations are panmictic. We combined ecological niche models (ENMs) with population genetic simulations to investigate the effects of climate change on population connectivity and genetic diversity of C. monodonta. The ENMs were constructed using bioclimatic and landscape data to project shifts in suitable habitat under future climate scenarios. We then used forward-time simulations to project potential changes in genetic diversity and population connectivity based on these range shifts. ENM results under current conditions indicated long stretches of highly suitable habitat in rivers where C. monodonta persists; populations in the upper Mississippi River remain connected by suitable habitat that does not impede gene flow. Future climate scenarios projected northward and headwater-ward range contraction and drastic declines in habitat suitability for most extant populations throughout the Mississippi River Basin. Simulations indicated that climate change would greatly reduce genetic diversity and connectivity across populations. Results suggest that a single, large population of C. monodonta will become further fragmented into smaller populations, each of which will be isolated and begin to differentiate genetically. Because C. monodonta is a widely distributed species and purely aquatic, our results suggest that persistence and connectivity of stream-dwelling organisms will be significantly altered in response to future climate change. © 2016 John Wiley & Sons Ltd.

Final Technical Report for DOE Award SC0006616

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Andrew

2015-08-01

This report summarizes research carried out by the project "Collaborative Research, Type 1: Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia. This collaborative project brought together climate dynamicists (UCLA, IRI), dendroclimatologists (LDEO Tree Ring Laboratory), computer scientists (UCI), and hydrologists (Columbia Water Center, CWC), together with applied scientists in climate risk management (IRI) to create new scientific approaches to quantify and exploit the role of climate variability and change in the growing water crisis across southern and eastern Asia. This project developed new tree-ring based streamflow reconstructions for rivers in monsoonal Asia; improved understanding of hydrologic spatio-temporal modesmore » of variability over monsoonal Asia on interannual-to-centennial time scales; assessed decadal predictability of hydrologic spatio-temporal modes; developed stochastic simulation tools for creating downscaled future climate scenarios based on historical/proxy data and GCM climate change; and developed stochastic reservoir simulation and optimization for scheduling hydropower, irrigation and navigation releases.« less

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

DOE PAGES

Collins, William J.; Lamarque, Jean -François; Schulz, Michael; ...

2017-02-09

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, William J.; Lamarque, Jean -François; Schulz, Michael

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

The WASCAL high-resolution climate projection ensemble for West Africa

NASA Astrophysics Data System (ADS)

Kunstmann, Harald; Heinzeller, Dominikus; Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Hamann, Ilse; Salack, Seyni

2017-04-01

With climate change being one of the most severe challenges to rural Africa in the 21st century, West Africa is facing an urgent need to develop effective adaptation and mitigation measures to protect its constantly growing population. We perform ensemble-based regional climate simulations at a high resolution of 12km for West Africa to allow a scientifically sound derivation of climate change adaptation measures. Based on the RCP4.5 scenario, our ensemble consist of three simulation experiments with the Weather Research & Forecasting Tool (WRF) and one additional experiment with the Consortium for Small-scale Modelling Model COSMO in Climate Mode (COSMO-CLM). We discuss the model performance over the validation period 1980-2010, including a novel, station-based precipitation database for West Africa obtained within the WASCAL (West African Science Service Centre for Climate Change and Adapted Land Use) program. Particular attention is paid to the representation of the dynamics of the West African Summer Monsoon and to the added value of our high-resolution models over existing data sets. We further present results on the climate change signal obtained for the two future periods 2020-2050 and 2070-2100 and compare them to current state-of-the-art projections from the CORDEX-Africa project. While the temperature change signal is similar to that obtained within CORDEX-Africa, our simulations predict a wetter future for the Coast of Guinea and the southern Soudano area and a slight drying in the northernmost part of the Sahel.

Analysis of Present Day and Future OH and Methane Lifetime in the ACCMIP Simulations

NASA Technical Reports Server (NTRS)

Voulgarakis, A.; Naik, V.; Lamarque, J. -F.; Shindell, D. T.; Young, P. J.; Prather, M. J.; Wild, O.; Field, R. D.; Bergmann, D.; Cameron-Smith P.;

Sensitivity of the Atmospheric Response to Warm Pool El Nino Events to Modeled SSTs and Future Climate Forcings

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Garfinkel, Chaim I.; Newman, Paul A.; Oman, Luke D.

2013-01-01

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. Under present-day climate conditions, WPEN events generate poleward propagating wavetrains and enhance midlatitude planetary wave activity, weakening the stratospheric polar vortices. The late 21st century extratropical atmospheric response to WPEN events is investigated using the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM), version 2. GEOSCCM simulations are forced by projected late 21st century concentrations of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) and by SSTs and sea ice concentrations from an existing ocean-atmosphere simulation. Despite known ocean-atmosphere model biases, the prescribed SST fields represent a best estimate of the structure of late 21st century WPEN events. The future Arctic vortex response is qualitatively similar to that observed in recent decades but is weaker in late winter. This response reflects the weaker SST forcing in the Nino 3.4 region and subsequently weaker Northern Hemisphere tropospheric teleconnections. The Antarctic stratosphere does not respond to WPEN events in a future climate, reflecting a change in tropospheric teleconnections: The meridional wavetrain weakens while a more zonal wavetrain originates near Australia. Sensitivity simulations show that a strong poleward wavetrain response to WPEN requires a strengthening and southeastward extension of the South Pacific Convergence Zone; this feature is not captured by the late 21st century modeled SSTs. Expected future increases in GHGs and decreases in ODSs do not affect the polar stratospheric responses to WPEN.

Climate mitigation and the future of tropical landscapes.

PubMed

Thomson, Allison M; Calvin, Katherine V; Chini, Louise P; Hurtt, George; Edmonds, James A; Bond-Lamberty, Ben; Frolking, Steve; Wise, Marshall A; Janetos, Anthony C

2010-11-16

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m(-2) (approximately 526 ppm CO(2)) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

Evaluation of skill at simulating heatwave and heat-humidity indices in Global and Regional Climate Models

NASA Astrophysics Data System (ADS)

Goldie, J. K.; Alexander, L. V.; Lewis, S. C.; Sherwood, S. C.

2017-12-01

A wide body of literature now establishes the harm of extreme heat on human health, and work is now emerging on the projection of future health impacts. However, heat-health relationships vary across different populations (Gasparrini et al. 2015), so accurate simulation of regional climate is an important component of joint health impact projection. Here, we evaluate the ability of nine Global Climate Models (GCMs) from CMIP5 and the NARCliM Regional Climate Model to reproduce a selection of 15 health-relevant heatwave and heat-humidity indices over the historical period (1990-2005) using the Perkins skill score (Perkins et al. 2007) in five Australian cities. We explore the reasons for poor model skill, comparing these modelled distributions to both weather station observations and gridded reanalysis data. Finally, we show changes in the modelled distributions from the highest-performing models under RCP4.5 and RCP8.5 greenhouse gas scenarios and discuss the implications of simulated heat stress for future climate change adaptation. ReferencesGasparrini, Antonio, Yuming Guo, Masahiro Hashizume, Eric Lavigne, Antonella Zanobetti, Joel Schwartz, Aurelio Tobias, et al. "Mortality Risk Attributable to High and Low Ambient Temperature: A Multicountry Observational Study." The Lancet 386, no. 9991 (July 31, 2015): 369-75. doi:10.1016/S0140-6736(14)62114-0. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney. "Evaluation of the AR4 Climate Models' Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions." Journal of Climate 20, no. 17 (September 1, 2007): 4356-76. doi:10.1175/JCLI4253.1.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

NASA Astrophysics Data System (ADS)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena

2016-09-01

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE PAGES

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; ...

2016-09-02

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

Persistent Cold Air Outbreaks over North America Under Climate Warming

NASA Astrophysics Data System (ADS)

Gao, Y.; Leung, L. R.; Lu, J.

2014-12-01

This study evaluates the change of cold air outbreaks (CAO) over North America using Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble of global climate simulations as well as regional high resolution climate simulations. In future, while robust decrease of CAO duration dominates in most of the North America, the decrease over northwestern U.S. was found to have much smaller magnitude than the surrounding regions. We found statistically significant increase of the sea level pressure over gulf of Alaska, leading to the advection of cold air to northwestern U.S.. By shifting the probability distribution of present temperature towards future warmer conditions, we identified the changes in large scale circulation contribute to about 50% of the enhanced sea level pressure. Using the high resolution regional climate model results, we found that increases of existing snowpack could potentially trigger the increase of CAO in the near future over the southwestern U.S. and Rocky Mountain through surface albedo effects. By the end of this century, the top 5 most extreme historical CAO events may still occur and wind chill warning will continue to have societal impacts over North America in particular over northwestern United States.

Modeling of larch forest dynamics under a changing climate in eastern Siberia

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Iijima, Y.; Ohta, T.; Kotani, A.; Maximov, T. C.; Hiyama, T.

2017-12-01

According to the projection by an earth system model under RCP8.5 scenario, boreal forest in eastern Siberia (near Yakutsk) is predicted to experience significant changes in climate, in which the mean annual air temperature is projected to be positive and the annual precipitation will be doubled by the end of 21st century. Since the forest in this region is underlain by continuous permafrost, both increasing temperature and precipitation can affect the dynamics of forest through the soil water processes. To investigate such effects, we adopted a newly developed terrestrial ecosystem dynamics model named S-TEDy (SEIB-DGVM-originated Terrestrial Ecosystem Dynamics model), which mechanistically simulates "the way of life" of each individual tree and resulting tree mortality under the future climate conditions. This model was first developed for the simulation of the dynamics of a tropical rainforest in the Borneo Island, and successfully reproduced higher mortality of large trees due to a prolonged drought induced by ENSO event of 1997-1998. To apply this model to a larch forest in eastern Siberia, we are developing a soil submodel to consider the effect of thawing-freezing processes. We will present a simulation results using the future climate projection.

Present-day and future Antarctic ice sheet climate and surface mass balance in the Community Earth System Model

DOE PAGES

Lenaerts, Jan T. M.; Vizcaino, Miren; Fyke, Jeremy Garmeson; ...

2016-02-01

Here, we present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ~1° in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131Gtyear –1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenariomore » RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gtyear –1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content.« less

Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.

PubMed

Braconnot, Pascale; Kageyama, Masa

2015-11-13

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results. © 2015 The Author(s).

The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies

USDA-ARS?s Scientific Manuscript database

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the...

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

D'Andrea, M.; Fiorucci, P.; Holmes, T. P.

2010-10-01

Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary - each cell either contains a tree or it is empty - and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.

Application of MC1 to Wind Cave National Park: Lessons from a small-scale study: Chapter 8

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2015-01-01

MC1 was designed for application to large regions that include a wide range in elevation and topography, thereby encompassing a broad range in climates and vegetation types. The authors applied the dynamic global vegetation model MC1 to Wind Cave National Park (WCNP) in the southern Black Hills of South Dakota, USA, on the ecotone between ponderosa pine forest to the northwest and mixed-grass prairie to the southeast. They calibrated MC1 to simulate adequate fire effects in the warmer southeastern parts of the park to ensure grasslands there, while allowing forests to grow to the northwest, and then simulated future vegetation with climate projections from three GCMs. The results suggest that fire frequency, as affected by climate and/or human intervention, may be more important than the direct effects of climate in determining the distribution of ponderosa pine in the Black Hills region, both historically and in the future.

Analysis of the present and future winter Pacific-North American teleconnection in the ECHAM5 global and RegCM3 regional climate models

USGS Publications Warehouse

Allan, Andrea M.; Hostetler, Steven W.; Alder, Jay R.

2014-01-01

We use the NCEP/NCAR Reanalysis (NCEP) and the MPI/ECHAM5 general circulation model to drive the RegCM3 regional climate model to assess the ability of the models to reproduce the spatiotemporal aspects of the Pacific-North American teleconnection (PNA) pattern. Composite anomalies of the NCEP-driven RegCM3 simulations for 1982–2000 indicate that the regional model is capable of accurately simulating the key features (500-hPa heights, surface temperature, and precipitation) of the positive and negative phases of the PNA with little loss of information in the downscaling process. The basic structure of the PNA is captured in both the ECHAM5 global and ECHAM5-driven RegCM3 simulations. The 1950–2000 ECHAM5 simulation displays similar temporal and spatial variability in the PNA index as that of NCEP; however, the magnitudes of the positive and negative phases are weaker than those of NCEP. The RegCM3 simulations clearly differentiate the climatology and associated anomalies of snow water equivalent and soil moisture of the positive and negative PNA phases. In the RegCM3 simulations of the future (2050–2100), changes in the location and extent of the Aleutian low and the continental high over North America alter the dominant flow patterns associated with positive and negative PNA modes. The future projections display a shift in the patterns of the relationship between the PNA and surface climate variables, which suggest the potential for changes in the PNA-related surface hydrology of North America.

Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kerns, B. K.; Halofsky, J.

2014-12-01

GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest point demonstrates the importance of using model out as a forum for discussion along with other information, rather than using model output in an inappropriately predictive sense. These lessons are being applied currently to other national forests in the Pacific Northwest to contribute in vulnerability assessments.

Possible future changes in extreme events over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Scott, Jeffery

2013-04-01

In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world's tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations presented in this paper were carried out for two emission scenarios, a "business as usual" scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.

Projected changes to rain-on-snow events over North America

NASA Astrophysics Data System (ADS)

Jeong, Dae Il; Sushama, Laxmi

2016-04-01

Rain-on-snow (ROS) events have significant impacts on cold region ecosystems and water-related natural hazards, and therefore it is very important to assess how this hydro-meteorological phenomenon will evolve in a changing climate. This study evaluates the changes in ROS characteristics (i.e., frequency, amounts, and runoff) for the future 2041-2070 period with respect to the current 1976-2005 period over North America using six simulations, based on two Canadian RCMs, driven by two driving GCMs for RCP4.5 and 8.5 emission pathways. Projected changes to extreme runoff caused by the changes of the ROS characteristics are also evaluated. All simulations suggest general increases in ROS days in late autumn, winter, and early spring periods for most Canadian regions and northwestern USA for the future period, due to an increase in rain days in a warmer climate. Increases in the future ROS amounts are projected mainly due to an increase in ROS days, although increases in precipitation intensity also contributes to the future increases. Future ROS runoff is expected to increase more than future ROS amounts during snowmelt months as ROS events usually enhance runoff, given the land state and asociated reduced soil infiltration rate and also due to the faster snowmelt rate occuring during these events. The simulations also show that ROS events usually lead to extreme runoff over most of Canada and north-western and -central USA in the January-May snowmelt months for the current period and these show no significant changes in the future climate. However, the future ROS to total runoff ratio will significantly decrease for western and eastern Canada as well as north-western USA for these months, due to an overall increase of the fraction of direct snowmelt and rainfall generated runoff in a warmer climate. These results indicate the difficulties of flood risk and water resource managements in the future, particularly in Canada and north-western and -central USA, requiring more in depth studies for these regions to facilitate appropriate adaptation measures.

Sensitivity of Regional Hydropower Generation to the Projected Changes in Future Watershed Hydrology

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.

2015-12-01

Hydropower is a key contributor to the renewable energy portfolio due to its established development history and the diverse benefits it provides to the electric power systems. With the projected change in the future watershed hydrology, including shift of snowmelt timing, increasing occurrence of extreme precipitation, and change in drought frequencies, there is a need to investigate how the regional hydropower generation may change correspondingly. To evaluate the sensitivity of watershed storage and hydropower generation to future climate change, a lumped Watershed Runoff-Energy Storage (WRES) model is developed to simulate the annual and seasonal hydropower generation at various hydropower areas in the United States. For each hydropower study area, the WRES model use the monthly precipitation and naturalized (unregulated) runoff as inputs to perform a runoff mass balance calculation for the total monthly runoff storage in all reservoirs and retention facilities in the watershed, and simulate the monthly regulated runoff release and hydropower generation through the system. The WRES model is developed and calibrated using the historic (1980-2009) monthly precipitation, runoff, and generation data, and then driven by a large set of dynamically- and statistically-downscaled Coupled Model Intercomparison Project Phase 5 climate projections to simulate the change of watershed storage and hydropower generation under different future climate scenarios. The results among different hydropower regions, storage capacities, emission scenarios, and timescales are compared and discussed in this study.

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

Importance of vegetation dynamics for future terrestrial carbon cycling

NASA Astrophysics Data System (ADS)

Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin

2015-05-01

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Effect of Climate Change on Surface Ozone over North America, Europe, and East Asia

NASA Technical Reports Server (NTRS)

Schnell, Jordan L.; Prather, Michael J.; Josse, Beatrice; Naik, Vaishali; Horowitz, Larry W.; Zeng, Guang; Shindell, Drew T.; Faluvegi, Greg

2016-01-01

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution.

A dynamic modelling approach for estimating critical loads of nitrogen based on plant community changes under a changing climate.

PubMed

Belyazid, Salim; Kurz, Dani; Braun, Sabine; Sverdrup, Harald; Rihm, Beat; Hettelingh, Jean-Paul

2011-03-01

A dynamic model of forest ecosystems was used to investigate the effects of climate change, atmospheric deposition and harvest intensity on 48 forest sites in Sweden (n = 16) and Switzerland (n = 32). The model was used to investigate the feasibility of deriving critical loads for nitrogen (N) deposition based on changes in plant community composition. The simulations show that climate and atmospheric deposition have comparably important effects on N mobilization in the soil, as climate triggers the release of organically bound nitrogen stored in the soil during the elevated deposition period. Climate has the most important effect on plant community composition, underlining the fact that this cannot be ignored in future simulations of vegetation dynamics. Harvest intensity has comparatively little effect on the plant community in the long term, while it may be detrimental in the short term following cutting. This study shows: that critical loads of N deposition can be estimated using the plant community as an indicator; that future climatic changes must be taken into account; and that the definition of the reference deposition is critical for the outcome of this estimate. Copyright © 2010 Elsevier Ltd. All rights reserved.

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Investigation of Climate Change Impact on Water Resources for an Alpine Basin in Northern Italy: Implications for Evapotranspiration Modeling Complexity

PubMed Central

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.

PubMed

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.

An enhanced archive facilitating climate impacts analysis

USGS Publications Warehouse

Maurer, E.P.; Brekke, L.; Pruitt, T.; Thrasher, B.; Long, J.; Duffy, P.; Dettinger, M.; Cayan, D.; Arnold, J.

2014-01-01

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrologi- cal variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_ cmip_projections).

Simulating soil organic carbon stock as affected by land cover change and climate change, Hyrcanian forests (northern Iran).

PubMed

Soleimani, Azam; Hosseini, Seyed Mohsen; Massah Bavani, Ali Reza; Jafari, Mostafa; Francaviglia, Rosa

2017-12-01

Soil organic carbon (SOC) contains a considerable portion of the world's terrestrial carbon stock, and is affected by changes in land cover and climate. SOC modeling is a useful approach to assess the impact of land use, land use change and climate change on carbon (C) sequestration. This study aimed to: (i) test the performance of RothC model using data measured from different land covers in Hyrcanian forests (northern Iran); and (ii) predict changes in SOC under different climate change scenarios that may occur in the future. The following land covers were considered: Quercus castaneifolia (QC), Acer velutinum (AV), Alnus subcordata (AS), Cupressus sempervirens (CS) plantations and a natural forest (NF). For assessment of future climate change projections the Fifth Assessment IPCC report was used. These projections were generated with nine Global Climate Models (GCMs), for two Representative Concentration Pathways (RCPs) leading to very low and high greenhouse gases concentration levels (RCP 2.6 and RCP 8.5 respectively), and for four 20year-periods up to 2099 (2030s, 2050s, 2070s and 2090s). Simulated values of SOC correlated well with measured data (R 2 =0.64 to 0.91) indicating a good efficiency of the RothC model. Our results showed an overall decrease in SOC stocks by 2099 under all land covers and climate change scenarios, but the extent of the decrease varied with the climate models, the emissions scenarios, time periods and land covers. Acer velutinum plantation was the most sensitive land cover to future climate change (range of decrease 8.34-21.83tCha -1 ). Results suggest that modeling techniques can be effectively applied for evaluating SOC stocks, allowing the identification of current patterns in the soil and the prediction of future conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

PubMed

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

An Assessment of IPCC 20th Century Climate Simulations Using the 15-year Sea Level Record from Altimetry

NASA Astrophysics Data System (ADS)

Leuliette, E.; Nerem, S.; Jakub, T.

2006-07-01

Recen tly, multiple ensemble climate simulations h ave been produced for th e forthco ming Fourth A ssessment Report of the Intergovernmental Panel on Climate Change (IPCC). N early two dozen coupled ocean- atmo sphere models have contr ibuted output for a variety of climate scen arios. One scenar io, the climate of the 20th century exper imen t (20C3 M), produces model output that can be comp ared to th e long record of sea level provided by altimetry . Generally , the output from the 20C3M runs is used to initialize simulations of future climate scenar ios. Hence, v alidation of the 20 C3 M experiment resu lts is crucial to the goals of th e IPCC. We present compar isons of global mean sea level (G MSL) , global mean steric sea level change, and regional patterns of sea lev el chang e from these models to r esults from altimetry, tide gauge measurements, and reconstructions.

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

Hydrological Assessment of Model Performance and Scenario Analyses of Land Use Change and Climate Change in lowlands of Veneto Region (Italy)

NASA Astrophysics Data System (ADS)

Pijl, Anton; Brauer, Claudia; Sofia, Giulia; Teuling, Ryan; Tarolli, Paolo

2017-04-01

Growing water-related challenges in lowland areas of the world call for good assessment of our past and present actions, in order to guide our future decisions. The novel Wageningen Lowland Runoff Simulator (WALRUS; Brauer et al., 2014) was developed to simulate hydrological processes and has showed promising performance in recent studies in the Netherlands. Here the model was applied to a coastal basin of 2800 ha in the Veneto Region (northern Italy) to test model performance and evaluate scenario analyses of land use change and climate change. Located partially below sea-level, the reclaimed area is facing persistent land transformation and climate change trends, which alter not only the processes in the catchment but also the demands from it (Tarolli and Sofia, 2016). Firstly results of the calibration (NSE = 0.77; year simulation, daily resolution) and validation (NSE = 0.53; idem) showed that the model is able to reproduce the dominant hydrological processes of this lowland area (e.g. discharge and groundwater fluxes). Land use scenarios between 1951 and 2060 were constructed using demographic models, supported by orthographic interpretation techniques. Climate scenarios were constructed by historical records and future projections by COSMO-CLM regional climate model (Rockel et al., 2008) under the RCP4.5 pathway. WALRUS simulations showed that the land use changes result in a wetter catchment with more discharge, and the climatic changes cause more extremes with longer droughts and stronger rain events. These changes combined show drier summers (-33{%} rainfall, +27{%} soil moisture deficit) and wetter (+13{%} rainfall) and intenser (+30{%} rain intensity) autumn and winters in the future. The simulated discharge regime -particularly peak flow- follows these polarising trends, in good agreement with similar studies in the geographical zone (e.g. Vezzoli et al., 2015). This will increase the pressure on the fully-artificial drainage and agricultural systems, that will need to adapt to prevent largescale floods or crop-failure. Additionally, simulations under 'business-as-usual' pathway RCP8.5 would likely amplify the polarising effects on the hydrological regime as presented here, further stressing the need for adequate adaptation. The proposed presentation at EGU 2017 will contain clear visual results of the model and quantitative scenario simulations. These results are particularly interesting, firstly because they prove how a simple conceptual model can become a powerful tool in scenario analysis of future pathways. Furthermore, they clearly indicate major challenges that lowland areas are facing in modern times - not only the 46.000 km2 Po valley, but all around the world where lowlands often host the centres of our societies and economies. REFERENCES Brauer, C., Teuling, A., Torfs, P., Uijlenhoet, R., 2014. The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall-runoff model for catchments with shallow groundwater. Geoscientific Model Development 7 (5), 2313-2332. Rockel, B., Will, A., Hense, A., 2008. The regional climate model COSMO-CLM (CCLM). Meteorologische Zeitschrift 17 (4), 347-348. Tarolli, P., Sofia, G., 2016. Human topographic signatures and derived geomorphic processes across landscapes. Geomorphology 255, 140-161. Vezzoli, R., Mercogliano, P., Pecora, S., Zollo, A., Cacciamani, C., 2015. Hydrological simulation of Po River (North Italy) discharge under climate change scenarios using the RCM COSMO-CLM. Science of The Total Environment 521, 346-358.

Climate change impact on the establishment and seasonal abundance of Invasive Mosquito Species: current state and future risk maps over southeast Europe

NASA Astrophysics Data System (ADS)

Tagaris, Efthimios; -Eleni Sotiropoulou, Rafaella; Sotiropoulos, Andreas; Spanos, Ioannis; Milonas, Panayiotis; Michaelakis, Antonios

2017-04-01

Establishment and seasonal abundance of a region for Invasive Mosquito Species (IMS) are related to climatic parameters such as temperature and precipitation. In this work the current state is assessed using data from the European Climate Assessment and Dataset (ECA&D) project over Greece and Italy for the development of current spatial risk databases of IMS. Results are validated from the installation of a prototype IMS monitoring device that has been designed and developed in the framework of the LIFE CONOPS project at key points across the two countries. Since climate models suggest changes in future temperature and precipitation rates, the future potentiality of IMS establishment and spread over Greece and Italy is assessed using the climatic parameters in 2050's provided by the NASA GISS GCM ModelE under the IPCC-A1B emissions scenarios. The need for regional climate projections in a finer grid size is assessed using the Weather Research and Forecasting (WRF) model to dynamically downscale GCM simulations. The estimated changes in the future meteorological parameters are combined with the observation data in order to estimate the future levels of the climatic parameters of interest. The final product includes spatial distribution maps presenting the future suitability of a region for the establishment and seasonal abundance of the IMS over Greece and Italy. Acknowledgement: LIFE CONOPS project "Development & demonstration of management plans against - the climate change enhanced - invasive mosquitoes in S. Europe" (LIFE12 ENV/GR/000466).

Simulation of future land use change and climate change impacts on hydrological processes in a tropical catchment

NASA Astrophysics Data System (ADS)

Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.

2017-12-01

Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment

Variability in Temperature-Related Mortality Projections under Climate Change

PubMed Central

Benmarhnia, Tarik; Sottile, Marie-France; Plante, Céline; Brand, Allan; Casati, Barbara; Fournier, Michel

2014-01-01

Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that < 1% of the variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. 2014. Variability in temperature-related mortality projections under climate change. Environ Health Perspect 122:1293–1298; http://dx.doi.org/10.1289/ehp.1306954 PMID:25036003

Characterization of extreme sea level at the European coast

NASA Astrophysics Data System (ADS)

Elizalde, Alberto; Jorda, Gabriel; Mathis, Moritz; Mikolajewicz, Uwe

2015-04-01

Extreme high sea levels arise as a combination of storm surges and particular high tides events. Future climate simulations not only project changes in the atmospheric circulation, which induces changes in the wind conditions, but also an increase in the global mean sea level by thermal expansion and ice melting. Such changes increase the risk of coastal flooding, which represents a possible hazard for human activities. Therefore, it is important to investigate the pattern of sea level variability and long-term trends at coastal areas. In order to analyze further extreme sea level events at the European coast in the future climate projections, a new setup for the global ocean model MPIOM coupled with the regional atmosphere model REMO is prepared. The MPIOM irregular grid has enhanced resolution in the European region to resolve the North and the Mediterranean Seas (up to 11 x 11 km at the North Sea). The ocean model includes as well the full luni-solar ephemeridic tidal potential for tides simulation. To simulate the air-sea interaction, the regional atmospheric model REMO is interactively coupled to the ocean model over Europe. Such region corresponds to the EuroCORDEX domain with a 50 x 50 km resolution. Besides the standard fluxes of heat, mass (freshwater), momentum and turbulent energy input, the ocean model is also forced with sea level pressure, in order to be able to capture the full variation of sea level. The hydrological budget within the study domain is closed using a hydrological discharge model. With this model, simulations for present climate and future climate scenarios are carried out to study transient changes on the sea level and extreme events. As a first step, two simulations (coupled and uncoupled ocean) driven by reanalysis data (ERA40) have been conducted. They are used as reference runs to evaluate the climate projection simulations. For selected locations at the coast side, time series of sea level are separated on its different components: tides, short time atmospheric process influence (1-30 days), seasonal cycle and interannual variability. Every sea level component is statistically compared with data from local tide gauges.

Mechanisms of shrub encroachment into Northern Chihuahuan Desert grasslands and impacts of climate change investigated using a cellular automata model

NASA Astrophysics Data System (ADS)

Caracciolo, Domenico; Istanbulluoglu, Erkan; Noto, Leonardo Valerio; Collins, Scott L.

2016-05-01

Arid and semiarid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of woody plant encroachment. Overgrazing, reduced fire frequency, and climate change are known drivers of woody plant encroachment into grasslands. In this study, relatively simple algorithms for encroachment factors (i.e., grazing, grassland fires, and seed dispersal by grazers) are proposed and implemented in the ecohydrological Cellular-Automata Tree Grass Shrub Simulator (CATGraSS). CATGraSS is used in a 7.3 km2 rectangular domain located in central New Mexico along a zone of grassland to shrubland transition, where shrub encroachment is currently active. CATGraSS is calibrated and used to investigate the relative contributions of grazing, fire frequency, seed dispersal by herbivores and climate change on shrub abundance over a 150-year period of historical shrub encroachment. The impact of future climate change is examined using a model output that realistically represents current vegetation cover as initial condition, in a series of stochastic CATGraSS future climate simulations. Model simulations are found to be highly sensitive to the initial distribution of shrub cover. Encroachment factors more actively lead to shrub propagation within the domain when the model starts with randomly distributed individual shrubs. However, when shrubs are naturally evolved into clusters, the model response to encroachment factors is muted unless the effect of seed dispersal by herbivores is amplified. The relative contribution of different drivers on modeled shrub encroachment varied based on the initial shrub cover condition used in the model. When historical weather data is used, CATGraSS predicted loss of shrub and grass cover during the 1950 s drought. While future climate change is found to amplify shrub encroachment (∼13% more shrub cover by 2100), grazing remains the dominant factor promoting shrub encroachment. When we modeled future climate change, however, encroachment still occurred at a reduced rate in the absence of grazing along with pre-grazing fire frequency because of lower shrub water stress leading to reduced shrub mortality which increases the probability of shrub establishment.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Vulnerability of Forests in India: A National Scale Assessment.

PubMed

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N H

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Vulnerability of Forests in India: A National Scale Assessment

NASA Astrophysics Data System (ADS)

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N. H.

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario

PubMed Central

Gross, Markus; Magar, Vanesa

2016-01-01

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. PMID:27788208

FUPSOL: Modelling the Future and Past Solar Influence on Earth Climate

NASA Astrophysics Data System (ADS)

Anet, J. G.; Rozanov, E.; Peter, T.

2012-04-01

Global warming is becoming one of the main threats to mankind. There is growing evidence that anthropogenic greenhouse gases have become the dominant factor since about 1970. At the same time natural factors of climate change such as solar and volcanic forcings cannot be neglected on longer time scales. Despite growing scientific efforts over the last decades in both, observations and simulations, the uncertainty of the solar contribution to the past climate change remained unacceptably high (IPCC, 2007), the reasons being on one hand missing observations of solar irradiance prior to the satellite era, and on the other hand a majority of models so far not including all processes relevant for solar-climate interactions. This project aims at elucidating the processes governing the effects of solar activity variations on Earth's climate. We use the state-of-the-art coupled atmosphere-ocean-chemistry-climate model (AOCCM) SOCOL (Schraner et al, 2008) developed in Switzerland by coupling the community Earth System Model (ESM) COSMOS distributed by MPI for Meteorology (Hamburg, Germany) with a comprehensive atmospheric chemistry module. The model solves an extensive set of equations describing the dynamics of the atmosphere and ocean, radiative transfer, transport of species, their chemical transformations, cloud formation and the hydrological cycle. The intention is to show how past solar variations affected climate and how the decrease in solar forcing expected for the next decades will affect climate on global and regional scales. We will simulate the global climate system behavior during Dalton minimum (1790 and 1830) and first half of 21st century with a series of multiyear ensemble experiments and perform these experiments using all known anthropogenic and natural climate forcing taken in different combinations to understand the effects of solar irradiance in different spectral regions and particle precipitation variability. Further on, we will quantify the solar influence on global climate in the future by evaluating the simulations and using information from past analogs such as the Dalton minimum. In the end, the project aims at reducing the uncertainty of the solar contribution to past and future climate change, which so far remained high despite many years of analyses of observational records and theoretical investigations with climate models of different complexity.

Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

PubMed

Gross, Markus; Magar, Vanesa

2016-01-01

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location.

Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions

NASA Astrophysics Data System (ADS)

Russo, T. A.; Sahoo, S.; Elliott, J. W.; Foster, I.

2016-12-01

Improving groundwater management practices under future drought conditions in agricultural regions requires three steps: 1) estimating the impacts of climate and drought on crop water demand, 2) projecting groundwater availability given climate and demand forcing, and 3) using this information to develop climate-smart policy and water use practices. We present an innovative combination of models to address the first two steps, and inform the third. Crop water demand was simulated using biophysical crop models forced by multiple climate models and climate scenarios, with one case simulating climate adaptation (e.g. modify planting or harvest time) and another without adaptation. These scenarios were intended to represent a range of drought projections and farm management responses. Nexty, we used projected climate conditions and simulated water demand across the United States as inputs to a novel machine learning-based groundwater model. The model was applied to major agricultural regions relying on the High Plains and Mississippi Alluvial aquifer systems in the US. The groundwater model integrates input data preprocessed using single spectrum analysis, mutual information, and a genetic algorithm, with an artificial neural network model. Model calibration and test results indicate low errors over the 33 year model run, and strong correlations to groundwater levels in hundreds of wells across each aquifer. Model results include a range of projected groundwater level changes from the present to 2050, and in some regions, identification and timeframe of aquifer depletion. These results quantify aquifer longevity under climate and crop scenarios, and provide decision makers with the data needed to compare scenarios of crop water demand, crop yield, and groundwater response, as they aim to balance water sustainability with food security.

High resolution projections for the western Iberian coastal low level jet in a changing climate

NASA Astrophysics Data System (ADS)

Soares, Pedro M. M.; Lima, Daniela C. A.; Cardoso, Rita M.; Semedo, Alvaro

2017-09-01

The Iberian coastal low-level jet (CLLJ) is one of the less studied boundary layer wind jet features in the Eastern Boundary Currents Systems (EBCS). These regions are amongst the most productive ocean ecosystems, where the atmosphere-land-ocean feedbacks, which include marine boundary layer clouds, coastal jets, upwelling and inland soil temperature and moisture, play an important role in defining the regional climate along the sub-tropical mid-latitude western coastal areas. Recently, the present climate western Iberian CLLJ properties were extensively described using a high resolution regional climate hindcast simulation. A summer maximum frequency of occurrence above 30 % was found, with mean maximum wind speeds around 15 ms-1, between 300 and 400 m heights (at the jet core). Since the 1990s the climate change impact on the EBCS is being studied, nevertheless some lack of consensus still persists regarding the evolution of upwelling and other components of the climate system in these areas. However, recently some authors have shown that changes are to be expected concerning the timing, intensity and spatial homogeneity of coastal upwelling, in response to future warming, especially at higher latitudes, namely in Iberia and Canaries. In this study, the first climate change assessment study regarding the Western Iberian CLLJ, using a high resolution (9 km) regional climate simulation, is presented. The properties of this CLLJ are studied and compared using two 30 years simulations: one historical simulation for the 1971-2000 period, and another simulation for future climate, in agreement with the RCP8.5 scenario, for the 2071-2100 period. Robust and consistent changes are found: (1) the hourly frequency of occurrence of the CLLJ is expected to increase in summer along the western Iberian coast, from mean maximum values of around 35 % to approximately 50 %; (2) the relative increase of the CLLJ frequency of occurrence is higher in the north off western Iberia; (3) the occurrence of the CLLJ covers larger areas both latitudinal and longitudinal; (4) the CLLJ season is lengthened extending to May and September; and, (5) there are shifts for higher occurrences of higher wind speeds and for the jet core to occur at higher heights.

Future changes in hydro-climatic extremes in the Upper Indus, Ganges, and Brahmaputra River basins

PubMed Central

Lutz, Arthur F.; Nepal, Santosh; Khanal, Sonu; Pradhananga, Saurav; Shrestha, Arun B.; Immerzeel, Walter W.

2017-01-01

Future hydrological extremes, such as floods and droughts, may pose serious threats for the livelihoods in the upstream domains of the Indus, Ganges, Brahmaputra. For this reason, the impacts of climate change on future hydrological extremes is investigated in these river basins. We use a fully-distributed cryospheric-hydrological model to simulate current and future hydrological fluxes and force the model with an ensemble of 8 downscaled General Circulation Models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios. The model is calibrated on observed daily discharge and geodetic mass balances. The climate forcing and the outputs of the hydrological model are used to evaluate future changes in climatic extremes, and hydrological extremes by focusing on high and low flows. The outcomes show an increase in the magnitude of climatic means and extremes towards the end of the 21st century where climatic extremes tend to increase stronger than climatic means. Future mean discharge and high flow conditions will very likely increase. These increases might mainly be the result of increasing precipitation extremes. To some extent temperature extremes might also contribute to increasing discharge extremes, although this is highly dependent on magnitude of change in temperature extremes. Low flow conditions may occur less frequently, although the uncertainties in low flow projections can be high. The results of this study may contribute to improved understanding on the implications of climate change for the occurrence of future hydrological extremes in the Hindu Kush–Himalayan region. PMID:29287098

Simulation of Deep Water Renewal in Crater Lake, Oregon, USA under Current and Future Climate Conditions

NASA Astrophysics Data System (ADS)

Piccolroaz, S.; Wood, T. M.; Wherry, S.; Girdner, S.

2015-12-01

We applied a 1-dimensional lake model developed to simulate deep mixing related to thermobaric instabilities in temperate lakes to Crater Lake, a 590-m deep caldera lake in Oregon's Cascade Range known for its stunning deep blue color and extremely clear water, in order to determine the frequency of deep water renewal in future climate conditions. The lake model was calibrated with 6 years of water temperature profiles, and then simulated 10 years of validation data with an RMSE ranging from 0.81°C at 50 m depth to 0.04°C at 350-460 m depth. The simulated time series of heat content in the deep lake accurately captured extreme years characterized by weak and strong deep water renewal. The lake model uses wind speed and lake surface temperature (LST) as boundary conditions. LST projections under six climate scenarios from the CMIP5 intermodel comparison project (2 representative concentration pathways X 3 general circulation models) were evaluated with air2water, a simple lumped model that only requires daily values of downscaled air temperature. air2water was calibrated with data from 1993-2011, resulting in a RMSE between simulated and observed daily LST values of 0.68°C. All future climate scenarios project increased water temperature throughout the water column and a substantive reduction in the frequency of deepwater renewal events. The least extreme scenario (CNRM-CM5, RCP4.5) projects the frequency of deepwater renewal events to decrease from about 1 in 2 years in the present to about 1 in 3 years by 2100. The most extreme scenario (HadGEM2-ES, RCP8.5) projects the frequency of deepwater renewal events to be less than 1 in 7 years by 2100 and lake surface temperatures never cooling to less than 4°C after 2050. In all RCP4.5 simulations the temperature of the entire water column is greater than 4°C for increasing periods of time. In the RCP8.5 simulations, the temperature of the entire water column is greater than 4°C year round by the year 2060 (HadGEM2) or 2080 (CNRM-CM5); thus, the conditions required for thermobaric instability induced mixing become rare or non-existent in these projections. The results indicate that the frequency of deep water renewal events could change substantially in a warmer future climate, potentially altering the lake ecosystem and water clarity.

Impact of global warming on tropical cyclone genesis in coupled and forced simulations: role of SST spatial anomalies

NASA Astrophysics Data System (ADS)

Royer, Jean-François; Chauvin, Fabrice; Daloz, Anne-Sophie

2010-05-01

The response of tropical cyclones (TC) activity to global warming has not yet reached a clear consensus in the Fourth Assessment Report (AR4) published by the Intergovernmental Panel on Climate Change (IPCC, 2007) or in the recent scientific literature. Observed series are neither long nor reliable enough for a statistically significant detection and attribution of past TC trends, and coupled climate models give widely divergent results for the future evolution of TC activity in the different ocean basins. The potential importance of the spatial structure of the future SST warming has been pointed out by Chauvin et al. (2006) in simulations performed at CNRM with the ARPEGE-Climat GCM. The current presentation describes a new set of simulations that have been performed with the ARPEGE-Climat model to try to understand the possible role of SST patterns in the TC cyclogenesis response in 15 CMIP3 coupled simulations analysed by Royer et al (2009). The new simulations have been performed with the atmospheric component of the ARPEGE-Climat GCM forced in 10 year simulations by the SST patterns from each of 15 CMIP3 simulations with different climate model at the end of the 21st century according to scenario A2. The TC analysis is based on the computation of a Convective Yearly Genesis Parameter (CYGP) and the Genesis Potential Index (GPI). The computed genesis indices for each of the ARPEGE-Climat forced simulations is compared with the indices computed directly from the initial coupled simulation. The influence of SST patterns can then be more easily assessed since all the ARPEGE-Climat simulations are performed with the same atmospheric model, whereas the original simulations used models with different parameterization and resolutions. The analysis shows that CYGP or GPI anomalies obtained with ARPEGE are as variable between each other as those obtained originally by the different IPCC models. The variety of SST patterns used to force ARPEGE explains a large part of the dispersion, though for a given SST pattern, ARPEGE does not necessarily reproduce the anomaly produced originally by the IPCC model which produced the SST anomaly. Many factors can contribute to this discrepancy, but the most prominent seems to be the absence of coupling between the forced atmospheric ARPEGE simulation and the underlying ocean. When the atmospheric model is forced by prescribed SST anomalies some retroactions between cyclogenesis and ocean are missing. There are however areas over the globe were models agree about the CYGP or GPI anomalies induced by global warming, such as the Indian Ocean that shows a better coherency in the coupled and forced responses. This could be an indication that interaction between ocean and atmosphere is not as strong there as in the other basins. Details of the results for all the other ocean basins will be presented. References: Chauvin F. and J.-F. Royer and M. Déqué , 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dynamics 27(4), 377-399. IPCC [Intergovernmental Panel for Climate Change], Climate change 2007: The physical science basis, in: S. Solomon et al. (eds.), Cambridge University Press. Royer JF, F Chauvin, 2009: Response of tropical cyclogenesis to global warming in an IPCC AR-4 scenario assessed by a modified yearly genesis parameter. "Hurricanes and Climate Change", J. B. Elsner and T. H. Jagger (Eds.), Springer, ISBN: 978-0-387-09409-0, pp 213-234.

Ecoclimatic indicators to study crop suitability in present and future climatic conditionsTIC CONDITIONS

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been simulated by the STICS, CERES and PANORAMIX crop models with the same input climatic data. Results showed that phenological stages tend to be reached earlier in the future. Significant differences were noted between indicators calculated for invariable calendar periods and indicators calculated during phenological phases. Therefore, ecoclimatic indicators are relevant to provide accurate information about crop suitability in the context of climate change. Whereas most of the indicators do not indicate any significant changes in the future, plant mortality due to frost risks from emergence to ear 1 cm tends to decrease and water supply tends to be more limiting in the future. These indicators do not replace models but represent additional tools for understanding and spatializing some results obtained by models. Their use can provide a spatial distribution of crops according to their suitability in present or future climatic conditions and enable us to minimize the risk of crop failure. It would be interesting to consider the response uncertainties according to the uncertainties we have in future climatic predictions by using different greenhouse emission scenarios and downscaling methods.

Ecoclimatic indicators to study crop suitability in present and future climatic conditions

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been simulated by the STICS, CERES and PANORAMIX crop models with the same input climatic data. Results showed that phenological stages tend to be reached earlier in the future. Significant differences were noted between indicators calculated for invariable calendar periods and indicators calculated during phenological phases. Therefore, ecoclimatic indicators are relevant to provide accurate information about crop suitability in the context of climate change. Whereas most of the indicators do not indicate any significant changes in the future, plant mortality due to frost risks from emergence to ear 1 cm tends to decrease and water supply tends to be more limiting in the future. These indicators do not replace models but represent additional tools for understanding and spatializing some results obtained by models. Their use can provide a spatial distribution of crops according to their suitability in present or future climatic conditions and enable us to minimize the risk of crop failure. It would be interesting to consider the response uncertainties according to the uncertainties we have in future climatic predictions by using different greenhouse emission scenarios and downscaling methods.

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

NASA Astrophysics Data System (ADS)

Betts, R. A.; Cox, P. M.; Collins, M.; Harris, P. P.; Huntingford, C.; Jones, C. D.

A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.

Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport

NASA Technical Reports Server (NTRS)

Kawa, S.R.; Douglass, A. R.; Patrick, L. C.; Allen, D. R.; Randall, C. E.

2004-01-01

The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.

Regional warming of hot extremes accelerated by surface energy fluxes consistent with drying soils

NASA Astrophysics Data System (ADS)

Donat, M.; Pitman, A.; Seneviratne, S. I.

2017-12-01

Strong regional differences exist in how hot temperature extremes increase under global warming. Using an ensemble of coupled climate models, we examine the regional warming rates of hot extremes relative to annual average warming rates in the same regions. We identify hotspots of accelerated warming of model-simulated hot extremes in Europe, North America, South America and Southeast China. These hotspots indicate where the warm tail of a distribution of temperatures increases faster than the average and are robust across most CMIP5 models. Exploring the conditions on the specific day the hot extreme occurs demonstrates the hotspots are explained by changes in the surface energy fluxes consistent with drying soils. Furthermore, in these hotspot regions we find a relationship between the temperature - heat flux correlation under current climate conditions and the magnitude of future projected changes in hot extremes, pointing to a potential emergent constraint for simulations of future hot extremes. However, the model-simulated accelerated warming of hot extremes appears inconsistent with observations of the past 60 years, except over Europe. The simulated acceleration of hot extremes may therefore be unreliable, a result that necessitates a re-evaluation of how climate models resolve the relevant terrestrial processes.

Projected future changes in vegetation in western North America in the 21st century

USGS Publications Warehouse

Xiaoyan, Jiang; Rauscher, Sara A.; Ringler, Todd D.; Lawrence, David M.; Williams, A. Park; Allen, Craig D.; Steiner, Allison L.; Cai, D. Michael; McDowell, Nate G.

2013-01-01

Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.

On the Value of Climate Elasticity Indices to Assess the Impact of Climate Change on Streamflow Projection using an ensemble of bias corrected CMIP5 dataset

NASA Astrophysics Data System (ADS)

Demirel, Mehmet; Moradkhani, Hamid

2015-04-01

Changes in two climate elasticity indices, i.e. temperature and precipitation elasticity of streamflow, were investigated using an ensemble of bias corrected CMIP5 dataset as forcing to two hydrologic models. The Variable Infiltration Capacity (VIC) and the Sacramento Soil Moisture Accounting (SAC-SMA) hydrologic models, were calibrated at 1/16 degree resolution and the simulated streamflow was routed to the basin outlet of interest. We estimated precipitation and temperature elasticity of streamflow from: (1) observed streamflow; (2) simulated streamflow by VIC and SAC-SMA models using observed climate for the current climate (1963-2003); (3) simulated streamflow using simulated climate from 10 GCM - CMIP5 dataset for the future climate (2010-2099) including two concentration pathways (RCP4.5 and RCP8.5) and two downscaled climate products (BCSD and MACA). The streamflow sensitivity to long-term (e.g., 30-year) average annual changes in temperature and precipitation is estimated for three periods i.e. 2010-40, 2040-70 and 2070-99. We compared the results of the three cases to reflect on the value of precipitation and temperature indices to assess the climate change impacts on Columbia River streamflow. Moreover, these three cases for two models are used to assess the effects of different uncertainty sources (model forcing, model structure and different pathways) on the two climate elasticity indices.

Modeling climate change impacts on combined sewer overflow using synthetic precipitation time series.

PubMed

Bendel, David; Beck, Ferdinand; Dittmer, Ulrich

2013-01-01

In the presented study climate change impacts on combined sewer overflows (CSOs) in Baden-Wuerttemberg, Southern Germany, were assessed based on continuous long-term rainfall-runoff simulations. As input data, synthetic rainfall time series were used. The applied precipitation generator NiedSim-Klima accounts for climate change effects on precipitation patterns. Time series for the past (1961-1990) and future (2041-2050) were generated for various locations. Comparing the simulated CSO activity of both periods we observe significantly higher overflow frequencies for the future. Changes in overflow volume and overflow duration depend on the type of overflow structure. Both values will increase at simple CSO structures that merely divide the flow, whereas they will decrease when the CSO structure is combined with a storage tank. However, there is a wide variation between the results of different precipitation time series (representative for different locations).

Climate change alters diffusion of forest pest: A model study

NASA Astrophysics Data System (ADS)

Jo, Woo Seong; Kim, Hwang-Yong; Kim, Beom Jun

2017-01-01

Population dynamics with spatial information is applied to understand the spread of pests. We introduce a model describing how pests spread in discrete space. The number of pest descendants at each site is controlled by local information such as temperature, precipitation, and the density of pine trees. Our simulation leads to a pest spreading pattern comparable to the real data for pine needle gall midge in the past. We also simulate the model in two different climate conditions based on two different representative concentration pathways scenarios for the future. We observe that after an initial stage of a slow spread of pests, a sudden change in the spreading speed occurs, which is soon followed by a large-scale outbreak. We found that a future climate change causes the outbreak point to occur earlier and that the detailed spatio-temporal pattern of the spread depends on the source position from which the initial pest infection starts.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

PubMed

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

Developing future precipitation events from historic events: An Amsterdam case study.

NASA Astrophysics Data System (ADS)

Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

2016-04-01

Due to climate change, the frequency and intensity of extreme precipitation events is expected to increase. It is therefore of high importance to develop climate change scenarios tailored towards the local and regional needs of policy makers in order to develop efficient adaptation strategies to reduce the risks from extreme weather events. Current approaches to tailor climate scenarios are often not well adopted in hazard management, since average changes in climate are not a main concern to policy makers, and tailoring climate scenarios to simulate future extremes can be complex. Therefore, a new concept has been introduced recently that uses known historic extreme events as a basis, and modifies the observed data for these events so that the outcome shows how the same event would occur in a warmer climate. This concept is introduced as 'Future Weather', and appeals to the experience of stakeholders and users. This research presents a novel method of projecting a future extreme precipitation event, based on a historic event. The selected precipitation event took place over the broader area of Amsterdam, the Netherlands in the summer of 2014, which resulted in blocked highways, disruption of air transportation, flooded buildings and public facilities. An analysis of rain monitoring stations showed that an event of such intensity has a 5 to 15 years return period. The method of projecting a future event follows a non-linear delta transformation that is applied directly on the observed event assuming a warmer climate to produce an "up-scaled" future precipitation event. The delta transformation is based on the observed behaviour of the precipitation intensity as a function of the dew point temperature during summers. The outcome is then compared to a benchmark method using the HARMONIE numerical weather prediction model, where the boundary conditions of the event from the Ensemble Prediction System of ECMWF (ENS) are perturbed to indicate a warmer climate. The two methodologies are statistically compared and evaluated. The comparison between the historic event generated by the model and the observed event will give information on the realism of the model for this event. The comparison between the delta transformation method and the future simulation will provide information on how the dynamics would affect the precipitation field, as compared to the statistical method.

Application of Temperature Index Model to Assess the Future Hydrological Regime of the Glacierized Catchments in Nepal.

NASA Astrophysics Data System (ADS)

Kayastha, R.; Kayastha, R. B.

2017-12-01

Unavailability of hydro meteorological data in the Himalayan regions is challenging on understanding the flow regimes. Temperature index model is simple yet the powerful glacio-hydrological model to simulate the discharge in the glacierized basin. Modified Positive Degree Day (MPDD) Model Version 2.0 is a grid-ded based semi distributed model with baseflow module is a robust melt modelling tools to estimate the discharge. MPDD model uses temperature and precipitation as a forcing datasets to simulate the discharge and also to obtain the snowmelt, icemelt, rain and baseflow contribution on total discharge. In this study two glacierized, Marsyangdi and Langtang catchment were investigated for the future hydrological regimes. Marsyangdi encompasses an area of 4026.19 sq. km with 20% glaciated area, whereas Langtang catchment with area of 354.64 sq. km with 36% glaciated area is studied to examine for the future climatic scenarios. The model simulates discharge well for the observed period; (1992-1998) in Marsyangdi and from (2007-2013) in Langtang catchment. The Nash-Sutcliffe Efficiency (NSE) for the both catchment were above 0.75 with the volume difference less than - 8 %. The snow and ice melts contribution in Marsyangdi were 4.7% and 10.2% whereas in Langtang the contribution is 15.3% and 23.4%, respectively. Rain contribution ( 40%) is higher than the baseflow contribution in total discharge in both basins. The future river discharge is also predicted using the future climate data from the regional climate models (RCMs) of CORDEX South Asia experiments for the medium stabilization scenario RCP4.5 and very high radiative forcing scenario RCP8.5 after bias correction. The projected future discharge of both catchment shows slightly increase in both scenarios with increase of snow and ice melt contribution on discharge. The result generated from the model can be utilized to understand the future hydrological regimes of the glacierized catchment also the impact of climate change on the snow and ice contribution on discharge. The future discharge projection is also helpful for the water resource management and also for the strategic planners.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2.

PubMed

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali; Archontoulis, Sotirios V; Zobel, Zachary; Kotamarthi, Veerabhadra R

2017-07-01

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO 2 concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high-resolution (12 km) dynamically downscaled climate projections for 1995-2004 and 2085-2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO 2 partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems. © 2017 John Wiley & Sons Ltd.

Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.; Ferschweiler, Ken; Hobbins, Michael

2014-01-01

The potential evapotranspiration (PET) that would occur with unlimited plant access to water is a central driver of simulated plant growth in many ecological models. PET is influenced by solar and longwave radiation, temperature, wind speed, and humidity, but it is often modeled as a function of temperature alone. This approach can cause biases in projections of future climate impacts in part because it confounds the effects of warming due to increased greenhouse gases with that which would be caused by increased radiation from the sun. We developed an algorithm for linking PET to extraterrestrial solar radiation (incoming top-of atmosphere solar radiation), as well as temperature and atmospheric water vapor pressure, and incorporated this algorithm into the dynamic global vegetation model MC1. We tested the new algorithm for the Northern Great Plains, USA, whose remaining grasslands are threatened by continuing woody encroachment. Both the new and the standard temperature-dependent MC1 algorithm adequately simulated current PET, as compared to the more rigorous PenPan model of Rotstayn et al. (2006). However, compared to the standard algorithm, the new algorithm projected a much more gradual increase in PET over the 21st century for three contrasting future climates. This difference led to lower simulated drought effects and hence greater woody encroachment with the new algorithm, illustrating the importance of more rigorous calculations of PET in ecological models dealing with climate change.

Combined top-down and bottom-up climate change impact assessment for the hydrological system in the Vu Gia- Thu Bon River Basin.

PubMed

Tra, Tran Van; Thinh, Nguyen Xuan; Greiving, Stefan

2018-07-15

Vu Gia- Thu Bon (VGTB) River Basin, located in the Central Coastal zone of Viet Nam currently faces water shortage. Climate change is expected to exacerbate the challenge. Therefore, there is a need to study the impacts of climate change on water shortage in the river basin. The study adopts a combined top-down and bottom-up climate change impact assessment to address the impacts of climate change on water shortage in the VGTB River Basin. A MIKE BASIN water balance model for the river basin was established to simulate the response of the hydrological system. Simulations were performed through parametrically varying temperature and precipitation to determine the vulnerability space of water shortage. General Circulation Models (GCMs) were then utilized to provide climate projections for the river basin. The output from GCMs was then mapped onto the vulnerability space determined earlier. In total, 9 out of 55 water demand nodes in the simulation are expected to face problematic conditions as future climate changes. Copyright © 2018 Elsevier B.V. All rights reserved.

Changes in groundwater recharge under projected climate in the upper Colorado River basin

USGS Publications Warehouse

Tillman, Fred; Gangopadhyay, Subhrendu; Pruitt, Tom

2016-01-01

Understanding groundwater-budget components, particularly groundwater recharge, is important to sustainably manage both groundwater and surface water supplies in the Colorado River basin now and in the future. This study quantifies projected changes in upper Colorado River basin (UCRB) groundwater recharge from recent historical (1950–2015) through future (2016–2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 climate projections. Simulated future groundwater recharge in the UCRB is generally expected to be greater than the historical average in most decades. Increases in groundwater recharge in the UCRB are a consequence of projected increases in precipitation, offsetting reductions in recharge that would result from projected increased temperatures.

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Untangling climatic and autogenic signals in peat records

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andrew J.; Young, Dylan M.; Swindles, Graeme T.

2016-04-01

Raised bogs contain potentially valuable information about Holocene climate change. However, autogenic processes may disconnect peatland hydrological behaviour from climate, and overwrite and degrade climatic signals in peat records. How can genuine climate signals be separated from autogenic changes? What level of detail of climatic information should we expect to be able to recover from peat-based reconstructions? We used an updated version of the DigiBog model to simulate peatland development and response to reconstructed Holocene rainfall and temperature reconstructions. The model represents key processes that are influential in peatland development and climate signal preservation, and includes a network of feedbacks between peat accumulation, decomposition, hydraulic structure and hydrological processes. It also incorporates the effects of temperature upon evapotranspiration, plant (litter) productivity and peat decomposition. Negative feedbacks in the model cause simulated water-table depths and peat humification records to exhibit homeostatic recovery from prescribed changes in rainfall, chiefly through changes in drainage. However, the simulated bogs show less resilience to changes in temperature, which cause lasting alterations to peatland structure and function and may therefore be more readily detectable in peat records. The network of feedbacks represented in DigiBog also provide both high- and low-pass filters for climatic information, meaning that the fidelity with which climate signals are preserved in simulated peatlands is determined by both the magnitude and the rate of climate change. Large-magnitude climatic events of an intermediate frequency (i.e., multi-decadal to centennial) are best preserved in the simulated bogs. We found that simulated humification records are further degraded by a phenomenon known as secondary decomposition. Decomposition signals are consistently offset from the climatic events that generate them, and decomposition records of dry-wet-dry climate sequences appear to be particularly vulnerable to overwriting. Our findings have direct implications not only for the interpretation of peat-based records of past climates, but also for understanding the likely vulnerability of peatland ecosystems and carbon stocks to future climate change.

Implications of plant acclimation for future climate-carbon cycle feedbacks

NASA Astrophysics Data System (ADS)

Mercado, Lina; Kattge, Jens; Cox, Peter; Sitch, Stephen; Knorr, Wolfgang; Lloyd, Jon; Huntingford, Chris

2010-05-01

The response of land ecosystems to climate change and associated feedbacks are a key uncertainty in future climate prediction (Friedlingstein et al. 2006). However global models generally do not account for the acclimation of plant physiological processes to increased temperatures. Here we conduct a first global sensitivity study whereby we modify the Joint UK land Environment Simulator (JULES) to account for temperature acclimation of two main photosynthetic parameters, Vcmax and Jmax (Kattge and Knorr 2007) and plant respiration (Atkin and Tjoelker 2003). The model is then applied over the 21st Century within the IMOGEN framework (Huntingford et al. 2004). Model simulations will provide new and improved projections of biogeochemical cycling, forest resilience, and thus more accurate projections of climate-carbon cycle feedbacks and the future evolution of the Earth System. Friedlingstein P, Cox PM, Betts R et al. (2006) Climate-carbon cycle feedback analysis, results from the C4MIP model intercomparison. Journal of Climate, 19, 3337-3353. Kattge J and Knorr W (2007): Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell and Environment 30, 1176-1190 Atkin O.K and Tjoelker, M. G. (2003): Thermal acclimation and the dynamic response of plant respiration to temperature. Trends in Plant Science 8 (7), 343-351 Huntingford C, et al. (2004) Using a GCM analogue model to investigate the potential for Amazonian forest dieback. Theoretical and Applied Climatology, 78, 177-185.

Simulating water quality and ecological status of Lake Vansjø, Norway, under land-use and climate change by linking process-oriented models with a Bayesian network.

PubMed

Couture, Raoul-Marie; Moe, S Jannicke; Lin, Yan; Kaste, Øyvind; Haande, Sigrid; Lyche Solheim, Anne

2018-04-15

Excess nutrient inputs and climate change are two of multiple stressors affecting many lakes worldwide. Lake Vansjø in southern Norway is one such eutrophic lake impacted by blooms of toxic blue-green algae (cyanobacteria), and classified as moderate ecological status under the EU Water Framework Directive. Future climate change may exacerbate the situation. Here we use a set of chained models (global climate model, hydrological model, catchment phosphorus (P) model, lake model, Bayesian Network) to assess the possible future ecological status of the lake, given the set of climate scenarios and storylines common to the EU project MARS (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). The model simulations indicate that climate change alone will increase precipitation and runoff, and give higher P fluxes to the lake, but cause little increase in phytoplankton biomass or changes in ecological status. For the storylines of future management and land-use, however, the model results indicate that both the phytoplankton biomass and the lake ecological status can be positively or negatively affected. Our results also show the value in predicting a biological indicator of lake ecological status, in this case, cyanobacteria biomass with a BN model. For all scenarios, cyanobacteria contribute to worsening the status assessed by phytoplankton, compared to using chlorophyll-a alone. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Climate change impacts on projections of excess mortality at 2030 using spatially varying ozone-temperature

EPA Science Inventory

We project the change in ozone-related mortality burden attributable to changes in climate between a historical (1995-2005) and near-future (2025-2035) time period while incorporating a non-linear and synergistic effect of ozone and temperature on mortality. We simulate air quali...

Suspended sediment source areas and future climate impact on soil erosion and sediment yield in a New York City water supply watershed, USA

NASA Astrophysics Data System (ADS)

Mukundan, Rajith; Pradhanang, Soni M.; Schneiderman, Elliot M.; Pierson, Donald C.; Anandhi, Aavudai; Zion, Mark S.; Matonse, Adão H.; Lounsbury, David G.; Steenhuis, Tammo S.

2013-02-01

High suspended sediment loads and the resulting turbidity can impact the use of surface waters for water supply and other designated uses. Changes in fluvial sediment loads influence material fluxes, aquatic geochemistry, water quality, channel morphology, and aquatic habitats. Therefore, quantifying spatial and temporal patterns in sediment loads is important both for understanding and predicting soil erosion and sediment transport processes as well as watershed-scale management of sediment and associated pollutants. A case study from the 891 km2 Cannonsville watershed, one of the major watersheds in the New York City water supply system is presented. The objective of this study was to apply Soil and Water Assessment Tool-Water Balance (SWAT-WB), a physically based semi-distributed model to identify suspended sediment generating source areas under current conditions and to simulate potential climate change impacts on soil erosion and suspended sediment yield in the study watershed for a set of future climate scenarios representative of the period 2081-2100. Future scenarios developed using nine global climate model (GCM) simulations indicate a sharp increase in the annual rates of soil erosion although a similar result in sediment yield at the watershed outlet was not evident. Future climate related changes in soil erosion and sediment yield appeared more significant in the winter due to a shift in the timing of snowmelt and also due to a decrease in the proportion of precipitation received as snow. Although an increase in future summer precipitation was predicted, soil erosion and sediment yield appeared to decrease owing to an increase in soil moisture deficit and a decrease in water yield due to increased evapotranspiration.

Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

Treesearch

Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew Peters

2013-01-01

Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...

High-resolution interpolation of climate scenarios for Canada derived from general circulation model simulations

Treesearch

D. T. Price; D. W. McKenney; L. A. Joyce; R. M. Siltanen; P. Papadopol; K. Lawrence

2011-01-01

Projections of future climate were selected for four well-established general circulation models (GCMs) forced by each of three greenhouse gas (GHG) emissions scenarios recommended by the Intergovernmental Panel on Climate Change (IPCC), namely scenarios A2, A1B, and B1 of the IPCC Special Report on Emissions Scenarios. Monthly data for the period 1961-2100 were...

Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Scenarios reveal pathways to sustain future ecosystem services in an agricultural landscape.

PubMed

Qiu, Jiangxiao; Carpenter, Stephen R; Booth, Eric G; Motew, Melissa; Zipper, Samuel C; Kucharik, Christopher J; Chen, Xi; Loheide, Steven P; Seifert, Jenny; Turner, Monica G

2018-01-01

Sustaining food production, water quality, soil retention, flood, and climate regulation in agricultural landscapes is a pressing global challenge given accelerating environmental changes. Scenarios are stories about plausible futures, and scenarios can be integrated with biophysical simulation models to explore quantitatively how the future might unfold. However, few studies have incorporated a wide range of drivers (e.g., climate, land-use, management, population, human diet) in spatially explicit, process-based models to investigate spatial-temporal dynamics and relationships of a portfolio of ecosystem services. Here, we simulated nine ecosystem services (three provisioning and six regulating services) at 220 × 220 m from 2010 to 2070 under four contrasting scenarios in the 1,345-km 2 Yahara Watershed (Wisconsin, USA) using Agro-IBIS, a dynamic model of terrestrial ecosystem processes, biogeochemistry, water, and energy balance. We asked (1) How does ecosystem service supply vary among alternative future scenarios? (2) Where on the landscape is the provision of ecosystem services most susceptible to future social-ecological changes? (3) Among alternative future scenarios, are relationships (i.e., trade-offs, synergies) among food production, water, and biogeochemical services consistent over time? Our results showed that food production varied substantially with future land-use choices and management, and its trade-offs with water quality and soil retention persisted under most scenarios. However, pathways to mitigate or even reverse such trade-offs through technological advances and sustainable agricultural practices were apparent. Consistent relationships among regulating services were identified across scenarios (e.g., trade-offs of freshwater supply vs. flood and climate regulation, and synergies among water quality, soil retention, and climate regulation), suggesting opportunities and challenges to sustaining these services. In particular, proactive land-use changes and management may buffer water quality against undesirable future climate changes, but changing climate may overwhelm management efforts to sustain freshwater supply and flood regulation. Spatially, changes in ecosystem services were heterogeneous across the landscape, underscoring the power of local actions and fine-scale management. Our research highlights the value of embracing spatial and temporal perspectives in managing ecosystem services and their complex interactions, and provides a system-level understanding for achieving sustainability of the food-water-climate nexus in agricultural landscapes. © 2017 by the Ecological Society of America.

Dynamical Downscaling of Climate Change over the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Wang, Y.; Zhang, C.; Hamilton, K. P.; Lauer, A.

2015-12-01

The pseudo-global-warming (PGW) method was applied to the Hawaii Regional Climate Model (HRCM) to dynamically downscale the projected climate in the late 21st century over the Hawaiian Islands. The initial and boundary conditions were adopted from MERRA reanalysis and NOAA SST data for the present-day simulations. The global warming increments constructed from the CMIP3 multi-model ensemble mean were added to the reanalysis and SST data to perform the future climate simulations. We found that the Hawaiian Islands are vulnerable to global warming effects and the changes are diverse due to the varied topography. The windward side will have more clouds and receive more rainfall. The increase of the moisture in the boundary layer makes the major contribution. On the contrary, the leeward side will have less clouds and rainfall. The clouds and rain can slightly slow down the warming trend over the windward side. The temperature increases almost linearly with the terrain height. Cloud base and top heights will slightly decline in response to the slightly lower trade wind inversion base height, while the trade wind occurrence frequency will increase by about 8% in the future. More extreme rainfall events will occur in the warming climate over the Hawaiian Islands. And the snow cover on the top of Mauna Kea and Mauna Loa will nearly disappear in the future winter.

Climatic Controls on Forest Productivity in Western North America; Variability, Covariability, and Projected Change

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Mote, P.; Sparrow, S.; Massey, N.

2016-12-01

The forests of western North America serve as a carbon sink sequestering carbon and slowing the rise of CO2 in the atmosphere. Though still positive, the rate of net carbon uptake has been in decline over the past two decades. Regional drought has been shown to slow forest productivity and net carbon uptake despite warmer temperatures and longer growing seasons. With drought conditions projected to increase in frequency and severity under climate change there is concern that these forests' capacity as an effective carbon sink will continue to decrease in the future. To investigate how changes in regional hydroclimate may affect future carbon uptake in western US forests we dynamically downscaled global climate simulations using a 25-km resolution regional climate model HadRM3P with the land surface scheme MOSES2. We generated a 100-member ensemble of simulations for an historical period (1985-2015) and mid-21st century period (2030-2060) under Representative Concentration Pathway 8.5. We evaluated the effects of regional changes in atmospheric moisture demand, seasonality of water supply, and water stress on forest productivity and carbon uptake. We investigated how these changes in hydroclimate interact with the relaxing of temperature controls. This work can inform future adaptation efforts through improving our understanding of climatic controls on forest carbon sequestration.

Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.

Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Miller, Paul A.; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

2013-09-01

One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

NASA Astrophysics Data System (ADS)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

Climate Change Impacts on Sediment Transport In a Lowland Watershed System: Controlling Processes and Projection

NASA Astrophysics Data System (ADS)

al Aamery, N. M. H.; Mahoney, D. T.; Fox, J.

2017-12-01

Future climate change projections suggest extreme impacts on watershed hydrologic systems for some regions of the world including pronounced increases in surface runoff and instream flows. Yet, there remains a lack of research focused on how future changes in hydrologic extremes, as well as relative hydrologic mean changes, impact sediment redistribution within a watershed and sediment flux from a watershed. The authors hypothesized that variations in mean and extreme changes in turn may impact sediments in depositional and erosional dominance in a manner that may not be obvious to the watershed manager. Therefore, the objectives of this study were to investigate the inner processes connecting the combined effect of extreme climate change projections on the vegetation, upland erosion, and instream processes to produce changes in sediment redistribution within watersheds. To do so, research methods were carried out by the authors including simulating sediment processes in forecast and hindcast periods for a lowland watershed system. Publically available climate realizations from several climate factors and the Soil Water Assessment Tool (SWAT) were used to predict hydrologic conditions for the South Elkhorn Watershed in central Kentucky, USA to 2050. The results of the simulated extreme and mean hydrological components were used in simulating upland erosion with the connectivity processes consideration and thereafter used in building and simulating the instream erosion and deposition of sediment processes with the consideration of surface fine grain lamina (SFGL) layer controlling the benthic ecosystem. Results are used to suggest the dominance of erosional and depositional redistribution of sediments under different scenarios associated with extreme and mean hydrologic forecasting. The results are discussed in reference to the benthic ecology of the stream system providing insight on how water managers might consider sediment redistribution in a changing climate.

Risk of spring frost to apple production under future climate scenarios: the role of phenological acclimation.

PubMed

Eccel, Emanuele; Rea, Roberto; Caffarra, Amelia; Crisci, Alfonso

2009-05-01

In the context of global warming, the general trend towards earlier flowering dates of many temperate tree species is likely to result in an increased risk of damage from exposure to frost. To test this hypothesis, a phenological model of apple flowering was applied to a temperature series from two locations in an important area for apple production in Europe (Trentino, Italy). Two simulated 50-year climatic projections (A2 and B2 of the Intergovernmental Panel on Climate Change--Special Report on Emission Scenarios) from the HadCM3 general circulation model were statistically downscaled to the two sites. Hourly temperature records over a 40-year period were used as the reference for past climate. In the phenological model, the heat requirement (degree hours) for flowering was parameterized using two approaches; static (constant over time) and dynamic (climate dependent). Parameterisation took into account the trees' adaptation to changing temperatures based on either past instrumental records or the downscaled outputs from the climatic simulations. Flowering dates for the past 40 years and simulated flowering dates for the next 50 years were used in the model. A significant trend towards earlier flowering was clearly detected in the past. This negative trend was also apparent in the simulated data. However, the significance was less apparent when the "dynamic" setting for the degree hours requirement was used in the model. The number of frost episodes and flowering dates, on an annual basis, were graphed to assess the risk of spring frost. Risk analysis confirmed a lower risk of exposure to frost at present than in the past, and probably either constant or a slightly lower risk in future, especially given that physiological processes are expected to acclimate to higher temperatures.

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

High-resolution RCMs as pioneers for future GCMs

NASA Astrophysics Data System (ADS)

Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H.

2017-12-01

Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies.

Evaluating the variability in surface water reservoir planning characteristics during climate change impacts assessment

NASA Astrophysics Data System (ADS)

Soundharajan, Bankaru-Swamy; Adeloye, Adebayo J.; Remesan, Renji

2016-07-01

This study employed a Monte-Carlo simulation approach to characterise the uncertainties in climate change induced variations in storage requirements and performance (reliability (time- and volume-based), resilience, vulnerability and sustainability) of surface water reservoirs. Using a calibrated rainfall-runoff (R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change-perturbed future runoff scenarios. The resulting runoff ensembles were used to force simulation models of the behaviour of the reservoir to produce 'populations' of required reservoir storage capacity to meet demands, and the performance. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the variability in the impacts. The methodology was applied to the Pong reservoir on the Beas River in northern India. The reservoir serves irrigation and hydropower needs and the hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall, both of which are predicted to change due to climate change. The results show that required reservoir capacity is highly variable with a coefficient of variation (CV) as high as 0.3 as the future climate becomes drier. Of the performance indices, the vulnerability recorded the highest variability (CV up to 0.5) while the volume-based reliability was the least variable. Such variabilities or uncertainties will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of their sheer magnitudes as obtained in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.

The effect of changing wind forcing on Antarctic ice shelf melting in high-resolution, global sea ice-ocean simulations with the Accelerated Climate Model for Energy (ACME)

NASA Astrophysics Data System (ADS)

Asay-Davis, Xylar; Price, Stephen; Petersen, Mark; Wolfe, Jonathan

2017-04-01

The capability for simulating sub-ice shelf circulation and submarine melting and freezing has recently been added to the U.S. Department of Energy's Accelerated Climate Model for Energy (ACME). With this new capability, we use an eddy permitting ocean model to conduct two sets of simulations in the spirit of Spence et al. (GRL, 41, 2014), who demonstrate increased warm water upwelling along the Antarctic coast in response to poleward shifting and strengthening of Southern Ocean westerly winds. These characteristics, symptomatic of a positive Southern Annular Mode (SAM), are projected to continue into the 21st century under anthropogenic climate change (Fyfe et al., J. Clim., 20, 2007). In our first simulation, we force the climate model using the standard CORE interannual forcing dataset (Large and Yeager; Clim. Dyn., 33, 2009). In our second simulation, we force our climate model using an altered version of CORE interannual forcing, based on the latter half of the full time series, which we take as a proxy for a future climate state biased towards a positive SAM. We compare ocean model states and sub-ice shelf melt rates with observations, exploring sources of model biases as well as the effects of the two forcing scenarios.

Detection and Attribution of Regional Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Simulations of the Mid-Pliocene Warm Period Using Two Versions of the NASA-GISS ModelE2-R Coupled Model

NASA Technical Reports Server (NTRS)

Chandler, M. A.; Sohl, L. E.; Jonas, J. A.; Dowsett, H. J.; Kelley, M.

2013-01-01

The mid-Pliocene Warm Period (mPWP) bears many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change (IPCC, 2007). Both marine and terrestrial data point to high-latitude temperature amplification, including large decreases in sea ice and land ice, as well as expansion of warmer climate biomes into higher latitudes. Here we present our most recent simulations of the mid-Pliocene climate using the CMIP5 version of the NASAGISS Earth System Model (ModelE2-R). We describe the substantial impact associated with a recent correction made in the implementation of the Gent-McWilliams ocean mixing scheme (GM), which has a large effect on the simulation of ocean surface temperatures, particularly in the North Atlantic Ocean. The effect of this correction on the Pliocene climate results would not have been easily determined from examining its impact on the preindustrial runs alone, a useful demonstration of how the consequences of code improvements as seen in modern climate control runs do not necessarily portend the impacts in extreme climates.Both the GM-corrected and GM-uncorrected simulations were contributed to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. The corrected version yields results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene, especially the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea, which in the new simulation appears to be far more realistic than previously found with older versions of the GISS model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterisations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

Can climate models be tuned to simulate the global mean absolute temperature correctly?

NASA Astrophysics Data System (ADS)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

Projecting optimal land-use and -management strategies under population growth and climate change using a coupled ecosystem & land use model framework

NASA Astrophysics Data System (ADS)

Rabin, Sam; Alexander, Peter; Anthoni, Peter; Henry, Roslyn; Huntingford, Chris; Pugh, Thomas; Rounsevell, Mark; Arneth, Almut

2017-04-01

A major question facing humanity is how well agricultural production systems will be able to feed the world in a future of rapid climate change, population growth, and demand shifts—all while minimizing our impact on the natural world. Global modeling has frequently been used to investigate certain aspects of this question, but in order to properly address the challenge, no one part of the human-environmental system can be assessed in isolation. It is especially critical that the effect on agricultural yields of changing temperature and precipitation regimes (including seasonal timing and frequency and intensity of extreme events), as well as rising atmospheric carbon dioxide levels, be taken into account when planning for future food security. Coupled modeling efforts, where changes in various parts of the Earth system are allowed to feed back onto one another, represent a powerful strategy in this regard. This presentation describes the structure and initial results of an effort to couple a biologically-representative vegetation and crop production simulator, LPJ-GUESS, with the climate emulator IMOGEN and the land-use model PLUMv2. With IMOGEN providing detailed future weather simulations, LPJ-GUESS simulates natural vegetation as well as cropland and pasture/rangeland; the simulated exchange of greenhouse gases between the land and atmosphere feeds back into IMOGEN's predictions. LPJ-GUESS also produces potential vegetation yields for irrigated vs. rainfed crops under three levels of nitrogen fertilizer addition. PLUMv2 combines these potential yields with endogenous demand and agricultural commodity price to calculate an optimal set of land use distributions and management strategies across the world for the next five years of simulation, based on socio-economic scenario data. These land uses are then fed back into LPJ-GUESS, and the cycle of climate, greenhouse gas emissions, crop yields, and land-use change continues. The globally gridded nature of the model—at 0.5-degree resolution across the world—generates spatially explicit projections at a sub-national scale relevant to individual land managers. Here, we present the results of using the LPJ-GUESS-PLUM-IMOGEN coupled model to project agricultural production and management strategies under several scenarios of greenhouse gas emissions (the Representative Concentration Pathways) and socioeconomic futures (the Shared Socioeconomic Pathways) through the year 2100. In the future, the coupled model could be used to generate projections for alternative scenarios: for example, to consider the implications from land-based climate change mitigation policies, or changes to international trade tariffs regimes.

Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain

NASA Astrophysics Data System (ADS)

Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

2016-01-01

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3˜3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0˜19.4 %) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha-1 year-1, except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain.

PubMed

Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

2016-01-01

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4%) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha(-1) year(-1), except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

Simulation of future stream alkalinity under changing deposition and climate scenarios.

PubMed

Welsch, Daniel L; Cosby, B Jack; Hornberger, George M

2006-08-31

Models of soil and stream water acidification have typically been applied under scenarios of changing acidic deposition, however, climate change is usually ignored. Soil air CO2 concentrations have potential to increase as climate warms and becomes wetter, thus affecting soil and stream water chemistry by initially increasing stream alkalinity at the expense of reducing base saturation levels on soil exchange sites. We simulate this change by applying a series of physically based coupled models capable of predicting soil air CO2 and stream water chemistry. We predict daily stream water alkalinity for a small catchment in the Virginia Blue Ridge for 60 years into the future given stochastically generated daily climate values. This is done for nine different combinations of climate and deposition. The scenarios for both climate and deposition include a static scenario, a scenario of gradual change, and a scenario of abrupt change. We find that stream water alkalinity continues to decline for all scenarios (average decrease of 14.4 microeq L-1) except where climate is gradually warming and becoming more moist (average increase of 13 microeq L-1). In all other scenarios, base cation removal from catchment soils is responsible for limited alkalinity increase resulting from climate change. This has implications given the extent that acidification models are used to establish policy and legislation concerning deposition and emissions.

Back to the future: using historical climate variation to project near-term shifts in habitat suitable for coast redwood.

PubMed

Fernández, Miguel; Hamilton, Healy H; Kueppers, Lara M

2015-11-01

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine-scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind-driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs' ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high-resolution historic climatic record, we developed multiple fine-scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under 'normal' combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020-2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high-resolution alternative to downscaled GCM outputs for near-term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean-atmosphere dynamics that are not represented by coarse-scale GCMs. © 2015 John Wiley & Sons Ltd.

Watershed scale response to climate change--Yampa River Basin, Colorado

USGS Publications Warehouse

Hay, Lauren E.; Battaglin, William A.; Markstrom, Steven L.

2012-01-01

General Circulation Model simulations of future climate through 2099 project a wide range of possible scenarios. To determine the sensitivity and potential effect of long-term climate change on the freshwater resources of the United States, the U.S. Geological Survey Global Change study, "An integrated watershed scale response to global change in selected basins across the United States" was started in 2008. The long-term goal of this national study is to provide the foundation for hydrologically based climate change studies across the nation. Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Yampa River Basin at Steamboat Springs, Colorado.

Long-term Ozone Changes and Associated Climate Impacts in CMIP5 Simulations

NASA Technical Reports Server (NTRS)

Eyring, V.; Arblaster, J. M.; Cionni, I.; Sedlacek, J.; Perlwitz, J.; Young, P. J.; Bekki, S.; Bergmann, D.; Cameron-Smith, P.; Collins, W. J.;

Reassessing Pliocene temperature gradients

NASA Astrophysics Data System (ADS)

Tierney, J. E.

2017-12-01

With CO2 levels similar to present, the Pliocene Warm Period (PWP) is one of our best analogs for climate change in the near future. Temperature proxy data from the PWP describe dramatically reduced zonal and meridional temperature gradients that have proved difficult to reproduce with climate model simulations. Recently, debate has emerged regarding the interpretation of the proxies used to infer Pliocene temperature gradients; these interpretations affect the magnitude of inferred change and the degree of inconsistency with existing climate model simulations of the PWP. Here, I revisit the issue using Bayesian proxy forward modeling and prediction that propagates known uncertainties in the Mg/Ca, UK'37, and TEX86 proxy systems. These new spatiotemporal predictions are quantitatively compared to PWP simulations to assess probabilistic agreement. Results show generally good agreement between existing Pliocene simulations from the PlioMIP ensemble and SST proxy data, suggesting that exotic changes in the ocean-atmosphere are not needed to explain the Pliocene climate state. Rather, the spatial changes in SST during the Pliocene are largely consistent with elevated CO2 forcing.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled futuremore » climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.« less

Ecosystem service impacts of future changes in CO2, climate, and land use as simulated by a coupled vegetation/land-use model system

NASA Astrophysics Data System (ADS)

Rabin, S. S.; Alexander, P.; Henry, R.; Anthoni, P.; Pugh, T.; Rounsevell, M.; Arneth, A.

2017-12-01

In a future of increasing atmospheric carbon dioxide (CO2) concentrations, changing climate, increasing human populations, and changing socioeconomic dynamics, the global agricultural system will need to adapt in order to feed the world. Global modeling can help to explore what these adaptations will look like, and their potential impacts on ecosystem services. To do so, however, the complex interconnections among the atmosphere, terrestrial ecosystems, and society mean that these various parts of the Earth system must be examined as an interconnected whole. With the goal of answering these questions, a model system has been developed that couples a biologically-representative global vegetation model, LPJ-GUESS, with the PLUMv2 land use model. LPJ-GUESS first simulates—at 0.5º resolution across the world—the potential yield of various crops and pasture under a range of management intensities for a time step given its atmospheric CO2 level and climatic forcings. These potential yield simulations are fed into PLUMv2, which uses them in conjunction with endogenous agricultural commodity demand and prices to produce land use and management inputs (fertilizer and irrigation water) at a sub-national level for the next time step. This process is performed through 2100 for a range of future climate and societal scenarios—the Representative Concentration Pathways (RCPs) and the Shared Socioeconomic Pathways (SSPs), respectively—providing a thorough exploration of possible trajectories of land use and land cover change. The land use projections produced by PLUMv2 are fed back into LPJ-GUESS to simulate the future impacts of land use change, along with increasing CO2 and climate change, on terrestrial ecosystems. This integrated analysis examines the resulting impacts on regulating and provisioning ecosystem services affecting biophysics (albedo); carbon, nitrogen, and water cycling; and the emission of biogenic volatile organic compounds (BVOCs).

Projected Irrigation Requirement Under Climate Change in Korean Peninsula by Apply Global Hydrologic Model to Local Scale.

NASA Astrophysics Data System (ADS)

Yang, B.; Lee, D. K.

2016-12-01

Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavas, Daniel R.; Izaurralde, Roberto C.; Thomson, Allison M.

Increasing atmospheric greenhouse gas concentrations are expected to induce significant climate change over the next century and beyond, but the impacts on society remain highly uncertain. This work examines potential climate change impacts on the productivity of five major crops in northeastern China: canola, corn, potato, rice, and winter wheat. In addition to determining domain-wide trends, the objective is to identify vulnerable and emergent regions under future climate conditions, defined as having a greater than 10% decrease and increase in productivity, respectively. Data from the ICTP RegCM3 regional climate model for baseline (1961-1990) and future (2071-2100) periods under A2 scenariomore » conditions are used as input in the EPIC agro-ecosystem simulation model in the domain [30ºN, 108ºE] to [42ºN, 123ºE]. Simulations are performed with and without the enhanced CO2 fertilization effect. Results indicate that aggregate potential productivity (i.e. if the crop is grown everywhere) increases 6.5% for rice, 8.3% for canola, 18.6% for corn, 22.9% for potato, and 24.9% for winter wheat, although with significant spatial variability for each crop. However, absent the enhanced CO2 fertilization effect, potential productivity declines in all cases ranging from 2.5-12%. Interannual yield variability remains constant or declines in all cases except rice. Climate variables are found to be more significant drivers of simulated yield changes than changes in soil properties, except in the case of potato production in the northwest where the effects of wind erosion are more significant. Overall, in the future period corn and winter wheat benefit significantly in the North China Plain, rice remains dominant in the southeast and emerges in the northeast, potato and corn yields become viable in the northwest, and potato yields suffer in the southwest with no other crop emerging as a clear beneficiary from among those simulated in this study.« less

Impacts of Ozone-vegetation Interactions and Biogeochemical Feedbacks on Atmospheric Composition and Air Quality Under Climate Change

NASA Astrophysics Data System (ADS)

Sadeke, M.; Tai, A. P. K.; Lombardozzi, D.; Val Martin, M.

2015-12-01

Surface ozone pollution is one of the major environmental concerns due to its damaging effects on human and vegetation. One of the largest uncertainties of future surface ozone prediction comes from its interaction with vegetation under a changing climate. Ozone can be modulated by vegetation through, e.g., biogenic emissions, dry deposition and transpiration. These processes are in turn affected by chronic exposure to ozone via lowered photosynthesis rate and stomatal conductance. Both ozone and vegetation growth are expected to be altered by climate change. To better understand these climate-ozone-vegetation interactions and possible feedbacks on ozone itself via vegetation, we implement an online ozone-vegetation scheme [Lombardozzi et al., 2015] into the Community Earth System Model (CESM) with active atmospheric chemistry, climate and land surface components. Previous overestimation of surface ozone in eastern US, Canada and Europe is shown to be reduced by >8 ppb, reflecting improved model-observation comparison. Simulated surface ozone is lower by 3.7 ppb on average globally. Such reductions (and improvements) in simulated ozone are caused mainly by lower isoprene emission arising from reduced leaf area index in response to chronic ozone exposure. Effects via transpiration are also potentially significant but require better characterization. Such findings suggest that ozone-vegetation interaction may substantially alter future ozone simulations, especially under changing climate and ambient CO2 levels, which would further modulate ozone-vegetation interactions. Inclusion of such interactions in Earth system models is thus necessary to give more realistic estimation and prediction of surface ozone. This is crucial for better policy formulation regarding air quality, land use and climate change mitigation. Reference list: Lombardozzi, D., et al. "The Influence of Chronic Ozone Exposure on Global Carbon and Water Cycles." Journal of Climate 28.1 (2015): 292-305.