WorldWideScience

Sample records for climate modelling sensitivity

  1. Climate Sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Lindzen, Richard [M.I.T.

    2011-11-09

    Warming observed thus far is entirely consistent with low climate sensitivity. However, the result is ambiguous because the sources of climate change are numerous and poorly specified. Model predictions of substantial warming aredependent on positive feedbacks associated with upper level water vapor and clouds, but models are notably inadequate in dealing with clouds and the impacts of clouds and water vapor are intimately intertwined. Various approaches to measuring sensitivity based on the physics of the feedbacks will be described. The results thus far point to negative feedbacks. Problems with these approaches as well as problems with the concept of climate sensitivity will be described.

  2. Climate stability and sensitivity in some simple conceptual models

    Energy Technology Data Exchange (ETDEWEB)

    Bates, J. Ray [University College Dublin, Meteorology and Climate Centre, School of Mathematical Sciences, Dublin (Ireland)

    2012-02-15

    A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 x CO{sub 2} sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa. (orig.)

  3. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  4. Feedbacks, climate sensitivity, and the limits of linear models

    Science.gov (United States)

    Rugenstein, M.; Knutti, R.

    2015-12-01

    The term "feedback" is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify, and quantify parts of the complex Earth system. We combine large (>120 member) ensemble GCM and EMIC step forcing simulations over a broad range of forcing levels with a historical and educational perspective to organize existing ideas around feedbacks and linear forcing-feedback models. With a new method overcoming internal variability and initial condition problems we quantify the non-constancy of the climate feedback parameter. Our results suggest a strong state- and forcing-dependency of feedbacks, which is not considered appropriately in many studies. A non-constant feedback factor likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. We discuss implications for the definition of the forcing term and its various adjustments. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.

  5. Sensitivity of Hydrologic Response to Climate Model Debiasing Procedures

    Science.gov (United States)

    Channell, K.; Gronewold, A.; Rood, R. B.; Xiao, C.; Lofgren, B. M.; Hunter, T.

    2017-12-01

    Climate change is already having a profound impact on the global hydrologic cycle. In the Laurentian Great Lakes, changes in long-term evaporation and precipitation can lead to rapid water level fluctuations in the lakes, as evidenced by unprecedented change in water levels seen in the last two decades. These fluctuations often have an adverse impact on the region's human, environmental, and economic well-being, making accurate long-term water level projections invaluable to regional water resources management planning. Here we use hydrological components from a downscaled climate model (GFDL-CM3/WRF), to obtain future water supplies for the Great Lakes. We then apply a suite of bias correction procedures before propagating these water supplies through a routing model to produce lake water levels. Results using conventional bias correction methods suggest that water levels will decline by several feet in the coming century. However, methods that reflect the seasonal water cycle and explicitly debias individual hydrological components (overlake precipitation, overlake evaporation, runoff) imply that future water levels may be closer to their historical average. This discrepancy between debiased results indicates that water level forecasts are highly influenced by the bias correction method, a source of sensitivity that is commonly overlooked. Debiasing, however, does not remedy misrepresentation of the underlying physical processes in the climate model that produce these biases and contribute uncertainty to the hydrological projections. This uncertainty coupled with the differences in water level forecasts from varying bias correction methods are important for water management and long term planning in the Great Lakes region.

  6. Comparison of two potato simulation models under climate change. I. Model calibration and sensitivity analyses

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

    To analyse the effects of climate change on potato growth and production, both a simple growth model, POTATOS, and a comprehensive model, NPOTATO, were applied. Both models were calibrated and tested against results from experiments and variety trials in The Netherlands. The sensitivity of model

  7. Differences between seasonal and mean annual energy balance model calculations of climate and climate sensitivity

    Science.gov (United States)

    North, G. R.; Coakley, J. A., Jr.

    1979-01-01

    The paper extends a simple Budyko-Sellers mean annual energy balance climate model with diffusive transport to include a seasonal cycle. In the model the latitudinal distribution of the zonal average surface temperature is represented by Legendre polynomials and its time-dependence by a Fourier sine-cosine series, and it has three parameters adjusted so that the observed amplitudes of the Northern Hemisphere zonal mean surface temperature are recovered. The seasonal model is used to reveal how the annual mean climate and the sensitivity to changes in incident radiation differ from the predictions obtained with the corresponding mean annual model. The distribution of the incident solar radiation in the models is shown to be insensitive to changes in the eccentricity and the longitude of perihelion and sensitive only to changes in the obliquity of the earth, and for past orbital changes both the seasonal and the mean annual model fail to produce glacial advances of the magnitude that are thought to have occurred.

  8. Increase of carbon cycle feedback with climate sensitivity: results from a coupled climate and carbon cycle model

    International Nuclear Information System (INIS)

    Govindasamy, B.; Thompson, S.; Mirin, A.; Wickett, M.; Caldeira, K.; Delire, C.

    2005-01-01

    Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO 2 content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 scenario are used. We use a fully coupled climate and carbon cycle model, the INtegrated Climate and CArbon model (INCCA), the NCAR/DOE Parallel Climate Model coupled to the IBIS terrestrial biosphere model and a modified OCMIP ocean biogeochemistry model. In our integrated model, for scenarios with year 2100 global warming increasing from 0 to 8 K, land uptake decreases from 47% to 29% of total CO 2 emissions. Due to competing effects, ocean uptake (16%) shows almost no change at all. Atmospheric CO 2 concentration increases are 48% higher in the run with 8 K global climate warming than in the case with no warming. Our results indicate that carbon cycle amplification of climate warming will be greater if there is higher climate sensitivity to increased atmospheric CO 2 content; the carbon cycle feedback factor increases from 1.13 to 1.48 when global warming increases from 3.2 to 8 K

  9. Sensitivity of climate models: Comparison of simulated and observed patterns for past climates

    International Nuclear Information System (INIS)

    Prell, W.L.; Webb, T. III.

    1992-08-01

    Predicting the potential climatic effects of increased concentrations of atmospheric carbon dioxide requires the continuing development of climate models. Confidence in the predictions will be much enhanced once the models are thoroughly tested in terms of their ability to simulate climates that differ significantly from today's climate. As one index of the magnitude of past climate change, the global mean temperature increase during the past 18,000 years is similar to that predicted for carbon dioxide--doubling. Simulating the climatic changes of the past 18,000 years, as well as the warmer-than-present climate of 6000 years ago and the climate of the last interglacial, around 126,000 years ago, provides an excellent opportunity to test the models that are being used in global climate change research. During the past several years, we have used paleoclimatic data to test the accuracy of the National Center for Atmospheric Research, Community Climate Model, Version 0, after changing its boundary conditions to those appropriate for past climates. We have assembled regional and near-global paleoclimatic data sets of pollen, lake level, and marine plankton data and calibrated many of the data in terms of climatic variables. We have also developed methods that permit direct quantitative comparisons between the data and model results. Our research has shown that comparing the model results with the data is an evolutionary process, because the models, the data, and the methods for comparison are continually being improved. During 1992, we have completed new modeling experiments, further analyzed previous model experiments, compiled new paleodata, made new comparisons between data and model results, and participated in workshops on paleoclimatic modeling

  10. The role of clouds in climate model bias and sensitivity

    NARCIS (Netherlands)

    Lacagnina, C.

    2014-01-01

    Clouds are prominent in the climate system, since they play a major role in the way energy and water are cycled through the atmosphere. One of the most relevant impacts of the clouds on the earth's climate is their interaction with the radiative fluxes. Changes in this interaction in response to an

  11. Analysis of Sea Ice Cover Sensitivity in Global Climate Model

    Directory of Open Access Journals (Sweden)

    V. P. Parhomenko

    2014-01-01

    Full Text Available The paper presents joint calculations using a 3D atmospheric general circulation model, an ocean model, and a sea ice evolution model. The purpose of the work is to analyze a seasonal and annual evolution of sea ice, long-term variability of a model ice cover, and its sensitivity to some parameters of model as well to define atmosphere-ice-ocean interaction.Results of 100 years simulations of Arctic basin sea ice evolution are analyzed. There are significant (about 0.5 m inter-annual fluctuations of an ice cover.The ice - atmosphere sensible heat flux reduced by 10% leads to the growth of average sea ice thickness within the limits of 0.05 m – 0.1 m. However in separate spatial points the thickness decreases up to 0.5 m. An analysis of the seasonably changing average ice thickness with decreasing, as compared to the basic variant by 0.05 of clear sea ice albedo and that of snow shows the ice thickness reduction in a range from 0.2 m up to 0.6 m, and the change maximum falls for the summer season of intensive melting. The spatial distribution of ice thickness changes shows, that on the large part of the Arctic Ocean there was a reduction of ice thickness down to 1 m. However, there is also an area of some increase of the ice layer basically in a range up to 0.2 m (Beaufort Sea. The 0.05 decrease of sea ice snow albedo leads to reduction of average ice thickness approximately by 0.2 m, and this value slightly depends on a season. In the following experiment the ocean – ice thermal interaction influence on the ice cover is estimated. It is carried out by increase of a heat flux from ocean to the bottom surface of sea ice by 2 W/sq. m in comparison with base variant. The analysis demonstrates, that the average ice thickness reduces in a range from 0.2 m to 0.35 m. There are small seasonal changes of this value.The numerical experiments results have shown, that an ice cover and its seasonal evolution rather strongly depend on varied parameters

  12. Sensitivity analysis of a forest gap model concerning current and future climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Lasch, P.; Suckow, F.; Buerger, G.; Lindner, M.

    1998-07-01

    The ability of a forest gap model to simulate the effects of climate variability and extreme events depends on the temporal resolution of the weather data that are used and the internal processing of these data for growth, regeneration and mortality. The climatological driving forces of most current gap models are based on monthly means of weather data and their standard deviations, and long-term monthly means are used for calculating yearly aggregated response functions for ecological processes. In this study, the results of sensitivity analyses using the forest gap model FORSKA{sub -}P and involving climate data of different resolutions, from long-term monthly means to daily time series, including extreme events, are presented for the current climate and for a climate change scenario. The model was applied at two sites with differing soil conditions in the federal state of Brandenburg, Germany. The sensitivity of the model concerning climate variations and different climate input resolutions is analysed and evaluated. The climate variability used for the model investigations affected the behaviour of the model substantially. (orig.)

  13. Analysis of Evapotranspiration Model Sensitivity to Climate and Vegetation Parameters With Dependence

    Science.gov (United States)

    Levy, M. C.

    2013-12-01

    Evapotranspiration (ET) is a dominant component of the global water balance and in the study of hydroclimatic effects of climate change. However, its computation remains challenging due to the multiple environmental factors that influence the magnitude of ET flux. Therefore, understanding the sensitivity of ET models to changes in climate and vegetation inputs remains a major concern for hydrologists, biometeorologists, and climatologists. To date, sensitivity analyses (SAs) of evapotranspiration (ET) models are incomplete on two counts: 1) contemporary, data-driven SAs do not account for the effects of both climate and vegetation input variables on model output (ET estimates); and 2) SAs do not account for the effects of input variable correlation on model output. This is problematic because of the potentially dominant role of vegetation in controlling ET, and the non-trivial interactions between climate variables, and climate and vegetation variables. Ignoring the role of interactions between variables limits the value of SAs for reducing model dimensionality and guiding model calibration, and may lead to incorrect assessments of environmental system response to climate change, where the synchronies between climate variables change over time and space. The problems addressed by this study are the issues identified above: the lack of accounting for both climate and vegetation inputs, and correlated inputs, on ET model SAs. This study: 1) performs a SA of the standardized American Society of Civil Engineers (ASCE) Penman-Monteith (PM) equation for reference ET to both climate and vegetation variables using a mixed empirical and simulation based global Sobol' SA; and 2) performs a SA of ASCE PM reference ET to both climate and vegetation variables through a simulation-based analysis using a new Sobol' SA analogue developed for models with correlated input variables. At the time of completion, this study constitutes the first use of a Sobol' SA (Sobol', 2001

  14. Modelled climate sensitivity of the mass balance of Morteratschgletscher and its dependence on albedo parameterization

    NARCIS (Netherlands)

    Klok, E.J.; Oerlemans, J.

    2004-01-01

    This paper presents a study of the climate sensitivity of the mass balance of Morteratschgletscher in Switzerland, estimated from a two-dimensional mass balance model. Since the albedo scheme chosen is often the largest error source in mass balance models, we investigated the impact of using

  15. Canadian RCM projected climate-change signal and its sensitivity to model errors

    Science.gov (United States)

    Sushama, L.; Laprise, R.; Caya, D.; Frigon, A.; Slivitzky, M.

    2006-12-01

    Climate change is commonly evaluated as the difference between simulated climates under future and current forcings, based on the assumption that systematic errors in the current-climate simulation do not affect the climate-change signal. In this paper, we investigate the Canadian Regional Climate Model (CRCM) projected climate changes in the climatological means and extremes of selected basin-scale surface fields and its sensitivity to model errors for Fraser, Mackenzie, Yukon, Nelson, Churchill and Mississippi basins, covering the major climate regions in North America, using current (1961-1990) and future climate simulations (2041-2070; A2 and IS92a scenarios) performed with two versions of CRCM.Assessment of errors in both model versions suggests the presence of nonnegligible biases in the surface fields, due primarily to the internal dynamics and physics of the regional model and to the errors in the driving data at the boundaries. In general, results demonstrate that, in spite of the errors in the two model versions, the simulated climate-change signals associated with the long-term monthly climatology of various surface water balance components (such as precipitation, evaporation, snow water equivalent (SWE), runoff and soil moisture) are consistent in sign, but differ in magnitude. The same is found for projected changes to the low-flow characteristics (frequency, timing and return levels) studied here. High-flow characteristics, particularly the seasonal distribution and return levels, appear to be more sensitive to the model version.CRCM climate-change projections indicate an increase in the average annual precipitation for all basins except Mississippi, while annual runoff increases in Fraser, Mackenzie and Yukon basins. A decrease in runoff is projected for Mississippi. A significant decrease in snow cover is projected for all basins, with maximum decrease in Fraser. Significant changes are also noted in the frequency, timing and return levels for low

  16. Climate change and voltinism in Californian insect pest species: sensitivity to location, scenario and climate model choice.

    Science.gov (United States)

    Ziter, Carly; Robinson, Emily A; Newman, Jonathan A

    2012-09-01

    Experimental studies of the impact of climatic change are hampered by their inability to consider multiple climate change scenarios and indeed often consider no more than simple climate sensitivity such as a uniform increase in temperature. Modelling efforts offer the ability to consider a much wider range of realistic climate projections and are therefore useful, in particular, for estimating the sensitivity of impact predictions to differences in geographical location, and choice of climate change scenario and climate model projections. In this study, we used well-established degree-day models to predict the voltinism of 13 agronomically important pests in California, USA. We ran these models using the projections from three Atmosphere-Ocean Coupled Global Circulation Models (AOCGCMs or GCMs), in conjunction with the SRES scenarios. We ran these for two locations representing northern and southern California. We did this for both the 2050s and 2090s. We used anova to partition the variation in the resulting voltinism among time period, climate change scenario, GCM and geographical location. For these 13 pest species, the choice of climate model explained an average of 42% of the total variation in voltinism, far more than did geographical location (33%), time period (17%) or scenario (1%). The remaining 7% of the variation was explained by various interactions, of which the location by GCM interaction was the strongest (5%). Regardless of these sources of uncertainty, a robust conclusion from our work is that all 13 pest species are likely to experience increases in the number of generations that they complete each year. Such increased voltinism is likely to have significant consequences for crop protection and production. © 2012 Blackwell Publishing Ltd.

  17. The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

    Science.gov (United States)

    Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

    1988-01-01

    A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

  18. Quantifying PM2.5-Meteorology Sensitivities in a Global Climate Model

    Science.gov (United States)

    Westervelt, D. M.; Horowitz, L. W.; Naik, V.; Tai, A. P. K.; Fiore, A. M.; Mauzerall, D. L.

    2016-01-01

    Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 micro-g/cu m3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by -0.06 micro-g/cu m (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 micro-g/cu m for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006-2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10e50

  19. A statistical bias correction for climate model data: parameter sensitivity analysis.

    Science.gov (United States)

    Piani, C.; Coppola, E.; Mariotti, L.; Haerter, J.; Hagemann, S.

    2009-04-01

    Water management adaptation strategies depend crucially on high quality projections of the hydrological cycle in view of anthropogenic climate change. The goodness of hydrological cycle projections depends, in turn, on the successful coupling of hydrological models to global (GCMs) or regional climate models (RCMs). It is well known within the climate modelling community that hydrological forcing output from climate models, in particular precipitation, is partially affected by large bias. The bias affects all aspects of the statistics, that is the mean, standard deviation (variability), skewness (drizzle versus intense events, dry days) etc. The state-of-the-art approach to bias correction is based on histogram equalization techniques. Such techniques intrinsically correct all moments of the statistical intensity distribution. However these methods are applicable to hydrological projections to the extent that the correction itself is robust, that is, defined by few parameters that are well constrained by available data and constant in time. Here we present details of the statistical bias correction methodology developed within the European project "Water and Global Change" (WATCH). We will suggest different versions of the method that allow it to be taylored to differently structured biases from different RCMs. Crucially, application of the methodology also allows for a sensitivity analysis of the correction parameters on other gridded variables such as orography and land use. Here we explore some of these sensitivities as well.

  20. Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

    Directory of Open Access Journals (Sweden)

    Dmitry V. Sein

    2014-07-01

    Full Text Available The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis. Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the

  1. Evaluating the sensitivity of Eurasian forest biomass to climate change using a dynamic vegetation model

    International Nuclear Information System (INIS)

    Shuman, J K; Shugart, H H

    2009-01-01

    Climate warming could strongly influence the structure and composition of the Eurasian boreal forest. Temperature related changes have occurred, including shifts in treelines and changes in regeneration. Dynamic vegetation models are well suited to the further exploration of the impacts that climate change may have on boreal forests. Using the individual-based gap model FAREAST, forest composition and biomass are simulated at over 2000 sites across Eurasia. Biomass output is compared to detailed forest data from a representative sample of Russian forests and a sensitivity analysis is performed to evaluate the impact that elevated temperatures and modified precipitation will have on forest biomass and composition in Eurasia. Correlations between model and forest inventory biomass are strong for several boreal tree species. A significant relationship is shown between altered precipitation and biomass. This analysis showed that a modest increase in temperature of 2 deg. C across 200 years had no significant effect on biomass; however further exploration with increased warming reflective of values measured within Siberia, or at an increased rate, are warranted. Overall, FAREAST accurately simulates forest biomass and composition at sites throughout a large geographic area with widely varying climatic conditions and produces reasonable biomass responses to simulated climatic shifts. These results indicate that this model is robust and useful in making predictions regarding the effect of future climate change on boreal forest structure across Eurasia.

  2. Commensurate comparisons of models with energy budget observations reveal consistent climate sensitivities

    Science.gov (United States)

    Armour, K.

    2017-12-01

    Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are

  3. An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1

    Directory of Open Access Journals (Sweden)

    Zachary Subin

    2012-02-01

    Full Text Available Lakes can influence regional climate, yet most general circulation models have, at best, simple and largely untested representations of lakes. We developed the Lake, Ice, Snow, and Sediment Simulator(LISSS for inclusion in the land-surface component (CLM4 of an earth system model (CESM1. The existing CLM4 lake modelperformed poorly at all sites tested; for temperate lakes, summer surface water temperature predictions were 10–25uC lower than observations. CLM4-LISSS modifies the existing model by including (1 a treatment of snow; (2 freezing, melting, and ice physics; (3 a sediment thermal submodel; (4 spatially variable prescribed lakedepth; (5 improved parameterizations of lake surface properties; (6 increased mixing under ice and in deep lakes; and (7 correction of previous errors. We evaluated the lake model predictions of water temperature and surface fluxes at three small temperate and boreal lakes where extensive observational data was available. We alsoevaluated the predicted water temperature and/or ice and snow thicknesses for ten other lakes where less comprehensive forcing observations were available. CLM4-LISSS performed very well compared to observations for shallow to medium-depth small lakes. For large, deep lakes, the under-prediction of mixing was improved by increasing the lake eddy diffusivity by a factor of 10, consistent with previouspublished analyses. Surface temperature and surface flux predictions were improved when the aerodynamic roughness lengths were calculated as a function of friction velocity, rather than using a constant value of 1 mm or greater. We evaluated the sensitivity of surface energy fluxes to modeled lake processes and parameters. Largechanges in monthly-averaged surface fluxes (up to 30 W m22 were found when excluding snow insulation or phase change physics and when varying the opacity, depth, albedo of melting lake ice, and mixing strength across ranges commonly found in real lakes. Typical

  4. Climate Sensitivity in the Anthropocene

    Science.gov (United States)

    Previdi, M.; Liepert, B. G.; Peteet, Dorothy M.; Hansen, J.; Beerling, D. J.; Broccoli, A. J.; Frolking, S.; Galloway, J. N.; Heimann, M.; LeQuere, C.; hide

    2014-01-01

    Climate sensitivity in its most basic form is defined as the equilibrium change in global surface temperature that occurs in response to a climate forcing, or externally imposed perturbation of the planetary energy balance. Within this general definition, several specific forms of climate sensitivity exist that differ in terms of the types of climate feedbacks they include. Based on evidence from Earth's history, we suggest here that the relevant form of climate sensitivity in the Anthropocene (e.g. from which to base future greenhouse gas (GHG) stabilization targets) is the Earth system sensitivity including fast feedbacks from changes in water vapour, natural aerosols, clouds and sea ice, slower surface albedo feedbacks from changes in continental ice sheets and vegetation, and climate-GHG feedbacks from changes in natural (land and ocean) carbon sinks. Traditionally, only fast feedbacks have been considered (with the other feedbacks either ignored or treated as forcing), which has led to estimates of the climate sensitivity for doubled CO2 concentrations of about 3 C. The 2×CO2 Earth system sensitivity is higher than this, being approx. 4-6 C if the ice sheet/vegetation albedo feedback is included in addition to the fast feedbacks, and higher still if climate-GHG feedbacks are also included. The inclusion of climate-GHG feedbacks due to changes in the natural carbon sinks has the advantage of more directly linking anthropogenic GHG emissions with the ensuing global temperature increase, thus providing a truer indication of the climate sensitivity to human perturbations. The Earth system climate sensitivity is difficult to quantify due to the lack of palaeo-analogues for the present-day anthropogenic forcing, and the fact that ice sheet and climate-GHG feedbacks have yet to become globally significant in the Anthropocene. Furthermore, current models are unable to adequately simulate the physics of ice sheet decay and certain aspects of the natural carbon and

  5. A climate sensitive model of carbon transfer through atmosphere, vegetation and soil in managed forest ecosystems

    Science.gov (United States)

    Loustau, D.; Moreaux, V.; Bosc, A.; Trichet, P.; Kumari, J.; Rabemanantsoa, T.; Balesdent, J.; Jolivet, C.; Medlyn, B. E.; Cavaignac, S.; Nguyen-The, N.

    2012-12-01

    For predicting the future of the forest carbon cycle in forest ecosystems, it is necessary to account for both the climate and management impacts. Climate effects are significant not only at a short time scale but also at the temporal horizon of a forest life cycle e.g. through shift in atmospheric CO2 concentration, temperature and precipitation regimes induced by the enhanced greenhouse effect. Intensification of forest management concerns an increasing fraction of temperate and tropical forests and untouched forests represents only one third of the present forest area. Predicting tools are therefore needed to project climate and management impacts over the forest life cycle and understand the consequence of management on the forest ecosystem carbon cycle. This communication summarizes the structure, main components and properties of a carbon transfer model that describes the processes controlling the carbon cycle of managed forest ecosystems. The model, GO+, links three main components, (i) a module describing the vegetation-atmosphere mass and energy exchanges in 3D, (ii) a plant growth module and a (iii) soil carbon dynamics module in a consistent carbon scheme of transfer from atmosphere back into the atmosphere. It was calibrated and evaluated using observed data collected on coniferous and broadleaved forest stands. The model predicts the soil, water and energy balance of entire rotations of managed stands from the plantation to the final cut and according to a range of management alternatives. It accounts for the main soil and vegetation management operations such as soil preparation, understorey removal, thinnings and clearcutting. Including the available knowledge on the climatic sensitivity of biophysical and biogeochemical processes involved in atmospheric exchanges and carbon cycle of forest ecosystems, GO+ can produce long-term backward or forward simulations of forest carbon and water cycles under a range of climate and management scenarios. This

  6. Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

    Science.gov (United States)

    Romanou, A.; Romanski, J.; Gregg, W. W.

    2014-01-01

    Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which

  7. Sensitivity of hydrological modeling to meteorological data and implications for climate change studies

    International Nuclear Information System (INIS)

    Roy, L.G.; Roy, R.; Desrochers, G.E.; Vaillancourt, C.; Chartier, I.

    2008-01-01

    There are uncertainties associated with the use of hydrological models. This study aims to analyse one source of uncertainty associated with hydrological modeling, particularly in the context of climate change studies on water resources. Additional intent of this study is to compare the ability of some meteorological data sources, used in conjunction with an hydrological model, to reproduce the hydrologic regime of a watershed. A case study on a watershed of south-western Quebec, Canada using five different sources of meteorological data as input to an offline hydrological model are presented in this paper. Data used came from weather stations, NCEP reanalysis, ERA40 reanalysis and two Canadian Regional Climate Model (CRCM) runs driven by NCEP and ERA40 reanalysis, providing atmospheric driving boundary conditions to this limited-area climate model. To investigate the sensitivity of simulated streamflow to different sources of meteorological data, we first calibrated the hydrological model with each of the meteorological data sets over the 1961-1980 period. The five different sets of parameters of the hydrological model were then used to simulate streamflow of the 1981-2000 validation period with the five meteorological data sets as inputs. The 25 simulated streamflow series have been compared to the observed streamflow of the watershed. The five meteorological data sets do not have the same ability, when used with the hydrological model, to reproduce streamflow. Our results show also that the hydrological model parameters used may have an important influence on results such as water balance, but it is linked with the differences that may have in the characteristics of the meteorological data used. For climate change impacts assessments on water resources, we have found that there is an uncertainty associated with the meteorological data used to calibrate the model. For expected changes on mean annual flows of the Chateauguay River, our results vary from a small

  8. Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation

    Directory of Open Access Journals (Sweden)

    A. Arneth

    2011-08-01

    Full Text Available Due to its effects on the atmospheric lifetime of methane, the burdens of tropospheric ozone and growth of secondary organic aerosol, isoprene is central among the biogenic compounds that need to be taken into account for assessment of anthropogenic air pollution-climate change interactions. Lack of process-understanding regarding leaf isoprene production as well as of suitable observations to constrain and evaluate regional or global simulation results add large uncertainties to past, present and future emissions estimates. Focusing on contemporary climate conditions, we compare three global isoprene models that differ in their representation of vegetation and isoprene emission algorithm. We specifically aim to investigate the between- and within model variation that is introduced by varying some of the models' main features, and to determine which spatial and/or temporal features are robust between models and different experimental set-ups. In their individual standard configurations, the models broadly agree with respect to the chief isoprene sources and emission seasonality, with maximum monthly emission rates around 20–25 Tg C, when averaged by 30-degree latitudinal bands. They also indicate relatively small (approximately 5 to 10 % around the mean interannual variability of total global emissions. The models are sensitive to changes in one or more of their main model components and drivers (e.g., underlying vegetation fields, climate input which can yield increases or decreases in total annual emissions of cumulatively by more than 30 %. Varying drivers also strongly alters the seasonal emission pattern. The variable response needs to be interpreted in view of the vegetation emission capacities, as well as diverging absolute and regional distribution of light, radiation and temperature, but the direction of the simulated emission changes was not as uniform as anticipated. Our results highlight the need for modellers to evaluate their

  9. Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather.

    Science.gov (United States)

    Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Mike D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent. Mouillot

    2006-01-01

    The purpose of this study was to compare the sensitivity of nlodelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...

  10. Climate sensitivity of a one-dimensional radiative-convective model with cloud feedback

    Science.gov (United States)

    Wang, W.-C.; Rossow, W. B.; Yao, M.-S.; Wolfson, M.

    1981-01-01

    The potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included is illustrated. This is done by studying the behavior of a one-dimensional radiative-convective model with two types of cloud variation: (1) variable cloud cover with constant optical thickness and (2) variable optical thickness with constant cloud cover. The variable parameter is calculated on the assumption that a correlation exists between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, the sensitivity of the results to two different critical lapse rates is examined. These are a constant 6.5 K/km lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are also examined. The model results reveal that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover.

  11. Wind climate estimation using WRF model output: method and model sensitivities over the sea

    DEFF Research Database (Denmark)

    Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo

    2015-01-01

    setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface...... temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce...

  12. Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model

    Science.gov (United States)

    Wang, W.-C.; Stone, P. H.

    1980-01-01

    The feedback between the ice albedo and temperature is included in a one-dimensional radiative-convective climate model. The effect of this feedback on global sensitivity to changes in solar constant is studied for the current climate conditions. This ice-albedo feedback amplifies global sensitivity by 26 and 39%, respectively, for assumptions of fixed cloud altitude and fixed cloud temperature. The global sensitivity is not affected significantly if the latitudinal variations of mean solar zenith angle and cloud cover are included in the global model. The differences in global sensitivity between one-dimensional radiative-convective models and energy balance models are examined. It is shown that the models are in close agreement when the same feedback mechanisms are included. The one-dimensional radiative-convective model with ice-albedo feedback included is used to compute the equilibrium ice line as a function of solar constant.

  13. Design and Implementation of Integrated Surveillance and Modeling Systems for Climate-Sensitive Diseases

    Science.gov (United States)

    Wimberly, M. C.; Merkord, C. L.; Davis, J. K.; Liu, Y.; Henebry, G. M.; Hildreth, M. B.

    2016-12-01

    Climatic variations have a multitude of effects on human health, ranging from the direct impacts of extreme heat events to indirect effects on the vectors and hosts that transmit infectious diseases. Disease surveillance has traditionally focused on monitoring human cases, and in some instances tracking populations sizes and infection rates of arthropod vectors and zoonotic hosts. For climate-sensitive diseases, there is a potential to strengthen surveillance and obtain early indicators of future outbreaks by monitoring environmental risk factors using broad-scale sensor networks that include earth-observing satellites as well as ground stations. We highlight the opportunities and challenges of this integration by presenting modeling results and discussing lessons learned from two projects focused on surveillance and forecasting of mosquito-borne diseases. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessement (EPIDEMIA) project integrates malaria case surveillance with remotely-sensed environmental data for early detection of malaria epidemics in the Amhara region of Ethiopia and has been producing weekly forecast reports since 2015. The South Dakota Mosquito Information System (SDMIS) project similarly combines entomological surveillance with environmental monitoring to generate weekly maps for West Nile virus (WNV) in the north-central United States. We are currently implementing a new disease forecasting and risk reporting framework for the state of South Dakota during the 2016 WNV transmission season. Despite important differences in disease ecology and geographic setting, our experiences with these projects highlight several important lessons learned that can inform future efforts at disease early warning based on climatic predictors. These include the need to engage end users in system design from the outset, the critical role of automated workflows to facilitate the timely integration of multiple data streams

  14. Climate of the Last Glacial Maximum: sensitivity studies and model-data comparison with the LOVECLIM coupled model

    Directory of Open Access Journals (Sweden)

    D. M. Roche

    2007-01-01

    Full Text Available The Last Glacial Maximum climate is one of the classical benchmarks used both to test the ability of coupled models to simulate climates different from that of the present-day and to better understand the possible range of mechanisms that could be involved in future climate change. It also bears the advantage of being one of the most well documented periods with respect to palaeoclimatic records, allowing a thorough data-model comparison. We present here an ensemble of Last Glacial Maximum climate simulations obtained with the Earth System model LOVECLIM, including coupled dynamic atmosphere, ocean and vegetation components. The climate obtained using standard parameter values is then compared to available proxy data for the surface ocean, vegetation, oceanic circulation and atmospheric conditions. Interestingly, the oceanic circulation obtained resembles that of the present-day, but with increased overturning rates. As this result is in contradiction with the current palaeoceanographic view, we ran a range of sensitivity experiments to explore the response of the model and the possibilities for other oceanic circulation states. After a critical review of our LGM state with respect to available proxy data, we conclude that the oceanic circulation obtained is not inconsistent with ocean circulation proxy data, although the water characteristics (temperature, salinity are not in full agreement with water mass proxy data. The consistency of the simulated state is further reinforced by the fact that the mean surface climate obtained is shown to be generally in agreement with the most recent reconstructions of vegetation and sea surface temperatures, even at regional scales.

  15. State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

    Science.gov (United States)

    Pfister, Patrik L.; Stocker, Thomas F.

    2017-10-01

    Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

  16. Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

    NARCIS (Netherlands)

    van Angelen, J.H.|info:eu-repo/dai/nl/325922470; Lenaerts, J.T.M.|info:eu-repo/dai/nl/314850163; Lhermitte, S.; Fettweis, X.; Kuipers Munneke, P.|info:eu-repo/dai/nl/304831891; van den Broeke, M.R.|info:eu-repo/dai/nl/073765643; van Meijgaard, E.; Smeets, C.J.P.P.|info:eu-repo/dai/nl/191522236

    2012-01-01

    We present a sensitivity study of the surface mass balance (SMB) of the Greenland Ice Sheet, as modeled using a regional atmospheric climate model, to various parameter settings in the albedo scheme. The snow albedo scheme uses grain size as a prognostic variable and further depends on cloud cover,

  17. Evaluation and Sensitivity of Climate Model Representation of Upper Arctic Hydrography

    Science.gov (United States)

    DiMaggio, D.; Maslowski, W.; Osinski, R.; Roberts, A.; Clement Kinney, J. L.; Frants, M.

    2016-12-01

    The satellite-derived rate of Arctic sea ice extent decline for the past decades is faster than those simulated by the models participating in the Coupled Model Intercomparison Project (CMIP5). In addition, time-varying Arctic sea ice concentration and thickness distribution in those models are often poorly represented, suggesting that predicted sea ice decline might be modeled in the wrong place or time and for the wrong reasons. We hypothesize that these limitations are in part the result of an inadequate representation of critical high-latitude processes controlling the accumulation and distribution of sub-surface oceanic heat content and its interaction with the sea ice cover, especially in the western Arctic. For the purpose of this study, we define the sub-surface ocean as that below the surface mixed layer and above the Atlantic layer. Those limitations are evidenced in the CMIP5 multi-model mean exhibiting a cold temperature bias near the surface and a warm bias at intermediate depths. In particular, CMIP5 models are found to be inadequately representing the key features of the upper ocean hydrography in the Canada Basin, including the near-surface temperature maximum (NSTM) and the secondary temperature maximum associated with Pacific Summer Water (PSW). To identify the sensitivity of upper Arctic Ocean hydrography to physical processes and model configurations, a series of experiments are performed using the Regional Arctic System Model (RASM), a high-resolution, fully-coupled regional climate model. Analysis of RASM output suggests that surface momentum coupling (air-ice, ice-ocean, and air-ocean) and brine-rejection parameterization strongly influence thermohaline structure down to 700 m. The implementation of elastic anisotropic plastic sea ice rheology improves mixed layer properties, which is also sensitive to changes in numerical convective viscosity and diffusivity. Sea ice formation during model spin-up essentially destroys the initial

  18. Sensitivity of simulated Greenland climate to the COSMO-CLM model setup

    Science.gov (United States)

    Karremann, Melanie K.; Schädler, Gerd

    2017-04-01

    About 50% of the ice mass loss of Greenland is connected to ice sheet dynamics. Global climate simulations are not able to resolve the accumulation and ablation of ice sheets over steep topography gradients correctly. Within the PalMod project, we aim to develop parameterisations to account for the effects of such unresolved scales and to optimize existing parametrisations. Simulations with the non-hydrostatic regional climate model COSMO-CLM allow to estimate mesoscale effects on the ice sheet surface mass balance. We adapted and set up COSMO-CLM for simulations of the Greenland ice sheet. The sensitivity to different model setups concerning e.g. the modeling domain, the resolution, or the importance of considering sea ice is investigated. The model is driven with reanalysis data from the European Centre for Medium-Range Weather Forecast (ECMWF) Interim Reanalysis (ERA-Interim) with a horizontal resolution of 0.7° on 60 vertical levels. Results are validated with an ensemble of observations and gridded reanalysis datasets for the period 1995-2015. The main focus is on precipitation and temperature, which are the main factors affecting the surface mass balance of the Greenland ice sheet. As the Greenland orography and climate characteristics are quite inhomogenous, the analysis is seperated in 7 regions: North, Northwest, Central, Northeast, Southwest, Southeast and South. Preliminary results show that the mean of precipitation and temperature generally agree well with observation data although biases are present, which depend on the region and season. For all regions, best agreement with observations of precipitation and temperature is achieved for the CORDEX-Arctic region as modeling domain. Furthermore, the consideration of sea ice contributes to more realistic results. The mean precipitation amount show good agreement with observation data for Greenland as a whole, while it is slightly overestimated in the North and slightly underestimated in southern regions

  19. Assessment of future scenarios for wind erosion sensitivity changes based on ALADIN and REMO regional climate model simulation data

    Directory of Open Access Journals (Sweden)

    Mezősi Gábor

    2016-07-01

    Full Text Available The changes in rate and pattern of wind erosion sensitivity due to climate change were investigated for 2021–2050 and 2071–2100 compared to the reference period (1961–1990 in Hungary. The sensitivities of the main influencing factors (soil texture, vegetation cover and climate factor were evaluated by fuzzy method and a combined wind erosion sensitivity map was compiled. The climate factor, as the driving factor of the changes, was assessed based on observed data for the reference period, while REMO and ALADIN regional climate model simulation data for the future periods. The changes in wind erosion sensitivity were evaluated on potentially affected agricultural land use types, and hot spot areas were allocated. Based on the results, 5–6% of the total agricultural areas were high sensitive areas in the reference period. In the 21st century slight or moderate changes of wind erosion sensitivity can be expected, and mostly ‘pastures’, ‘complex cultivation patterns’, and ‘land principally occupied by agriculture with significant areas of natural vegetation’ are affected. The applied combination of multi-indicator approach and fuzzy analysis provides novelty in the field of land sensitivity assessment. The method is suitable for regional scale analysis of wind erosion sensitivity changes and supports regional planning by allocating priority areas where changes in agro-technics or land use have to be considered.

  20. Sensitivity of hydrological modeling to meteorological data and implications for climate change studies

    International Nuclear Information System (INIS)

    Roy, L.G.; Roy, R.; Desrochers, G.E.; Vaillancourt, C.; Chartier, I.

    2008-01-01

    Sources of uncertainty associated with hydrological modelling were explored in relation to climatic change. The aim of the study was to compare and evaluate meteorological data sources used in conjunction with a hydrological model of a watershed in southwestern Quebec. Projected changes of mean annual flow were simulated. Five different sources of meteorological data from weather stations, reanalysis data, and 2 regional climate models were used to provide atmospheric driving boundary conditions for a limited area climate model. The hydrological model was calibrated with each of the datasets from 1961 to 1980. The model's different parameter sets were then used to model streamflow between 1981 and 2000. The resulting streamflow series were then compared with observed streamflows of the Quebec watershed. Results of the study demonstrated significant differences between the 5 datasets. Hydrological model parameters also influenced the accuracy of the model. Uncertainties related to climatic change were largely associated with the meteorological data used to calibrate the model. It was concluded that further studies are needed to understand the influence of meteorological data in climatic change watershed studies. refs., tabs., figs

  1. The mass balance of the Greenland ice sheet: sensitivity to climate change as revealed by energy-balance modelling

    NARCIS (Netherlands)

    Oerlemans, J.

    1991-01-01

    The sensitivity of the mass balance of the Greenland ice sheet to climate change is studied with an energy-balance model of the ice/snow surface, applied at 200 m elevation intervals for four characteristic regions of the ice sheet. Solar radiation, longwave radiation, turbulent heat fluxes

  2. Modelling the effect of climate change on recovery of acidified freshwaters. Relative sensitivity of individual processes in the MAGIC model

    Energy Technology Data Exchange (ETDEWEB)

    Wright, R.F. [Norwegian Institute for Water Research, Box 173, N-0411 Oslo (Norway); Aherne, J. [Environmental and Resources Studies Programme, Trent University, Peterborough, Ontario (Canada); Bishop, K.; Erlandsson, M. [Department of Environmental Assessment, Swedish Agricultural University, Box 7070, SE75007 Uppsala (Sweden); Camarero, L. [Centre d' Estudis Avancats de Blanes-CSIC, Acces Cala St. Francecs, 14, E-17300 Blanes (Spain); Cosby, B.J. [Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904-4123 (United States); Evans, C.D. [Centre for Ecology and Hydrology, Deiniol Road, Bangor, Gwynedd, LL57 2UP (United Kingdom); Forsius, M. [Finnish Environment Institute, Box140, FIN-00251 Helsinki (Finland); Hardekopf, D.W. [Institute for Environmental Studies, Charles University, Benatska 2, CZ-12801 Prague 2 (Czech Republic); Helliwell, R. [Macaulay Institute, Craigiebuckler, Aberdeen, AB15 8QH (United Kingdom); Hruska, J. [Czech Geological Survey, Klarov 3 CZ-11821 Prague (Czech Republic); Jenkins, A. [Centre for Ecology and Hydrology, Wallingford, OX 10 8BB (United Kingdom); Kopacek, J. [Hydrobiological Institute, AS CR and Faculty of Biological Sciences, USB, Na Sadkach 7, CZ-370 05 Ceske Budejovice (Czech Republic); Moldan, F. [Swedish Environmental Research Institute, Box 5302, SE-40014 Gothenburg (Sweden); Posch, M. [Netherlands Environmental Assessment Agency, PO Box 303, NL-3720 AH Bilthoven (Netherlands); Rogora, M. [CNR Institute for Ecosystem Study, Section of Hydrobiology and Ecology of Inland Waters, L. go Tonolli, I-28922 Verbania Pallanza (Italy)

    2006-07-15

    The MAGIC model was used to evaluate the relative sensitivity of several possible climate-induced effects on the recovery of soil and surface water from acidification. A common protocol was used at 14 intensively studied sites in Europe and eastern North America. The results show that several of the factors are of only minor importance (increase in pCO{sub 2} in soil air and runoff, for example), several are important at only a few sites (seasalts at near-coastal sites, for example) and several are important at nearly all sites (increased concentrations of organic acids in soil solution and runoff, for example). In addition changes in forest growth and decomposition of soil organic matter are important at forested sites and sites at risk of nitrogen saturation. The trials suggest that in future modelling of recovery from acidification should take into account possible concurrent climate changes and focus specially on the climate-induced changes in organic acids and nitrogen retention. (author)

  3. Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

    Directory of Open Access Journals (Sweden)

    Sulin Tao

    2016-02-01

    Full Text Available A sensitivity analysis of the responses of crops to the chosen production adaptation options under regional climate change was conducted in this study. Projections of winter wheat production for different sowing dates and cultivars were estimated for a major economic and agricultural province of China from 2021 to 2080 using the World Food Study model (WOFOST under representative concentration pathways (RCPs scenarios. A modeling chain was established and a correction method was proposed to reduce the bias of the resulting model-simulated climate data. The results indicated that adjusting the sowing dates and cultivars could mitigate the influences of climate change on winter wheat production in Jinagsu. The yield gains were projected from the chosen sowing date and cultivar. The following actions are recommended to ensure high and stable yields under future climate changes: (i advance the latest sowing date in some areas of northern Jiangsu; and (ii use heat-tolerant or heat-tolerant and drought-resistant varieties in most areas of Jiangsu rather than the currently used cultivar. Fewer of the common negative effects of using a single climate model occurred when using the sensitivity analysis because our bias correction method was effective for scenario data and because the WOFOST performed well for Jiangsu after calibration.

  4. Expanding Greenland Ice Sheet Enhances Sensitivity of Plio-Pleistocene Climate to Obliquity Forcing in the Kiel Climate Model

    Science.gov (United States)

    Song, Zhaoyang; Latif, Mojib; Park, Wonsun

    2017-10-01

    Proxy data suggest the onset of Northern Hemisphere glaciation during the Plio-Pleistocene transition from 3.2 to 2.5 Ma before present resulted in enhanced climate variability at the obliquity (41 kyr) frequency. Here we investigate the influence of the expanding Greenland ice sheet on the mean climate and obliquity-related variability in a series of climate model simulations. These suggest that an expanding GrIS weakens the Atlantic Meridional Overturning Circulation (AMOC) by 1 Sverdrup, mainly due to reduced heat loss in the Greenland-Iceland-Norwegian Sea. Moreover, the growing GrIS amplifies the Hadley circulation response to obliquity forcing driving variations in freshwater export from the tropical Atlantic and in turn variations of the AMOC. The stronger AMOC response to obliquity forcing, by about a factor of 2, results in a stronger global mean near-surface temperature response. We conclude that the AMOC response to obliquity forcing is important to understand the enhanced climate variability at the obliquity frequency during the Plio-Pleistocene transition.

  5. Climate change due to the gradual increase in atmospheric CO2: a climate system model sensitivity study

    International Nuclear Information System (INIS)

    Park, H.S.; Joh, M.

    2005-01-01

    A numerical experiment investigating climate change due to the gradual increase in atmospheric carbon dioxide (CO 2 ) has been performed with the community climate system model (CCSM) developed by National Center for Atmospheric Research (NCAR). Composed of four independent component models simulating the Earth's atmosphere, ocean, land surface, and sea-ice and one central coupler, the CCSM is used to simulate and understand the Earth's past, present and future climate states. The model experiment consists of a control run with a fixed atmospheric CO 2 concentration at a standardized value for 1990 to 2000 (355 ppmv) and a transient run with a gradually increased atmospheric CO 2 at the rate of 1% per year. ja The initial CO 2 concentration of the transient run is 355 ppmv. Each run has been performed for 80 simulated years. In this experiment, climate change due to the gradually increased atmospheric CO 2 is defined as the difference between the results from the transient and control runs. At the time of CO 2 doubling (about year 70), the globally averaged surface air temperature increases by 1.25 C. The surface air temperature increases are more predominant over the higher-latitude land areas than over other areas, especially in boreal winter. With an increase in the surface air temperature, there is a decrease in the diurnal temperature range, with the nighttime minimum temperature increasing more than the daytime maximum temperature. And air temperature shows tropospheric warming and stratospheric cooling causing the strong temperature gradient and polar jet intensifications. (orig.)

  6. Watershed sensitivity and hydrologic response to high-resolution climate model

    Science.gov (United States)

    Troin, M.; Caya, D.

    2012-12-01

    Global climate models (GCMs) are fundamental research tools to assess climate change impacts on water resources. Regional climate models (RCMs) are complementary to GCMs. The added benefit of RCMs for hydrological applications is still not well understood because watersheds respond differently to RCM experiments. It is expected that the new generation of RCMs improve the representation of climate processes making it more attractive for impact studies. Given the cost of RCMs, it is ascertain to identify whether high-resolution RCMs allow offering more details than what is simulated in GCMs or RCMs with coarser resolution to address impacts on water resources. This study aims to assess the added value of RCM with emphasis on using high-resolution climate models. More specifically is how the hydrological cycle is represented when the resolution in climate models is increased (45 vs 200km; 15 vs 45km). We used simulations from the Canadian RCM (CRCM) driven by reanalyses integrated on high-resolution domains (45 and 15km) and CRCM driven by multiple members of two GCMs (the Canadian CGCM3; the German ECHAM5) with a horizontal resolution of 45 km. CRCM data and data from their host GCMs are compared to observation over 1971-2000. Precipitation and temperature from CRCM and GCMs' simulations are inputted into the hydrological SWAT model to simulate streamflow in watersheds for the historical period. The selected watersheds are two basins in Quebec (QC) and one basin in British Columbia (BC), Canada. CRCM-45km driven by GCMs performs well in representing precipitation but shows a cold bias of 3.3°C. Such bias in temperature is more significant for the BC basin (4.5°C) due to the Rocky Mountains. For the CRCM-45km/GCM combination (CGCM3 or ECHAM5), comparable skills in reproducing the observed climate are identified even though CGCM3 analyzed alone provides more accurate indication of climatology in the basins than ECHAM5. When we compared to GCMs results, CRCM-45km

  7. Deep time evidence for climate sensitivity increase with warming:Climate Sensitivity Rise With Warming

    OpenAIRE

    Shaffer, Gary; Huber, Matthew; Rondanelli, Roberto; Pedersen, Jens Olaf Pepke

    2016-01-01

    Future global warming from anthropogenic greenhouse gas emissions will depend on climate feedbacks, the effect of which is expressed by climate sensitivity, the warming for a doubling of atmospheric CO2 content. It is not clear how feedbacks, sensitivity, and temperature will evolve in our warming world, but past warming events may provide insight. Here we employ paleoreconstructions and new climate-carbon model simulations in a novel framework to explore a wide scenario range for the Paleoce...

  8. The doubled CO2 climate and the sensitivity of the modeled hydrologic cycle

    Science.gov (United States)

    Rind, D.

    1988-01-01

    Four doubled CO2 experiments with the GISS general circulation model are compared to investigate the consistency of changes in water availability over the United States. The experiments compare the influence of model sensitivity, model resolution, and the sea-surface temperature gradient. The results show that the general mid-latitude drying over land is dependent upon the degree of mid-latitude eddy energy decrease, and thus the degree of high-latitude temperature change amplification. There is a general tendency in the experiments for the northern and western United States to become wetter, while the southern and eastern portions dry. However, there is much variability from run to run, with different regions showing different degrees of sensitivity to the parameters tested. The results for the western United States depend most on model resolution; those for the central United States, on the sea-surface temperature gradient and the degree of mid-latitude ocean warming; and those for the eastern United States, on model sensitivity. The changes in particular seasons depend on changes in other seasons, and will therefore be sensitive to the realism of the ground hydrology parameterization.

  9. Cumulus Microphysics and Climate Sensitivity.

    Science.gov (United States)

    del Genio, Anthony D.; Kovari, William; Yao, Mao-Sung; Jonas, Jeffrey

    2005-07-01

    Precipitation processes in convective storms are potentially a major regulator of cloud feedback. An unresolved issue is how the partitioning of convective condensate between precipitation-size particles that fall out of updrafts and smaller particles that are detrained to form anvil clouds will change as the climate warms. Tropical Rainfall Measuring Mission (TRMM) observations of tropical oceanic convective storms indicate higher precipitation efficiency at warmer sea surface temperature (SST) but also suggest that cumulus anvil sizes, albedos, and ice water paths become insensitive to warming at high temperatures. International Satellite Cloud Climatology Project (ISCCP) data show that instantaneous cirrus and deep convective cloud fractions are positively correlated and increase with SST except at the highest temperatures, but are sensitive to variations in large-scale vertical velocity. A simple conceptual model based on a Marshall-Palmer drop size distribution, empirical terminal velocity-particle size relationships, and assumed cumulus updraft speeds reproduces the observed tendency for detrained condensate to approach a limiting value at high SST. These results suggest that the climatic behavior of observed tropical convective clouds is intermediate between the extremes required to support the thermostat and adaptive iris hypotheses.

  10. Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model

    Directory of Open Access Journals (Sweden)

    P. Räisänen

    2017-12-01

    Full Text Available Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR model and in the Los Alamos sea ice model, version 4 (CICE4, both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM. In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH is compared with another (NONSPH in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77–0.78 in the visible region than in the spherical case ( ≈  0.89. Therefore, for the same effective snow grain size (or equivalently, the same specific projected area, the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02–0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. −0.22 W m−2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain

  11. Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model

    Science.gov (United States)

    Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf; Debernard, Jens B.

    2017-12-01

    Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77-0.78 in the visible region) than in the spherical case ( ≈ 0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02-0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. -0.22 W m-2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the

  12. Modeling land surface hydrology sensitivity in the Colorado River Basin to historical climate variability

    Science.gov (United States)

    Whitney, K. M.; Bohn, T. J.; Vivoni, E. R.

    2017-12-01

    Over the past century, the Colorado River Basin (CRB) has experienced substantial warming and interannual climate variations, including prolonged drought periods. These patterns are projected to accelerate in the 21st century, with major consequences for water resources in the southwestern U.S. and northwestern Mexico. To evaluate future projections appropriately, however, it is important to first quantify the regional hydrologic response to historical climate variability in the CRB. In the current effort, we force the Variable Infiltration Capacity (VIC) land surface hydrology model and a river routing model with historical meteorological data to estimate water balance components and naturalized streamflow response in the CRB at 1/16o spatial resolution and at an hourly time step over the period 1950-2013. We utilize data products from satellite remote sensing to specify spatiotemporal variations in vegetation parameters and include an irrigation scheme to account for evapotranspiration from croplands in the CRB. Furthermore, we apply recent modifications in VIC to more properly account for bare soil evaporation in arid and semiarid ecosystems. Analyses of the historical model simulations are focused on quantifying the spatiotemporal variability of the soil moisture, evapotranspiration, streamflow and snowmelt response and their linkages to extreme meteorological events. Here we characterize the annual and monthly distributions, trends, and statistical extremes and central tendencies of water balance terms averaged over the CRB and its sub-basins for the entire study period 1950-2013. By building a model-based hydrologic climatology and catalog of historical extreme events for the CRB, we aim to construct a basis for future activities that analyze the impact of statistically downscaled climate change projections on the hydrology of the CRB and its urban areas.

  13. Comparing Climate Sensitivity, Past and Present

    Science.gov (United States)

    Rohling, Eelco J.; Marino, Gianluca; Foster, Gavin L.; Goodwin, Philip A.; von der Heydt, Anna S.; Köhler, Peter

    2018-01-01

    Climate sensitivity represents the global mean temperature change caused by changes in the radiative balance of climate; it is studied for both present/future (actuo) and past (paleo) climate variations, with the former based on instrumental records and/or various types of model simulations. Paleo-estimates are often considered informative for assessments of actuo-climate change caused by anthropogenic greenhouse forcing, but this utility remains debated because of concerns about the impacts of uncertainties, assumptions, and incomplete knowledge about controlling mechanisms in the dynamic climate system, with its multiple interacting feedbacks and their potential dependence on the climate background state. This is exacerbated by the need to assess actuo- and paleoclimate sensitivity over different timescales, with different drivers, and with different (data and/or model) limitations. Here, we visualize these impacts with idealized representations that graphically illustrate the nature of time-dependent actuo- and paleoclimate sensitivity estimates, evaluating the strengths, weaknesses, agreements, and differences of the two approaches. We also highlight priorities for future research to improve the use of paleo-estimates in evaluations of current climate change.

  14. Sensitivity experiments of a regional climate model to the different convective schemes over Central Africa

    Science.gov (United States)

    Armand J, K. M.

    2017-12-01

    In this study, version 4 of the regional climate model (RegCM4) is used to perform 6 years simulation including one year for spin-up (from January 2001 to December 2006) over Central Africa using four convective schemes: The Emmanuel scheme (MIT), the Grell scheme with Arakawa-Schulbert closure assumption (GAS), the Grell scheme with Fritsch-Chappell closure assumption (GFC) and the Anthes-Kuo scheme (Kuo). We have investigated the ability of the model to simulate precipitation, surface temperature, wind and aerosols optical depth. Emphasis in the model results were made in December-January-February (DJF) and July-August-September (JAS) periods. Two subregions have been identified for more specific analysis namely: zone 1 which corresponds to the sahel region mainly classified as desert and steppe and zone 2 which is a region spanning the tropical rain forest and is characterised by a bimodal rain regime. We found that regardless of periods or simulated parameters, MIT scheme generally has a tendency to overestimate. The GAS scheme is more suitable in simulating the aforementioned parameters, as well as the diurnal cycle of precipitations everywhere over the study domain irrespective of the season. In JAS, model results are similar in the representation of regional wind circulation. Apart from the MIT scheme, all the convective schemes give the same trends in aerosols optical depth simulations. Additional experiment reveals that the use of BATS instead of Zeng scheme to calculate ocean flux appears to improve the quality of the model simulations.

  15. Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

    International Nuclear Information System (INIS)

    Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S.

    2008-01-01

    Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter μ ± 1σ), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha -1 ·year -1 . This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat boreal forests, was shown to be

  16. Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

    Energy Technology Data Exchange (ETDEWEB)

    Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)

    2008-06-15

    Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat

  17. Report of the workshop on Climate Sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

    The IPCC Working Group I (WGI) held this Workshop on Climate Sensitivity as a major keystone in activities preparing for the WGI contribution to the IPCC Fourth Assessment Report (AR4). One of the most important parameters in climate science is the 'climate sensitivity', broadly defined as the global mean temperature change for a given forcing, often that of a doubling of atmospheric carbon dioxide. Climate sensitivity has played a central role throughout the history of IPCC in interpretation of model outputs, in evaluation of future climate changes expected from various scenarios, and it is closely linked to attribution of currently observed climate changes. An ongoing challenge to models and to climate projections has been to better define this key parameter, and to understand the differences in computed values between various models. Throughout the last three IPCC assessments the climate sensitivity has been estimated as being in the range 1.5 to 4.5 deg. C for CO{sub 2} doubling (i.e., uncertain by a factor of three), making this parameter central to discussions of uncertainty in climate change. The aims of the workshop were to: - Evaluate a range of climate model results so as to relate different climate sensitivity estimates to differences descriptions of physical processes, particularly those related to atmospheric water vapor, clouds, lapse rate changes, ocean heat uptake, treatment of evapotranspiration, land-atmosphere coupling, etc.; - Obtain a more comprehensive picture of the relationships between climate sensitivity and other model features such as resolution, numerical approach, radiative transfer parameters, etc.; - Consider how current, historical, and paleo-climatic data can aid in the determination of the likely range of climate sensitivity; - Improve the understanding of the interpretation and limits of the climate sensitivity concept, including for example possible dependencies upon different forcing agents, predictability questions

  18. Report of the workshop on Climate Sensitivity

    International Nuclear Information System (INIS)

    2004-01-01

    The IPCC Working Group I (WGI) held this Workshop on Climate Sensitivity as a major keystone in activities preparing for the WGI contribution to the IPCC Fourth Assessment Report (AR4). One of the most important parameters in climate science is the 'climate sensitivity', broadly defined as the global mean temperature change for a given forcing, often that of a doubling of atmospheric carbon dioxide. Climate sensitivity has played a central role throughout the history of IPCC in interpretation of model outputs, in evaluation of future climate changes expected from various scenarios, and it is closely linked to attribution of currently observed climate changes. An ongoing challenge to models and to climate projections has been to better define this key parameter, and to understand the differences in computed values between various models. Throughout the last three IPCC assessments the climate sensitivity has been estimated as being in the range 1.5 to 4.5 deg. C for CO 2 doubling (i.e., uncertain by a factor of three), making this parameter central to discussions of uncertainty in climate change. The aims of the workshop were to: - Evaluate a range of climate model results so as to relate different climate sensitivity estimates to differences descriptions of physical processes, particularly those related to atmospheric water vapor, clouds, lapse rate changes, ocean heat uptake, treatment of evapotranspiration, land-atmosphere coupling, etc.; - Obtain a more comprehensive picture of the relationships between climate sensitivity and other model features such as resolution, numerical approach, radiative transfer parameters, etc.; - Consider how current, historical, and paleo-climatic data can aid in the determination of the likely range of climate sensitivity; - Improve the understanding of the interpretation and limits of the climate sensitivity concept, including for example possible dependencies upon different forcing agents, predictability questions, and transient

  19. Future changes in regional precipitation simulated by a half-degree coupled climate model: Sensitivity to horizontal resolution

    Science.gov (United States)

    Shields, Christine A.; Kiehl, Jeffrey T.; Meehl, Gerald A.

    2016-06-01

    The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the half-degree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to higher resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. Differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.

  20. Sensitivity of the Atmospheric Response to Warm Pool El Nino Events to Modeled SSTs and Future Climate Forcings

    Science.gov (United States)

    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.

  1. Relating health and climate impacts to grid-scale emissions using adjoint sensitivity modeling for the Climate and Clean Air Coalition

    Science.gov (United States)

    Henze, D. K.; Lacey, F.; Seltzer, M.; Vallack, H.; Kuylenstierna, J.; Bowman, K. W.; Anenberg, S.; Sasser, E.; Lee, C. J.; Martin, R.

    2013-12-01

    The Climate and Clean Air Coalition (CCAC) was initiated in 2012 to develop, understand and promote measures to reduce short lived climate forcers such as aerosol, ozone and methane. The Coalition now includes over 30 nations, and as a service to these nations is committed to providing a decision support toolkit that allows member nations to explore the benefits of a range of emissions mitigation measures in terms of the combined impacts on air quality and climate and so help in the development of their National Action Plans. Here we will present recent modeling work to support the development of the CCAC National Action Plans toolkit. Adjoint sensitivity analysis is presented as a means of efficiently relating air quality, climate and crop impacts back to changes in emissions from each species, sector and location at the grid-scale resolution of typical global air quality model applications. The GEOS-Chem adjoint model is used to estimate the damages per ton of emissions of PM2.5 related mortality, the impacts of ozone precursors on crops and ozone-related health effects, and the combined impacts of these species on regional surface temperature changes. We show how the benefits-per-emission vary spatially as a function of the surrounding environment, and how this impacts the overall benefit of sector-specific control strategies. We present initial findings for Bangladesh, as well as Mexico, Ghana and Colombia, some of the first countries to join the CCAC, and discuss general issues related to adjoint-based metrics for quantifying air quality and climate co-benefits.

  2. Representation of monsoon intraseasonal oscillations in regional climate model: sensitivity to convective physics

    KAUST Repository

    Umakanth, U.

    2015-11-07

    The aim of the study is to evaluate the performance of regional climate model (RegCM) version 4.4 over south Asian CORDEX domain to simulate seasonal mean and monsoon intraseasonal oscillations (MISOs) during Indian summer monsoon. Three combinations of Grell (G) and Emanuel (E) cumulus schemes namely, RegCM-EG, RegCM-EE and RegCM-GE have been used. The model is initialized at 1st January, 2000 for a 13-year continuous simulation at a spatial resolution of 50 km. The models reasonably simulate the seasonal mean low level wind pattern though they differ in simulating mean precipitation pattern. All models produce dry bias in precipitation over Indian land region except in RegCM-EG where relatively low value of dry bias is observed. On seasonal scale, the performance of RegCM-EG is more close to observation though it fails at intraseasonal time scales. In wave number-frequency spectrum, the observed peak in zonal wind (850 hPa) at 40–50 day scale is captured by all models with a slight change in amplitude, however, the 40–50 day peak in precipitation is completely absent in RegCM-EG. The space–time characteristics of MISOs are well captured by RegCM-EE over RegCM-GE, however it fails to show the eastward propagation of the convection across the Maritime Continent. Except RegCM-EE all other models completely underestimates the moisture advection from Equatorial Indian Ocean onto Indian land region during life-cycle of MISOs. The characteristics of MISOs are studied for strong (SM) and weak (WM) monsoon years and the differences in model performances are analyzed. The wavelet spectrum of rainfall over central India denotes that, the SM years are dominated by high frequency oscillations (period <20 days) whereas little higher periods (>30 days) along with dominated low periods (<20 days) observed during WM years. During SM, RegCM-EE is dominated with high frequency oscillations (period <20 days) whereas in WM, RegCM-EE is dominated with periods >20

  3. Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

    Science.gov (United States)

    Kim, Go-Un; Seo, Kyong-Hwan

    2018-01-01

    A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

  4. Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

    Science.gov (United States)

    Battisti, R.; Sentelhas, P. C.; Boote, K. J.

    2017-12-01

    Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

  5. Sensitivity of the tropical stratospheric ozone response to the solar rotational cycle in observations and chemistry-climate model simulations

    Science.gov (United States)

    Thiéblemont, Rémi; Marchand, Marion; Bekki, Slimane; Bossay, Sébastien; Lefèvre, Franck; Meftah, Mustapha; Hauchecorne, Alain

    2017-08-01

    The tropical stratospheric ozone response to solar UV variations associated with the rotational cycle (˜ 27 days) is analyzed using MLS satellite observations and numerical simulations from the LMDz-Reprobus chemistry-climate model. The model is used in two configurations, as a chemistry-transport model (CTM) where dynamics are nudged toward ERA-Interim reanalysis and as a chemistry-climate model (free-running) (CCM). An ensemble of five 17-year simulations (1991-2007) is performed with the CCM. All simulations are forced by reconstructed time-varying solar spectral irradiance from the Naval Research Laboratory Solar Spectral Irradiance model. We first examine the ozone response to the solar rotational cycle during two 3-year periods which correspond to the declining phases of solar cycle 22 (October 1991-September 1994) and solar cycle 23 (September 2004-August 2007), when the satellite ozone observations of the two Microwave Limb Sounders (UARS MLS and Aura MLS) are available. In the observations, during the first period, ozone and UV flux are found to be correlated between about 10 and 1 hPa with a maximum of 0.29 at ˜ 5 hPa; the ozone sensitivity (% change in ozone for 1 % change in UV) peaks at ˜ 0.4. Correlation during the second period is weaker and has a peak ozone sensitivity of only 0.2, possibly due to the fact that the solar forcing is weaker during that period. The CTM simulation reproduces most of these observed features, including the differences between the two periods. The CCM ensemble mean results comparatively show much smaller differences between the two periods, suggesting that the amplitude of the rotational ozone signal estimated from MLS observations or the CTM simulation is strongly influenced by other (non-solar) sources of variability, notably dynamics. The analysis of the ensemble of CCM simulations shows that the estimation of the ensemble mean ozone sensitivity does not vary significantly either with the amplitude of the solar

  6. Abrupt millennial variability and interdecadal-interstadial oscillations in a global coupled model: sensitivity to the background climate state

    Energy Technology Data Exchange (ETDEWEB)

    Arzel, Olivier [The University of New South Wales, Climate Change Research Centre (CCRC), Sydney (Australia); Universite de Bretagne Occidentale, Laboratoire de Physique des Oceans (LPO), Brest (France); England, Matthew H. [The University of New South Wales, Climate Change Research Centre (CCRC), Sydney (Australia); Verdiere, Alain Colin de; Huck, Thierry [Universite de Bretagne Occidentale, Laboratoire de Physique des Oceans (LPO), Brest (France)

    2012-07-15

    The origin and bifurcation structure of abrupt millennial-scale climate transitions under steady external solar forcing and in the absence of atmospheric synoptic variability is studied by means of a global coupled model of intermediate complexity. We show that the origin of Dansgaard-Oeschger type oscillations in the model is caused by the weaker northward oceanic heat transport in the Atlantic basin. This is in agreement with previous studies realized with much simpler models, based on highly idealized geometries and simplified physics. The existence of abrupt millennial-scale climate transitions during glacial times can therefore be interpreted as a consequence of the weakening of the negative temperature-advection feedback. This is confirmed through a series of numerical experiments designed to explore the sensitivity of the bifurcation structure of the Atlantic meridional overturning circulation to increased atmospheric CO{sub 2} levels under glacial boundary conditions. Contrasting with the cold, stadial, phases of millennial oscillations, we also show the emergence of strong interdecadal variability in the North Atlantic sector during warm interstadials. The instability driving these interdecadal-interstadial oscillations is shown to be identical to that found in ocean-only models forced by fixed surface buoyancy fluxes, that is, a large-scale baroclinic instability developing in the vicinity of the western boundary current in the North Atlantic. Comparisons with modern observations further suggest a physical mechanism similar to that driving the 30-40 years time scale associated with the Atlantic multidecadal oscillation. (orig.)

  7. Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

    Directory of Open Access Journals (Sweden)

    J. H. van Angelen

    2012-10-01

    Full Text Available We present a sensitivity study of the surface mass balance (SMB of the Greenland Ice Sheet, as modeled using a regional atmospheric climate model, to various parameter settings in the albedo scheme. The snow albedo scheme uses grain size as a prognostic variable and further depends on cloud cover, solar zenith angle and black carbon concentration. For the control experiment the overestimation of absorbed shortwave radiation (+6% at the K-transect (west Greenland for the period 2004–2009 is considerably reduced compared to the previous density-dependent albedo scheme (+22%. To simulate realistic snow albedo values, a small concentration of black carbon is needed, which has strongest impact on melt in the accumulation area. A background ice albedo field derived from MODIS imagery improves the agreement between the modeled and observed SMB gradient along the K-transect. The effect of enhanced meltwater retention and refreezing is a decrease of the albedo due to an increase in snow grain size. As a secondary effect of refreezing the snowpack is heated, enhancing melt and further lowering the albedo. Especially in a warmer climate this process is important, since it reduces the refreezing potential of the firn layer that covers the Greenland Ice Sheet.

  8. Ocean acidification over the next three centuries using a simple global climate carbon-cycle model: projections and sensitivities

    Energy Technology Data Exchange (ETDEWEB)

    Hartin, Corinne A.; Bond-Lamberty, Benjamin; Patel, Pralit; Mundra, Anupriya

    2016-08-01

    projections and sensitivity analyses, and it is capable of emulating both current observations and large-scale climate models under multiple emission pathways.

  9. Assessment of Potential Yield andClimate Change Sensitivity of Peanut Crop in Cagayan Valley, Philippines using DSSAT Simulation Model

    Science.gov (United States)

    Balderama, O. F.

    2013-12-01

    Peanut is a major upland crop in Cagayan Valley and a leguminous crop that requires less water and therefore, considered an important crop in improving productivity of upland and rainfed areas. However, little information is available on the potential productivity of the crop and analysis on the production constraints including climate change sensitivity. This study was aimed to determine yield potential and production constraints of peanut crop in Cagayan Valley through the use of Decision Support System for Agrotechnology Transfer (DSSAT) simulation modeling; analyze yield gaps between simulated and actual yield levels and to provide decision support to further optimize peanut production under climate change condition. Site of experiment for model calibration and validation was located on-station at Isabela State University, Echague, Isabela. Rainfall and other climatic variables were monitored using a HOBO weather station (Automatic Weather Station) which is strategically installed inside experimental zone.The inputs required to run the CSM model include information on soil and weather conditions, crop management practices and cultivar specific genetic coefficients. In the first step,a model calibration was conducted to determine the cultivar coefficients for certain peanut cultivar that are normally grown in Cagayan Valley. Crop growth and yield simulation modeling was undertaken using the Decision Support System for Agro-Technology Transfer (DSSAT) for small seeded peanut (Pn9). An evaluation of the CSM-CROPGRO-peanut model was performed with data sets from peanut experiment conducted from December 2011 to April 2012. The model was evaluated in the estimation of potential yield of peanut under rainfed condition and low-nitrogen application. Yield potential for peanut limited only by temperature and solar radiation and no-water and nutrient stress, ranged from 3274 to 4805 kg per hectare for six planting dates (October 1, October 15, November 1, November 15

  10. Energy balance climate models

    Science.gov (United States)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1981-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  11. Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

    Science.gov (United States)

    Rollinson, Christine R; Liu, Yao; Raiho, Ann; Moore, David J P; McLachlan, Jason; Bishop, Daniel A; Dye, Alex; Matthes, Jaclyn H; Hessl, Amy; Hickler, Thomas; Pederson, Neil; Poulter, Benjamin; Quaife, Tristan; Schaefer, Kevin; Steinkamp, Jörg; Dietze, Michael C

    2017-07-01

    Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO 2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO 2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO 2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO 2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO 2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO 2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the

  12. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

    Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

    2017-12-01

    Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

  13. Effects of snow grain non-sphericity on climate simulations: Sensitivity tests with the NorESM model

    Science.gov (United States)

    Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf

    2017-04-01

    optically thick snowpack with a given snow grain effective size, the absorbing aerosol RE is smaller for non-spherical than for spherical snow grains. The reason for this is that due to the lower asymmetry parameter of the non-spherical snow grains, solar radiation does not penetrate as deep in snow as in the case of spherical snow grains. However, in a climate model simulation, the RE is sensitive to patterns of aerosol deposition and simulated snow cover. In fact, the global land-area mean absorbing aerosol RE is larger in the NONSPH than SPH experiment (0.193 vs. 0.168 W m-2), owing to later snowmelt in spring.

  14. TRACKING CLIMATE MODELS

    Data.gov (United States)

    National Aeronautics and Space Administration — CLAIRE MONTELEONI*, GAVIN SCHMIDT, AND SHAILESH SAROHA* Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate...

  15. Deep time evidence for climate sensitivity increase with warming

    DEFF Research Database (Denmark)

    Shaffer, Gary; Huber, Matthew; Rondanelli, Roberto

    2016-01-01

    Future global warming from anthropogenic greenhouse gas emissions will depend on climate feedbacks, the effect of which is expressed by climate sensitivity, the warming for a doubling of atmospheric CO2 content. It is not clear how feedbacks, sensitivity, and temperature will evolve in our warming...... world, but past warming events may provide insight. Here we employ paleoreconstructions and new climate-carbon model simulations in a novel framework to explore a wide scenario range for the Paleocene-Eocene Thermal Maximum (PETM) carbon release and global warming event 55.8Ma ago, a possible future...... indicates climate sensitivity increase with global warming....

  16. The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection

    Energy Technology Data Exchange (ETDEWEB)

    Hourdin, Frederic; Musat, Ionela; Bony, Sandrine; Codron, Francis; Dufresne, Jean-Louis; Fairhead, Laurent; Grandpeix, Jean-Yves; LeVan, Phu; Li, Zhao-Xin; Lott, Francois [CNRS/UPMC, Laboratoire de Meteorologie Dynamique (LMD/IPSL), Paris Cedex 05 (France); Braconnot, Pascale; Friedlingstein, Pierre [Laboratoire des Sciences du Climat et de l' Environnement (LSCE/IPSL), Saclay (France); Filiberti, Marie-Angele [Institut Pierre Simon Laplace (IPSL), Paris (France); Krinner, Gerhard [Laboratoire de Glaciologie et Geophysique de l' Environnement, Grenoble (France)

    2006-12-15

    The LMDZ4 general circulation model is the atmospheric component of the IPSL-CM4 coupled model which has been used to perform climate change simulations for the 4th IPCC assessment report. The main aspects of the model climatology (forced by observed sea surface temperature) are documented here, as well as the major improvements with respect to the previous versions, which mainly come form the parametrization of tropical convection. A methodology is proposed to help analyse the sensitivity of the tropical Hadley-Walker circulation to the parametrization of cumulus convection and clouds. The tropical circulation is characterized using scalar potentials associated with the horizontal wind and horizontal transport of geopotential (the Laplacian of which is proportional to the total vertical momentum in the atmospheric column). The effect of parametrized physics is analysed in a regime sorted framework using the vertical velocity at 500 hPa as a proxy for large scale vertical motion. Compared to Tiedtke's convection scheme, used in previous versions, the Emanuel's scheme improves the representation of the Hadley-Walker circulation, with a relatively stronger and deeper large scale vertical ascent over tropical continents, and suppresses the marked patterns of concentrated rainfall over oceans. Thanks to the regime sorted analyses, these differences are attributed to intrinsic differences in the vertical distribution of convective heating, and to the lack of self-inhibition by precipitating downdraughts in Tiedtke's parametrization. Both the convection and cloud schemes are shown to control the relative importance of large scale convection over land and ocean, an important point for the behaviour of the coupled model. (orig.)

  17. Temperature targets revisited under climate sensitivity uncertainty

    Science.gov (United States)

    Neubersch, Delf; Roth, Robert; Held, Hermann

    2015-04-01

    While the 2° target has become an official goal of the COP (Conference of the Parties) process recent work has shown that it requires re-interpretation if climate sensitivity uncertainty in combination with anticipated future learning is considered (Schmidt et al., 2011). A strict probabilistic limit as suggested by the Copenhagen diagnosis may lead to conceptual flaws in view of future learning such a negative expected value of information or even ill-posed policy recommendations. Instead Schmidt et al. suggest trading off the probabilistic transgression of a temperature target against mitigation-induced welfare losses and call this procedure cost risk analysis (CRA). Here we spell out CRA for the integrated assessment model MIND and derive necessary conditions for the exact nature of that trade-off. With CRA at hand it is for the first time that the expected value of climate information, for a given temperature target, can meaningfully be assessed. When focusing on a linear risk function as the most conservative of all possible risk functions, we find that 2° target-induced mitigation costs could be reduced by up to 1/3 if the climate response to carbon dioxide emissions were known with certainty, amounting to hundreds of billions of Euros per year (Neubersch et al., 2014). Further benefits of CRA over strictly formulated temperature targets are discussed. References: D. Neubersch, H. Held, A. Otto, Operationalizing climate targets under learning: An application of cost-risk analysis, Climatic Change, 126 (3), 305-318, DOI 10.1007/s10584-014-1223-z (2014). M. G. W. Schmidt, A. Lorenz, H. Held, E. Kriegler, Climate Targets under Uncertainty: Challenges and Remedies, Climatic Change Letters, 104 (3-4), 783-791, DOI 10.1007/s10584-010-9985-4 (2011).

  18. Sensitivity of remote aerosol distributions to representation of cloud–aerosol interactions in a global climate model

    Directory of Open Access Journals (Sweden)

    H. Wang

    2013-06-01

    Full Text Available Many global aerosol and climate models, including the widely used Community Atmosphere Model version 5 (CAM5, have large biases in predicting aerosols in remote regions such as the upper troposphere and high latitudes. In this study, we conduct CAM5 sensitivity simulations to understand the role of key processes associated with aerosol transformation and wet removal affecting the vertical and horizontal long-range transport of aerosols to the remote regions. Improvements are made to processes that are currently not well represented in CAM5, which are guided by surface and aircraft measurements together with results from a multi-scale aerosol–climate model that explicitly represents convection and aerosol–cloud interactions at cloud-resolving scales. We pay particular attention to black carbon (BC due to its importance in the Earth system and the availability of measurements. We introduce into CAM5 a new unified scheme for convective transport and aerosol wet removal with explicit aerosol activation above convective cloud base. This new implementation reduces the excessive BC aloft to better simulate observed BC profiles that show decreasing mixing ratios in the mid- to upper-troposphere. After implementing this new unified convective scheme, we examine wet removal of submicron aerosols that occurs primarily through cloud processes. The wet removal depends strongly on the subgrid-scale liquid cloud fraction and the rate of conversion of liquid water to precipitation. These processes lead to very strong wet removal of BC and other aerosols over mid- to high latitudes during winter months. With our improvements, the Arctic BC burden has a 10-fold (5-fold increase in the winter (summer months, resulting in a much-better simulation of the BC seasonal cycle as well. Arctic sulphate and other aerosol species also increase but to a lesser extent. An explicit treatment of BC aging with slower aging assumptions produces an additional 30-fold (5-fold

  19. Sensitivity of seawater oxygen isotopes to climatic and tectonic boundary conditions in an early Paleogene simulation with GISS ModelE-R

    Science.gov (United States)

    Roberts, Christopher D.; Legrande, Allegra N.; Tripati, Aradhna K.

    2011-12-01

    An isotope-enabled ocean-atmosphere general circulation model (GISS ModelE-R) is used to estimate the spatial gradients of the oxygen isotopic composition of seawater (δ18Osw, where δ is the deviation from a known reference material in per mil) during the early Paleogene (45-65 Ma). Understanding the response of δ18Osw to changes in climatic and tectonic boundary conditions is important because records of carbonate δ18O document changes in hydrology, as well as changes in temperature and global ice-volume. We present results from an early Paleogene configuration of ModelE-R which indicate that spatial gradients of surface ocean δ18Osw during this period could have been significantly different to those in the modern ocean. The differences inferred from ModelE-R are sufficient to change early Paleogene sea surface temperature estimates derived from primary carbonate δ18O signatures by more than ±2°C in large areas of the ocean. In the North Atlantic, Indian, and Southern Oceans, the differences in δ18Osw inferred from our simulation with ModelE-R are in direct contrast with those from another δ18O-tracing model study which used different, but equally plausible, early Paleogene boundary conditions. The large differences in δ18Osw between preindustrial and early Paleogene simulations, and between models, emphasizes the sensitivity of δ18Osw to climatic and tectonic boundary conditions. For this reason, absolute estimates of Eocene/Paleocene temperature derived from carbonate δ18O alone are likely to have larger uncertainties than are usually assumed.

  20. Modelling the effect of climate change on recovery of acidified freshwaters: Relative sensitivity of individual processes in the MAGIC model

    Czech Academy of Sciences Publication Activity Database

    Wright, R. F.; Aherne, J.; Bishop, K.; Camarero, L.; Cosby, B.J.; Erlandsson, M.; Evans, C.D.; Forsius, M.; Hardekopf, D.W.; Helliwell, R.; Hruška, J.; Jenkins, A.; Kopáček, Jiří; Moldan, F.; Posch, M.; Rogora, M.

    2006-01-01

    Roč. 365, 1-3 (2006), s. 154-166 ISSN 0048-9697 Grant - others:CEC(XE) GOCE-CT-2003-505540; RCN(NO) - Institutional research plan: CEZ:AV0Z60170517 Keywords : freshwaters * acidification * climate change Subject RIV: DJ - Water Pollution ; Quality Impact factor: 2.359, year: 2006

  1. Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.

    Science.gov (United States)

    Peng, Jing; Dan, Li; Huang, Mei

    2014-01-01

    Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.

  2. Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.

    Directory of Open Access Journals (Sweden)

    Jing Peng

    Full Text Available Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5, we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet. The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.

  3. Sensitivity of Global and Regional Terrestrial Carbon Storage to the Direct CO2 Effect and Climate Change Based on the CMIP5 Model Intercomparison

    Science.gov (United States)

    Peng, Jing; Dan, Li; Huang, Mei

    2014-01-01

    Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics. PMID:24748331

  4. Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

    Science.gov (United States)

    Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

    2013-01-01

    Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

  5. Aboveground Allometric Models for Freeze-Affected Black Mangroves (Avicennia germinans): Equations for a Climate Sensitive Mangrove-Marsh Ecotone

    Science.gov (United States)

    Osland, Michael J.; Day, Richard H.; Larriviere, Jack C.; From, Andrew S.

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone. PMID:24971938

  6. Aboveground allometric models for freeze-affected black mangroves (Avicennia germinans): equations for a climate sensitive mangrove-marsh ecotone

    Science.gov (United States)

    Osland, Michael J.; Day, Richard H.; Larriviere, Jack C.; From, Andrew S.

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone.

  7. Aboveground allometric models for freeze-affected black mangroves (Avicennia germinans: equations for a climate sensitive mangrove-marsh ecotone.

    Directory of Open Access Journals (Sweden)

    Michael J Osland

    Full Text Available Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1 total aboveground biomass; (2 leaf biomass; (3 stem plus branch biomass; and (4 leaf area. Plant volume (i.e., a combination of crown area and plant height was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone.

  8. Aboveground allometric models for freeze-affected black mangroves (Avicennia germinans): equations for a climate sensitive mangrove-marsh ecotone.

    Science.gov (United States)

    Osland, Michael J; Day, Richard H; Larriviere, Jack C; From, Andrew S

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone.

  9. Modeling thermal structure, ice cover regime and sensitivity to climate change of two regulated lakes - a Norwegian case study

    Science.gov (United States)

    Gebre, Solomon; Boissy, Thibault; Alfredsen, Knut

    2013-04-01

    A great number of river and lakes in Norway and the Nordic region at large are regulated for water management such as hydropower production. Such regulations have the potential to alter the thermal and hydrological regimes in the lakes and rivers downstream impacting on river environment and ecology. Anticipated changes as a result of climate change in meteorological forcing data such as air temperature and precipitation cause changes in the water balance, water temperature and ice cover duration in the reservoirs. This may necessitate changes in operational rules as part of an adaptation strategy for the future. In this study, a one dimensional (1D) lake thermodynamic and ice cover model (MyLake) has been modified to take into account the effect of dynamic outflows in reservoirs and applied to two small but relatively deep regulated lakes (reservoirs) in Norway (Follsjøen and Tesse). The objective was to assess climate change impacts on the seasonal thermal characteristics, the withdrawal temperatures, and the reservoir ice cover dynamics with current operational regimes. The model solves the vertical energy balance on a daily time-step driven by meteorological and hydrological forcings: 2m air temperature, precipitation, 2m relative humidity, 10m wind speed, cloud cover, air pressure, solar insolation, inflow volume, inflow temperature and reservoir outflows. Model calibration with multi-seasonal data of temperature profiles showed that the model performed well in simulating the vertical water temperature profiles for the two study reservoirs. The withdrawal temperatures were also simulated reasonably well. The comparison between observed and simulated lake ice phenology (which were available only for one of the reservoirs - Tesse) was also reasonable taking into account the uncertainty in the observational data. After model testing and calibration, the model was then used to simulate expected changes in the future (2080s) due to climate change by considering

  10. Modelling the impacts of European emission and climate change scenarios on acid-sensitive catchments in Finland

    Directory of Open Access Journals (Sweden)

    M. Posch

    2008-03-01

    Full Text Available The dynamic hydro-chemical Model of Acidification of Groundwater in Catchments (MAGIC was used to predict the response of 163 Finnish lake catchments to future acidic deposition and climatic change scenarios. Future deposition was assumed to follow current European emission reduction policies and a scenario based on maximum (technologically feasible reductions (MFR. Future climate (temperature and precipitation was derived from the HadAM3 and ECHAM4/OPYC3 general circulation models under two global scenarios of the Intergovernmental Panel on Climate Change (IPCC: A2 and B2. The combinations resulting in the widest range of future changes were used for simulations, i.e., the A2 scenario results from ECHAM4/OPYC3 (highest predicted change and B2 results from HadAM3 (lowest predicted change. Future scenarios for catchment runoff were obtained from the Finnish watershed simulation and forecasting system. The potential influence of future changes in surface water organic carbon concentrations was also explored using simple empirical relationships based on temperature and sulphate deposition. Surprisingly, current emission reduction policies hardly show any future recovery; however, significant chemical recovery of soil and surface water from acidification was predicted under the MFR emission scenario. The direct influence of climate change (temperate and precipitation on recovery was negligible, as runoff hardly changed; greater precipitation is offset by increased evapotranspiration due to higher temperatures. However, two exploratory empirical DOC models indicated that changes in sulphur deposition or temperature could have a confounding influence on the recovery of surface waters from acidification, and that the corresponding increases in DOC concentrations may offset the recovery in pH due to reductions in acidifying depositions.

  11. Climate models and scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Fortelius, C.; Holopainen, E.; Kaurola, J.; Ruosteenoja, K.; Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

    1996-12-31

    In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

  12. Exploring the sensitivities of crenulate bay shorelines to wave climates using a new vector-based one-line model

    Science.gov (United States)

    Hurst, Martin D.; Barkwith, Andrew; Ellis, Michael A.; Thomas, Chris W.; Murray, A. Brad

    2015-12-01

    We use a new exploratory model that simulates the evolution of sandy coastlines over decadal to centennial timescales to examine the behavior of crenulate-shaped bays forced by differing directional wave climates. The model represents the coastline as a vector in a Cartesian reference frame, and the shoreface evolves relative to its local orientation, allowing simulation of coasts with high planform-curvature. Shoreline change is driven by gradients in alongshore transport following newly developed algorithms that facilitate dealing with high planform-curvature coastlines. We simulated the evolution of bays from a straight coast between two fixed headlands with no external sediment inputs to an equilibrium condition (zero net alongshore sediment flux) under an ensemble of directional wave climate conditions. We find that planform bay relief increases with obliquity of the mean wave direction, and decreases with the spread of wave directions. Varying bay size over 2 orders of magnitude (0.1-16 km), the model predicts bay shape to be independent of bay size. The time taken for modeled bays to attain equilibrium was found to scale with the square of the distance between headlands, so that, all else being equal, small bays are likely to respond to and recover from perturbations more rapidly (over just a few years) compared to large bays (hundreds of years). Empirical expressions predicting bay shape may be misleading if used to predict their behavior over planning timescales.

  13. Glacial climate sensitivity to different states of the Atlantic Meridional Overturning Circulation: results from the IPSL model

    Directory of Open Access Journals (Sweden)

    M. Kageyama

    2009-09-01

    Full Text Available Paleorecords from distant locations on the globe show rapid and large amplitude climate variations during the last glacial period. Here we study the global climatic response to different states of the Atlantic Meridional Overturning Circulation (AMOC as a potential explanation for these climate variations and their possible connections. We analyse three glacial simulations obtained with an atmosphere-ocean coupled general circulation model and characterised by different AMOC strengths (18, 15 and 2 Sv resulting from successive ~0.1 Sv freshwater perturbations in the North Atlantic. These AMOC states suggest the existence of a freshwater threshold for which the AMOC collapses. A weak (18 to 15 Sv AMOC decrease results in a North Atlantic and European cooling. This cooling is not homogeneous, with even a slight warming over the Norwegian Sea. Convection in this area is active in both experiments, but surprisingly stronger in the 15 Sv simulation, which appears to be related to interactions with the atmospheric circulation and sea-ice cover. Far from the North Atlantic, the climatic response is not significant. The climate differences for an AMOC collapse (15 to 2 Sv are much larger and of global extent. The timing of the climate response to this AMOC collapse suggests teleconnection mechanisms. Our analyses focus on the North Atlantic and surrounding regions, the tropical Atlantic and the Indian monsoon region. The North Atlantic cooling associated with the AMOC collapse induces a cyclonic atmospheric circulation anomaly centred over this region, which modulates the eastward advection of cold air over the Eurasian continent. This can explain why the cooling is not as strong over western Europe as over the North Atlantic. In the Tropics, the southward shift of the Inter-Tropical Convergence Zone appears to be strongest over the Atlantic and Eastern Pacific and results from an adjustment of the atmospheric and oceanic heat transports. Finally, the

  14. Sensitivity of Climate to Changes in NDVI

    Science.gov (United States)

    Bounoua, L.; Collatz, G. J.; Los, S. O.; Sellers, P. J.; Dazlich, D. A.; Tucker, C. J.; Randall, D. A.

    1999-01-01

    The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere-atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (ndvi). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982-1990. Albedo decreased in the northern latitudes and increased in the tropics with increased ndvi. The increase in vegetation density revealed that the vegetation's physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic C02 uptake on a global annual basis. This caused the canopy transpiration and interception fluxes to increase, and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting. Important effects of increased vegetation on climate are : (1) A cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy. and (2) A year round cooling of 0.8 K in the tropics. These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming . Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however increased more than precipitation resulting in a global soil-water deficit of about 15 %. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low

  15. Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF

    Energy Technology Data Exchange (ETDEWEB)

    Flaounas, Emmanouil; Bastin, Sophie [UPMC, CNRS/INSU, LATMOS/IPSL, Paris cedex 05 (France); Janicot, Serge [UPMC, IRD, LOCEAN-IPSL, Paris (France)

    2011-03-15

    Regional climate model (RCM) is a valuable scientific tool to address the mechanisms of regional atmospheric systems such as the West African monsoon (WAM). This study aims to improve our understanding of the impact of some physical schemes of RCM on the WAM representation. The weather research and forecasting model has been used by performing six simulations of the 2006 summer WAM season. These simulations use all combinations of three convective parameterization schemes (CPSs) and two planetary boundary layer schemes (PBLSs). By comparing the simulations to a large set of observations and analysis products, we have evaluated the ability of these RCM parameterizations to reproduce different aspects of the regional atmospheric circulation of the WAM. This study focuses in particular on the WAM onset and the rainfall variability simulated over this domain. According to the different parameterizations tested, the PBLSs seem to have the strongest effect on temperature, humidity vertical distribution and rainfall amount. On the other hand, dynamics and precipitation variability are strongly influenced by CPSs. In particular, the Mellor-Yamada-Janjic PBLS attributes more realistic values of humidity and temperature. Combined with the Kain-Fritsch CPS, the WAM onset is well represented. The different schemes combination tested also reveal the role of different regional climate features on WAM dynamics, namely the low level circulation, the land-atmosphere interactions and the meridional temperature gradient between the Guinean coast and the Sahel. (orig.)

  16. Cloud/climate sensitivity experiments

    Science.gov (United States)

    Roads, J. O.; Vallis, G. K.; Remer, L.

    1982-01-01

    A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

  17. Sensitivity of modelled sulfate aerosol and its radiative effect on climate to ocean DMS concentration and air–sea flux

    Directory of Open Access Journals (Sweden)

    J.-E. Tesdal

    2016-09-01

    Full Text Available Dimethylsulfide (DMS is a well-known marine trace gas that is emitted from the ocean and subsequently oxidizes to sulfate in the atmosphere. Sulfate aerosols in the atmosphere have direct and indirect effects on the amount of solar radiation reaching the Earth's surface. Thus, as a potential source of sulfate, ocean efflux of DMS needs to be accounted for in climate studies. Seawater concentration of DMS is highly variable in space and time, which in turn leads to high spatial and temporal variability in ocean DMS emissions. Because of sparse sampling (in both space and time, large uncertainties remain regarding ocean DMS concentration. In this study, we use an atmospheric general circulation model with explicit aerosol chemistry (CanAM4.1 and several climatologies of surface ocean DMS concentration to assess uncertainties about the climate impact of ocean DMS efflux. Despite substantial variation in the spatial pattern and seasonal evolution of simulated DMS fluxes, the global-mean radiative effect of sulfate is approximately linearly proportional to the global-mean surface flux of DMS; the spatial and temporal distribution of ocean DMS efflux has only a minor effect on the global radiation budget. The effect of the spatial structure, however, generates statistically significant changes in the global-mean concentrations of some aerosol species. The effect of seasonality on the net radiative effect is larger than that of spatial distribution and is significant at global scale.

  18. What Climate Sensitivity Index Is Most Useful for Projections?

    Science.gov (United States)

    Grose, Michael R.; Gregory, Jonathan; Colman, Robert; Andrews, Timothy

    2018-02-01

    Transient climate response (TCR), transient response at 140 years (T140), and equilibrium climate sensitivity (ECS) indices are intended as benchmarks for comparing the magnitude of climate response projected by climate models. It is generally assumed that TCR or T140 would explain more variability between models than ECS for temperature change over the 21st century, since this timescale is the realm of transient climate change. Here we find that TCR explains more variability across Coupled Model Intercomparison Project phase 5 than ECS for global temperature change since preindustrial, for 50 or 100 year global trends up to the present, and for projected change under representative concentration pathways in regions of delayed warming such as the Southern Ocean. However, unexpectedly, we find that ECS correlates higher than TCR for projected change from the present in the global mean and in most regions. This higher correlation does not relate to aerosol forcing, and the physical cause requires further investigation.

  19. Implications for Climate Sensitivity from the Response to Individual Forcings

    Science.gov (United States)

    Marvel, Kate; Schmidt, Gavin A.; Miller, Ron L.; Nazarenko, Larissa

    2015-01-01

    Climate sensitivity to doubled CO2 is a widely-used metric of the large-scale response to external forcing. Climate models predict a wide range for two commonly used definitions: the transient climate response (TCR: the warming after 70 years of CO2 concentrations that riseat 1 per year), and the equilibrium climate sensitivity (ECS: the equilibrium temperature change following a doubling of CO2 concentrations). Many observational datasets have been used to constrain these values, including temperature trends over the recent past 16, inferences from paleo-climate and process-based constraints from the modern satellite eras. However, as the IPCC recently reported different classes of observational constraints produce somewhat incongruent ranges. Here we show that climate sensitivity estimates derived from recent observations must account for the efficacy of each forcing active during the historical period. When we use single forcing experiments to estimate these efficacies and calculate climate sensitivity from the observed twentieth-century warming, our estimates of both TCR and ECS are revised upward compared to previous studies, improving the consistency with independent constraints.

  20. Regionalizing global climate models

    NARCIS (Netherlands)

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  1. Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

    Science.gov (United States)

    Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

    2012-01-01

    Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

  2. Sensitivity of streamflow to climate change in California

    Science.gov (United States)

    Grantham, T.; Carlisle, D.; Wolock, D.; McCabe, G. J.; Wieczorek, M.; Howard, J.

    2015-12-01

    Trends of decreasing snowpack and increasing risk of drought are looming challenges for California water resource management. Increasing vulnerability of the state's natural water supplies threatens California's social-economic vitality and the health of its freshwater ecosystems. Despite growing awareness of potential climate change impacts, robust management adaptation has been hindered by substantial uncertainty in future climate predictions for the region. Down-scaled global climate model (GCM) projections uniformly suggest future warming of the region, but projections are highly variable with respect to the direction and magnitude of change in regional precipitation. Here we examine the sensitivity of California surface water supplies to climate variation independently of GCMs. We use a statistical approach to construct predictive models of monthly streamflow based on historical climate and river basin features. We then propagate an ensemble of synthetic climate simulations through the models to assess potential streamflow responses to changes in temperature and precipitation in different months and regions of the state. We also consider the range of streamflow change predicted by bias-corrected downscaled GCMs. Our results indicate that the streamflow in the xeric and coastal mountain regions of California is more sensitive to changes in precipitation than temperature, whereas streamflow in the interior mountain region responds strongly to changes in both temperature and precipitation. Mean climate projections for 2025-2075 from GCM ensembles are highly variable, indicating streamflow changes of -50% to +150% relative to baseline (1980-2010) for most months and regions. By quantifying the sensitivity of streamflow to climate change, rather than attempting to predict future hydrologic conditions based on uncertain GCM projections, these results should be more informative to water managers seeking to assess, and potentially reduce, the vulnerability of surface

  3. Energy-balance climate models

    Science.gov (United States)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1980-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  4. Sensitivity of global terrestrial ecosystems to climate variability

    Science.gov (United States)

    Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

    2016-03-01

    The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

  5. Sensitivity of global terrestrial ecosystems to climate variability.

    Science.gov (United States)

    Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

    2016-03-10

    The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

  6. Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

    Science.gov (United States)

    Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

    2017-08-01

    The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over

  7. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    Past warm climate states could potentially provide information on future global warming. The past warming was driven by changed insolation rather than an increased greenhouse effect, and thus the warm climate states are expected to be different. Nonetheless, the response of the climate system...... involves some of the same mechanisms in the two climate states. This thesis aims to investigate these mechanisms through climate model experiments. This two-part study has a special focus on the Arctic region, and the main paleoclimate experiments are supplemented by idealized experiments detailing...... the impact of a changing sea ice cover. The first part focusses on the last interglacial climate (125,000 years before present) which was characterized by substantial warming at high northern latitudes due to an increased insolation during summer. The simulations reveal that the oceanic changes dominate...

  8. How does the sensitivity of climate affect stratospheric solar radiation management?

    Science.gov (United States)

    Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.

    2011-12-01

    If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best

  9. the sensitivity of evapotranspiration models to errors in model ...

    African Journals Online (AJOL)

    Dr Obe

    ABSTRACT. Five evapotranspiration (Et) model-the penman, Blaney - Criddel, Thornthwaite, the Blaney –. Morin-Nigeria, and the Jensen and Haise models – were analyzed for parameter sensitivity under Nigerian Climatic conditions. The sensitivity of each model to errors in any of its measured parameters (variables) was ...

  10. Range position and climate sensitivity: The structure of among-population demographic responses to climatic variation.

    Science.gov (United States)

    Amburgey, Staci M; Miller, David A W; Campbell Grant, Evan H; Rittenhouse, Tracy A G; Benard, Michael F; Richardson, Jonathan L; Urban, Mark C; Hughson, Ward; Brand, Adrianne B; Davis, Christopher J; Hardin, Carmen R; Paton, Peter W C; Raithel, Christopher J; Relyea, Rick A; Scott, A Floyd; Skelly, David K; Skidds, Dennis E; Smith, Charles K; Werner, Earl E

    2018-01-01

    Species' distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species' climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species' climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to

  11. Range position and climate sensitivity: The structure of among-population demographic responses to climatic variation

    Science.gov (United States)

    Amburgey, Staci M.; Miller, David A. W.; Grant, Evan H. Campbell; Rittenhouse, Tracy A. G.; Benard, Michael F.; Richardson, Jonathan L.; Urban, Mark C.; Hughson, Ward; Brand, Adrianne B,; Davis, Christopher J.; Hardin, Carmen R.; Paton, Peter W. C.; Raithel, Christopher J.; Relyea, Rick A.; Scott, A. Floyd; Skelly, David K.; Skidds, Dennis E.; Smith, Charles K.; Werner, Earl E.

    2018-01-01

    Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the

  12. The application of a coupled water-balance-salinity model to evaluate the sensitivity of a lake dominated by groundwater to climatic variability

    Science.gov (United States)

    Crowe, A. S.

    1993-01-01

    A dynamic hydrologic model, specifically designed to assess lake-groundwater systems, has been used to provide insight into the effects of climatic variability on Wabamun Lake and its watershed, in Alberta, Canada. This lake is typical of many lakes in the prairies of Canada or western plains of the United States in that groundwater exhibits a dominant role in the hydrologic balance of the lake. Sensitivity analyses indicate that small changes in temperature (1-2°C rise) or precipitation (5-10% decline) throughout the watershed, may significantly impact upon the quality of the lake water and the availability of groundwater resources. Specifically, a long-term temperature rise that increases evaporation, or a decrease in precipitation, will reduce the amount of water available to recharge the groundwater-flow regime. Groundwater storage in the watershed will further decline due to continued discharge to the lake. The effect of climatic variability on the quantity of water in Wabamun Lake (as reflected by its surface elevation) is relatively small. However, the salinity of the lake will increase dramatically, due to: (1) the loss of surface runod and direct precipitation, which act to dilute the salinity; (2) increased evaporation, which concentrates the salts left in the lake water; (3) reduced surface discharge from the lake as its surface elevation falls below the elevation of the outlet, which removes dissolved mass from the lake.

  13. Modeling glacial climates

    Science.gov (United States)

    North, G. R.; Crowley, T. J.

    1984-01-01

    Mathematical climate modelling has matured as a discipline to the point that it is useful in paleoclimatology. As an example a new two dimensional energy balance model is described and applied to several problems of current interest. The model includes the seasonal cycle and the detailed land-sea geographical distribution. By examining the changes in the seasonal cycle when external perturbations are forced upon the climate system it is possible to construct hypotheses about the origin of midlatitude ice sheets and polar ice caps. In particular the model predicts a rather sudden potential for glaciation over large areas when the Earth's orbital elements are only slightly altered. Similarly, the drift of continents or the change of atmospheric carbon dioxide over geological time induces radical changes in continental ice cover. With the advance of computer technology and improved understanding of the individual components of the climate system, these ideas will be tested in far more realistic models in the near future.

  14. Hydrological Sensitivity of Land Use Scenarios for Climate Mitigation

    Science.gov (United States)

    Boegh, E.; Friborg, T.; Hansen, K.; Jensen, R.; Seaby, L. P.

    2014-12-01

    Bringing atmospheric concentration to 550 ppm CO2 or below by 2100 will require large-scale changes to global and national energy systems, and potentially the use of land (IPCC, 2013) The Danish government aims at reducing greenhouse gas emissions (GHG) by 40 % in 1990-2020 and energy consumption to be based on 100 % renewable energy by 2035. By 2050, GHG emissions should be reduced by 80-95 %. Strategies developed to reach these goals require land use change to increase the production of biomass for bioenergy, further use of catch crops, reduced nitrogen inputs in agriculture, reduced soil tillage, afforestation and establishment of permanent grass fields. Currently, solar radiation in the growing season is not fully exploited, and it is expected that biomass production for bioenergy can be supported without reductions in food and fodder production. Impacts of climate change on the hydrological sensitivity of biomass growth and soil carbon storage are however not known. The present study evaluates the hydrological sensitivity of Danish land use options for climate mitigation in terms of crop yields (including straw for bioenergy) and net CO2 exchange for wheat, barley, maize and clover under current and future climate conditions. Hydrological sensitivity was evaluated using the agrohydrological model Daisy. Simulations during current climate conditions were in good agreement with measured dry matter, crop nitrogen content and eddy covariance fluxes of water vapour and CO2. Climate scenarios from the European ENSEMBLES database were downscaled for simulating water, nitrogen and carbon balance for 2071-2100. The biomass potential generally increase, but water stress also increases in strength and extends over a longer period, thereby increasing sensitivity to water availability. The potential of different land use scenarios to maximize vegetation cover and biomass for climate mitigation is further discussed in relation to impacts on the energy- and water balance.

  15. Phenological sensitivity to climate across taxa and trophic levels

    DEFF Research Database (Denmark)

    Thackeray, Stephen J.; Henrys, Peter; Hemming, Deborah

    2016-01-01

    Differences in phenological responses to climate change among species can desynchronise ecological interactions and thereby threaten ecosystem function. To assess these threats, we must quantify the relative impact of climate change on species at different trophic levels. Here, we apply a Climate...... Sensitivity Profile approach to 10,003 terrestrial and aquatic phenological data sets, spatially matched to temperature and precipitation data, to quantify variation in climate sensitivity. The direction, magnitude and timing of climate sensitivity varied markedly among organisms within taxonomic and trophic...... groups. Despite this variability, we detected systematic variation in the direction and magnitude of phenological climate sensitivity. Secondary consumers showed consistently lower climate sensitivity than other groups. We used mid-century climate change projections to estimate that the timing...

  16. Model confirmation in climate economics.

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K J

    2016-08-02

    Benefit-cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth-one of its most important economic components-had questionable predictive power over the 20th century.

  17. Effectiveness of stratospheric solar-radiation management as a function of climate sensitivity

    Science.gov (United States)

    Ricke, Katharine L.; Rowlands, Daniel J.; Ingram, William J.; Keith, David W.; Granger Morgan, M.

    2012-02-01

    If implementation of proposals to engineer the climate through solar-radiation management (SRM) ever occurs, it is likely to be contingent on climate sensitivity. However, modelling studies examining the effectiveness of SRM as a strategy to offset anthropogenic climate change have used only the standard parameterizations of atmosphere-ocean general circulation models that yield climate sensitivities close to the Coupled Model Intercomparison Project mean. Here, we use a perturbed-physics ensemble modelling experiment to examine how the response of the climate to SRM implemented in the stratosphere (SRM-S) varies under different greenhouse-gas climate sensitivities. When SRM-S is used to compensate for rising atmospheric concentrations of greenhouse gases, its effectiveness in stabilizing regional climates diminishes with increasing climate sensitivity. However, the potential of SRM-S to slow down unmitigated climate change, even regionally, increases with climate sensitivity. On average, in variants of the model with higher sensitivity, SRM-S reduces regional rates of temperature change by more than 90% and rates of precipitation change by more than 50%.

  18. Climate sensitivity of major river basins in Africa

    Science.gov (United States)

    Beyene, T.; Lettenmaier, D. P.; Kabat, P.; Ludwig, F.

    2011-12-01

    We simulate the land surface water balance of five major African river basins using the Variable Infiltration Capacity (VIC) land surface hydrologic model forced by gridded climate data of precipitation and temperature for the period 1979-1999. The seasonality and inter-annual variability of the water balance terms vary across the continent and at each river basin. The long-term mean vapor flux convergence P-E agrees well with observed runoff for the eastern and north western basins, whereas there is a relatively large imbalance (28%) for the Oranje River basin possibly because of its small size. The Zambezi and Oranje River basins act as a net source of moisture in dry seasons (strong negative P-E). Both the Nile and Zambezi basins have a low runoff efficiency and a high dryness index, indicating a high sensitivity to climate change in the case of the Nile, and moderate sensitivity in the case of the Zambezi. Although the severity of climate change impacts depends primarily on the magnitude of change, the different hydrological sensitivities of the basins are also important. Precipitation elasticities range from 2.2 to 3.1 for 10% increase and -2.1 to -2.7 for 10% decrease in precipitation respectively over the five river basins, whereas the sensitivity of runoff to temperature ranges (absolute value) from a high of -5%/degC for the Niger basin to a low of -1% for the Orange basin.

  19. Modeling the sensitivity of sediment and water runoff dynamics to Holocene climate and land use changes at the catchment scale

    NARCIS (Netherlands)

    Notebaert, B.; Verstraeten, G.; Ward, P.J.; Renssen, H.; Van Rompaey, A.

    2011-01-01

    An increasing number of studies have indicated that soil erosion, sediment redistribution and water discharge during the Holocene have varied greatly under influence of environmental changes. In this paper we have used a modeling approach to study the driving forces for soil erosion and sediment

  20. Abrupt change in climate and climate models

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2006-01-01

    Full Text Available First, we review the evidence that abrupt climate changes have occurred in the past and then demonstrate that climate models have developing capacity to simulate many of these changes. In particular, the processes by which changes in the ocean circulation drive abrupt changes appear to be captured by climate models to a degree that is encouraging. The evidence that past changes in the ocean have driven abrupt change in terrestrial systems is also convincing, but these processes are only just beginning to be included in climate models. Second, we explore the likelihood that climate models can capture those abrupt changes in climate that may occur in the future due to the enhanced greenhouse effect. We note that existing evidence indicates that a major collapse of the thermohaline circulation seems unlikely in the 21st century, although very recent evidence suggests that a weakening may already be underway. We have confidence that current climate models can capture a weakening, but a collapse in the 21st century of the thermohaline circulation is not projected by climate models. Worrying evidence of instability in terrestrial carbon, from observations and modelling studies, is beginning to accumulate. Current climate models used by the Intergovernmental Panel on Climate Change for the 4th Assessment Report do not include these terrestrial carbon processes. We therefore can not make statements with any confidence regarding these changes. At present, the scale of the terrestrial carbon feedback is believed to be small enough that it does not significantly affect projections of warming during the first half of the 21st century. However, the uncertainties in how biological systems will respond to warming are sufficiently large to undermine confidence in this belief and point us to areas requiring significant additional work.

  1. The Earth's Equilibrium Climate Sensitivity and Thermal Inertia

    OpenAIRE

    Royce, B. S. H.; Lam, S. H.

    2013-01-01

    The Earth's equilibrium climate sensitivity has received much attention because of its relevance and importance for global warming policymaking. This paper focuses on the Earth's \\emph{thermal inertia time scale} which has received relatively little attention. The difference between the observed transient climate sensitivity and the equilibrium climate sensitivity is shown to be proportional to the thermal inertia time scale, and the numerical value of the proportionality factor is determined...

  2. State-dependence of climate sensitivity : attractor constraints and palaeoclimate regimes

    NARCIS (Netherlands)

    von der Heydt, Anna; Ashwin, Peter

    2016-01-01

    Equilibrium climate sensitivity (ECS) is a key predictor of climate change. However, it is not very well constrained, either by climate models or by observational data. The reasons for this include strong internal variability and forcing on many time scales. In practise this means that the

  3. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  4. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  5. Evaluating sub-national building-energy efficiency policy options under uncertainty: Efficient sensitivity testing of alternative climate, technological, and socioeconomic futures in a regional integrated-assessment model

    International Nuclear Information System (INIS)

    Scott, Michael J.; Daly, Don S.; Zhou, Yuyu; Rice, Jennie S.; Patel, Pralit L.; McJeon, Haewon C.; Page Kyle, G.; Kim, Son H.; Eom, Jiyong

    2014-01-01

    Improving the energy efficiency of building stock, commercial equipment, and household appliances can have a major positive impact on energy use, carbon emissions, and building services. Sub-national regions such as the U.S. states wish to increase energy efficiency, reduce carbon emissions, or adapt to climate change. Evaluating sub-national policies to reduce energy use and emissions is difficult because of the large uncertainties in socioeconomic factors, technology performance and cost, and energy and climate policies. Climate change itself may undercut such policies. However, assessing all of the uncertainties of large-scale energy and climate models by performing thousands of model runs can be a significant modeling effort with its accompanying computational burden. By applying fractional–factorial methods to the GCAM-USA 50-state integrated-assessment model in the context of a particular policy question, this paper demonstrates how a decision-focused sensitivity analysis strategy can greatly reduce computational burden in the presence of uncertainty and reveal the important drivers for decisions and more detailed uncertainty analysis. - Highlights: • We evaluate building energy codes and standards for climate mitigation. • We use an integrated assessment model and fractional factorial methods. • Decision criteria are energy use, CO2 emitted, and building service cost. • We demonstrate sensitivity analysis for three states. • We identify key variables to propagate with Monte Carlo or surrogate models

  6. The Southern Oscillation in a coupled GCM: Implications for climate sensitivity and climate change

    International Nuclear Information System (INIS)

    Meehl, G.A.

    1991-01-01

    Results are presented from a global coupled ocean-atmosphere general circulation climate model developed at the National Center for Atmospheric Research. The atmospheric part of the coupled model is a global spectral (R15, 4.5 degree latitude by 7.5 degree longitude, 9 layers in the vertical) general circulation model. The ocean is coarse-grid (5 degree latitude by 5 degree longitude, 4 layers in the vertical) global general circulation model. The coupled model includes a simple thermodynamic sea-ice model. Due mainly to inherent limitations in the ocean model, the coupled model simulates sea surface temperatures that are too low in the tropics and too high in the extratropics in the mean. In spite of these limitations, the coupled model simulates active interannual variability of the global climate system involving signals in the tropical Pacific that resemble, in some respects, the observed Southern Oscillation. These signals in the tropics are associated with teleconnections to the extratropics of both hemispheres. The implications of this model-simulated interannual variability of the coupled system relating to climate sensitivity and climate change due to an increase of atmospheric carbon dioxide are discussed. 25 refs.; 9 figs

  7. The Southern Oscillation in a coupled GCM: Implications for climate sensitivity and climate change

    International Nuclear Information System (INIS)

    Meehl, G.A.

    1990-01-01

    Results are presented from a global coupled ocean-atmosphere general circulation climate model developed at the National Center for Atmospheric Research. The atmospheric part of the coupled model is a global spectral (R15, 4.5 degree latitude by 7.5 degree longitude, 9 layers in the vertical) general circulation model. The ocean is coarse-grid (5 degree latitude by 5 degree longitude, 4 layers in the vertical) global general circulation model. The coupled model includes a simple thermodynamic sea-ice model. Due mainly to inherent limitations in the ocean model, the coupled model simulates sea surface temperatures that are too low in the tropics and too high in the extratropics in the mean. In spite of these limitations, the coupled model simulates active interannual variability of the global climate system involving signals in the tropical Pacific that resemble, in some respects, the observed Southern Oscillation. These signals in the tropics are associated with teleconnections to the extratropics of both hemispheres. The implications of this model-simulated interannual variability of the coupled system relating to climate sensitivity and climate change due to an increase of atmospheric carbon dioxide are discussed

  8. Sensitivity of the atmospheric water cycle to corrections of the sea surface temperature bias over southern Africa in a regional climate model

    Science.gov (United States)

    Weber, Torsten; Haensler, Andreas; Jacob, Daniela

    2017-12-01

    Regional climate models (RCMs) have been used to dynamically downscale global climate projections at high spatial and temporal resolution in order to analyse the atmospheric water cycle. In southern Africa, precipitation pattern were strongly affected by the moisture transport from the southeast Atlantic and southwest Indian Ocean and, consequently, by their sea surface temperatures (SSTs). However, global ocean models often have deficiencies in resolving regional to local scale ocean currents, e.g. in ocean areas offshore the South African continent. By downscaling global climate projections using RCMs, the biased SSTs from the global forcing data were introduced to the RCMs and affected the results of regional climate projections. In this work, the impact of the SST bias correction on precipitation, evaporation and moisture transport were analysed over southern Africa. For this analysis, several experiments were conducted with the regional climate model REMO using corrected and uncorrected SSTs. In these experiments, a global MPI-ESM-LR historical simulation was downscaled with the regional climate model REMO to a high spatial resolution of 50 × 50 km2 and of 25 × 25 km2 for southern Africa using a double-nesting method. The results showed a distinct impact of the corrected SST on the moisture transport, the meridional vertical circulation and on the precipitation pattern in southern Africa. Furthermore, it was found that the experiment with the corrected SST led to a reduction of the wet bias over southern Africa and to a better agreement with observations as without SST bias corrections.

  9. Sensitivity of Regional Climate to Deforestation in the Amazon Basin

    Science.gov (United States)

    Eltahir, Elfatih A. B.; Bras, Rafael L.

    1994-01-01

    The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.

  10. Context Sensitive Modeling of Cancer Drug Sensitivity.

    Directory of Open Access Journals (Sweden)

    Bo-Juen Chen

    Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.

  11. Emergent constraint on equilibrium climate sensitivity from global temperature variability

    Science.gov (United States)

    Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.

    2018-01-01

    Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5–4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2–3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

  12. Sensitivity of the Freie Universität Berlin Climate Middle Atmosphere Model (FUB-CMAM to different gravity-wave drag parameterisations

    Directory of Open Access Journals (Sweden)

    P. Mieth

    2004-09-01

    Full Text Available We report the sensitivity of the Berlin Climate Middle Atmosphere Model (CMAM to different gravity-wave (GW parameterisations. We perform five perpetual January experiments: 1 Rayleigh friction (RF (control, 2 non-orographic GWs, 3 orographic GWs, 4 orographic and non-orographic GWs with no background stress, and 5 as for 4 but with background stress. We also repeat experiment 4 but for July conditions. Our main aim is to improve the model climatology by introducing orographic and non-orographic parameterisations and to investigate the individual effect of these schemes in the Berlin CMAM. We compare with an RF control to determine the improvement upon a previously-published model version employing RF. Results are broadly similar to previously-published works. The runs having both orographic and non-orographic GWs produce a statistically-significant warming of 4-8K in the wintertime polar lower stratosphere. These runs also feature a cooling of the warm summer pole in the mesosphere by 10-15K, more in line with observations. This is associated with the non-orographic GW scheme. This scheme is also associated with a heating feature in the winter polar upper stratosphere directly below the peak GW-breaking region. The runs with both orographic and non-orographic GWs feature a statistically-significant deceleration in the polar night jet (PNJ of 10-20ms-1 in the lower stratosphere. Both orographic and non-orographic GWs individually produce some latitudinal tilting of the polar jet with height, although the main effect comes from the non-orographic waves. The resulting degree of tilt, although improved, is nevertheless still weaker than that observed. Accordingly, wintertime variability in the zonal mean wind, which peaks at the edge of the vortex, tends to maximise too far polewards in the model compared with observations. Gravity-planetary wave interaction leads to a decrease in the amplitudes of stationary planetary waves 1 and 2 by up to 50% in

  13. Sensitivity of the Freie Universität Berlin Climate Middle Atmosphere Model (FUB-CMAM to different gravity-wave drag parameterisations

    Directory of Open Access Journals (Sweden)

    P. Mieth

    2004-09-01

    Full Text Available We report the sensitivity of the Berlin Climate Middle Atmosphere Model (CMAM to different gravity-wave (GW parameterisations. We perform five perpetual January experiments: 1 Rayleigh friction (RF (control, 2 non-orographic GWs, 3 orographic GWs, 4 orographic and non-orographic GWs with no background stress, and 5 as for 4 but with background stress. We also repeat experiment 4 but for July conditions. Our main aim is to improve the model climatology by introducing orographic and non-orographic parameterisations and to investigate the individual effect of these schemes in the Berlin CMAM. We compare with an RF control to determine the improvement upon a previously-published model version employing RF. Results are broadly similar to previously-published works. The runs having both orographic and non-orographic GWs produce a statistically-significant warming of 4-8K in the wintertime polar lower stratosphere. These runs also feature a cooling of the warm summer pole in the mesosphere by 10-15K, more in line with observations. This is associated with the non-orographic GW scheme. This scheme is also associated with a heating feature in the winter polar upper stratosphere directly below the peak GW-breaking region. The runs with both orographic and non-orographic GWs feature a statistically-significant deceleration in the polar night jet (PNJ of 10-20ms-1 in the lower stratosphere. Both orographic and non-orographic GWs individually produce some latitudinal tilting of the polar jet with height, although the main effect comes from the non-orographic waves. The resulting degree of tilt, although improved, is nevertheless still weaker than that observed. Accordingly, wintertime variability in the zonal mean wind, which peaks at the edge of the vortex, tends to maximise too far polewards in the model compared with observations. Gravity-planetary wave interaction leads to a decrease in the amplitudes of stationary planetary waves 1 and 2 by

  14. Model Democracy: Are All Climate Models Equally Good?

    Science.gov (United States)

    Shukla, J.

    2008-05-01

    We compare the ability of IPCC climate models to simulate present climate and their sensitivity to increased greenhouse gases. We find that models with higher fidelity in simulating the present climate produce higher values of global warming due to increased greenhouse gases. We also compare the forecast skill of dynamical seasonal prediction by coupled ocean-atmosphere models and their ability to simulate observed climate. Although all the current generation of coupled models have large error in simulating observed climate, yet the models with higher fidelity have higher skill. We conclude that there is a significant relationship between model fidelity and model sensitivity, and therefore, the IPCC assessments should not accept the concept of model democracy. We further conjecture that inaccuracy of climate models is the most dominant obstacle in both realizing the potential predictability of climate variations, and in providing reliable information on regional climate change. We make some proposals for the future pathways to improve the fidelity of climate models, and to harvest the realizable predictability.

  15. Assessing climate-sensitive ecosystems in the southeastern United States

    Science.gov (United States)

    Costanza, Jennifer; Beck, Scott; Pyne, Milo; Terando, Adam; Rubino, Matthew J.; White, Rickie; Collazo, Jaime

    2016-08-11

    Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing

  16. The influence of the albedo-temperature feedback on climate sensitivity

    NARCIS (Netherlands)

    Bintanja, R.; Oerlemans, J.

    1995-01-01

    A vertically integrated, zonally averaged energy-balance climate model coupled to a two-dimensional ocean model with prescribed overturning pattern is employed to assess the seasonally and latitudinally varying response of the climate system to changes in radiative forcing. Since the sensitivity

  17. Impact of Greenland and Antarctic ice sheet interactions on climate sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Goelzer, H.; Huybrechts, P. [Vrije Universiteit Brussel, Earth System Sciences and Departement Geografie, Brussels (Belgium); Loutre, M.F.; Goosse, H.; Fichefet, T. [Universite Catholique de Louvain, Georges Lemaitre Centre for Earth and Climate Research (TECLIM), Earth and Life Institute, Louvain-la-Neuve (Belgium); Mouchet, A. [Universite de Liege, Laboratoire de Physique Atmospherique et Planetaire, Liege (Belgium)

    2011-09-15

    We use the Earth system model of intermediate complexity LOVECLIM to show the effect of coupling interactive ice sheets on the climate sensitivity of the model on a millennial time scale. We compare the response to a 2 x CO{sub 2} warming scenario between fully coupled model versions including interactive Greenland and Antarctic ice sheet models and model versions with fixed ice sheets. For this purpose an ensemble of different parameter sets have been defined for LOVECLIM, covering a wide range of the model's sensitivity to greenhouse warming, while still simulating the present-day climate and the climate evolution over the last millennium within observational uncertainties. Additional freshwater fluxes from the melting ice sheets have a mitigating effect on the model's temperature response, leading to generally lower climate sensitivities of the fully coupled model versions. The mitigation is effectuated by changes in heat exchange within the ocean and at the sea-air interface, driven by freshening of the surface ocean and amplified by sea-ice-related feedbacks. The strength of the effect depends on the response of the ice sheets to the warming and on the model's climate sensitivity itself. The effect is relatively strong in model versions with higher climate sensitivity due to the relatively large polar amplification of LOVECLIM. With the ensemble approach in this study we cover a wide range of possible model responses. (orig.)

  18. Modeling Uncertainty in Climate Change: A Multi-Model Comparison

    Energy Technology Data Exchange (ETDEWEB)

    Gillingham, Kenneth; Nordhaus, William; Anthoff, David; Blanford, Geoffrey J.; Bosetti, Valentina; Christensen, Peter; McJeon, Haewon C.; Reilly, J. M.; Sztorc, Paul

    2015-10-01

    The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity and estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insight on tail events.

  19. Nonlinear climate sensitivity and its implications for future greenhouse warming

    Science.gov (United States)

    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

  20. Modeling the sensitivity of the Greenland Ice Sheet (GrIS) over the last deglaciation using improved climate reconstructions of temperature and precipitation in the Ice Sheet System Model (ISSM)

    Science.gov (United States)

    Cuzzone, J. K.; Larour, E. Y.; Morlighem, M.; Schlegel, N.; Badgeley, J.; Steig, E. J.; Buizert, C.

    2017-12-01

    Paleoclimate spinups of ice sheets can provide an important boundary condition for simulating ice sheets under present and future climate scenarios, while also providing a context on how sensitive ice sheets were to past climate change. Currently, many ice sheet models that simulate the past behavior of ice sheets rely on tuning of model specific parameter space or by adjusting the surface forcings (i.e. temperature and precipitation) to achieve the best fit with paleoclimate evidence of the ice sheet history. To create the necessary surface mass balance fields, a crude approximation based upon isotopic variations in ice core δ18O is often used to scale a modern day gridded climatology of temperature and precipitation back in time. This method is advantageous for long spinups, where variations in ice core δ18O is only needed to create the necessary surface forcings driving the past ice sheet surface mass balance. However, it cannot provide any information regarding changes in past climate seasonality and it assumes precipitation follows a purely thermodynamic relationship, therefore disregarding changes in past atmospheric circulation. Recent work has been performed to merge ice core temperature reconstructions with climate simulations during the last deglaciation, providing a continental wide Greenland Ice Sheet (GrIS) gridded temperature and precipitation reconstruction that extends back to the last glacial maximum (LGM). These new datasets resolve changes in past seasonality and incorporate changes in past atmospheric circulation by using information from climate models. This work will use two independent reconstructions of the past GrIS temperature and precipitation climatology that utilize different data assimilation techniques to drive simulations of the last deglaciation of the GrIS in the Ice Sheet System Model (ISSM). The simulation performed with ISSM relies on a 3 dimensional, thermomechanical higher order model. The results presented here will outline

  1. Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

    Science.gov (United States)

    Ruane, Alex C.; Cecil, L. Dewayne; Horton, Radley M.; Gordon, Roman; McCollum, Raymond (Brown, Douglas); Brown, Douglas; Killough, Brian; Goldberg, Richard; Greeley, Adam P.; Rosenzweig, Cynthia

    2011-01-01

    We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the

  2. WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

    Science.gov (United States)

    Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu. Gao

    2014-01-01

    Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...

  3. Greenhouse Effect, Radiative Forcing and Climate Sensitivity

    Science.gov (United States)

    Ponater, Michael; Dietmüller, Simone; Sausen, Robert

    Temperature conditions and climate on Earth are controlled by the balance between absorbed solar radiation and outgoing terrestrial radiation. The greenhouse effect is a synonym for the trapping of infrared radiation by radiatively active atmospheric constituents. It generally causes a warming of the planet's surface, compared to the case without atmosphere. Perturbing the radiation balance of the planet, e.g., by anthropogenic greenhouse gas emissions, induces climate change. Individual contributions to a total climate impact are usually quantified and ranked in terms of their respective radiative forcing. This method involves some limitations, because the effect of the external forcing is modified by radiative feedbacks. Here the current concept of radiative forcing and potential improvements are explained.

  4. Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

    Science.gov (United States)

    Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

    2014-01-01

    Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

  5. Electric climate-model

    Science.gov (United States)

    Koertvelyessy, L.

    Does the Sun heat variably by its varying magnetic fields? The main problem of all magnetic models is that SOHO found neither a "solar dynamo" nor "deep magnetic tubes". Also TRACE discovered too thin and straight filaments which could not have emerged through the boiling solar layers but grew out geyser-like from one foot-point. NASA stated some months ago that a "magnetic tube" would be unstable due to its own magnetic repulsion. A new, an electric climate-model is described based on the solar thermoelectric processes. TRACE- and LASCO-pictures show that solar filaments have an exact circular cross section i.e. they are electric direct currents shaped by the pinch-effect. Our climate is maximally correlated to the aa index of the magnetic storms which are the results of solar direct currents conducting by Earth. The burning out of the transformers of Hydro-Quebec (in 1989) is re-analysed on the base of these positive direct currents. The results are that the positive (active) Sun repulses the positive cosmic ray particles which are seeds of clouds. In addition, new movies show that this active Sun directly charges our clouds positively via red sprites during a proton storm. The hit clouds emit gamma rays and are perhaps diffused by this solar positive charge. Both effects could be responsible for the fact that the area of the clouds was found to be by 2-4.5 % lower in the middle magnetic latitudes during the last solar maximum. Parallel to both electric influences, the sunspots were re- discovered as "awesome solar hurricanes". ACRIM showed that their huge rotational energy can increase the solar irradiation . The present 88 year period will end in about 2045 probably with the highest irradiation of the last two millennia.

  6. Limits to global and Australian temperature change this century based on expert judgment of climate sensitivity

    Science.gov (United States)

    Grose, Michael R.; Colman, Robert; Bhend, Jonas; Moise, Aurel F.

    2017-05-01

    The projected warming of surface air temperature at the global and regional scale by the end of the century is directly related to emissions and Earth's climate sensitivity. Projections are typically produced using an ensemble of climate models such as CMIP5, however the range of climate sensitivity in models doesn't cover the entire range considered plausible by expert judgment. Of particular interest from a risk-management perspective is the lower impact outcome associated with low climate sensitivity and the low-probability, high-impact outcomes associated with the top of the range. Here we scale climate model output to the limits of expert judgment of climate sensitivity to explore these limits. This scaling indicates an expanded range of projected change for each emissions pathway, including a much higher upper bound for both the globe and Australia. We find the possibility of exceeding a warming of 2 °C since pre-industrial is projected under high emissions for every model even scaled to the lowest estimate of sensitivity, and is possible under low emissions under most estimates of sensitivity. Although these are not quantitative projections, the results may be useful to inform thinking about the limits to change until the sensitivity can be more reliably constrained, or this expanded range of possibilities can be explored in a more formal way. When viewing climate projections, accounting for these low-probability but high-impact outcomes in a risk management approach can complement the focus on the likely range of projections. They can also highlight the scale of the potential reduction in range of projections, should tight constraints on climate sensitivity be established by future research.

  7. Increased sensitivity to climate change in disturbed ecosystems.

    Science.gov (United States)

    Kröel-Dulay, György; Ransijn, Johannes; Schmidt, Inger Kappel; Beier, Claus; De Angelis, Paolo; de Dato, Giovanbattista; Dukes, Jeffrey S; Emmett, Bridget; Estiarte, Marc; Garadnai, János; Kongstad, Jane; Kovács-Láng, Edit; Larsen, Klaus Steenberg; Liberati, Dario; Ogaya, Romà; Riis-Nielsen, Torben; Smith, Andrew R; Sowerby, Alwyn; Tietema, Albert; Penuelas, Josep

    2015-03-24

    Human domination of the biosphere includes changes to disturbance regimes, which push many ecosystems towards early-successional states. Ecological theory predicts that early-successional ecosystems are more sensitive to perturbations than mature systems, but little evidence supports this relationship for the perturbation of climate change. Here we show that vegetation (abundance, species richness and species composition) across seven European shrublands is quite resistant to moderate experimental warming and drought, and responsiveness is associated with the dynamic state of the ecosystem, with recently disturbed sites responding to treatments. Furthermore, most of these responses are not rapid (2-5 years) but emerge over a longer term (7-14 years). These results suggest that successional state influences the sensitivity of ecosystems to climate change, and that ecosystems recovering from disturbances may be sensitive to even modest climatic changes. A research bias towards undisturbed ecosystems might thus lead to an underestimation of the impacts of climate change.

  8. Uncertainty Quantification in Climate Modeling and Projection

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Yun; Jackson, Charles; Giorgi, Filippo; Booth, Ben; Duan, Qingyun; Forest, Chris; Higdon, Dave; Hou, Z. Jason; Huerta, Gabriel

    2016-05-01

    The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for

  9. Diagnosis of Middle Atmosphere Climate Sensitivity by the Climate Feedback Response Analysis Method

    Science.gov (United States)

    Zhu, Xun; Yee, Jeng-Hwa; Cai, Ming; Swartz, William H.; Coy, Lawrence; Aquila, Valentina; Talaat, Elsayed R.

    2014-01-01

    We present a new method to diagnose the middle atmosphere climate sensitivity by extending the Climate Feedback-Response Analysis Method (CFRAM) for the coupled atmosphere-surface system to the middle atmosphere. The Middle atmosphere CFRAM (MCFRAM) is built on the atmospheric energy equation per unit mass with radiative heating and cooling rates as its major thermal energy sources. MCFRAM preserves the CFRAM unique feature of an additive property for which the sum of all partial temperature changes due to variations in external forcing and feedback processes equals the observed temperature change. In addition, MCFRAM establishes a physical relationship of radiative damping between the energy perturbations associated with various feedback processes and temperature perturbations associated with thermal responses. MCFRAM is applied to both measurements and model output fields to diagnose the middle atmosphere climate sensitivity. It is found that the largest component of the middle atmosphere temperature response to the 11-year solar cycle (solar maximum vs. solar minimum) is directly from the partial temperature change due to the variation of the input solar flux. Increasing CO2 always cools the middle atmosphere with time whereas partial temperature change due to O3 variation could be either positive or negative. The partial temperature changes due to different feedbacks show distinctly different spatial patterns. The thermally driven globally averaged partial temperature change due to all radiative processes is approximately equal to the observed temperature change, ranging from 0.5 K near 70 km from the near solar maximum to the solar minimum.

  10. Comparing Hydrologic Sensitivities to Climate Change in the headwaters of the Colorado River basin

    Science.gov (United States)

    Mendoza, Pablo; Clark, Martyn; Rajagopalan, Balaji; Mizukami, Naoki

    2013-04-01

    Over the last few decades, many sources of uncertainty have been identified in climate change studies: different emissions scenarios, different general circulation model (GCM) structures and parameters, distinct GCM initial conditions, several downscaling methods, multiple hydrological model structures and multiple hydrological model parameters. Although the hydrological community has recognized the relevance and practical utility of applying this "cascade of uncertainty" paradigm, this approach does not help to advance process understanding or predictive capabilities. Additionally, recent studies have demonstrated that the choice of hydrologic model structure is a critical issue for the assessment of climate change impacts, but we still have limited understanding of why different models have different sensitivities to climate change. In this study, we assess the climate sensitivity of three different hydrologic/land surface models (PRMS, VIC and Noah-MP) over a small set of case study basins located in the headwaters of the Colorado River, USA. Our goal is to evaluate how hydrologic sensitivities vary across models in terms of 1) the main water balance components, and 2) seasonal changes in individual states and fluxes. Despite the partitioning of precipitation into ET and runoff is clearly model-dependent, all models predict an increase in ET and decrease in SWE and runoff for a future climate scenario. Noah-MP is the most sensitive model in water balance budget components, and all models reflect very similar seasonal changes in basin-averaged snowpack. Some individual fluxes are more sensitive to changes in climate than others (e.g. baseflow), and ongoing research is currently focused on parameter perturbation experiments to improve understanding of the relative role of parameters and model structures in determining the conclusions of climate impact assessments.

  11. Higher climatological temperature sensitivity of soil carbon in cold than warm climates

    Science.gov (United States)

    Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

    2017-11-01

    The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

  12. Methyl bromide: ocean sources, ocean sinks, and climate sensitivity.

    Science.gov (United States)

    Anbar, A D; Yung, Y L; Chavez, F P

    1996-03-01

    perturbations to temperature or productivity can modify atmospheric CH3Br. Therefore atmospheric CH3Br should be sensitive to climate conditions. Our modeling indicates that climate-induced CH3Br variations can be larger than those resulting from small (+/- 25%) changes in the anthropogenic source, assuming that this source comprises less than half of all inputs. Future measurements of marine CH3Br, temperature, and primary production should be combined with such models to determine the relationship between marine biological activity and CH3Br production. Better understanding of the biological term is especially important to assess the importance of non-anthropogenic sources to stratospheric ozone loss and the sensitivity of these sources to global climate change.

  13. A seasonal climate model for earth

    Science.gov (United States)

    North, G. R.; Coakley, J. A.

    1979-01-01

    A simple seasonal climate model for earth is developed on the basis of a few terms extracted from monthly and zonally averaged climatic data fields represented in latitude by Legendre polynomials and in time by Fourier series. This simple, physically motivated model accounts for the gross features of the present zonally averaged seasonal climate (root mean square error of two deg C). The sensitivities of the seasonal model and a corresponding mean annual model are approximately equal if ice and snow lines (for albedo purposes) are attached to certain mean-annual and instantaneous isotherms. More dynamics (in particular, cryospheric) are needed in the seasonal model to explain the relationship between glacial rhythms and changes in the earth's orbital elements.

  14. Ultra-sensitive Alpine lakes and climate change

    Directory of Open Access Journals (Sweden)

    Roland SCHMIDT

    2005-08-01

    Full Text Available Global warming is one of the major issues with which mankind is being confronted, having vital ecological and economic consequences. Ice-cover, snow-cover and water temperatures in alpine catchments are controlled by air temperatures, and so are very susceptible to shifts in climate. Local factors such as wind exposure, shading, and snow patches that persist during cold summers can, however, modify the sensitivities of the relationships to air temperature. Thermistors exposed in 45 mountain lakes of the central Austrian Alps (Niedere Tauern measured water temperatures during 1998 – 2003 at two or four hourly intervals. Degree-day and exponential smoothing models tuned with this data suggest we can anticipate extremely large temperature rises in some of the Niedere Tauern lakes in the coming century. Lakes at around 1500 to 2000 m altitude are found to be ultra-sensitive as they lie in the elevation range where changes in both ice-cover and snow-cover duration will be particularly pronounced. In the more extreme cases, our impact models predict a summer-epilimnion water-temperature rise of over 10 degrees. One example of a lake most at risk to future climate change is Moaralmsee. This lake is located at 1825 m a.s.l. on the northern slopes of the Niedere Tauern; its water temperature is likely to rise by 12 degrees. The projected water discharge, ice-cover duration and water temperature changes for the Tauern catchments in the coming century far exceed the variations experienced at any stage during the last ten thousand years.

  15. Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

    Science.gov (United States)

    Quetin, G. R.; Swann, A. L. S.

    2017-12-01

    Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to

  16. Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Tian [Pacific Northwest National Laboratory, Richland, Washington; Voisin, Nathalie [Pacific Northwest National Laboratory, Richland, Washington; Leng, Guoyong [Pacific Northwest National Laboratory, Richland, Washington; Huang, Maoyi [Pacific Northwest National Laboratory, Richland, Washington; Kraucunas, Ian [Pacific Northwest National Laboratory, Richland, Washington

    2018-03-01

    Water management activities or flow regulations modify water fluxes at the land surface and affect water resources in space and time. We hypothesize that flow regulations change the sensitivity of river flow to climate change with respect to unmanaged water resources. Quantifying these changes in sensitivity could help elucidate the impacts of water management at different spatiotemporal scales and inform climate adaptation decisions. In this study, we compared the emergence of significant changes in natural and regulated river flow regimes across the Western United States from simulations driven by multiple climate models and scenarios. We find that significant climate change-induced alterations in natural flow do not cascade linearly through water management activities. At the annual time scale, 50% of the Hydrologic Unit Code 4 (HUC4) sub-basins over the Western U.S. regions tend to have regulated flow regime more sensitive to the climate change than natural flow regime. Seasonality analyses show that the sensitivity varies remarkably across the seasons. We also find that the sensitivity is related to the level of water management. For 35% of the HUC4 sub-basins with the highest level of water management, the summer and winter flows tend to show a heightened sensitivity to climate change due to the complexity of joint reservoir operations. We further demonstrate that the impacts of considering water management in models are comparable to those that arises from uncertainties across climate models and emission scenarios. This prompts further climate adaptation studies research about nonlinearity effects of climate change through water management activities.

  17. Final Report. Evaluating the Climate Sensitivity of Dissipative Subgrid-Scale Mixing Processes and Variable Resolution in NCAR's Community Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-12-14

    The goals of this project were to (1) assess and quantify the sensitivity and scale-dependency of unresolved subgrid-scale mixing processes in NCAR’s Community Earth System Model (CESM), and (2) to improve the accuracy and skill of forthcoming CESM configurations on modern cubed-sphere and variable-resolution computational grids. The research thereby contributed to the description and quantification of uncertainties in CESM’s dynamical cores and their physics-dynamics interactions.

  18. Modelling climate change and malaria transmission.

    Science.gov (United States)

    Parham, Paul E; Michael, Edwin

    2010-01-01

    The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here

  19. Can climate sensitivity be estimated from short-term relationships of top-of-atmosphere net radiation and surface temperature?

    International Nuclear Information System (INIS)

    Lin Bing; Min Qilong; Sun Wenbo; Hu Yongxiang; Fan, Tai-Fang

    2011-01-01

    Increasing the knowledge in climate radiative feedbacks is critical for current climate studies. This work focuses on short-term relationships between global mean surface temperature and top-of-atmosphere (TOA) net radiation. The relationships may be used to characterize the climate feedback as suggested by some recent studies. As those recent studies, an energy balance model with ocean mixed layer and both radiative and non-radiative heat sources is used here. The significant improvement of current model is that climate system memories are considered. Based on model simulations, short-term relationship between global mean surface temperature and TOA net radiation (or the linear striation feature as suggested by previous studies) might represent climate feedbacks when the system had no memories. However, climate systems with the same short-term feedbacks but different memories would have a similar linear striation feature. This linear striation feature reflects only fast components of climate feedbacks and may not represent the total climate feedback even when the memory length of climate systems is minimal. The potential errors in the use of short-term relationships in estimations of climate sensitivity could be big. In short time scales, fast climate processes may overwhelm long-term climate feedbacks. Thus, the climate radiative feedback parameter obtained from short-term data may not provide a reliable estimate of climate sensitivity. This result also suggests that long-term observations of global surface temperature and TOA radiation are critical in the understanding of climate feedbacks and sensitivities.

  20. Plio-Pleistocene climate sensitivity evaluated using high-resolution CO2 records.

    Science.gov (United States)

    Martínez-Botí, M A; Foster, G L; Chalk, T B; Rohling, E J; Sexton, P F; Lunt, D J; Pancost, R D; Badger, M P S; Schmidt, D N

    2015-02-05

    Theory and climate modelling suggest that the sensitivity of Earth's climate to changes in radiative forcing could depend on the background climate. However, palaeoclimate data have thus far been insufficient to provide a conclusive test of this prediction. Here we present atmospheric carbon dioxide (CO2) reconstructions based on multi-site boron-isotope records from the late Pliocene epoch (3.3 to 2.3 million years ago). We find that Earth's climate sensitivity to CO2-based radiative forcing (Earth system sensitivity) was half as strong during the warm Pliocene as during the cold late Pleistocene epoch (0.8 to 0.01 million years ago). We attribute this difference to the radiative impacts of continental ice-volume changes (the ice-albedo feedback) during the late Pleistocene, because equilibrium climate sensitivity is identical for the two intervals when we account for such impacts using sea-level reconstructions. We conclude that, on a global scale, no unexpected climate feedbacks operated during the warm Pliocene, and that predictions of equilibrium climate sensitivity (excluding long-term ice-albedo feedbacks) for our Pliocene-like future (with CO2 levels up to maximum Pliocene levels of 450 parts per million) are well described by the currently accepted range of an increase of 1.5 K to 4.5 K per doubling of CO2.

  1. Climate Model Diagnostic Analyzer

    Data.gov (United States)

    National Aeronautics and Space Administration — Both the National Research Council (NRC) Decadal Survey and the latest Intergovernmental Panel on Climate Change (IPCC) Assessment Report stressed the need for the...

  2. Sensitivity of ocean acidification and oxygen to the uncertainty in climate change

    International Nuclear Information System (INIS)

    Cao, Long; Wang, Shuangjing; Zheng, Meidi; Zhang, Han

    2014-01-01

    Due to increasing atmospheric CO 2 concentrations and associated climate change, the global ocean is undergoing substantial physical and biogeochemical changes. Among these, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would also affect the projection of oxygen and carbonate chemistry. To investigate this issue, we use an Earth system model of intermediate complexity to perform a set of simulations, including that which involves no radiative effect of atmospheric CO 2 and those which involve CO 2 -induced climate change with climate sensitivity varying from 0.5 °C to 4.5 °C. Atmospheric CO 2 concentration is prescribed to follow RCP 8.5 pathway and its extensions. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. It is found that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO 2 -induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO 2 -induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change. (letters)

  3. Sensitivity of North American agriculture to ENSO-based climate scenarios and their socio-economic consequences: Modeling in an integrated assessment framework

    Energy Technology Data Exchange (ETDEWEB)

    Rosenberg, N.J.; Izaurralde, R.C.; Brown, R.A.; Sands, R.D. [Pacific Northwest National Lab., Richland, WA (United States); Legler, D. [Florida State Univ., Tallahassee, FL (United States). Center for Ocean Atmosphere Prediction Studies; Srinivasan, R. [Texas A and M Univ., College Station, TX (United States). Blacklands Research Center; Tiscareno-Lopez, M.

    1997-09-01

    A group of Canadian, US and Mexican natural resource specialists, organized by the Pacific Northwest National Laboratory (PNNL) under its North American Energy, Environment and Economy (NA3E) Program, has applied a simulation modeling approach to estimating the impact of ENSO-driven climatic variations on the productivity of major crops grown in the three countries. Methodological development is described and results of the simulations presented in this report. EPIC (the Erosion Productivity Impact Calculator) was the agro-ecosystem model selected-for this study. EPIC uses a daily time step to simulate crop growth and yield, water use, runoff and soil erosion among other variables. The model was applied to a set of so-called representative farms parameterized through a specially-assembled Geographic Information System (GIS) to reflect the soils, topography, crop management and weather typical of the regions represented. Fifty one representative farms were developed for Canada, 66 for the US and 23 for Mexico. El Nino-Southern Oscillation (ENSO) scenarios for the EPIC simulations were created using the historic record of sea-surface temperature (SST) prevailing in the eastern tropical Pacific for the period October 1--September 30. Each year between 1960 and 1989 was thus assigned to an ENSO category or state. The ENSO states were defined as El Nino (EN, SST warmer than the long-term mean), Strong El Nino (SEN, much warmer), El Viejo (EV, cooler) and Neutral (within {+-}0.5 C of the long-term mean). Monthly means of temperature and precipitation were then calculated at each farm for the period 1960--1989 and the differences (or anomalies) between the means in Neutral years and EN, SEN and EV years determined. The average monthly anomalies for each ENSO state were then used to create new monthly statistics for each farm and ENSO-state combination. The adjusted monthly statistics characteristic of each ENSO state were then used to drive a stochastic-weather simulator

  4. Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2009-01-01

    This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

  5. Climate sensitivity of shrub growth across the tundra biome

    DEFF Research Database (Denmark)

    Myers-Smith, Isla H; Elmendorf, Sarah C; Beck, Pieter S.A.

    2015-01-01

    Rapid climate warming in the tundra biome has been linked to increasing shrub dominance1–4. Shrub expansion can modify climate by altering surface albedo, energy and water balance, and permafrost2,5–8, yet the drivers of shrub growth remain poorly understood. Dendroecological data consisting...... be incorporated into Earth system models to improve future projections of climate change impacts across the tundra biome....

  6. A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

    Science.gov (United States)

    Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

    2017-12-01

    Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

  7. Sensitivity of the Himalayan orography representation in simulation of winter precipitation using Regional Climate Model (RegCM) nested in a GCM

    Science.gov (United States)

    Tiwari, P. R.; Kar, S. C.; Mohanty, U. C.; Dey, S.; Sinha, P.; Shekhar, M. S.

    2017-12-01

    The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in NCMRWF global spectral model is examined in simulating the winter circulation and associated precipitation over the Northwest India (NWI; 23°-37.5°N and 69°-85°E) region. For this purpose, nine different set of orography representations for nine distinct precipitation years (three years each for wet, normal and dry) have been considered by increasing (decreasing) 5, 10, 15, and 20% from the mean height (CNTRL) of the Himalaya in RegCM4 model. Validation with various observations revealed a good improvement in reproducing the precipitation intensity and distribution with increased model height compared to the results obtained from CNTRL and reduced orography experiments. Further it has been found that, increase in height by 10% (P10) increases seasonal precipitation about 20%, while decrease in height by 10% (M10) results around 28% reduction in seasonal precipitation as compared to CNTRL experiment over NWI region. This improvement in precipitation simulation comes due to better representation of vertical pressure velocity and moisture transport as these factors play an important role in wintertime precipitation processes over NWI region. Furthermore, a comparison of model-simulated precipitation with observed precipitation at 17 station locations has been also carried out. Overall, the results suggest that when the orographic increment of 10% (P10) is applied on RegCM4 model, it has better skill in simulating the precipitation over the NWI region and this model is a useful tool for further regional downscaling studies.

  8. Modeling sensitivity study of the possible impact of snow and glaciers developing over Tibetan Plateau on Holocene African-Asian summer monsoon climate

    Directory of Open Access Journals (Sweden)

    L. Jin

    2009-08-01

    Full Text Available The impacts of various scenarios of a gradual snow and glaciers developing over the Tibetan Plateau on climate change in Afro-Asian monsoon region and other regions during the Holocene (9 kyr BP–0 kyr BP are studied by using the Earth system model of intermediate complexity, CLIMBER-2. The simulations show that the imposed snow and glaciers over the Tibetan Plateau in the mid-Holocene induce global summer temperature decreases over most of Eurasia but in the Southern Asia temperature response is opposite. With the imposed snow and glaciers, summer precipitation decreases strongly in North Africa and South Asia as well as northeastern China, while it increases in Southeast Asia and the Mediterranean. For the whole period of Holocene (9 kyr BP–0 kyr BP, the response of vegetation cover to the imposed snow and glaciers cover over the Tibetan Plateau is not synchronous in South Asia and in North Africa, showing an earlier and a more rapid decrease in vegetation cover in North Africa from 9 kyr BP to 6 kyr BP while it has only minor influence on that in South Asia until 5 kyr BP. The precipitation decreases rapidly in North Africa and South Asia while it decreases slowly or unchanged during 6 kyr BP to 0 kyr BP with imposed snow and glacier cover over the Tibetan Plateau. The different scenarios of snow and glacier developing over the Tibetan Plateau would result in differences in variation of temperature, precipitation and vegetation cover in North Africa, South Asia and Southeast Asia. The model results suggest that the development of snow and ice cover over Tibetan Plateau represents an additional important climate feedback, which amplify orbital forcing and produces a significant synergy with the positive vegetation feedback.

  9. Sensitivity of Distributions of Climate System Properties to Surface Temperature Datasets

    Science.gov (United States)

    Libardoni, A. G.; Forest, C. E.

    2011-12-01

    Predictions of climate change from models depend strongly on the representation of climate system properties emerging from the processes and feedbacks in the models. The quality of any model prediction can be evaluated by determining how well its output reproduces the observed climate system. With this evaluation, the reliability of climate projections derived from the model and provided for policy makers is assessed and quantified. In this study, surface temperature, upper-air temperature, and ocean heat content data are used to constrain the distributions of the parameters that define three climate system properties in the MIT Integrated Global Systems Model: climate sensitivity, the rate of ocean heat uptake into the deep ocean, and net anthropogenic aerosol forcing. In particular, we explore the sensitivity of the distributions to the surface temperature dataset used to estimate the likelihood of model output given the observed climate records. In total, five different reconstructions of past surface temperatures are used and the resulting parameter distribution functions differ from each other. Differences in estimates of climate sensitivity mode and mean are as great as 1 K between the datasets, with an overall range of 1.2 to 5.3 K using the 5-95 confidence intervals. Ocean effective diffusivity is poorly constrained regardless of which dataset is used. All distributions show broad distributions and only three show signs of a distribution mode. When a mode is present, they tend to be for low diffusivity values. Distributions for the net aerosol forcing show similar shapes and cluster into two groups that are shifted by approximately 0.1 watts per square meter. However, the overall spread of forcing values from the 5-95 confidence interval, -0.19 to -0.83 watts per square meter, is small compared to other uncertainties in climate forcings. Transient climate response estimates derived from these distributions range between 0.87 and 2.41 K. Similar to the

  10. Hydroelectric Optimized System Sensitivity to Climate

    Science.gov (United States)

    Howard, J. C.; Howard, C. D.

    2009-12-01

    This paper compares the response of a large hydro system, globally optimized for daily operations, under a range of reservoir system inflows. The modeled system consists of Projects and hydro operating constraints on the South Saskatchewan River, Lake Winnipeg, Southern Indian Lake, Churchill Diversion, Red River, Winnipeg River, and the Nelson River. The river system is continental in scale, stretching from the Rocky Mountains to Hudson Bay. The hydro storage is large enough to operate with a two year cycle, which includes freezeup conditions. The objective is to maximize seasonal value of energy generation over a two year time horizon. Linear and quadratic constraints represent reservoir stage-storage curves, tailwater stage-discharge curves, transient river routing, and seasonally dependent environmental constraints on operations. This paper describes the optimization modeling approaches used to represent an actual physical system and to accommodate uncertainties in the historical datasets used for calibration. The results are hypothetical, not a forecast.

  11. Sensitivity Assessment of Ozone Models

    Energy Technology Data Exchange (ETDEWEB)

    Shorter, Jeffrey A.; Rabitz, Herschel A.; Armstrong, Russell A.

    2000-01-24

    The activities under this contract effort were aimed at developing sensitivity analysis techniques and fully equivalent operational models (FEOMs) for applications in the DOE Atmospheric Chemistry Program (ACP). MRC developed a new model representation algorithm that uses a hierarchical, correlated function expansion containing a finite number of terms. A full expansion of this type is an exact representation of the original model and each of the expansion functions is explicitly calculated using the original model. After calculating the expansion functions, they are assembled into a fully equivalent operational model (FEOM) that can directly replace the original mode.

  12. Thermal tolerance and climate warming sensitivity in tropical snails.

    Science.gov (United States)

    Marshall, David J; Rezende, Enrico L; Baharuddin, Nursalwa; Choi, Francis; Helmuth, Brian

    2015-12-01

    Tropical ectotherms are predicted to be especially vulnerable to climate change because their thermal tolerance limits generally lie close to current maximum air temperatures. This prediction derives primarily from studies on insects and lizards and remains untested for other taxa with contrasting ecologies. We studied the HCT (heat coma temperatures) and ULT (upper lethal temperatures) of 40 species of tropical eulittoral snails (Littorinidae and Neritidae) inhabiting exposed rocky shores and shaded mangrove forests in Oceania, Africa, Asia and North America. We also estimated extremes in animal body temperature at each site using a simple heat budget model and historical (20 years) air temperature and solar radiation data. Phylogenetic analyses suggest that HCT and ULT exhibit limited adaptive variation across habitats (mangroves vs. rocky shores) or geographic locations despite their contrasting thermal regimes. Instead, the elevated heat tolerance of these species (HCT = 44.5 ± 1.8°C and ULT = 52.1 ± 2.2°C) seems to reflect the extreme temperature variability of intertidal systems. Sensitivity to climate warming, which was quantified as the difference between HCT or ULT and maximum body temperature, differed greatly between snails from sunny (rocky shore; Thermal Safety Margin, TSM = -14.8 ± 3.3°C and -6.2 ± 4.4°C for HCT and ULT, respectively) and shaded (mangrove) habitats (TSM = 5.1 ± 3.6°C and 12.5 ± 3.6°C). Negative TSMs in rocky shore animals suggest that mortality is likely ameliorated during extreme climatic events by behavioral thermoregulation. Given the low variability in heat tolerance across species, habitat and geographic location account for most of the variation in TSM and may adequately predict the vulnerability to climate change. These findings caution against generalizations on the impact of global warming across ectothermic taxa and highlight how the consideration of nonmodel animals, ecological transitions

  13. Which climatic modeling to assess climate change impacts on vineyards?

    OpenAIRE

    Quenol, Herve; Garcia De Cortazar Atauri, Inaki; Bois, Benjamin; Sturman, Andrew; Bonnardot, Valerie; Le Roux, Renan

    2017-01-01

    The impact of climatic change on viticulture is significant: main phenological stages appear earlier, wine characteristics are changing, ... This clearly illustrates the point that the adaptation of viticulture to climate change is crucial and should be based on simulations of future climate. Several types of models exist and are used to represent viticultural climates at various scales. In this paper, we propose a review of different types of climate models (methodology and uncertainties) an...

  14. Normal Forms for Reduced Stochastic Climate Models

    Science.gov (United States)

    Franzke, C.; Majda, A.; Crommelin, D.

    2009-04-01

    The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOF) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It will be shown that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large-scales by the small scales and simultaneously strong cubic damping. This normal form should prove useful for developing systematic regression fitting strategies for stochastic models of climate data. The validity of the one and two dimensional normal forms will be presented. Also the analytical PDF form for one-dimensional reduced models will be derived. This PDF can exhibit power-law decay only over a limited range and its ultimate decay is determined by the cubic damping. This cubic damping produces a Gaussian tail.

  15. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

    Science.gov (United States)

    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.

  16. Climate sensitivity of DSSAT under different agriculture practice scenarios in China

    Science.gov (United States)

    Xia, L.; Robock, A.

    2014-12-01

    Crop yields are sensitive to both agricultural practice and climate changes. Under different agricultural practice scenarios, crop yield may have different climate sensitivities. Since it is important to understand how future climate changes affect agriculture productivity and what the potential adaptation strategies would be to compensate for possible negative impacts on crop production, we performed experiments to study climate sensitivity under different agricultural practice scenarios for rice, maize and wheat in the top four production provinces in China using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The agricultural practice scenarios include four categories: different amounts of nitrogen fertilizer or no nitrogen stress; irrigation turned on or off, or no water stress; all possible seeds in the DSSAT cultivar data base; and different planting dates. For the climate sensitivity test, the control climate is from 1998 to 2007, and we individually modify four climate variables: daily maximum and minimum temperature by +2 °C and -2 °C, daily precipitation by +20% and -20%, and daily solar radiation by + 20% and -20%. With more nitrogen fertilizer applied, crops are more sensitive to temperature changes as well as precipitation changes because of their release from nitrogen limitation. With irrigation turned on, crop yield sensitivity to temperature decreases in most of the regions depending on the amount of the local precipitation, since more water is available and soil temperature varies less with higher soil moisture. Those results indicate that there could be possible agriculture adaptation strategies under certain future climate scenarios. For example, increasing nitrogen fertilizer usage by a certain amount might compensate for the negative impact on crop yield from climate changes. However, since crops are more sensitive to climate changes when there is more nitrogen fertilizer applied, if the climate changes are

  17. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  18. Eocene Hyperthermal Climate Sensitivity to Greenhouse Gas and Aerosol Forcing

    Science.gov (United States)

    Winguth, A. M. E.; Hughlett, T. M.; Brown, M.; Rothstein, M.; Shields, C. A.; Winguth, C.

    2017-12-01

    A series of DeepMIP climate sensitivity experiments have been carried out with the Community Earth System Model CESM1.2 to evaluate how changes in the radiative forcing could have contributed to explain Eocene hyperthermal events. A rise in Eocene greenhouse gas forcing could have been linked to an increase in volcanism and associated destabilization of marine carbon reservoirs by dissociation of clathrathes, reorganization of the marine microbial loop, or terrestrial sources from e.g. wetlands. Such environmental changes could potentially have led to additional biophysical feedbacks altering the cloud aerosol optical depth for example by alteration of marine plankton productivity and DMS emissions to the atmosphere. The analysis of our simulations suggests a substantial warming from 3x to 12x CO2 PAL, reaching moderate temperatures of up to 20 °C over Antarctica and in the Article realm in the most extreme scenario, consistent to proxy estimates in a high CO2 world. The lower equator-to-pole temperature gradient compared to present-day is due to the lack of an ice sheet, an increase in greenhouse gases, and a lower cloud optical depth. The climate simulations suggest an intensified hydrological cycle with higher precipitation in the tropics, particularly over the Indian Eocene continent, and in mid-latitudes, whereas mega-droughts are prominent in the subtropics, particularly in Africa and South America. The Eocene geography (the closure of the Drake Passage and the more southern location of Australia) and a lower-than-present meridional temperature gradient contribute to a much weaker surface ocean circulation near the Antarctic continent as compared to the current pronounced Antarctic Circumpolar Current.

  19. Sensitivity of the regional climate in the Middle East and North Africa to volcanic perturbations

    Science.gov (United States)

    Dogar, Muhammad Mubashar; Stenchikov, Georgiy; Osipov, Sergey; Wyman, Bruce; Zhao, Ming

    2017-08-01

    The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/National Centers for Environmental Prediction Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model. A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon, and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.

  20. Determination of a lower bound on Earth's climate sensitivity

    Directory of Open Access Journals (Sweden)

    STEPHEN E. Schwartz

    2013-09-01

    Full Text Available Transient and equilibrium sensitivity of Earth's climate has been calculated using global temperature, forcing and heating rate data for the period 1970–2010. We have assumed increased long-wave radiative forcing in the period due to the increase of the long-lived greenhouse gases. By assuming the change in aerosol forcing in the period to be zero, we calculate what we consider to be lower bounds to these sensitivities, as the magnitude of the negative aerosol forcing is unlikely to have diminished in this period. The radiation imbalance necessary to calculate equilibrium sensitivity is estimated from the rate of ocean heat accumulation as 0.37±0.03 W m−2 (all uncertainty estimates are 1−σ. With these data, we obtain best estimates for transient climate sensitivity 0.39±0.07 K (W m−2−1 and equilibrium climate sensitivity 0.54±0.14 K (W m−2−1, equivalent to 1.5±0.3 and 2.0±0.5 K (3.7 W m−2−1, respectively. The latter quantity is equal to the lower bound of the ‘likely’ range for this quantity given by the 2007 IPCC Assessment Report. The uncertainty attached to the lower-bound equilibrium sensitivity permits us to state, within the assumptions of this analysis, that the equilibrium sensitivity is greater than 0.31 K (W m−2−1, equivalent to 1.16 K (3.7 W m−2−1, at the 95% confidence level.

  1. The Finer Details: Climate Modeling

    Science.gov (United States)

    2000-01-01

    If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

  2. What can decadal variability tell us about climate feedbacks and sensitivity?

    Science.gov (United States)

    Colman, Robert; Power, Scott B.

    2018-02-01

    Radiative feedbacks are known to determine climate sensitivity. Global top-of-atmosphere radiation correlations with surface temperature performed here show that decadal variability in surface temperature is also reinforced by strong positive feedbacks in models, both in the long wave (LW) and short wave (SW), offsetting much of the Planck radiative damping. Net top-of-atmosphere feedback is correlated with the magnitude of decadal temperature variability, particularly in the tropics. This indicates decadal-timescale radiative reinforcement of surface temperature variability. Assuming a simple global ocean mixed layer response, the reinforcement is found to be of a magnitude comparable to that required for typical decadal global scale anomalies. The magnitude of decadal variability in the tropics is uncorrelated with LW feedbacks, but it is correlated with total SW feedbacks, which are, in turn, correlated with tropical SW cloud feedback. Globally, water vapour/lapse rate, surface albedo and cloud feedbacks on decadal timescales are, on average, as strong as those operating under climate change. Together these results suggest that some of the physical processes responsible for setting the magnitude of global temperature change in the twenty-first century and climate sensitivity also help set the magnitude of the natural decadal variability. Furthermore, a statistically significant correlation exists between climate sensitivity and decadal variability in the tropics across CMIP5 models, although this is not apparent in the earlier generation of CMIP3 models. Thus although the link to sensitivity is not conclusive, this opens up potential paths to improve our understanding of climate feedbacks, climate sensitivity and decadal climate variability, and has the potential to reduce the associated uncertainty.

  3. Sensitivity of water resources in the Delaware River basin to climate variability and change

    Science.gov (United States)

    Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

    1994-01-01

    Because of the greenhouse effect, projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climate change; and presents the results of sensitivity analyses of how climate change might affect water resources in the Delaware River basin. Sensitivity analyses suggest that potentially serious shortfalls of certain water resources in the basin could result if some scenarios for climate change come true . The results of model simulations of the basin streamflow demonstrate the difficulty in distinguishing the effects that climate change versus natural climate variability have on streamflow and water supply . The future direction of basin changes in most water resources, furthermore, cannot be precisely determined because of uncertainty in current projections of regional temperature and precipitation . This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant . The sensitivity analyses could be useful in developing contingency plans for evaluating and responding to changes, should they occur.

  4. Chaotic Attractor Crisis and Climate Sensitivity: a Transfer Operator Approach

    Science.gov (United States)

    Tantet, A.; Lucarini, V.; Lunkeit, F.; Dijkstra, H. A.

    2015-12-01

    The rough response to a smooth parameter change of some non-chaotic climate models, such as the warm to snowball-Earth transition in energy balance models due to the ice-albedo feedback, can be studied in the framework of bifurcation theory, in particular by analysing the Lyapunov spectrum of fixed points or periodic orbits. However, bifurcation theory is of little help to study the destruction of a chaotic attractor which can occur in high-dimensional General Circulation Models (GCM). Yet, one would expect critical slowing down to occur before the crisis, since, as the system becomes susceptible to the physical instability mechanism responsible for the crisis, it turns out to be less and less resilient to exogenous perturbations and to spontaneous fluctuations due to other types of instabilities on the attractor. The statistical physics framework, extended to nonequilibrium systems, is particularly well suited for the study of global properties of chaotic and stochastic systems. In particular, the semigroup of transfer operators governs the evolution of distributions in phase space and its spectrum characterises both the relaxation rate of distributions to a statistical steady-state and the stability of this steady-state to perturbations. If critical slowing down indeed occurs in the approach to an attractor crisis, the gap in the spectrum of the semigroup of transfer operators is expected to shrink. We show that the chaotic attractor crisis due to the ice-albedo feedback and resulting in a transition from a warm to a snowball-Earth in the Planet Simulator (PlaSim), a GCM of intermediate complexity, is associated with critical slowing down, as observed by the slower decay of correlations before the crisis (cf. left panel). In addition, we demonstrate that this critical slowing down can be traced back to the shrinkage of the gap between the leading eigenvalues of coarse-grained approximations of the transfer operators and that these eigenvalues capture the

  5. Climate and climate sensitivity to changing CO2 on an idealized land planet

    Science.gov (United States)

    Becker, Tobias; Stevens, Bjorn

    2014-12-01

    The comprehensive general circulation model ECHAM6 is used in a radiative-convective equilibrium configuration. It is coupled to a perfectly conducting slab. To understand the local impact of thermodynamic surface properties on the land-ocean warming contrast, the surface latent heat flux and surface heat capacity are reduced stepwise, aiming for a land-like climate. Both ocean-like and land-like RCE simulation reproduce the tropical atmosphere over ocean and land in a satisfactory manner and lead to reasonable land-ocean warming ratios. A small surface heat capacity induces a high diurnal surface temperature range which triggers precipitation during the day and decouples the free troposphere from the diurnal mean temperature. With increasing evaporation resistance, the net atmospheric cooling rate decreases because cloud base height rises, causing a reduction of precipitation. Climate sensitivity depends more on changes in evaporation resistance than on changes in surface heat capacity. A feedback analysis with the partial radiation perturbation method shows that amplified warming over idealized land can be associated with disproportional changes in the lapse rate versus the water vapor feedback. Cloud feedbacks, convective aggregation, and changes in global mean surface temperature confuse the picture.

  6. Increased sensitivity to climate change in disturbed ecosystems

    DEFF Research Database (Denmark)

    Kroël-Dulay, György; Ransijn, Johannes; Schmidt, Inger Kappel

    2015-01-01

    this relationship for the perturbation of climate change. Here we show that vegetation (abundance, species richness and species composition) across seven European shrublands is quite resistant to moderate experimental warming and drought, and responsiveness is associated with the dynamic state of the ecosystem......Human domination of the biosphere includes changes to disturbance regimes, which push many ecosystems towards early-successional states. Ecological theory predicts that early-successional ecosystems are more sensitive to perturbations than mature systems, but little evidence supports......, with recently disturbed sites responding to treatments. Furthermore, most of these responses are not rapid (2-5 years) but emerge over a longer term (7-14 years). These results suggest that successional state influences the sensitivity of ecosystems to climate change, and that ecosystems recovering from...

  7. Modeling Aeolian Transport of Contaminated Sediments at Los Alamos National Laboratory, Technical Area 54, Area G: Sensitivities to Succession, Disturbance, and Future Climate

    International Nuclear Information System (INIS)

    Whicker, Jeffrey J.; Kirchner, Thomas B.; Breshears, David D.; Field, Jason P.

    2012-01-01

    The Technical Area 54 (TA-54) Area G disposal facility is used for the disposal of radioactive waste at Los Alamos National Laboratory (LANL). U.S. Department of Energy (DOE) Order 435.1 (DOE, 2001) requires that radioactive waste be managed in a manner that protects public health and safety and the environment. In compliance with that requirement, DOE field sites must prepare and maintain site-specific radiological performance assessments for facilities that receive waste after September 26, 1988. Sites are also required to conduct composite analyses for facilities that receive waste after this date; these analyses account for the cumulative impacts of all waste that has been (and will be) disposed of at the facilities and other sources of radioactive material that may interact with these facilities. LANL issued Revision 4 of the Area G performance assessment and composite analysis in 2008. In support of those analyses, vertical and horizontal sediment flux data were collected at two analog sites, each with different dominant vegetation characteristics, and used to estimate rates of vertical resuspension and wind erosion for Area G. The results of that investigation indicated that there was no net loss of soil at the disposal site due to wind erosion, and suggested minimal impacts of wind on the long-term performance of the facility. However, that study did not evaluate the potential for contaminant transport caused by the horizontal movement of soil particles over long time frames. Since that time, additional field data have been collected to estimate wind threshold velocities for initiating sediment transport due to saltation and rates of sediment transport once those thresholds are reached. Data such as these have been used in the development of the Vegetation Modified Transport (VMTran) model. This model is designed to estimate patterns and long-term rates of contaminant redistribution caused by winds at the site, taking into account the impacts of plant

  8. Modeling Aeolian Transport of Contaminated Sediments at Los Alamos National Laboratory, Technical Area 54, Area G: Sensitivities to Succession, Disturbance, and Future Climate

    Energy Technology Data Exchange (ETDEWEB)

    Whicker, Jeffrey J. [Los Alamos National Laboratory; Kirchner, Thomas B. [New Mexico State University; Breshears, David D. [University of Arizona; Field, Jason P. [University of Arizona

    2012-03-27

    The Technical Area 54 (TA-54) Area G disposal facility is used for the disposal of radioactive waste at Los Alamos National Laboratory (LANL). U.S. Department of Energy (DOE) Order 435.1 (DOE, 2001) requires that radioactive waste be managed in a manner that protects public health and safety and the environment. In compliance with that requirement, DOE field sites must prepare and maintain site-specific radiological performance assessments for facilities that receive waste after September 26, 1988. Sites are also required to conduct composite analyses for facilities that receive waste after this date; these analyses account for the cumulative impacts of all waste that has been (and will be) disposed of at the facilities and other sources of radioactive material that may interact with these facilities. LANL issued Revision 4 of the Area G performance assessment and composite analysis in 2008. In support of those analyses, vertical and horizontal sediment flux data were collected at two analog sites, each with different dominant vegetation characteristics, and used to estimate rates of vertical resuspension and wind erosion for Area G. The results of that investigation indicated that there was no net loss of soil at the disposal site due to wind erosion, and suggested minimal impacts of wind on the long-term performance of the facility. However, that study did not evaluate the potential for contaminant transport caused by the horizontal movement of soil particles over long time frames. Since that time, additional field data have been collected to estimate wind threshold velocities for initiating sediment transport due to saltation and rates of sediment transport once those thresholds are reached. Data such as these have been used in the development of the Vegetation Modified Transport (VMTran) model. This model is designed to estimate patterns and long-term rates of contaminant redistribution caused by winds at the site, taking into account the impacts of plant

  9. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

    Science.gov (United States)

    Cox, Peter M; Pearson, David; Booth, Ben B; Friedlingstein, Pierre; Huntingford, Chris; Jones, Chris D; Luke, Catherine M

    2013-02-21

    The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.

  10. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    Science.gov (United States)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  11. Central sensitization and perceived indoor climate among workers with chronic upper-limb pain

    DEFF Research Database (Denmark)

    Sundstrup, Emil; Jakobsen, Markus D.; Brandt, Mikkel

    2015-01-01

    threshold (PPT) was measured in muscles of the arm, shoulder, and lower leg. Cross-sectional associations were determined using general linear models controlled for age, smoking, and job position. The number of indoor climate complaints was twice as high among workers with chronic pain compared with pain......Monitoring of indoor climate is an essential part of occupational health and safety. While questionnaires are commonly used for surveillance, not all workers may perceive an identical indoor climate similarly. The aim of this study was to evaluate perceived indoor climate among workers with chronic...... pain compared with pain-free colleagues and to determine the influence of central sensitization on this perception. Eighty-two male slaughterhouse workers, 49 with upper-limb chronic pain and 33 pain-free controls, replied to a questionnaire with 13 items of indoor climate complaints. Pressure pain...

  12. Relationship of tropospheric stability to climate sensitivity and Earth's observed radiation budget.

    Science.gov (United States)

    Ceppi, Paulo; Gregory, Jonathan M

    2017-12-12

    Climate feedbacks generally become smaller in magnitude over time under CO 2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO 2 Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.

  13. Relationship of tropospheric stability to climate sensitivity and Earth's observed radiation budget

    Science.gov (United States)

    Ceppi, Paulo; Gregory, Jonathan M.

    2017-12-01

    Climate feedbacks generally become smaller in magnitude over time under CO2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO2. Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.

  14. Growing sensitivity of maize to water scarcity under climate change.

    Science.gov (United States)

    Meng, Qingfeng; Chen, Xinping; Lobell, David B; Cui, Zhenling; Zhang, Yi; Yang, Haishun; Zhang, Fusuo

    2016-01-25

    Climate change can reduce crop yields and thereby threaten food security. The current measures used to adapt to climate change involve avoiding crops yield decrease, however, the limitations of such measures due to water and other resources scarcity have not been well understood. Here, we quantify how the sensitivity of maize to water availability has increased because of the shift toward longer-maturing varieties during last three decades in the Chinese Maize Belt (CMB). We report that modern, longer-maturing varieties have extended the growing period by an average of 8 days and have significantly offset the negative impacts of climate change on yield. However, the sensitivity of maize production to water has increased: maize yield across the CMB was 5% lower with rainfed than with irrigated maize in the 1980s and was 10% lower (and even >20% lower in some areas) in the 2000s because of both warming and the increased requirement for water by the longer-maturing varieties. Of the maize area in China, 40% now fails to receive the precipitation required to attain the full yield potential. Opportunities for water saving in maize systems exist, but water scarcity in China remains a serious problem.

  15. A scenario neutral approach to assess low flow sensitivity to climate change

    Science.gov (United States)

    Sauquet, Eric; Prudhomme, Christel

    2015-04-01

    Most impact studies of climate change on river flow regime are performed following top-down approaches, where changes in hydrological characteristics are obtained from rainfall-runoff models forced by downscaled projections provided by GCMs. However, such approaches are not always considered robust enough to bridge the gap between climate research and stake holders needs to develop relevant adaptation strategy (Wilby et al., 2014). Alternatively, 'bottom-up' approaches can be applied to climate change impact studies on water resources to assess the intrinsic vulnerability of the catchments and ultimately help to prioritize adaptation actions for areas highly sensitive to small deviations from the present-day climate conditions. A general framework combining the scenario-neutral methodology developed by Prudhomme et al. (2010) and climate elasticity analyses (Sankarasubramanian et al., 2001) is presented and applied to measure the vulnerability of low flows and droughts on a large dataset of more than 400 French gauged basins. The different steps involved in the suggested framework are: - Calibration of the GR5J rainfall runoff model (Pushpalatha et al., 2011) against observations, - Identification of the main climate factors influencing low flows, - Definition of the sensitivity domain for precipitation (P), temperature (T) and potential evapotranspiration (PE) scenarios consistent with most recent climate change projections, - Derivation of the response surface describing changes in low flow and drought regime in terms of severity, duration and seasonality (Catalogne, 2012), - Uncertainty assessment. Results are the basis for a classification of river basins according to their sensitivity at national scale and for discussions on adaptation requirements with stakeholders. Catalogne C (2012) Amélioration des méthodes de prédétermination des débits de référence d'étiage en sites peu ou pas jaugés. PHD thesis, Université Joseph Fourier, Grenoble, 285 pp

  16. Intervention model in organizational climate

    OpenAIRE

    Cárdenas Niño, Lucila; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Arciniegas Rodríguez, Yuly Cristina; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05; Barrera Cárdenas, Mónica; Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias de la Salud, Escuela de Psicología, Hospital Antiguo, Carrera 10 No 16ª05

    2015-01-01

    The aim of this study was to assess whether the intervention model in organizational climate PMCO, was effective in the Hospital of Yopal, Colombia. The following five phases, proposed by the model, were implemented: 1) problem analysis, 2) awareness, 3) strategies design and planning, at the individual, intergroup, and organizational levels, 4) implementation of the strategy, and 5) process evaluation. A design composed of two groups, experimental and control, was chosen, analyzing whether t...

  17. Catchment sensitivity to changing climate conditions: the importance of landscape characteristic

    Science.gov (United States)

    Teutschbein, C.; Karlsen, R.; Grabs, T.; Laudon, H.; Bishop, K. H.

    2014-12-01

    The scientific literature is full of studies analyzing future climate change impacts on hydrology with focus on individual catchments. However, we recently found that hydrologic behavior and specific discharge vary considerably even in neighboring and rather similar catchments under current climate conditions and that these variations are related to landscape characteristics. Therefore we hypothesize that these landscape characteristics also play a fundamental role for the sensitivity of a catchment to changing climate conditions. We analyzed the hydrological response of 14 neighboring catchments in Northern Sweden with slightly different topography, land cover, size and geology. Current (1981-2010) and future (2061-2090) streamflow was simulated with the HBV light model. Climate projections were based on 14 regional climate models (ENSEMBLES EU project) and bias-corrected with a distribution-mapping approach. Our simulations revealed that future spring flood peaks will occur much earlier and decrease by 13 to 32 %, whereas winter base flows will increase slightly. These changes are somewhat expected and mainly triggered by a projected increase in winter temperature, which leads to less snow accumulation on the ground. However, these values also highlight that there is a large variability amongst the catchments in their hydrological response to the same future climate conditions. For example, spring flood peaks in catchments without wetlands decrease by only 13 to 15 %, whereas catchments with wetlands show a spring flood peak reduction of 20 to 32 %. In addition to wetlands, we also identified lakes, peat soils and higher elevations as factors that seem to cause a stronger hydrological response to the climate change signal, whereas catchments dominated by forests, steeper slopes and till soils seem to be less strongly affected by a changing climate. Therefore, our results suggest that the sensitivity of catchments to future climate conditions is strongly linked to

  18. The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

    Science.gov (United States)

    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.

  19. Lakes sensitivity to climatic stress – a sociological assessment

    Directory of Open Access Journals (Sweden)

    Lackowska Marta

    2016-12-01

    Full Text Available One of the conditions for effective water resources management in protected areas is local decision makers’ knowledge about potential threats caused by climate changes. Our study, conducted in the UNESCO Biosphere Reserve of Tuchola Forest in Poland, analyses the perception of threats by local stakeholders. Their assessments of the sensitivity of four lakes to the extreme weather events are compared with hydrological studies. The survey shows that the lakes’ varying responses to extreme weather conditions is rarely noticed by ordinary observers. Their perception is usually far from the hydrological facts, which indicates a lack of relevant information or a failure in making it widely accessible and understandable. Moreover, it is rather the human impact, not climate change, which is seen as the biggest threat to the lakes. Insufficient environmental knowledge may hinder the effective protection and management of natural resources, due to bad decisions and lack of the local communities’ support for adaptation and mitigation policies.

  20. Is equilibrium climate sensitivity the best predictor for future global warming? (Invited)

    Science.gov (United States)

    Rypdal, M.; Rypdal, K.

    2013-12-01

    When the climate system is subject to radiative forcing the planet is brought out of radiative balance and the thermal inertia of the planet makes the surface temperature lag behind the forcing. The time constant, which is the time for relaxation to a new equilibrium after a sudden change in forcing, has been considered to be an important parameter to determine. The equilibrium climate sensitivity Seq, the temperature raise per unit forcing after relaxation is complete, is another. In the industrialized epoch a major source for the present energy imbalance is the steady increase in anthropogenic forcing. If the climate system can be modeled as a hierarchy of interacting subsystems with increasing heat capacities and response times there will also be a hierarchy of climate sensitivities. One way of modeling this feature is to replace the standard exponentially decaying impulse-response function with one that is scale free, i.e., decaying like a power law. For a climate system which is subject only to random forcing modeled as a white Gaussian noise, the resulting climate variable is then a long-memory fractional Gaussian noise with a scale-free power spectral density. The final response to a step increase in the forcing is infinite for such a perfectly scale-free response function, since the response to an increase in the forcing will never saturate. This is of course unphysical, but rather than invalidating the scale-free response model it suggests the introduction of a frequency-dependent climate sensitivity S(f). Even in the exponential response model the amplitude response to an oscillation vanishes for high frequencies, but converges to Seq in the limit of low frequencies f. In the scale-free response model S(f) diverges in the low-frequency limit. We demonstrate that long-memory responses can explain important aspects of Northern hemisphere temperature variability over the last millennium and lead to new predictions of how much more warming there will be 'in

  1. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate......To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  2. The Monash University Interactive Simple Climate Model

    Science.gov (United States)

    Dommenget, D.

    2013-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  3. Computer experiments with a coarse-grid hydrodynamic climate model

    International Nuclear Information System (INIS)

    Stenchikov, G.L.

    1990-01-01

    A climate model is developed on the basis of the two-level Mintz-Arakawa general circulation model of the atmosphere and a bulk model of the upper layer of the ocean. A detailed model of the spectral transport of shortwave and longwave radiation is used to investigate the radiative effects of greenhouse gases. The radiative fluxes are calculated at the boundaries of five layers, each with a pressure thickness of about 200 mb. The results of the climate sensitivity calculations for mean-annual and perpetual seasonal regimes are discussed. The CCAS (Computer Center of the Academy of Sciences) climate model is used to investigate the climatic effects of anthropogenic changes of the optical properties of the atmosphere due to increasing CO 2 content and aerosol pollution, and to calculate the sensitivity to changes of land surface albedo and humidity

  4. Annual mean sea level and its sensitivity to wind climate

    Science.gov (United States)

    Gerkema, Theo; Duran Matute, Matias

    2017-04-01

    the west-east component of the net wind energy vector, with some further improvement if one also includes the south-north component and annual mean atmospheric pressure. Knowledge of these local correlations can then be used to correct values of annual mean sea for these atmospheric effects. This halves the margin of error (expressed as 95%-confidence interval) for linear trends in a 20-year sea level record. The sensitivity on wind direction has a regional variability, even on a small scale like the Dutch Wadden Sea. Model results illustrate the detailed spatial patterns in inter-annual variability of annual mean sea level. This study also implies that climatic changes in wind direction, or in the strength of winds from a specific direction, may affect local annual mean sea level quite significantly.

  5. Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance

    Directory of Open Access Journals (Sweden)

    B. Lin

    2010-02-01

    Full Text Available Large climate feedback uncertainties limit the accuracy in predicting the response of the Earth's climate to the increase of CO2 concentration within the atmosphere. This study explores a potential to reduce uncertainties in climate sensitivity estimations using energy balance analysis, especially top-of-atmosphere (TOA radiation imbalance. The time-scales studied generally cover from decade to century, that is, middle-range climate sensitivity is considered, which is directly related to the climate issue caused by atmospheric CO2 change. The significant difference between current analysis and previous energy balance models is that the current study targets at the boundary condition problem instead of solving the initial condition problem. Additionally, climate system memory and deep ocean heat transport are considered. The climate feedbacks are obtained based on the constraints of the TOA radiation imbalance and surface temperature measurements of the present climate. In this study, the TOA imbalance value of 0.85 W/m2 is used. Note that this imbalance value has large uncertainties. Based on this value, a positive climate feedback with a feedback coefficient ranging from −1.3 to −1.0 W/m2/K is found. The range of feedback coefficient is determined by climate system memory. The longer the memory, the stronger the positive feedback. The estimated time constant of the climate is large (70~120 years mainly owing to the deep ocean heat transport, implying that the system may be not in an equilibrium state under the external forcing during the industrial era. For the doubled-CO2 climate (or 3.7 W/m2 forcing, the estimated global warming would be 3.1 K if the current estimate of 0.85 W/m2 TOA net radiative heating could be confirmed. With accurate long-term measurements of TOA radiation, the analysis method suggested by this study provides a great potential in the

  6. Characterizing the Sensitivity of Groundwater Storage to Climate variation in the Indus Basin

    Science.gov (United States)

    Huang, L.; Sabo, J. L.

    2017-12-01

    Indus Basin represents an extensive groundwater aquifer facing the challenge of effective management of limited water resources. Groundwater storage is one of the most important variables of water balance, yet its sensitivity to climate change has rarely been explored. To better estimate present and future groundwater storage and its sensitivity to climate change in the Indus Basin, we analyzed groundwater recharge/discharge and their historical evolution in this basin. Several methods are applied to specify the aquifer system including: water level change and storativity estimates, gravity estimates (GRACE), flow model (MODFLOW), water budget analysis and extrapolation. In addition, all of the socioeconomic and engineering aspects are represented in the hydrological system through the change of temporal and spatial distributions of recharge and discharge (e.g., land use, crop structure, water allocation, etc.). Our results demonstrate that the direct impacts of climate change will result in unevenly distributed but increasing groundwater storage in the short term through groundwater recharge. In contrast, long term groundwater storage will decrease as a result of combined indirect and direct impacts of climate change (e.g. recharge/discharge and human activities). The sensitivity of groundwater storage to climate variation is characterized by topography, aquifer specifics and land use. Furthermore, by comparing possible outcomes of different human interventions scenarios, our study reveals human activities play an important role in affecting the sensitivity of groundwater storage to climate variation. Over all, this study presents the feasibility and value of using integrated hydrological methods to support sustainable water resource management under climate change.

  7. Observational constraints on mixed-phase clouds imply higher climate sensitivity.

    Science.gov (United States)

    Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D

    2016-04-08

    Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. We point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback. Copyright © 2016, American Association for the Advancement of Science.

  8. Stomatal sensitivity to vapour pressure deficit relates to climate of origin in Eucalyptus species.

    Science.gov (United States)

    Bourne, Aimee E; Haigh, Anthony M; Ellsworth, David S

    2015-03-01

    Selecting plantation species to balance water use and production requires accurate models for predicting how species will tolerate and respond to environmental conditions. Although interspecific variation in water use occurs, species-specific parameters are rarely incorporated into physiologically based models because often the appropriate species parameters are lacking. To determine the physiological control over water use in Eucalyptus, five stands of Eucalyptus species growing in a common garden were measured for sap flux rates and their stomatal response to vapour pressure deficit (D) was assessed. Maximal canopy conductance and whole-canopy stomatal sensitivity to D and reduced water availability were lower in species originating from more arid climates of origin than those from humid climates. Species from humid climates showed a larger decline in maximal sap flux density (JSmax) with reduced water availability, and a lower D at which stomatal closure occurred than species from more arid climates, implying larger sensitivity to water availability and D in these species. We observed significant (P species climate of origin with mean vessel diameter (R(2) = 0.90), stomatal sensitivity to D (R(2) = 0.83) and the size of the decline in JSmax to restricted water availability (R(2) = 0.94). Thus aridity of climate of origin appears to have a selective role in constraining water-use response among the five Eucalyptus plantation species. These relationships emphasize that within this congeneric group of species, climate aridity constrains water use. These relationships have implications for species choices for tree plantation success against drought-induced losses and the ability to manage Eucalyptus plantations against projected changes in water availability and evaporation in the future. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. Disentangling Greenhouse Warming and Aerosol Cooling to Reveal Earth's Transient Climate Sensitivity

    Science.gov (United States)

    Storelvmo, T.

    2015-12-01

    Earth's climate sensitivity has been the subject of heated debate for decades, and recently spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of the most likely range of climate sensitivities. Here, we present an observation-based study based on the time period 1964 to 2010, which is unique in that it does not rely on global climate models (GCMs) in any way. The study uses surface observations of temperature and incoming solar radiation from approximately 1300 surface sites, along with observations of the equivalent CO2 concentration (CO2,eq) in the atmosphere, to produce a new best estimate for the transient climate sensitivity of 1.9K (95% confidence interval 1.2K - 2.7K). This is higher than other recent observation-based estimates, and is better aligned with the estimate of 1.8K and range (1.1K - 2.5K) derived from the latest generation of GCMs. The new estimate is produced by incorporating the observations in an energy balance framework, and by applying statistical methods that are standard in the field of Econometrics, but less common in climate studies. The study further suggests that about a third of the continental warming due to increasing CO2,eq was masked by aerosol cooling during the time period studied.

  10. Disentangling Aerosol Cooling and Greenhouse Warming to Reveal Earth's Climate Sensitivity

    Science.gov (United States)

    Storelvmo, Trude; Leirvik, Thomas; Phillips, Petter; Lohmann, Ulrike; Wild, Martin

    2015-04-01

    Earth's climate sensitivity has been the subject of heated debate for decades, and recently spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of the most likely range of climate sensitivities. Here, we present a study based on the time period 1964 to 2010, which is unique in that it does not rely on global climate models (GCMs) in any way. The study uses surface observations of temperature and incoming solar radiation from approximately 1300 surface sites, along with observations of the equivalent CO2 concentration (CO2,eq) in the atmosphere, to produce a new best estimate for the transient climate sensitivity of 1.9K (95% confidence interval 1.2K - 2.7K). This is higher than other recent observation-based estimates, and is better aligned with the estimate of 1.8K and range (1.1K - 2.5K) derived from the latest generation of GCMs. The new estimate is produced by incorporating the observations in an energy balance framework, and by applying statistical methods that are standard in the field of Econometrics, but less common in climate studies. The study further suggests that about a third of the continental warming due to increasing CO2,eq was masked by aerosol cooling during the time period studied.

  11. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian

    2016-01-01

    on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land......Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared...

  12. Statistical downscaling of multi-decadal climate change projections: Bridging the gap between climate models and the end-user

    CSIR Research Space (South Africa)

    Landman, WA

    2013-09-01

    Full Text Available temperatures across the region. The statistical model is found to be able to replicate the increasing maximum temperature trends of the driving regional climate model. Since dry-land crops are not explicitly produced by climate models but are sensitive...

  13. Issues in Establishing Climate Sensitivity in Recent Studies

    Directory of Open Access Journals (Sweden)

    John T. Fasullo

    2011-09-01

    Full Text Available Numerous attempts have been made to constrain climate sensitivity with observations [1-10] (with [6] as LC09, [8] as SB11. While all of these attempts contain various caveats and sources of uncertainty, some efforts have been shown to contain major errors and are demonstrably incorrect. For example, multiple studies [11-13] separately addressed weaknesses in LC09 [6]. The work of Trenberth et al. [13], for instance, demonstrated a basic lack of robustness in the LC09 method that fundamentally undermined their results. Minor changes in that study’s subjective assumptions yielded major changes in its main conclusions. Moreover, Trenberth et al. [13] criticized the interpretation of El Niño-Southern Oscillation (ENSO as an analogue for exploring the forced response of the climate system. In addition, as many cloud variations on monthly time scales result from internal atmospheric variability, such as the Madden-Julian Oscillation, cloud variability is not a deterministic response to surface temperatures. Nevertheless, many of the problems in LC09 [6] have been perpetuated, and Dessler [10] has pointed out similar issues with two more recent such attempts [7,8]. Here we briefly summarize more generally some of the pitfalls and issues involved in developing observational constraints on climate feedbacks. [...

  14. Sensitivity of the Regional Climate in the Middle East and North Africa to Volcanic Perturbations

    KAUST Repository

    Dogar, Muhammad Mubashar

    2017-07-27

    The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/NCEP Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory\\'s High-Resolution Atmospheric Model (HiRAM). A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.

  15. Sensitivity of the terrestrial biosphere to climatic changes: impact on the carbon cycle.

    Science.gov (United States)

    Friedlingstein, P; Müller, J F; Brasseur, G P

    1994-01-01

    The biosphere is a major pool in the global carbon cycle; its response to climatic change is therefore of great importance. We developed a 5 degrees x 5 degrees longitude-latitude resolution model of the biosphere in which the global distributions of the major biospheric variables, i.e. the vegetation types and the main carbon pools and fluxes, are determined from climatic variables. We defined nine major broad vegetation types: perennial ice, desert and semi-desert, tundra, coniferous forest, temperate deciduous forest, grassland and shrubland, savannah, seasonal tropical forest and evergreen tropical forest. Their geographical repartition is parameterized using correlations between observed vegetation type, precipitation and biotemperature distributions. The model computes as a function of climate and vegetation type, the variables related to the continental biospheric carbon cycle, i.e. the carbon pools such as the phytomass, the litter and the soil organic carbon; and carbon fluxes such as net primary production, litter production and heterotrophic respiration. The modeled present-day biosphere is in good agreement with observation. The model is used to investigate the response of the terrestrial biosphere to climatic changes as predicted by different General Circulation Models (GCM). In particular, the impact on the biosphere of climatic conditions corresponding to the last glacial climate (LGM), 18 000 years ago, is investigated. Comparison with results from present-day climate simulations shows the high sensitivity of the geographical distribution of vegetation types and carbon content as well as biospheric trace gases emissions to climatic changes. The general trend for LGM compared to the present is an increase in low density vegetation types (tundra, desert, grassland) to the detriment of forested areas, in tropical as well as in other regions. Consequently, the biospheric activity (carbon fluxes and trace gases emissions) was reduced.

  16. Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography

    Science.gov (United States)

    Crossman, J.; Futter, M. N.; Whitehead, P. G.; Stainsby, E.; Baulch, H. M.; Jin, L.; Oni, S. K.; Wilby, R. L.; Dillon, P. J.

    2014-12-01

    Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which are expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as it is to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of global climate model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the INtegrated CAtchment model of Phosphorus dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968-1997) to two future periods: 2020-2049 and 2060-2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivities) were highly varied. Sensitivity was governed by quaternary geology (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly

  17. Earth system sensitivity inferred from Pliocene modelling and data

    Science.gov (United States)

    Lunt, D.J.; Haywood, A.M.; Schmidt, G.A.; Salzmann, U.; Valdes, P.J.; Dowsett, H.J.

    2010-01-01

    Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earths climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere-ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30-50% greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. ?? 2010 Macmillan Publishers Limited. All rights reserved.

  18. A simple explanation for the sensitivity of the hydrologic cycle to global climate change

    Science.gov (United States)

    Kleidon, Axel; Renner, Maik

    2014-05-01

    The global hydrologic cycle is likely to increase in strength with global warming, although some studies indicate that warming due to solar absorption may result in a different sensitivity than warming due to an elevated greenhouse effect. Here we show that these sensitivities of the hydrologic cycle can be derived analytically from an extremely simple surface energy balance model that is constrained by the assumption that vertical convective exchange within the atmosphere operates at the thermodynamic limit of maximum power. Using current climatic mean conditions, this model predicts a sensitivity of the hydrologic cycle of 2.2 % K-1 to greenhouse-induced surface warming which is the sensitivity reported from climate models. The sensitivity to solar-induced warming includes an additional term, which increases the total sensitivity to 3.2 % K-1. These sensitivities are explained by shifts in the turbulent fluxes in the case of greenhouse-induced warming, which is proportional to the change in slope of the saturation vapor pressure, and in terms of an additional increase in turbulent fluxes in the case of solar radiation-induced warming. We illustrate an implication of this explanation for geoengineering, which aims to undo surface temperature differences by solar radiation management. Our results show that when such an intervention compensates surface warming, it cannot simultaneously compensate the changes in hydrologic cycling because of the differences in sensitivities for solar vs. greenhouse-induced surface warming. We conclude that the sensitivity of the hydrologic cycle to surface temperature can be understood and predicted with very simple physical considerations but this needs to reflect on the different roles that solar and terrestrial radiation play in forcing the hydrologic cycle.

  19. Evaluating Climate Models: Should We Use Weather or Climate Observations?

    Science.gov (United States)

    Oglesby, R. J.; Rowe, C. M.; Maasch, K. A.; Erickson, D. J.; Hays, C.

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their ability to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.

  20. The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity

    Science.gov (United States)

    Garuba, Oluwayemi A.; Lu, Jian; Liu, Fukai; Singh, Hansi A.

    2018-01-01

    The temporal evolution of the effective climate sensitivity is shown to be influenced by the changing pattern of sea surface temperature (SST) and ocean heat uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully coupled CO2 quadrupling community Earth System Model (CESM) simulation against a partially coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is responsible for the reduced effective climate sensitivity and weaker surface warming response in the fully coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO2 quadrupling in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the nonunitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully and partially coupled responses.

  1. Semiarid watershed response in central New Mexico and its sensitivity to climate variability and change

    Directory of Open Access Journals (Sweden)

    E. R. Vivoni

    2009-06-01

    Full Text Available Hydrologic processes in the semiarid regions of the Southwest United States are considered to be highly susceptible to variations in temperature and precipitation characteristics due to the effects of climate change. Relatively little is known about the potential impacts of climate change on the basin hydrologic response, namely streamflow, evapotranspiration and recharge, in the region. In this study, we present the development and application of a continuous, semi-distributed watershed model for climate change studies in semiarid basins of the Southwest US. Our objective is to capture hydrologic processes in large watersheds, while accounting for the spatial and temporal variations of climate forcing and basin properties in a simple fashion. We apply the model to the Río Salado basin in central New Mexico since it exhibits both a winter and summer precipitation regime and has a historical streamflow record for model testing purposes. Subsequently, we use a sequence of climate change scenarios that capture observed trends for winter and summer precipitation, as well as their interaction with higher temperatures, to perform long-term ensemble simulations of the basin response. Results of the modeling exercise indicate that precipitation uncertainty is amplified in the hydrologic response, in particular for processes that depend on a soil saturation threshold. We obtained substantially different hydrologic sensitivities for winter and summer precipitation ensembles, indicating a greater sensitivity to more intense summer storms as compared to more frequent winter events. In addition, the impact of changes in precipitation characteristics overwhelmed the effects of increased temperature in the study basin. Nevertheless, combined trends in precipitation and temperature yield a more sensitive hydrologic response throughout the year.

  2. The sensitivity of agricultural impacts assessment to climate data and scenario methodologies

    Science.gov (United States)

    Ruane, A. C.; Rosenzweig, C.

    2011-12-01

    Assessments of climate change impacts on the agricultural sector are crucially important from the farm- to global levels. While impacts assessments have made wide and creative use of data products, climate models, and methods for downscaling and scenario generation, this variety also hinders our ability to compare impacts from one study to other assessments. The unique nature of many impacts assessments is especially problematic when evaluating the impacts of climate change on large agricultural regions and global production; a crucial scale in understanding the economic impacts and market influence on food security and land use. This presentation examines the influence of methodological choices on agricultural impacts assessment by describing results from several projects. First, the utility of a wide variety of global and regional observational data products are compared for an agricultural system in the Florida Panhandle to determine the influence of observational uncertainties, reanalysis products, remotely sensed information, and downscaled models on impacts assessment. Second, the role of future climate scenarios is isolated by running the same Panhandle station with scenarios generated through a variety of generation methods with a focus on downscaling methodologies and the climate statistics allowed to change. Finally, an ensemble of weather generators are compared across an ensemble of wheat models in a variety of major agricultural regions, isolating important sensitivities in the crop models and corresponding strengths and weaknesses in the weather generators.

  3. The influence of extratropical cloud phase and amount feedbacks on climate sensitivity

    Science.gov (United States)

    Frey, William R.; Kay, Jennifer E.

    2018-04-01

    Global coupled climate models have large long-standing cloud and radiation biases, calling into question their ability to simulate climate and climate change. This study assesses the impact of reducing shortwave radiation biases on climate sensitivity within the Community Earth System Model (CESM). The model is modified by increasing supercooled cloud liquid to better match absorbed shortwave radiation observations over the Southern Ocean while tuning to reduce a compensating tropical shortwave bias. With a thermodynamic mixed-layer ocean, equilibrium warming in response to doubled CO2 increases from 4.1 K in the control to 5.6 K in the modified model. This 1.5 K increase in equilibrium climate sensitivity is caused by changes in two extratropical shortwave cloud feedbacks. First, reduced conversion of cloud ice to liquid at high southern latitudes decreases the magnitude of a negative cloud phase feedback. Second, warming is amplified in the mid-latitudes by a larger positive shortwave cloud feedback. The positive cloud feedback, usually associated with the subtropics, arises when sea surface warming increases the moisture gradient between the boundary layer and free troposphere. The increased moisture gradient enhances the effectiveness of mixing to dry the boundary layer, which decreases cloud amount and optical depth. When a full-depth ocean with dynamics and thermodynamics is included, ocean heat uptake preferentially cools the mid-latitude Southern Ocean, partially inhibiting the positive cloud feedback and slowing warming. Overall, the results highlight strong connections between Southern Ocean mixed-phase cloud partitioning, cloud feedbacks, and ocean heat uptake in a climate forced by greenhouse gas changes.

  4. Catchment Sensitivity to Changing Climate Conditions: The Importance of Landscape Characteristics

    Science.gov (United States)

    Teutschbein, Claudia; Karlsen, Reinert; Grabs, Thomas; Laudon, Hjalmar; Bishop, Kevin

    2015-04-01

    The scientific literature is full of studies analyzing future climate change impacts on hydrology with focus on individual catchments. We recently found, however, that hydrologic behavior and specific discharge vary considerably even in neighboring and rather similar catchments under current climate conditions and that these variations are related to landscape characteristics. Therefore we hypothesize that these landscape characteristics also play a fundamental role for the sensitivity of a catchment to changing climate conditions. We analyzed the hydrological response of 14 partially nested catchments in Northern Sweden with slightly different topography, land cover, size and geology. Current (1981-2010) and future (2061-2090) streamflows were simulated with the hydrological model HBV light based on 15 regional climate model projections that were bias-corrected with a distribution-mapping approach. Our simulations revealed that - in a future climate- the total annual streamflow will be higher, spring flood peaks will occur earlier and decrease considerably, whereas winter base flows will more than double. These changes are somewhat expected and mainly triggered by a projected increase in winter temperature, which leads to less snow accumulation on the ground. However, our results also show that there is a large variability amongst these catchments in their hydrological response to the same future climate conditions. We identified wetlands, lakes, peat soils and higher elevations as factors that had a stronger effect on spring floods, whereas catchments dominated by forests, steeper slopes and till soils showed stronger responses in winter base flows and total annual streamflow. Therefore, our results suggest that the sensitivity of catchments to future climate conditions is strongly linked to landscape characteristics and also depends on the streamflow characteristic as well as season analyzed.

  5. Sensitivity of Asian and African climate to variations in seasonal insolation, glacial ice cover, sea surface temperature, and Asian orography

    Science.gov (United States)

    Demenocal, Peter B.; Rind, David

    1993-01-01

    A general circulation model was used to investigate the sensitivity of Asian and African climate to prescribed changes in boundary conditions with the objective of identifying the relative importance of individual high-latitude glacial boundary conditions on seasonal climate and providing a physical basis for interpreting the paleoclimate record. The circulation model is described and results are presented. Insolation forcing increased summer Asian monsoon winds, while increased high-latitude ice cover strengthened winter Asian trade winds causing decreased precipitation. These factors had little effect on African climate. Cooler North Atlantic sea surface temperatures enhanced winter trade winds over North Africa, southern Asian climate was relatively unaffected. Reducing Asian orography enhanced Asian winter circulation while decreasing the summer monsoon. These model results suggest that African and southern Asian climate respond differently to separate elements of high-latitude climate variability.

  6. A National Strategy for Advancing Climate Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Dunlea, Edward; Elfring, Chris

    2012-12-04

    Climate models are the foundation for understanding and projecting climate and climate-related changes and are thus critical tools for supporting climate-related decision making. This study developed a holistic strategy for improving the nation's capability to accurately simulate climate and related Earth system changes on decadal to centennial timescales. The committee's report is a high level analysis, providing a strategic framework to guide progress in the nation's climate modeling enterprise over the next 10-20 years. This study was supported by DOE, NSF, NASA, NOAA, and the intelligence community.

  7. Structural sensitivity of biological models revisited.

    Science.gov (United States)

    Cordoleani, Flora; Flora, Cordoleani; Nerini, David; David, Nerini; Gauduchon, Mathias; Mathias, Gauduchon; Morozov, Andrew; Andrew, Morozov; Poggiale, Jean-Christophe; Jean-Christophe, Poggiale

    2011-08-21

    Enhancing the predictive power of models in biology is a challenging issue. Among the major difficulties impeding model development and implementation are the sensitivity of outcomes to variations in model parameters, the problem of choosing of particular expressions for the parametrization of functional relations, and difficulties in validating models using laboratory data and/or field observations. In this paper, we revisit the phenomenon which is referred to as structural sensitivity of a model. Structural sensitivity arises as a result of the interplay between sensitivity of model outcomes to variations in parameters and sensitivity to the choice of model functions, and this can be somewhat of a bottleneck in improving the models predictive power. We provide a rigorous definition of structural sensitivity and we show how we can quantify the degree of sensitivity of a model based on the Hausdorff distance concept. We propose a simple semi-analytical test of structural sensitivity in an ODE modeling framework. Furthermore, we emphasize the importance of directly linking the variability of field/experimental data and model predictions, and we demonstrate a way of assessing the robustness of modeling predictions with respect to data sampling variability. As an insightful illustrative example, we test our sensitivity analysis methods on a chemostat predator-prey model, where we use laboratory data on the feeding of protozoa to parameterize the predator functional response. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. Estimating climate model systematic errors in a climate change impact study of the Okavango River basin, southwestern Africa using a mesoscale model

    Science.gov (United States)

    Raghavan, S. V.; Todd, M.

    2007-12-01

    Simulating the impact of future climate variability and change on hydrological systems requires estimates of climate at high spatial resolution compatible with hydrological models. Here we present initial results of a project to simulate future climate over the Okavango River basin and delta in Southwestern Africa. Given the significance of the delta to biodiversity and as a resource to the local population, there is considerable concern regarding the sensitivity of the system to future climate change. An important component of climate variability/change impact studies is an assessment of errors in the modeling suite. Here, we attempt to quantify errors and uncertainties involved in regional climate modelling that will impact on hydrological simulations. The study determines the ability of the MM5 Regional Climate Model to simulate the present day regional climate at the high resolution required by the hydrological models and the effectiveness of the RCM in downscaling GCM outputs to study regional climate change and impacts.

  9. Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

    KAUST Repository

    Imbers, Jara

    2014-05-01

    The Intergovernmental Panel on Climate Change\\'s (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

  10. Sensitivity of the Eocene climate to CO2 and orbital variability

    Science.gov (United States)

    Keery, John S.; Holden, Philip B.; Edwards, Neil R.

    2018-02-01

    The early Eocene, from about 56 Ma, with high atmospheric CO2 levels, offers an analogue for the response of the Earth's climate system to anthropogenic fossil fuel burning. In this study, we present an ensemble of 50 Earth system model runs with an early Eocene palaeogeography and variation in the forcing values of atmospheric CO2 and the Earth's orbital parameters. Relationships between simple summary metrics of model outputs and the forcing parameters are identified by linear modelling, providing estimates of the relative magnitudes of the effects of atmospheric CO2 and each of the orbital parameters on important climatic features, including tropical-polar temperature difference, ocean-land temperature contrast, Asian, African and South (S.) American monsoon rains, and climate sensitivity. Our results indicate that although CO2 exerts a dominant control on most of the climatic features examined in this study, the orbital parameters also strongly influence important components of the ocean-atmosphere system in a greenhouse Earth. In our ensemble, atmospheric CO2 spans the range 280-3000 ppm, and this variation accounts for over 90 % of the effects on mean air temperature, southern winter high-latitude ocean-land temperature contrast and northern winter tropical-polar temperature difference. However, the variation of precession accounts for over 80 % of the influence of the forcing parameters on the Asian and African monsoon rainfall, and obliquity variation accounts for over 65 % of the effects on winter ocean-land temperature contrast in high northern latitudes and northern summer tropical-polar temperature difference. Our results indicate a bimodal climate sensitivity, with values of 4.36 and 2.54 °C, dependent on low or high states of atmospheric CO2 concentration, respectively, with a threshold at approximately 1000 ppm in this model, and due to a saturated vegetation-albedo feedback. Our method gives a quantitative ranking of the influence of each of the

  11. Impact of Radiatively Interactive Dust Aerosols in the NASA GEOS-5 Climate Model: Sensitivity to Dust Particle Shape and Refractive Index

    Science.gov (United States)

    Colarco, Peter R.; Nowottnick, Edward Paul; Randles, Cynthia A.; Yi, Bingqi; Yang, Ping; Kim, Kyu-Myong; Smith, Jamison A.; Bardeen, Charles D.

    2013-01-01

    We investigate the radiative effects of dust aerosols in the NASA GEOS-5 atmospheric general circulation model. GEOS-5 is improved with the inclusion of a sectional aerosol and cloud microphysics module, the Community Aerosol and Radiation Model for Atmospheres (CARMA). Into CARMA we introduce treatment of the dust and sea salt aerosol lifecycle, including sources, transport evolution, and sinks. The aerosols are radiatively coupled to GEOS-5, and we perform a series of multi-decade AMIP-style simulations in which dust optical properties (spectral refractive index and particle shape distribution) are varied. Optical properties assuming spherical dust particles are from Mie theory, while those for non-spherical shape distributions are drawn from a recently available database for tri-axial ellipsoids. The climatologies of the various simulations generally compare well to data from the MODIS, MISR, and CALIOP space-based sensors, the ground-based AERONET, and surface measurements of dust deposition and concentration. Focusing on the summertime Saharan dust cycle we show significant variability in our simulations resulting from different choices of dust optical properties. Atmospheric heating due to dust enhances surface winds over important Saharan dust sources, and we find a positive feedback where increased dust absorption leads to increased dust emissions. We further find that increased dust absorption leads to a strengthening of the summertime Hadley cell circulation, increasing dust lofting to higher altitudes and strengthening the African Easterly Jet. This leads to a longer atmospheric residence time, higher altitude, and generally more northward transport of dust in simulations with the most absorbing dust optical properties. We find that particle shape, although important for radiance simulations, is a minor effect compared to choices of refractive index, although total atmospheric forcing is enhanced by greater than 10 percent for simulations incorporating a

  12. On the Baltic Sea Response to Climate Change: Model Implications

    International Nuclear Information System (INIS)

    Omstedt, Anders; Leppaeranta, Matti

    1999-01-01

    The sensitivity of the Baltic Sea to climate change is reviewed on the basis of recent model studies. In general, the presently available models indicate that the Baltic Sea is a most sensitive system to climate change, particularly in air temperature, wind, fresh water inflow and the barotropic forcing in the entrance area. Available scenarios for ice conditions and climate warming around year 2100 show 2-3 months' shortening of the ice season in the Bothnian Bay and about 0.4 m decrease in the maximum annual ice thickness. Corresponding scenarios for climate cooling show 1-2 months' longer ice season in the Bothnian Bay and 0.2 - 0.5 m increase in the maximum annual ice thickness

  13. Paleoclimate validation of a numerical climate model

    International Nuclear Information System (INIS)

    Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

    1994-01-01

    An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

  14. Advances in urban climate modeling.

    Science.gov (United States)

    Hidalgo, Julia; Masson, Valéry; Baklanov, Alexander; Pigeon, Grégoire; Gimeno, Luis

    2008-12-01

    Cities interact with the atmosphere over a wide range of scales from the large-scale processes, which have a direct impact on global climate change, to smaller scales, ranging from the conurbation itself to individual buildings. The review presented in this paper analyzes some of the ways in which cities influence atmospheric thermodynamics and airborne pollutant transport. We present the main physical processes that characterize the urban local meteorology (the urban microclimate) and air pollution. We focus on small-scale impacts, including the urban heat island and its causes. The impact on the lower atmosphere over conurbations, air pollution in cities, and the effect on meteorological processes are discussed. An overview of the recent principal advances in urban climatology and air quality modeling in atmospheric numerical models is also presented.

  15. Potential evaporation estimation through an unstressed surface energy balance and its sensitivity to climate change

    Science.gov (United States)

    Barella-Ortiz, A.; Polcher, J.; Tuzet, A.; Laval, K.

    2013-06-01

    Potential evaporation (ETP) is a basic input for hydrological and agronomic models, as well as a key variable in most actual evaporation estimations. It has been approached through several diffusive and energy balance methods, out of which the Penman-Monteith equation is recommended as the standard one. In order to deal with the diffusive approach, ETP must be estimated at a sub-diurnal frequency, as currently done in land surface models (LSM). This study presents an improved method, developed in the ORCHIDEE LSM, which consists in estimating ETP through an unstressed surface energy balance (USEB method). The results confirm the quality of the estimation which is currently implemented in the model (Milly, 1992). ETP has also been estimated using a reference equation (computed at a daily time step) provided by the Food and Agriculture Organization (FAO). First, a comparison for a reference period under current climate conditions, shows that both formulations differ, specially in arid areas. However, they supply similar values when FAO's assumption of neutral stability conditions is relaxed, by replacing FAO's aerodynamic resistance by the model's one. Furthermore, if the vapour pressure deficit (VPD) estimated for FAO's equation, is substituted by ORCHIDEE's VPD or its humidity gradient, the daily mean estimate is further improved. In a second step, ETP's sensitivity to climate change is assessed comparing trends in both formulations for the 21st Century. It is found that the USEB method shows a higher sensitivity. Both VPD and the model's humidity gradient, as well as the aerodynamic resistance have been identified as key parameters in governing ETP trends. Finally, the sensitivity study is extended to three empirical approximations based on temperature, net radiation and mass transfer (Hargreaves, Priestley-Taylor and Rohwer, respectively). The sensitivity of these methods is compared to the USEB method's one to test if simplified equations are able to reproduce

  16. On the state dependency of the equilibrium climate sensitivity during the last 5 million years

    Directory of Open Access Journals (Sweden)

    P. Köhler

    2015-12-01

    Full Text Available It is still an open question how equilibrium warming in response to increasing radiative forcing – the specific equilibrium climate sensitivity S – depends on background climate. We here present palaeodata-based evidence on the state dependency of S, by using CO2 proxy data together with a 3-D ice-sheet-model-based reconstruction of land ice albedo over the last 5 million years (Myr. We find that the land ice albedo forcing depends non-linearly on the background climate, while any non-linearity of CO2 radiative forcing depends on the CO2 data set used. This non-linearity has not, so far, been accounted for in similar approaches due to previously more simplistic approximations, in which land ice albedo radiative forcing was a linear function of sea level change. The latitudinal dependency of ice-sheet area changes is important for the non-linearity between land ice albedo and sea level. In our set-up, in which the radiative forcing of CO2 and of the land ice albedo (LI is combined, we find a state dependence in the calculated specific equilibrium climate sensitivity, S[CO2,LI], for most of the Pleistocene (last 2.1 Myr. During Pleistocene intermediate glaciated climates and interglacial periods, S[CO2,LI] is on average ~ 45 % larger than during Pleistocene full glacial conditions. In the Pliocene part of our analysis (2.6–5 Myr BP the CO2 data uncertainties prevent a well-supported calculation for S[CO2,LI], but our analysis suggests that during times without a large land ice area in the Northern Hemisphere (e.g. before 2.82 Myr BP, the specific equilibrium climate sensitivity, S[CO2,LI], was smaller than during interglacials of the Pleistocene. We thus find support for a previously proposed state change in the climate system with the widespread appearance of northern hemispheric ice sheets. This study points for the first time to a so far overlooked non-linearity in the land ice albedo radiative forcing, which is important for similar

  17. Sensitivity of the French Alps snow cover to the variation of climatic variables

    Directory of Open Access Journals (Sweden)

    E. Martin

    Full Text Available In order to study the sensitivity of snow cover to changes in meteorological variables at a regional scale, a numerical snow model and an analysis system of the meteorological conditions adapted to relief were used. This approach has been successfully tested by comparing simulated and measured snow depth at 37 sites in the French Alps during a ten year data period. Then, the sensitivity of the snow cover to a variation in climatic conditions was tested by two different methods, which led to very similar results. To assess the impact of a particular "doubled CO2" scenario, coherent perturbations were introduced in the input data of the snow model. It was found that although the impact would be very pronounced, it would also be extremely differentiated, dependent on the internal state of the snow cover. The most sensitive areas are the elevations below 2400 m, especially in the southern part of the French Alps.

  18. Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part II. Sensitivity to Heterogeneous Ice Nucleation Parameterizations and Dust Emissions

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2015-09-01

    Full Text Available Aerosol particles can affect cloud microphysical properties by serving as ice nuclei (IN. Large uncertainties exist in the ice nucleation parameterizations (INPs used in current climate models. In this Part II paper, to examine the sensitivity of the model predictions to different heterogeneous INPs, WRF-CAM5 simulation using the INP of Niemand et al. (N12 [1] is conducted over East Asia for two full years, 2006 and 2011, and compared with simulation using the INP of Meyers et al. (M92 [2], which is the original INP used in CAM5. M92 calculates the nucleated ice particle concentration as a function of ice supersaturation, while N12 represents the nucleated ice particle concentration as a function of temperature and the number concentrations and surface areas of dust particles. Compared to M92, the WRF-CAM5 simulation with N12 produces significantly higher nucleated ice crystal number concentrations (ICNCs in the northern domain where dust sources are located, leading to significantly higher cloud ice number and mass concentrations and ice water path, but the opposite is true in the southern domain where temperatures and moistures play a more important role in ice formation. Overall, the simulation with N12 gives lower downward shortwave radiation but higher downward longwave radiation, cloud liquid water path, cloud droplet number concentrations, and cloud optical depth. The increase in cloud optical depth and the decrease in downward solar flux result in a stronger shortwave and longwave cloud forcing, and decreases temperature at 2-m and precipitation. Changes in temperature and radiation lower surface concentrations of OH, O3, SO42−, and PM2.5, but increase surface concentrations of CO, NO2, and SO2 over most of the domain. By acting as cloud condensation nuclei (CCN and IN, dust particles have different impacts on cloud water and ice number concentrations, radiation, and temperature at 2-m and precipitation depending on whether the

  19. Separating sensitivity from exposure in assessing extinction risk from climate change.

    Science.gov (United States)

    Dickinson, Maria G; Orme, C David L; Suttle, K Blake; Mace, Georgina M

    2014-11-04

    Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk.

  20. CRETACEOUS CLIMATE SENSITIVITY STUDY USING DINOSAUR & PLANT PALEOBIOGEOGRAPHY

    Science.gov (United States)

    Goswami, A.; Main, D. J.; Noto, C. R.; Moore, T. L.; Scotese, C.

    2009-12-01

    The Early Cretaceous was characterized by cool poles and moderate global temperatures (~16° C). During the mid and late Cretaceous, long-term global warming (~20° - 22° C) was driven by increasing levels of CO2, rising sea level (lowering albedo) and the continuing breakup of Pangea. Paleoclimatic reconstructions for four time intervals during the Cretaceous: Middle Campanian (80 Ma), Cenomanian/Turonian (90 Ma), Early Albian (110 Ma) and Barremian-Hauterivian (130Ma) are presented here. These paleoclimate simulations were prepared using the Fast Ocean and Atmosphere Model (FOAM). The simulated results show the pattern of the pole-to-Equator temperature gradients, rainfall, surface run-off, the location of major rivers and deltas. In order to investigate the effect of potential dispersal routes on paleobiogeographic patterns, a time-slice series of maps from Early - Late Cretaceous were produced showing plots of dinosaur and plant fossil distributions. These Maps were created utilizing: 1) plant fossil localities from the GEON and Paleobiology (PBDB) databases; and 2) dinosaur fossil localities from an updated version of the Dinosauria (Weishampel, 2004) database. These results are compared to two different types of datasets, 1) Paleotemperature database for the Cretaceous and 2) locality data obtained from GEON, PBDB and Dinosauria database. Global latitudinal mean temperatures from both the model and the paelotemperature database were plotted on a series of latitudinal graphs along with the distributions of fossil plants and dinosaurs. It was found that most dinosaur localities through the Cretaceous tend to cluster within specific climate belts, or envelopes. Also, these Cretaceous maps show variance in biogeographic zonation of both plants and dinosaurs that is commensurate with reconstructed climate patterns and geography. These data are particularly useful for understanding the response of late Mesozoic ecosystems to geographic and climatic conditions that

  1. The effect of brokenness on cloud-climate sensitivity

    Science.gov (United States)

    Harshvardhan, MR.

    1982-01-01

    A study has been made of the effect of brokenness on the infrared and albedo feedback of clouds in climate models using a simplified treatment of broken cloudiness. It is shown that the individual feedback terms computed using the plane-parallel assumption differ markedly from the computations performed for a regular array of cuboidal clouds. If the cloudiness changes such that clear areas become cloudy but the nature of the broken cloud field remains unchanged, then both the feedbacks are magnified, the infrared more so than the albedo. However, if individual elements in the cloud field are increased horizontally in a constrained area, the feedbacks can be enhanced or diminished depending on the cloud fraction and aspect ratio of the elements. It is also shown that, in the global average, the ratio of the change in outgoing infrared flux to global albedo, as deduced from satellite measurements, will be larger than model simulations using planiform clouds.

  2. Estimating the Health Impact of Climate Change with Calibrated Climate Model Output.

    Science.gov (United States)

    Zhou, Jingwen; Chang, Howard H; Fuentes, Montserrat

    2012-09-01

    Studies on the health impacts of climate change routinely use climate model output as future exposure projection. Uncertainty quantification, usually in the form of sensitivity analysis, has focused predominantly on the variability arise from different emission scenarios or multi-model ensembles. This paper describes a Bayesian spatial quantile regression approach to calibrate climate model output for examining to the risks of future temperature on adverse health outcomes. Specifically, we first estimate the spatial quantile process for climate model output using nonlinear monotonic regression during a historical period. The quantile process is then calibrated using the quantile functions estimated from the observed monitoring data. Our model also down-scales the gridded climate model output to the point-level for projecting future exposure over a specific geographical region. The quantile regression approach is motivated by the need to better characterize the tails of future temperature distribution where the greatest health impacts are likely to occur. We applied the methodology to calibrate temperature projections from a regional climate model for the period 2041 to 2050. Accounting for calibration uncertainty, we calculated the number of of excess deaths attributed to future temperature for three cities in the US state of Alabama.

  3. A Regional Climate Model Evaluation System

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

  4. A Regional Climate Model Evaluation System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

  5. Selecting global climate models for regional climate change studies.

    Science.gov (United States)

    Pierce, David W; Barnett, Tim P; Santer, Benjamin D; Gleckler, Peter J

    2009-05-26

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.

  6. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  7. Ocean Biological Pump Sensitivities and Implications for Climate Change Impacts

    Science.gov (United States)

    Romanou, Anastasia

    2013-01-01

    The ocean is one of the principal reservoirs of CO2, a greenhouse gas, and therefore plays a crucial role in regulating Earth's climate. Currently, the ocean sequesters about a third of anthropogenic CO2 emissions, mitigating the human impact on climate. At the same time, the deeper ocean represents the largest carbon pool in the Earth System and processes that describe the transfer of carbon from the surface of the ocean to depth are intimately linked to the effectiveness of carbon sequestration.The ocean biological pump (OBP), which involves several biogeochemical processes, is a major pathway for transfer of carbon from the surface mixed layer into the ocean interior. About 75 of the carbon vertical gradient is due to the carbon pump with only 25 attributed to the solubility pump. However, the relative importance and role of the two pumps is poorly constrained. OBP is further divided to the organic carbon pump (soft tissue pump) and the carbonate pump, with the former exporting about 10 times more carbon than the latter through processes like remineralization.Major uncertainties about OBP, and hence in the carbon uptake and sequestration, stem from uncertainties in processes involved in OBP such as particulate organicinorganic carbon sinkingsettling, remineralization, microbial degradation of DOC and uptakegrowth rate changes of the ocean biology. The deep ocean is a major sink of atmospheric CO2 in scales of hundreds to thousands of years, but how the export efficiency (i.e. the fraction of total carbon fixation at the surface that is transported at depth) is affected by climate change remains largely undetermined. These processes affect the ocean chemistry (alkalinity, pH, DIC, particulate and dissolved organic carbon) as well as the ecology (biodiversity, functional groups and their interactions) in the ocean. It is important to have a rigorous, quantitative understanding of the uncertainties involved in the observational measurements, the models and the

  8. Selecting representative climate models for climate change impact studies : An advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; ter Maat, Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  9. Selecting representative climate models for climate change impact studies: an advanced envelope-based selection approach

    NARCIS (Netherlands)

    Lutz, Arthur F.; Maat, ter Herbert W.; Biemans, Hester; Shrestha, Arun B.; Wester, Philippus; Immerzeel, Walter W.

    2016-01-01

    Climate change impact studies depend on projections of future climate provided by climate models. The number of climate models is large and increasing, yet limitations in computational capacity make it necessary to compromise the number of climate models that can be included in a climate change

  10. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    mitigation level of 3.7 W/m2, as well as consideration of different levels of climate sensitivity (2, 3, 4.5 and 6oC) and different initial conditions for addressing uncertainty. Since the CMIP 3 and CMIP5 protocols did not include this mitigation level or consider alternative levels of climate sensitivity, additional climate projections were required. These two cases will be discussed to illustrate some of the trade-offs made in development of methodologies for climate impact assessments that are intended for a specific user or audience, and oriented towards addressing a specific topic of interest and providing useable results. This involvement of stakeholders from the design phase of climate impacts methodology serves to both define the appropriate method for the question at hand and also to engage and inform the stakeholders of the myriad options and uncertainties associated with different methodology choices. This type of engagement should benefit decision making in the long run through greater stakeholder understanding of the science of future climate model projections, scenarios, the climate impacts sector models and the types of outputs that can be generated by each along with the respective uncertainties at each step of the climate impacts assessment process.

  11. Sensitivity of arctic summer sea ice coverage to global warming forcing: towards reducing uncertainty in arctic climate change projections

    Science.gov (United States)

    Zhang, Xiangdong

    2010-05-01

    Substantial uncertainties have emerged in Arctic climate change projections by the fourth Intergovernmental Panel on Climate Change assessment report climate models. In particular, the models as a group considerably underestimate the recent accelerating sea ice reduction. To better understand the uncertainties, we evaluated sensitivities of summer sea ice coverage to global warming forcing in models and observations. The result suggests that the uncertainties result from the large range of sensitivities involved in the computation of sea ice mass balance by the climate models, specifically with the changes in sea ice area (SIA) ranging from 0.09 × 106 to -1.23 × 106km2 in response to 1.0 K increase of air temperature. The sensitivities also vary largely across ensemble members in the same model, indicating impacts of initial condition on evolution of feedback strength with model integrations. Through observationally constraining, the selected model runs by the sensitivity analysis well captured the observed changes in SIA and surface air temperatures and greatly reduced their future projection uncertainties to a certain range from the currently announced one. The projected ice-free summer Arctic Ocean may occur as early as in the late 2030s using a criterion of 80% SIA loss and the Arctic regional mean surface air temperature will be likely increased by 8.5 +/- 2.5 °C in winter and 3.7 +/- 0.9 °C in summer by the end of this century.

  12. Sensitivity of the Palaeocene-Eocene Thermal Maximum climate to cloud properties.

    Science.gov (United States)

    Kiehl, Jeffrey T; Shields, Christine A

    2013-10-28

    The Palaeocene-Eocene Thermal Maximum (PETM) was a significant global warming event in the Earth's history (approx. 55 Ma). The cause for this warming event has been linked to increases in greenhouse gases, specifically carbon dioxide and methane. This rapid warming took place in the presence of the existing Early Eocene warm climate. Given that projected business-as-usual levels of atmospheric carbon dioxide reach concentrations of 800-1100 ppmv by 2100, it is of interest to study past climates where atmospheric carbon dioxide was higher than present. This is especially the case given the difficulty of climate models in simulating past warm climates. This study explores the sensitivity of the simulated pre-PETM and PETM periods to change in cloud condensation nuclei (CCN) and microphysical properties of liquid water clouds. Assuming lower levels of CCN for both of these periods leads to significant warming, especially at high latitudes. The study indicates that past differences in cloud properties may be an important factor in accurately simulating past warm climates. Importantly, additional shortwave warming from such a mechanism would imply lower required atmospheric CO2 concentrations for simulated surface temperatures to be in reasonable agreement with proxy data for the Eocene.

  13. Reservoir Performance Under Future Climate For Basins With Different Hydrologic Sensitivities

    Science.gov (United States)

    Mateus, M. C.; Tullos, D. D.

    2013-12-01

    In addition to long-standing uncertainties related to variable inflows and market price of power, reservoir operators face a number of new uncertainties related to hydrologic nonstationarity, changing environmental regulations, and rapidly growing water and energy demands. This study investigates the impact, sensitivity, and uncertainty of changing hydrology on hydrosystem performance across different hydrogeologic settings. We evaluate the performance of reservoirs in the Santiam River basin, including a case study in the North Santiam Basin, with high permeability and extensive groundwater storage, and the South Santiam Basin, with low permeability, little groundwater storage and rapid runoff response. The modeling objective is to address the following study questions: (1) for the two hydrologic regimes, how does the flood management, water supply, and environmental performance of current reservoir operations change under future 2.5, 50 and 97.5 percentile streamflow projections; and (2) how much change in inflow is required to initiate a failure to meet downstream minimum or maximum flows in the future. We couple global climate model results with a rainfall-runoff model and a formal Bayesian uncertainty analysis to simulate future inflow hydrographs as inputs to a reservoir operations model. To evaluate reservoir performance under a changing climate, we calculate reservoir refill reliability, changes in flood frequency, and reservoir time and volumetric reliability of meeting minimum spring and summer flow target. Reservoir performance under future hydrology appears to vary with hydrogeology. We find higher sensitivity to floods for the North Santiam Basin and higher sensitivity to minimum flow targets for the South Santiam Basin. Higher uncertainty is related with basins with a more complex hydrologeology. Results from model simulations contribute to understanding of the reliability and vulnerability of reservoirs to a changing climate.

  14. Response of climate to regional emissions of ozone precursors: sensitivities and warming potentials

    International Nuclear Information System (INIS)

    Berntsen, T.K.; Fuglestvedt, J.S.; Joshi, M.M.; Shine, K.P.; Hauglustaine, D.A.; Li, L.

    2005-01-01

    The response of climate to ozone perturbations caused by regional emissions of NO x or CO has been studied through a sequence of model simulations. Changes C and OH concentrations due to emission perturbations in Europe and southeast Asia have been calculated with two global 3-D chemical tracer models(CTMs; LMDzINCA and Oslo-CTM2). The radiative transfer codes of three general circulation models (GCMs; ECHAM4, UREAD and LMD) have been used to calculate the radiative forcing of the O 3 perturbations, and for a subset of the cases full GCM simulations have been performed with ECHAM4 and UREAD. The results have been aggregated to a global number in two ways: first, through integrating the global-mean radiative forcing of a sustained step change in emissions, and second through a modified concept (SGWP*) which includes possible differences in the climate sensitivity of O 3 , CH 4 and CO 2 changes. In terms of change in global tropospheric O 3 burden the two CTMs differ by less than 30%. Both CTMs show a higher north/south gradient in the sensitivity to changes in NO x emission than for CO. We are not able to conclude whether real O 3 perturbations in general have a different climate sensitivity from CO 2 . However, in both GCMs high-latitude emission perturbations lead to climate perturbations with higher (10-30%) climate sensitivities. The calculated SGWP*, for a 100 yr time horizon, are negative for three of the four CTM/GCM combinations for European emissions (-9.6 to +6.9), while for the Asian emissions the SGWP* (H=100) is always positive (+2.9 to +25) indicating a warming. For CO the SGWP* values (3.8 and 4.4 for European and Asian emissions respectively, with only the Oslo-CTM2/ECHAM4 model combination) are less regionally dependent. Our results support the view that for NO x , regionally different weighting factors for the emissions are necessary. For CO the results are more robust and one global number may be acceptable

  15. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

    Czech Academy of Sciences Publication Activity Database

    Fronzek, S.; Pirttioja, N. K.; Carter, T. R.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, Miroslav; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M. F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, Petr; Jacquemin, I.; Kersebaum, K. C.; Kollas, C.; Krzyszczak, J.; Lorite, I. J.; Minet, J.; Ines Minguez, M.; Montesino, M.; Moriondo, M.; Mueller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodriguez, A.; Ruane, A. C.; Ruget, F.; Sanna, M.; Semenov, M. A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R.

    2018-01-01

    Roč. 159, jan (2018), s. 209-224 ISSN 0308-521X Keywords : climate-change * crop models * probabilistic assessment * simulating impacts * british catchments * uncertainty * europe * productivity * calibration * adaptation * Classification * Climate change * Crop model * Ensemble * Sensitivity analysis * Wheat Impact factor: 2.571, year: 2016

  16. Weak hydrological sensitivity to temperature change over land, independent of climate forcing

    Science.gov (United States)

    Samset, Bjorn H.

    2017-04-01

    As the global surface temperature changes, so will patterns and rates of precipitation. Theoretically, these changes can be understood in terms of changes to the energy balance of the atmosphere, caused by introducing drivers of climate change such as greenhouse gases, aerosols and altered insolation. Climate models, however, disagree strongly in their prediction of precipitation changes, both for historical and future emission pathways, and per degree of surface warming in idealized experiments. The latter value, often termed the apparent hydrological sensitivity, has also been found to differ substantially between climate drivers. Here, we present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from 10 climate models participating in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we show how modeled global mean precipitation increases by 2-3 % per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature driven (slow) ocean HS of 3-5 %/K, while the slow land HS is only 0-2 %/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. Convective precipitation in the Arctic and large scale precipitation

  17. Battlescale Forecast Model Sensitivity Study

    National Research Council Canada - National Science Library

    Sauter, Barbara

    2003-01-01

    .... Changes to the surface observations used in the Battlescale Forecast Model initialization led to no significant changes in the resulting forecast values of temperature, relative humidity, wind speed, or wind direction...

  18. Model Driven Development of Data Sensitive Systems

    DEFF Research Database (Denmark)

    Olsen, Petur

    2014-01-01

    to the values of variables. This theses strives to improve model-driven development of such data-sensitive systems. This is done by addressing three research questions. In the first we combine state-based modeling and abstract interpretation, in order to ease modeling of data-sensitive systems, while allowing...... efficient model-checking and model-based testing. In the second we develop automatic abstraction learning used together with model learning, in order to allow fully automatic learning of data-sensitive systems to allow learning of larger systems. In the third we develop an approach for modeling and model-based...... detection and pushing error detection to earlier stages of development. The complexity of modeling and the size of systems which can be analyzed is severely limited when introducing data variables. The state space grows exponentially in the number of variable and the domain size of the variables...

  19. Seasonality of Tropical Dry Forests and its Sensitivity to Climate Change

    Science.gov (United States)

    Xu, X.; Medvigy, D.; Powers, J. S.; Becknell, J. M.

    2013-12-01

    Tropical dry forests (TDFs) are characterized by an annual dry season of 3-6 months duration. Although TDFs account for nearly 42% by area of total tropical vegetation, their representation in current dynamic vegetation models has rarely been challenged by ground-based observations. In this study, we assimilate several unique field datasets and MODIS-derived Leaf Area Index (LAI) into the Ecosystem Demography Model version 2 (ED2). The field measurements were taken at 18 forested stands in Costa Rica including annual tree-level censuses, species-level leaf trait, monthly measurements of stand litterfall and soil properties since 2008. These measurements were used to develop plant functional types (PFTs) suitable for modeling TDFs, especially in terms of their allometry, phenology, and growth rates. The model was then forced with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections for Central America to quantify the response and sensitivity of vegetation dynamics to different radiative forcing scenarios. We expect that this study will improve our knowledge of TDFs, including their phenology and sensitivity future climate change, and also has implications for TDF carbon dynamics, energy budgets and hydrological cycling.

  20. Probabilistic evaluation of competing climate models

    Directory of Open Access Journals (Sweden)

    A. Braverman

    2017-10-01

    Full Text Available Climate models produce output over decades or longer at high spatial and temporal resolution. Starting values, boundary conditions, greenhouse gas emissions, and so forth make the climate model an uncertain representation of the climate system. A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. In this article, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. Here, we compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set as an illustration.

  1. Probabilistic evaluation of competing climate models

    Science.gov (United States)

    Braverman, Amy; Chatterjee, Snigdhansu; Heyman, Megan; Cressie, Noel

    2017-10-01

    Climate models produce output over decades or longer at high spatial and temporal resolution. Starting values, boundary conditions, greenhouse gas emissions, and so forth make the climate model an uncertain representation of the climate system. A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. In this article, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. Here, we compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set as an illustration.

  2. Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

    Directory of Open Access Journals (Sweden)

    N. Mahowald

    2011-02-01

    Full Text Available Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climate feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.

  3. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [Lawrence Livermore National Laboratory, Livermore, California; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Marchand, Roger [University of Washington, Seattle, Washington; Kollias, Pavlos [Stony Brook University, Stony Brook, New York; Clothiaux, Eugene E. [The Pennsylvania State University, University Park, Pennsylvania; Lin, Wuyin [Brookhaven National Laboratory, Upton, New York; Johnson, Karen [Brookhaven National Laboratory, Upton, New York; Swales, Dustin [CIRES and NOAA/Earth System Research Laboratory, Boulder, Colorado; Bodas-Salcedo, Alejandro [Met Office Hadley Centre, Exeter, United Kingdom; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California; Haynes, John M. [Cooperative Institute for Research in the Atmosphere/Colorado State University, Fort Collins, Colorado; Collis, Scott [Argonne National Laboratory, Argonne, Illinois; Jensen, Michael [Brookhaven National Laboratory, Upton, New York; Bharadwaj, Nitin [Pacific Northwest National Laboratory, Richland, Washington; Hardin, Joseph [Pacific Northwest National Laboratory, Richland, Washington; Isom, Bradley [Pacific Northwest National Laboratory, Richland, Washington

    2018-01-01

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are

  4. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

    Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

  5. Sensitivity of Arctic Summer Sea Ice Coverage to Global Warming Forcing: Toward Reducing Uncertainty in Arctic Climate Change Projections

    Science.gov (United States)

    Zhang, Xiangdong

    2010-05-01

    Substantial uncertainties have emerged in Arctic climate change projections by the fourth Intergovernmental Panel on Climate Change assessment report (IPCC AR4) climate models. The recently observed acceleration of sea ice decline and the extreme event of sea ice cover loss in summer 2007 and the out-of-phase anomalies of surface air temperature between high- and mid-latitudes in winter 2009 further enhance such uncertainties. The models as a group considerably underestimate the recent changes in sea ice. To better understand the uncertainties, following our previous study (Zhang and Walsh 2006), we evaluated sensitivities of summer sea ice coverage to global warming forcing in models and observations. The result suggests that the uncertainties result from the large range of sensitivities involved in the computation of sea ice mass balance by the climate models. Perturbations in model initialization can also result in different feedback strength in the ensemble runs. Selected, observationally-constrained model runs by the sensitivity analysis well captured the observed changes in and reduced future projection uncertainties of sea ice area and surface air temperatures. The projected ice-free summer Arctic Ocean may occur as early as in the late 2030s and the Arctic regional mean surface air temperature will be likely increased by 8.5C in winter and 3.7C in summer by the end of this century. This study for the first time employs the concept and approach of climate sensitivity to evaluate summer sea ice uncertainties in climate model simulations. It provides useful information for improving model simulations and projections for the forthcoming IPCC AR5.

  6. Interpretation of cloud-climate feedback as produced by 14 atmospheric general circulation models

    Science.gov (United States)

    Cess, R. D.; Potter, G. L.; Ghan, S. J.; Blanchet, J. P.; Boer, G. J.

    1989-01-01

    Understanding the cause of differences among general circulation model projections of carbon dioxide-induced climatic change is a necessary step toward improving the models. An intercomparison of 14 atmospheric general circulation models, for which sea surface temperature perturbations were used as a surrogate climate change, showed that there was a roughly threefold variation in global climate sensitivity. Most of this variation is attributable to differences in the models' depictions of cloud-climate feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as climatic predictors.

  7. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

    2015-12-01

    Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

  8. An explanation for the different climate sensitivities of land and ocean surfaces based on the diurnal cycle

    Science.gov (United States)

    Kleidon, Axel; Renner, Maik

    2017-09-01

    Observations and climate model simulations consistently show a higher climate sensitivity of land surfaces compared to ocean surfaces. Here we show that this difference in temperature sensitivity can be explained by the different means by which the diurnal variation in solar radiation is buffered. While ocean surfaces buffer the diurnal variations by heat storage changes below the surface, land surfaces buffer it mostly by heat storage changes above the surface in the lower atmosphere that are reflected in the diurnal growth of a convective boundary layer. Storage changes below the surface allow the ocean surface-atmosphere system to maintain turbulent fluxes over day and night, while the land surface-atmosphere system maintains turbulent fluxes only during the daytime hours, when the surface is heated by absorption of solar radiation. This shorter duration of turbulent fluxes on land results in a greater sensitivity of the land surface-atmosphere system to changes in the greenhouse forcing because nighttime temperatures are shaped by radiative exchange only, which are more sensitive to changes in greenhouse forcing. We use a simple, analytic energy balance model of the surface-atmosphere system in which turbulent fluxes are constrained by the maximum power limit to estimate the effects of these different means to buffer the diurnal cycle on the resulting temperature sensitivities. The model predicts that land surfaces have a 50 % greater climate sensitivity than ocean surfaces, and that the nighttime temperatures on land increase about twice as much as daytime temperatures because of the absence of turbulent fluxes at night. Both predictions compare very well with observations and CMIP5 climate model simulations. Hence, the greater climate sensitivity of land surfaces can be explained by its buffering of diurnal variations in solar radiation in the lower atmosphere.

  9. An explanation for the different climate sensitivities of land and ocean surfaces based on the diurnal cycle

    Directory of Open Access Journals (Sweden)

    A. Kleidon

    2017-09-01

    Full Text Available Observations and climate model simulations consistently show a higher climate sensitivity of land surfaces compared to ocean surfaces. Here we show that this difference in temperature sensitivity can be explained by the different means by which the diurnal variation in solar radiation is buffered. While ocean surfaces buffer the diurnal variations by heat storage changes below the surface, land surfaces buffer it mostly by heat storage changes above the surface in the lower atmosphere that are reflected in the diurnal growth of a convective boundary layer. Storage changes below the surface allow the ocean surface–atmosphere system to maintain turbulent fluxes over day and night, while the land surface–atmosphere system maintains turbulent fluxes only during the daytime hours, when the surface is heated by absorption of solar radiation. This shorter duration of turbulent fluxes on land results in a greater sensitivity of the land surface–atmosphere system to changes in the greenhouse forcing because nighttime temperatures are shaped by radiative exchange only, which are more sensitive to changes in greenhouse forcing. We use a simple, analytic energy balance model of the surface–atmosphere system in which turbulent fluxes are constrained by the maximum power limit to estimate the effects of these different means to buffer the diurnal cycle on the resulting temperature sensitivities. The model predicts that land surfaces have a 50 % greater climate sensitivity than ocean surfaces, and that the nighttime temperatures on land increase about twice as much as daytime temperatures because of the absence of turbulent fluxes at night. Both predictions compare very well with observations and CMIP5 climate model simulations. Hence, the greater climate sensitivity of land surfaces can be explained by its buffering of diurnal variations in solar radiation in the lower atmosphere.

  10. Climatically sensitive tree-ring chronologies from Crimea, Ukraine

    Science.gov (United States)

    Solomina, O.; Davi, N.; D Arrigo, R.

    2003-04-01

    Several tree species in Crimea can reach ages of 1000 years or more (Crimea..., 1999), including Taxus baccata L., Arbutus andrachne L., Quercus pubescens Willd, Quercus petraea (Mattuschka) Liebl., Quercus robur L., Juniperus excelsa M.B., and Pistacia mutica Fisch.et Mey. In September 2002, we collected samples from several long-lived tree sites described in the literature (Vulf, 1948, Ivanenko, 1951, Ena, 1983, Podgorniy, 1990), located in the mountains of Central Crimea (Sokolinoye, Chufut-Kale, Chelter) and on the coast of the Black Sea (Ai-Todor, Kharaks, Ai-Petri). The trees sampled generally had 300-350 rings. At Ai-Todor, most oaks, junipers, and pistachio showed decay. However, enough samples of oak, juniper and pine were collected to build three chronologies with good replication over the last 350 years. Long meteorological records (for Sevastopol since 1821, Ai-Petri and Yalta since the 1880's) as well as detailed historical data on extreme climatic events since 1687 (summarized by Borisov 1956) are available for this area and can be used to calibrate and verify the tree growth/climate models. Resulting dendroclimatic reconstructions will be the first from this region. The tree-ring time-series may also be used for archaeological dating of historical wood from several medieval fortresses, towns and palaces. In turn, the archaeological wood could be used to extend the tree-ring time series. Stalactites and stalagmites (Dubliansky, 1977) found in numerous caves, as well as 4000-years old laminated lake sediments (Shostakovich, 1934) are also potentially important sources of paleoclimatic information in the area.

  11. Leveraging atmospheric CO2 observations to constrain the climate sensitivity of terrestrial ecosystems

    Science.gov (United States)

    Keppel-Aleks, G.

    2015-12-01

    A significant challenge in understanding, and therefore modeling, the response of terrestrial carbon cycling to climate and environmental drivers is that vegetation varies on spatial scales of order a few kilometers whereas Earth system models (ESMs) are run with characteristic length scales of order 100 km. Atmospheric CO2 provides a constraint on carbon fluxes at spatial scales compatible with the resolution of ESMs due to the fact that atmospheric mixing renders a single site representative of fluxes within a large spatial footprint. The variations in atmospheric CO2 at both seasonal and interannual timescales largely reflect terrestrial influence. I discuss the use of atmospheric CO2 observations to benchmark model carbon fluxes over a range of spatial scales. I also discuss how simple models can be used to test functional relationships between the CO2 growth rate and climate variations. In particular, I show how atmospheric CO2 provides constraints on ecosystem sensitivity to climate drivers in the tropics, where tropical forests and semi-arid ecosystems are thought to account for much of the variability in the contemporary carbon sink.

  12. Diurnal cloud cycle biases in climate models.

    Science.gov (United States)

    Yin, Jun; Porporato, Amilcare

    2017-12-22

    Clouds' efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.

  13. Quantitative Study of Green Area for Climate Sensitive Terraced Housing Area Design in Malaysia

    International Nuclear Information System (INIS)

    Yeo, O T S; Saito, K; Said, I

    2014-01-01

    Neighbourhood plays a significant role in peoples' daily lives. Nowadays, terraced housing is common in Malaysia, and green areas in the neighborhood are not used to their maximum. The aim of the research is to quantify the types of green area that are most efficient for cooling the environment for thermal comfort and mitigation of Urban Heat Island. Spatial and environmental inputs are manipulated for the simulation using Geographic Information System (GIS) integrated with computational microclimate simulation. The outcome of this research is a climate sensitive housing environment model framework on the green area to solve the problem of Urban Heat Island

  14. Water sensitive design as a means of adaptation for climate change and urbanisation

    International Nuclear Information System (INIS)

    Semadeni-Davies, Annette

    2007-01-01

    Full text: Full text: This presentation uses urban drainage to show how climate change impact assessments should also consider changes in resource management, land-use and technology. Although the work was carried out in Sweden (Semadeni-Davies 2004; 2007 a, b), the findings are relevant for Australia and New Zealand as these countries are currently moving away from pipe stormwater networks towards open water systems. Urban areas are characterised by high peak flows and fast response times. A central issue here is that there has been a paradigm shift in urban water management, particularly in new developments where the stormwater system is fast becoming a landscape feature. The shift is part of a worldwide trend called water sensitive design (WSD) or low impact design (LID). Ponds, wetlands, infiltration trenches, and porous paving are common examples of WSD elements intended to reduce peak stormwater and contaminant transport while maintaining low flows. Even in city centres where land values are at a premium, there has been an interest in retro-fitting for WSD. It is important for those interested in the impacts of climate change on urban areas to know this background information, as WSD may offer a means of adapting to climate change. However, there is a major stumbling block - the output from regional climate models is currently not at a sufficient spatial or temporal resolution to assess theimpact on urban drainage as the processes operate on a scale of minutes and metres (Shilling 1991). The disparity in resolution is also problematic for the design of future-proofed urban water systems as this requires information on rainfall intensity and frequency. To illustrate the effect of WSD, the potential impacts of climate change and urbanisation on flow were assessed both separately and together using DHI software (MIKE SHE, MOUSE) for Helsingborg in two related studies for combined and separate sewers. The Swedish regional climate model developed at the Rossby

  15. Comparing the sensitivity of permafrost and marine gas hydrate to climate warming

    International Nuclear Information System (INIS)

    Taylor, A.E.; Dallimore, S.R.; Hyndman, R.D.; Wright, F.

    2005-01-01

    The sensitivity of Arctic subpermafrost gas hydrate at the Mallik borehole was compared to temperate marine gas hydrate located offshore southwestern Canada. In particular, a finite element geothermal model was used to determine the sensitivity to the end of the ice age, and contemporary climate warming of a 30 m thick methane hydrate layer lying at the base of a gas hydrate stability zone prior to 13.5 kiloannum (ka) before present (BP). It was suggested that the 30 m gas-hydrate-bearing layer would have disappeared by now, according to the thermal signal alone. However, the same gas-hydrate-bearing layer underlying permafrost would persist until at least 4 ka after present, even with contemporary climate warming. The longer time for subpermafrost gas hydrate comes from the thawing pore ice at the base of permafrost, at the expense of dissociation of the deeper gas hydrate. The dissociation of underlying gas hydrate from climate surface warming is buffered by the overlying permafrost

  16. Improved regional climate modelling through dynamical downscaling

    International Nuclear Information System (INIS)

    Corney, Stuart; Grose, Michael; Holz, Greg; White, Chris; Bennett, James; Gaynor, Suzie; Bindoff, Nathan; Katzfey, Jack; McGregor, John

    2010-01-01

    Coupled Ocean-Atmosphere General Circulation Models (GCMs) provide the best estimates for assessing potential changes to our climate on a global scale out to the end of this century. Because coupled GCMs have a fairly coarse resolution they do not provide a detailed picture of climate (and climate change) at the local scale. Tasmania, due to its diverse geography and range of climate over a small area is a particularly difficult region for drawing conclusions regarding climate change when relying solely on GCMs. The foundation of the Climate Futures for Tasmania project is to take the output produced by multiple GCMs, using multiple climate change scenarios, and use this output as input into the Conformal Cubic Atmospheric Model (CCAM) to downscale the GCM output. CCAM is a full atmospheric global general circulation model, formulated using a conformal-cubic grid that covers the globe but can be stretched to provide higher resolution in the area of interest (Tasmania). By modelling the atmosphere at a much finer scale than is possible using a coupled GCM we can more accurately capture the processes that drive Tasmania's weather/climate, and thus can more clearly answer the question of how Tasmania's climate will change in the future. We present results that show the improvements in capturing the local-scale climate and climate drivers that can be achieved through downscaling, when compared to a gridded observational data set. The underlying assumption of this work is that a better simulated current climatology will also produce a more credible climate change signal.

  17. Runoff sensitivity over Asia: Role of climate variables and initial soil conditions

    Science.gov (United States)

    Liu, Di; Mishra, Ashok K.; Zhang, Ke

    2017-02-01

    We applied statistical and numerical modeling approach to evaluate the sensitivity of runoff (ROF) to climate variables using Global Land Data Assimilation System (GLDAS) data and regional climate model (RegCM4). It was observed that ROF is more sensitive to precipitation (P) compared to other analyzed hydroclimatic variables (potential evapotranspiration (PET), 2 m air temperature (T2m), solar radiation (Rn), specific humidity (SSH), and wind speed (U), especially over India, Indochina, and south-north-northeast China semihumid-humid climate transition zones based on the higher correlation coefficient (>0.7) and elasticity (>2). The abnormal positive T2m-ROF observed over Tibetan Plateau region (TP) may be due to its high topography and cold weather regime, while positive PET-ROF over India and north China-southeast Mongolia regions can be attributed to the stronger influence of local land-atmosphere interactions. Soil moisture (SM) reflects high correlation with runoff, especially over the climate transition zones (i.e., India and Indochina-southeast China). The initial wet (dry) soil moisture (SM) anomalies lead to an increase (decrease) of ROF in each season with the hot spots mainly located in middle to high latitudes (spring), TP and northeast (summer and autumn), and Indochina (autumn) regions. Such influence can persist almost 4 months in spring while only about 1 month in autumn during dry and wet conditions. The wet condition has stronger influence at beginning but dissipates quickly, while the dry condition can last longer within the same season. The impact of initial soil temperature anomalies on ROF is weaker than SM, with the only obvious ROF changes located over south China (spring and summer) and north India (autumn).

  18. Sensitivity of the North Atlantic climate to Greenland Ice Sheet melting during the Last Interglacial

    Directory of Open Access Journals (Sweden)

    P. Bakker

    2012-06-01

    Full Text Available During the Last Interglacial (LIG; ~130 000 yr BP, part of the Greenland Ice Sheet (GIS melted due to a warmer than present-day climate. However, the impact of this melting on the LIG climate in the North Atlantic region is relatively unknown. Using the LOVECLIM Earth system model of intermediate complexity, we have systematically tested the sensitivity of the LIG climate to increased freshwater runoff from the GIS. In addition, experiments have been performed to investigate the impact of an idealized reduction of both surface elevation and extent of the GIS on the LIG climate. Based on changes in the maximum sea-ice cover and the strength of the overturning circulation, three regimes have been identified, which are characterized by a specific pattern of surface temperature change in the North Atlantic region. By comparing the simulated deep ocean circulation with proxy-based reconstructions, the most realistic simulated climate could be discerned. The resulting climate is characterized by a shutdown of deep convection and a subsequent ~4 °C cooling in the Labrador Sea. Furthermore, a cooling of ~1 °C over the North Atlantic Ocean between 40° N and 70° N is seen. The prescribed reduction in surface elevation and extent of the GIS results in a local warming of up to 4 °C and amplifies the freshwater-forced reduction in deep convection and the resultant cooling in the Nordic Seas. A further comparison of simulated summer temperatures with both continental and oceanic proxy records reveals that the partial melting of the GIS during the LIG could have delayed maximum summer temperatures in the western part of the North Atlantic region relative to the insolation maximum.

  19. Modeling Past Abrupt Climate Changes

    DEFF Research Database (Denmark)

    Marchionne, Arianna

    of the orbital variations on Earth's climate; however, the knowledge and tools needed to complete a unied theory for ice ages have not been developed yet. Here, we focus on the climatic variations that have occurred over the last few million years. Paleoclimatic records show that the glacial cycles are linked...... to the orbitally driven variations in insolation. However, the relationship is far from linear, and insolation alone can not explain the climatic variability seen in the records. In the rst part of this thesis, we discuss the possible dynamical mechanisms for linking the frequencies observed in the records...... discuss a third possible mechanism for the climate response to an external periodic forcing. In this scenario, the system is excitable: a small perturbation from the xed point may produce large excursions....

  20. Responses of the ocean carbon cycle to climate change: Results from an earth system climate model simulation

    Directory of Open Access Journals (Sweden)

    Shuang-Jing Wang

    2014-09-01

    Full Text Available Based on simulations using the University of Victoria's Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by 4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic's ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean's ability to absorb CO2 from the atmosphere.

  1. Predicting Climate-sensitive Infectious Diseases: Development of a Federal Science Plan and the Path Forward

    Science.gov (United States)

    Trtanj, J.; Balbus, J. M.; Brown, C.; Shimamoto, M. M.

    2017-12-01

    The transmission and spread of infectious diseases, especially vector-borne diseases, water-borne diseases and zoonosis, are influenced by short and long-term climate factors, in conjunction with numerous other drivers. Public health interventions, including vaccination, vector control programs, and outreach campaigns could be made more effective if the geographic range and timing of increased disease risk could be more accurately targeted, and high risk areas and populations identified. While some progress has been made in predictive modeling for transmission of these diseases using climate and weather data as inputs, they often still start after the first case appears, the skill of those models remains limited, and their use by public health officials infrequent. And further, predictions with lead times of weeks, months or seasons are even rarer, yet the value of acting early holds the potential to save more lives, reduce cost and enhance both economic and national security. Information on high-risk populations and areas for infectious diseases is also potentially useful for the federal defense and intelligence communities as well. The US Global Change Research Program, through its Interagency Group on Climate Change and Human Health (CCHHG), has put together a science plan that pulls together federal scientists and programs working on predictive modeling of climate-sensitive diseases, and draws on academic and other partners. Through a series of webinars and an in-person workshop, the CCHHG has convened key federal and academic stakeholders to assess the current state of science and develop an integrated science plan to identify data and observation systems needs as well as a targeted research agenda for enhancing predictive modeling. This presentation will summarize the findings from this effort and engage AGU members on plans and next steps to improve predictive modeling for infectious diseases.

  2. Wind climate from the regional climate model REMO

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

    2010-01-01

    Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...

  3. Climate Predictions: The Chaos and Complexity in Climate Models

    Directory of Open Access Journals (Sweden)

    D. T. Mihailović

    2014-01-01

    Full Text Available Some issues which are relevant for the recent state in climate modeling have been considered. A detailed overview of literature related to this subject is given. The concept in modeling of climate, as a complex system, seen through Gödel’s theorem and Rosen’s definition of complexity and predictability is discussed. Occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form is pointed out. A coupled system of equations, often used in climate models, was analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this system. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, was analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameter, the logistic parameter, and the parameter of exchange, were studied calculating the Lyapunov exponent under simulations with the closed contour of N=100 environmental interfaces. Finally, we have explored possible differences in complexities of two global and two regional climate models using their air temperature and precipitation output time series. The complexities were obtained with the algorithm for calculating the Kolmogorov complexity.

  4. Modeling and assessing international climate financing

    Science.gov (United States)

    Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

    2016-06-01

    Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.

  5. Time-dependent climate sensitivity and the legacy of anthropogenic greenhouse gas emissions.

    Science.gov (United States)

    Zeebe, Richard E

    2013-08-20

    Climate sensitivity measures the response of Earth's surface temperature to changes in forcing. The response depends on various climate processes that feed back on the initial forcing on different timescales. Understanding climate sensitivity is fundamental to reconstructing Earth's climatic history as well as predicting future climate change. On timescales shorter than centuries, only fast climate feedbacks including water vapor, lapse rate, clouds, and snow/sea ice albedo are usually considered. However, on timescales longer than millennia, the generally higher Earth system sensitivity becomes relevant, including changes in ice sheets, vegetation, ocean circulation, biogeochemical cycling, etc. Here, I introduce the time-dependent climate sensitivity, which unifies fast-feedback and Earth system sensitivity. I show that warming projections, which include a time-dependent climate sensitivity, exhibit an enhanced feedback between surface warming and ocean CO2 solubility, which in turn leads to higher atmospheric CO2 levels and further warming. Compared with earlier studies, my results predict a much longer lifetime of human-induced future warming (23,000-165,000 y), which increases the likelihood of large ice sheet melting and major sea level rise. The main point regarding the legacy of anthropogenic greenhouse gas emissions is that, even if the fast-feedback sensitivity is no more than 3 K per CO2 doubling, there will likely be additional long-term warming from slow climate feedbacks. Time-dependent climate sensitivity also helps explaining intense and prolonged warming in response to massive carbon release as documented for past events such as the Paleocene-Eocene Thermal Maximum.

  6. Climatic Calibration of Paleoecological Data and Data/Model Comparisons

    Science.gov (United States)

    Webb, T.; Bartlein, P. J.; Shuman, B.; Williams, J. W.

    2004-12-01

    When accurately and precisely dated, paleoecological data along with geochemical data and geomorphological features indicate past changes in climate. Calibrating these data in terms of standard climatic (e.g. July mean temperature) or bioclimatic (e.g. winter extreme temperatures) variables has allowed construction of paleoclimatic maps and time series that not only show the magnitude and extent of the difference in past climates but also can be compared to the output from global climate and earth-system models. Key to judging the reliability of the derived paleoclimatic estimates is the qualitative and quantitative comparison of estimates from different paleoclimatic indicators to show whether consistent or discrepant patterns exist. Here "multi-proxy" studies of independent paleoclimatic indicators from single cores, single basins, and multiple sites are providing many new opportunities to test calibration methods and results. The multi-proxy studies are also allowing researchers to develop a multivariate view of climate because different types of data, whether paleoecological or geochemical, often are sensitive to different aspects of climate change. These can be temperature changes and/or moisture changes as well as changes in seasonality or climatic extremes. Recent research mapping late Quaternary pollen, geochemical, and lake-level data across eastern North America in 1000-yr intervals illustrates some the advances gained from this multi-proxy approach to the reconstruction of past climates since the last glacial maximum 21,000 years ago.

  7. Exploitation of Parallelism in Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Baer, F.; Tribbia, J.J.; Williamson, D.L.

    1999-03-01

    The US Department of Energy (DOE), through its CHAMMP initiative, hopes to develop the capability to make meaningful regional climate forecasts on time scales exceeding a decade, such capability to be based on numerical prediction type models. We propose research to contribute to each of the specific items enumerated in the CHAMMP announcement (Notice 91-3); i.e., to consider theoretical limits to prediction of climate and climate change on appropriate time scales, to develop new mathematical techniques to utilize massively parallel processors (MPP), to actually utilize MPPs as a research tool, and to develop improved representations of some processes essential to climate prediction. In particular, our goals are to: (1) Reconfigure the prediction equations such that the time iteration process can be compressed by use of MMP architecture, and to develop appropriate algorithms. (2) Develop local subgrid scale models which can provide time and space dependent parameterization for a state- of-the-art climate model to minimize the scale resolution necessary for a climate model, and to utilize MPP capability to simultaneously integrate those subgrid models and their statistics. (3) Capitalize on the MPP architecture to study the inherent ensemble nature of the climate problem. By careful choice of initial states, many realizations of the climate system can be determined concurrently and more realistic assessments of the climate prediction can be made in a realistic time frame. To explore these initiatives, we will exploit all available computing technology, and in particular MPP machines. We anticipate that significant improvements in modeling of climate on the decadal and longer time scales for regional space scales will result from our efforts.

  8. Sensitivity-Based Guided Model Calibration

    Science.gov (United States)

    Semnani, M.; Asadzadeh, M.

    2017-12-01

    A common practice in automatic calibration of hydrologic models is applying the sensitivity analysis prior to the global optimization to reduce the number of decision variables (DVs) by identifying the most sensitive ones. This two-stage process aims to improve the optimization efficiency. However, Parameter sensitivity information can be used to enhance the ability of the optimization algorithms to find good quality solutions in a fewer number of solution evaluations. This improvement can be achieved by increasing the focus of optimization on sampling from the most sensitive parameters in each iteration. In this study, the selection process of the dynamically dimensioned search (DDS) optimization algorithm is enhanced by utilizing a sensitivity analysis method to put more emphasis on the most sensitive decision variables for perturbation. The performance of DDS with the sensitivity information is compared to the original version of DDS for different mathematical test functions and a model calibration case study. Overall, the results show that DDS with sensitivity information finds nearly the same solutions as original DDS, however, in a significantly fewer number of solution evaluations.

  9. Complementarity among climate related energy sources: Sensitivity study to climate characteristics across Europe

    Science.gov (United States)

    Francois, Baptiste; Hingray, Benoit; Creutin, Jean-Dominique; Raynaud, Damien; Borga, Marco; Vautard, Robert

    2015-04-01

    Climate related energy sources like solar-power, wind-power and hydro-power are important contributors to the transitions to a low-carbon economy. Past studies, mainly based on solar and wind powers, showed that the power from such energy sources fluctuates in time and space following their driving climatic variables. However, when combining different energy sources together, their intermittent feature is smoothed, resulting to lower time variability of the produced power and to lower storage capacity required for balancing. In this study, we consider solar, wind and hydro energy sources in a 100% renewable Europe using a set of 12 regions following two climate transects, the first one going from the Northern regions (Norway, Finland) to the Southern ones (Greece, Andalucía, Tunisia) and the second one going from the oceanic climate (West of France, Galicia) to the continental one (Romania, Belorussia). For each of those regions, we combine wind and solar irradiance data from the Weather Research and Forecasting Model (Vautard et al., 2014), temperature data from the European Climate Assessment & Dataset (Haylock et al., 2008) and runoff from the Global Runoff Data Center (GRDC, 1999) for estimating solar-power, wind-power, run-of-the-river hydro-power and the electricity demand over a time period of 30 years. The use of this set of 12 regions across Europe allows integrating knowledge about time and space variability for each different energy sources. We then assess the optimal share of each energy sources, aiming to decrease the time variability of the regional energy balance at different time scales as well as the energy storage required for balancing within each region. We also evaluate how energy transport among regions contributes for smoothing out both the energy balance and the storage requirement. The strengths of this study are i) to handle with run-of-the-river hydro power in addition to wind and solar energy sources and ii) to carry out this analysis

  10. COP21 climate negotiators' responses to climate model forecasts

    Science.gov (United States)

    Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo

    2017-02-01

    Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest.

  11. Potential evaporation estimation through an unstressed surface-energy balance and its sensitivity to climate change

    Science.gov (United States)

    Barella-Ortiz, A.; Polcher, J.; Tuzet, A.; Laval, K.

    2013-11-01

    Potential evaporation (ETP) is a basic input for many hydrological and agronomic models, as well as a key variable in most actual evaporation estimations. It has been approached through several diffusive and energy balance methods, out of which the Penman-Monteith equation is recommended as the standard one. In order to deal with the diffusive approach, ETP must be estimated at a sub-diurnal frequency, as currently done in land surface models (LSMs). This study presents an improved method, developed in the ORCHIDEE LSM, which consists of estimating ETP through an unstressed surface-energy balance (USEB method). The results confirm the quality of the estimation which is currently implemented in the model (Milly, 1992). The ETP underlying the reference evaporation proposed by the Food and Agriculture Organization, FAO, (computed at a daily time step) has also been analysed and compared. First, a comparison for a reference period under current climate conditions shows that USEB and FAO's ETP estimations differ, especially in arid areas. However, they produce similar values when the FAO's assumption of neutral stability conditions is relaxed, by replacing FAO's aerodynamic resistance by that of the model's. Furthermore, if the vapour pressure deficit (VPD) estimated for the FAO's equation, is substituted by ORCHIDEE's VPD or its humidity gradient, the agreement between the daily mean estimates of ETP is further improved. In a second step, ETP's sensitivity to climate change is assessed by comparing trends in these formulations for the 21st century. It is found that the USEB method shows a higher sensitivity than the FAO's. Both VPD and the model's humidity gradient, as well as the aerodynamic resistance have been identified as key parameters in governing ETP trends. Finally, the sensitivity study is extended to two empirical approximations based on net radiation and mass transfer (Priestley-Taylor and Rohwer, respectively). The sensitivity of these ETP estimates is

  12. Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

    Science.gov (United States)

    D'Orangeville, Loïc; Maxwell, Justin; Kneeshaw, Daniel; Pederson, Neil; Duchesne, Louis; Logan, Travis; Houle, Daniel; Arseneault, Dominique; Beier, Colin M; Bishop, Daniel A; Druckenbrod, Daniel; Fraver, Shawn; Girard, François; Halman, Joshua; Hansen, Chris; Hart, Justin L; Hartmann, Henrik; Kaye, Margot; Leblanc, David; Manzoni, Stefano; Ouimet, Rock; Rayback, Shelly; Rollinson, Christine R; Phillips, Richard P

    2018-02-20

    Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ 50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors. © 2018 John Wiley & Sons Ltd.

  13. Sensitivity Analysis in Sequential Decision Models.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

    2017-02-01

    Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

  14. Quantifying the increasing sensitivity of power systems to climate variability

    Science.gov (United States)

    Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

    2016-12-01

    Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

  15. Intercomparison of model response and internal variability across climate model ensembles

    Science.gov (United States)

    Kumar, Devashish; Ganguly, Auroop R.

    2017-10-01

    Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

  16. Land use change affecting our (modelled) climate

    Science.gov (United States)

    Weiß, M.; van den Hurk, B.

    2012-04-01

    Up until now, climate models often have used a static representation of land cover characteristics and only recently, the impact of a changing land surface on climate and climate simulations has attracted more attention. With climate scenarios to the fifth Assessment Report currently in preparation, this time considering different representative concentration pathways and associated land cover scenarios, we are still building up process-knowledge on the strength of land-atmosphere coupling. This study contributes to our understanding of the impact of land cover changes on the atmosphere by running global simulations with the EC-Earth climate model, using different historical land use data as well as two land use scenarios to analyse the following aspects in more detail: On the one hand the impact of land cover change via modified albedo, and on the other hand its impact via modified surface resistance, rooting depth and soil-moisture capacity on available energy, evapotranspiration, wind and temperature.

  17. Components of Population Vulnerability and Their Relationship With Climate-Sensitive Health Threats.

    Science.gov (United States)

    English, P B; Richardson, M J

    2016-03-01

    Climate change is increasingly being framed as risks that will impact the poorest and most vulnerable communities among us. This has led to more efforts to estimate climate change risks across populations and in the context of human health and health equity. We describe the public health dimensions of climate vulnerability-exposure, population sensitivity, and adaptive capacity-and explore how these dimensions can modify population health impacts and their distribution. An overview of health disparities associated with specific climate risks is presented, and we offer potential solutions grounded in equitable urban development and improved characterization of climate vulnerabilities.

  18. Impact of Albedo Contrast Between Cirrus and Boundary-Layer Clouds on Climate Sensitivity

    Science.gov (United States)

    Chou, Ming-Dah; Lindzen, R. S.; Hou, A. Y.; Lau, William K. M. (Technical Monitor)

    2001-01-01

    In assessing the iris effect suggested by Lindzen et al. (2001), Fu et al. (2001) found that the response of high-level clouds to the sea surface temperature had an effect of reducing the climate sensitivity to external radiative forcing, but the effect was not as strong as LCH found. This weaker reduction in climate sensitivity was due to the smaller contrasts in albedos and effective emitting temperatures between cirrus clouds and the neighboring regions. FBH specified the albedos and the outgoing longwave radiation (OLR) in the LCH 3.5-box radiative-convective model by requiring that the model radiation budgets at the top of the atmosphere be consistent with that inferred from the Earth Radiation Budget Experiment (ERBE). In point of fact, the constraint by radiation budgets alone is not sufficient for deriving the correct contrast in radiation properties between cirrus clouds and the neighboring regions, and the approach of FBH to specifying those properties is, we feel inappropriate for assessing the iris effect.

  19. LBLOCA sensitivity analysis using meta models

    International Nuclear Information System (INIS)

    Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

    2014-01-01

    This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

  20. Implications of the choice and configuration of hydrologic models on the portrayal of climate change impact

    Science.gov (United States)

    Mendoza, P. A.; Clark, M. P.; Rajagopalan, B.; Mizukami, N.; Gutmann, E. D.

    2013-12-01

    Climate change studies involve several methodological choices that impact the hydrological sensitivities obtained. Among these, hydrologic model structure selection and parameter identification are particularly relevant and usually have a strong subjective component. This subjectivity is not only limited to engineering applications, but also extends to many of our research studies, resulting in problems such as missing processes in our models, inappropriate parameterizations and compensatory effects of model parameters. The goal of this research is to identify the role of model structures and parameter values on the assessment of hydrologic sensitivity to climate change. We conduct our study in three basins located in the Colorado Headwaters Region, using four different hydrologic models (PRMS, VIC, Noah and Noah-MP). We first compare both model performance and climate sensitivities using default parameterizations and parameter values calibrated with the Shuffled Complex Evolution algorithm. Our results demonstrate that calibration doesn't necessarily improve the representation of hydrological processes or decrease inter-model differences in the change of signature measures of hydrologic behavior with respect to a future climate scenario. We found that inter-model differences in hydrologic sensitivities to climate change may be larger than the climate change signal even after models have been calibrated. Results demonstrate that both model choice (after calibration) and parameter selection have important effects in the portrayal of climate change impacts, and work is ongoing to identify more robust modeling strategies that explicitly account for the subjectivity in these choices. Location of the basins of interest Hydrological models used in this study

  1. A local scale assessment of the climate change sensitivity of snow in Pyrenean ski resorts

    Science.gov (United States)

    Pesado, Cristina; Pons, Marc; Vilella, Marc; López-Moreno, Juan Ignacio

    2016-04-01

    The Pyrenees host one of the largest ski area in Europe after the Alps that encompasses the mountain area of the south of France, the north of Spain and the small country of Andorra. In this region, winter tourism is one of the main source of income and driving force of local development on these mountain communities. However, this activity was identified as one of the most vulnerable to a future climate change due to the projected decrease of natural snow and snowmaking capacity. However, within the same ski resorts different areas showed to have a very different vulnerability within the same resort based on the geographic features of the area and the technical management of the slopes. Different areas inside a same ski resort could have very different vulnerability to future climate change based on aspect, steepness or elevation. Furthermore, the technical management of ski resorts, such as snowmaking and grooming were identified to have a significant impact on the response of the snowpack in a warmer climate. In this line, two different ski resorts were deeply analyzed taken into account both local geographical features as well as the effect of the technical management of the runs. Principal Component Analysis was used to classify the main areas of the resort based on the geographic features (elevation, aspect and steepness) and identify the main representative areas with different local features. Snow energy and mass balance was simulated in the different representative areas using the Cold Regions Hydrological Model (CRHM) assuming different magnitudes of climate warming (increases of 2°C and 4°C in the mean winter temperature) both in natural conditions and assuming technical management of the slopes. Theses first results showed the different sensitivity and vulnerability to climate changes based on the local geography of the resort and the management of the ski runs, showing the importance to include these variables when analyzing the local vulnerability

  2. A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

    Science.gov (United States)

    Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

    2012-12-01

    Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter

  3. Sensitivity of weather besed irrigation scheduling model

    International Nuclear Information System (INIS)

    Laghari, K.Q.; Lashari, B.K.; Laghari, N.U.Z.

    2009-01-01

    This study describes the sensitivity of irrigation scheduling model (Mehran) carried out by changing input weather parameters (Temperatures, Wind velocity, Rainfall, and Sunshine hours) to see model sensitivity in computation/estimations (output) for Transpiration (T), Evaporation (E), and allocation of irrigation (I) water. Sensitivity analysis depends on the site and environmental conditions and is therefore an essential step in model validation and application. Mehran Model is weather based crop growth simulation model, which uses daily input data of max and min temperatures (temp), dew point temp (humidity), wind speed, daily sunshine hours (radiation) and computes T/sub c/E/sub s/, and allocates Irrigation accordingly. The input and output base values are taken as an average of three years actual field data used during the Mehran Model testing and calibration on wheat and cotton crops. The model sensitivity of specific input parameter was obtained by varying its value and keeping other input parameters at their base values. The input base values varied by+-10 and +-25%. The model was run for each modified input parameter, and output was compared statistically with base outputs. The ME% (Mean Percent Error) was used to obtain variations in output values. The results reveal that the model is most sensitive with variations in temperature. The 10 and 25% increase in temperature resulted increase in Cotton crop's Tc by 12.18 and 28.54%, corresponding Es by 22.32 and 37.88% and irrigation water allocation by 18.41 and 47.83 % respectively increased from average base values. (author)

  4. Carbon Dioxide Supersaturation in Lakes – Causes, Consequences and Sensitivity to Climate Change

    OpenAIRE

    Sobek, Sebastian

    2005-01-01

    The global carbon cycle is intimately linked with the earth’s climate system. Knowledge about carbon cycling in the biosphere is therefore crucial for predictions of climate change. This thesis investigates the carbon dioxide balance of Swedish boreal lakes, its regulation, significance to the carbon budget of the boreal landscape, and sensitivity to climate change. Swedish boreal lakes were almost exclusively supersaturated in CO2 with respect to the atmosphere, resulting in an emission of C...

  5. Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

    Science.gov (United States)

    McCusker, Kelly E.

    . We show that upon cessation, an abrupt, spatially broad, and sustained warming over land occurs that is well outside the bounds of 20th century climate variability. We then use an upwelling-diffusion energy balance climate model to further show the sensitivity of these trends to background greenhouse gas emissions, termination year, and climate sensitivity. We find that the rate of warming from cessation of solar radiation management -- of critical importance for ecological and human systems -- is principally controlled by the background greenhouse gas concentrations. It follows that the only way to avoid the risk of an abrupt and dangerous warming that is inherent to the large-scale implementation of solar radiation management is to also strongly reduce greenhouse gas emissions. The climate system responds to radiative forcing on a diverse spectrum of timescales, which will affect what goals can be achieved for a given stratospheric aerosol implementation. We next investigate how different rates of stratospheric sulfate aerosol deployment affect what climate impacts can be avoided by simulating two rates of increasing stratospheric sulfate concentrations in a fully-coupled global climate model. We find that disparate goals are achieved for different rates of deployment; for a slow ramping of sulfate, land surface temperature trends remain small but sea levels continue to rise for decades, whereas a quick ramp-up of sulfate yields large land surface cooling trends and immediately reduces sea level. However, atmospheric circulation changes also act to create a large-scale subsurface ocean environment around Antarctica that is favorable for increased basal melting of ice sheet outlets, thereby leaving the potential open for increased sea level rise even in the absence of large atmospheric surface warming. We show that instead, when greenhouse gases are abruptly returned to preindustrial levels, circulation anomalies are reversed, and the subsurface ocean environment

  6. Optimising the FAMOUS climate model: inclusion of global carbon cycling

    Directory of Open Access Journals (Sweden)

    J. H. T. Williams

    2013-01-01

    Full Text Available FAMOUS fills an important role in the hierarchy of climate models, both explicitly resolving atmospheric and oceanic dynamics yet being sufficiently computationally efficient that either very long simulations or large ensembles are possible. An improved set of carbon cycle parameters for this model has been found using a perturbed physics ensemble technique. This is an important step towards building the "Earth System" modelling capability of FAMOUS, which is a reduced resolution, and hence faster running, version of the Hadley Centre Climate model, HadCM3. Two separate 100 member perturbed parameter ensembles were performed; one for the land surface and one for the ocean. The land surface scheme was tested against present-day and past representations of vegetation and the ocean ensemble was tested against observations of nitrate. An advantage of using a relatively fast climate model is that a large number of simulations can be run and hence the model parameter space (a large source of climate model uncertainty can be more thoroughly sampled. This has the associated benefit of being able to assess the sensitivity of model results to changes in each parameter. The climatologies of surface and tropospheric air temperature and precipitation are improved relative to previous versions of FAMOUS. The improved representation of upper atmosphere temperatures is driven by improved ozone concentrations near the tropopause and better upper level winds.

  7. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  8. Sensitivity of summer stream temperatures to climate variability in the Pacific Northwest

    Science.gov (United States)

    Charles Luce; Brian Staab; Marc Kramer; Seth Wenger; Dan Isaak; Callie McConnell

    2014-01-01

    Estimating the thermal response of streams to a warming climate is important for prioritizing native fish conservation efforts. While there are plentiful estimates of air temperature responses to climate change, the sensitivity of streams, particularly small headwater streams, to warming temperatures is less well understood. A substantial body of literature correlates...

  9. A sensitive slope: estimating landscape patterns of forest resilience in a changing climate

    Science.gov (United States)

    Jill F. Johnstone; Eliot J.B. McIntire; Eric J. Pedersen; Gregory King; Michael J.F. Pisaric

    2010-01-01

    Changes in Earth's environment are expected to stimulate changes in the composition and structure of ecosystems, but it is still unclear how the dynamics of these responses will play out over time. In long-lived forest systems, communities of established individuals may be resistant to respond to directional climate change, but may be highly sensitive to climate...

  10. Future extreme events in European climate: An exploration of regional climate model projections

    DEFF Research Database (Denmark)

    Beniston, M.; Stephenson, D.B.; Christensen, O.B.

    2007-01-01

    -90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...... variability. Precipitation - Heavy winter precipitation increases in central and northern Europe and decreases in the south; heavy summer precipitation increases in north-eastern Europe and decreases in the south. Mediterranean droughts start earlier in the year and last longer. Winter storms - Extreme wind...... regions of Holland, Germany and Denmark, in particular. These results are found to depend to different degrees on model formulation. While the responses of heat waves are robust to model formulation, the magnitudes of changes in precipitation and wind speed are sensitive to the choice of regional model...

  11. Is Convection Sensitive to Model Vertical Resolution and Why?

    Science.gov (United States)

    Xie, S.; Lin, W.; Zhang, G. J.

    2017-12-01

    Model sensitivity to horizontal resolutions has been studied extensively, whereas model sensitivity to vertical resolution is much less explored. In this study, we use the US Department of Energy (DOE)'s Accelerated Climate Modeling for Energy (ACME) atmosphere model to examine the sensitivity of clouds and precipitation to the increase of vertical resolution of the model. We attempt to understand what results in the behavior change (if any) of convective processes represented by the unified shallow and turbulent scheme named CLUBB (Cloud Layers Unified by Binormals) and the Zhang-McFarlane deep convection scheme in ACME. A short-term hindcast approach is used to isolate parameterization issues from the large-scale circulation. The analysis emphasizes on how the change of vertical resolution could affect precipitation partitioning between convective- and grid-scale as well as the vertical profiles of convection-related quantities such as temperature, humidity, clouds, convective heating and drying, and entrainment and detrainment. The goal is to provide physical insight into potential issues with model convective processes associated with the increase of model vertical resolution. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  12. Sensitivity analysis of the evaporation module of the E-DiGOR model

    OpenAIRE

    AYDIN, Mehmet; KEÇECİOĞLU, Suzan Filiz

    2010-01-01

    Sensitivity analysis of the soil-water-evaporation module of the E-DiGOR (Evaporation and Drainage investigations at Ground of Ordinary Rainfed-areas) model is presented. The model outputs were generated using measured climatic data and soil properties. The first-order sensitivity formulas were derived to compute relative sensitivity coefficients. A change in the net solar radiation significantly affected potential evaporation from bare soils estimated by the Penman-Monteith equation. The se...

  13. Evaluation of the Australian Community Climate and Earth-System Simulator Chemistry-Climate Model

    Science.gov (United States)

    Stone, K. A.; Morgenstern, O.; Karoly, D. J.; Klekociuk, A. R.; French, W. J. R.; Abraham, N. L.; Schofield, R.

    2015-07-01

    Chemistry climate models are important tools for addressing interactions of composition and climate in the Earth System. In particular, they are used for assessing the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator-Chemistry Climate Model, focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry-Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO) distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October averaged Antarctic TCO from 1960 to 2010 show a similar amount of depletion compared to observations. A significant innovation is the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (up to 26.4 % at Davis during winter) and stratospheric cold biases (up to 10.1 K at the South Pole) outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centered around 100 hPa in ozonesonde data compared to above 50 hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux) are artificially enhancing polar stratospheric cloud formation at high altitudes. The models inability to explicitly simulated supercooled ternary solution may also explain the lack of depletion at lower altitudes. The simulated Southern Annular Mode (SAM) index compares well with ERA-Interim data. Accompanying these

  14. Potential Evaporation Computation through an Unstressed Surface Energy Balance and its Sensitivity to Climate Change Effect

    Science.gov (United States)

    Barella-Ortiz, Anaïs; Polcher, Jan; Tuzet, Andrée; Laval, Katia

    2013-04-01

    Potential evaporation (ETP) is a basic input for hydrological and agronomic models, as well as a key variable in most actual evaporation estimations. It has been approached through several diffusive and energy balance methods, out of which the Penman-Monteith equation is recommended as the standard one. In order to deal with the diffusive approach, ETP must be estimated at a sub-diurnal frequency, as currently done in land surface models (LSM). This study presents an improved method, developed in the ORCHIDEE LSM, which consists in estimating ETP through an unstressed surface energy balance (USEB method). The values provided confirm the quality of the estimation which is currently implemented (Milly, 1992). ETP has also been estimated using a reference equation (computed at a daily time step) provided by the Food and Agriculture Organization (FAO). In the first place, a comparison for a reference period of 11 years shows that both formulations differ, specially in arid areas. However, they supply similar values when FAO's assumption of neutral stability conditions is relaxed, by replacing FAO's aerodynamic resistance by the model's one. Additionally, if the vapour pressure deficit (VPD) is also substituted by either ORCHIDEE's VPD or its humidity gradient, the daily mean estimate is further improved. ETP's sensitivity to climate change is assessed comparing trends in both formulations for the 21st Century. It is found that the USEB method shows a higher sensitivity mainly due to FAO's assumption of neutral stability conditions and to a lesser extent, to the approximation proposed for the VPD. Both FAO's VPD and the model's humidity gradient, as well as ORCHIDEE's aerodynamic resistance have been identified as key parameters in governing ETP trends. Finally, the sensitivity study is extended to 3 empirical approximations based on temperature, net radiation and mass transfer (Hargreaves, Priestley - Taylor and Rohwer, respectively). When compared to the USEB method

  15. Large diurnal temperature range increases bird sensitivity to climate change

    NARCIS (Netherlands)

    Briga, Michael; Verhulst, Simon

    2015-01-01

    Climate variability is changing on multiple temporal scales, and little is known of the consequences of increases in short-term variability, particularly in endotherms. Using mortality data with high temporal resolution of zebra finches living in large outdoor aviaries (5 years, 359.220 bird-days),

  16. Sensitivity of SWAT simulated streamflow to climatic changes within the Eastern Nile River basin

    Science.gov (United States)

    Mengistu, D. T.; Sorteberg, A.

    2012-02-01

    The hydrological model SWAT was run with daily station based precipitation and temperature data for the whole Eastern Nile basin including the three subbasins: the Abbay (Blue Nile), BaroAkobo and Tekeze. The daily and monthly streamflows were calibrated and validated at six outlets with station-based streamflow data in the three different subbasins. The model performed very well in simulating the monthly variability while the validation against daily data revealed a more diverse performance. The simulations indicated that around 60% of the average annual rainfalls of the subbasins were lost through evaporation while the estimated runoff coefficients were 0.24, 0.30 and 0.18 for Abbay, BaroAkobo and Tekeze subbasins, respectively. About half to two-thirds of the runoff could be attributed to surface runoff while the other contributions came from groundwater. Twenty hypothetical climate change scenarios (perturbed temperatures and precipitation) were conducted to test the sensitivity of SWAT simulated annual streamflow. The result revealed that the annual streamflow sensitivity to changes in precipitation and temperature differed among the basins and the dependence of the response on the strength of the changes was not linear. On average the annual streamflow responses to a change in precipitation with no temperature change were 19%, 17%, and 26% per 10% change in precipitation while the average annual streamflow responses to a change in temperature and no precipitation change were -4.4% K-1, -6.4% K-1, and -1.3% K-1 for Abbay, BaroAkobo and Tekeze river basins, respectively. 47 temperature and precipitation scenarios from 19 AOGCMs participating inCMIP3 were used to estimate future changes in streamflow due to climate changes. The climate models disagreed on both the strength and the direction of future precipitation changes. Thus, no clear conclusions could be made about future changes in the Eastern Nile streamflow. However, such types of assessment are important

  17. Corrigendum to "Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM" published in Atmos. Chem. Phys., 12, 5985–6007, 2012

    Directory of Open Access Journals (Sweden)

    K. Peters

    2013-07-01

    Full Text Available An error in the calculation of the emitted number of primary sulfate particles for a given mass of emitted elementary sulfur has recently been identified in HAM, i.e. the aerosol module utilised in the ECHAM-HAM aerosol climate model. Correcting for this error substantially alters the estimates of top-of-atmosphere radiative forcing due to aerosol indirect effects from global shipping emissions (year 2000 as presented in Peters et al. (2012. Here, we shortly present these new results.

  18. Influence of Regional Climate Model spatial resolution on wind climates

    Science.gov (United States)

    Pryor, S. C.; Barthelmie, R. J.; Nikulin, G.; Jones, C.

    2010-12-01

    Global and regional climate models are being run at increasingly fine horizontal and vertical resolution with the goal of increased skill. However, relatively few studies have quantified the change in modeled wind climates that derives from applying a Regional Climate Model (RCM) at varying resolutions, and the response to varying resolution may be highly non-linear since most models run in climate mode are hydrostatic. Thus, herein we examine the influence of grid-resolution on modelled wind speeds and gusts and derived extremes thereof over southern Scandinavia using output from the Rossby Centre (RCA3) RCM run at four different resolutions from 50 x 50 km to 6 x 6 km, and with two different vertical grid-spacings. Domain averaged fifty-year return period wind speeds and wind gusts derived using the method of moments approach to compute the Gumbel parameters, increase with resolution (Table 1), though the change is strongly mediated by the model grid-cell surface characteristics. Power spectra of the 3-hourly model time-step ‘instantaneous’ wind speeds and daily wind gusts at all four resolutions show clear peaks in the variance associated with bi-annual, annual, seasonal and synoptic frequencies. The variance associated with these peaks is enhanced with increased resolution, though not in a monotonic fashion, and is more marked in wind gusts than wind speeds. Relative to in situ observations, the model generally underestimates the variance, particularly associated with the synoptic time scale, even for the highest resolution simulations. There is some evidence to suggest that the change in the power spectra with horizontal resolution is less marked in the transition from 12.5 km to 6.25 km, than from 50 to 25 km, or 25 km to 12.5 km.Table 1. Domain averaged mean annual wind speed (U), 50-year return period extreme wind speed (U50yr) and wind gust (Gust50yr) (m/s) from the four RCA3 simulations at different resolution based on output from 1987-2008. The

  19. Runoff and Evapotranspiration Sensitivities to a Changing Climate in the Western U.S.

    Science.gov (United States)

    Gao, M.; Xiao, M.; Lettenmaier, D. P.

    2017-12-01

    Climate change is likely to alter streamflow seasonal patterns, affect water availability, and otherwise pose challenges to water resources management. It is therefore important to understand how streamflow will respond to changes in climate. Previous studies have mostly focused on runoff sensitivity to precipitation (P) and temperature change, but runoff sensitivity to potential evapotranspiration (PET) is less well understood. In order to investigate how variations in precipitation and PET influence runoff, we conducted both statistical and model-based analyses of 84 near-natural basins in California, Oregon, and Washington. We obtained meteorological forcing data at 1/16 degree spatial resolution for each basin from the University of Washington/UCLA Experimental Surface Water Monitor, and observed runoff data from USGS. For the statistical method, we applied three estimators of the precipitation elasticity of runoff from previous studies. We also estimated the PET elasticity of runoff, using Penman-Monteith reference ET as a surrogate for PET. For the modelling method, we implemented the Sacramento Soil Moisture Accounting (SAC-SMA) Model, where PET is an explicit input. We performed experiments in which we changed P and PET by 1% individually to examine their effects on runoff, from which we computed the P and PET elasticities. We explore the spatial patterns in the elasticities of runoff and their relationships with basin characteristics and climatology. We also evaluate how well the statistical and model-based results meet the complementary relationship posited by Dooge (based on the Budyko Hypothesis) that the precipitation and PET elasticities of annual runoff should sum to one.

  20. Sensitivity of climate change in Europe to the Northern Atlantic warming

    Energy Technology Data Exchange (ETDEWEB)

    Timbal, B.; Mahfouf, J.F.; Royer, J.F. [Centre National de Recherches Meteoroloques, Toulouse (France)

    1995-12-31

    The increase in atmospheric carbon dioxide since the beginning of the industrial revolution has raised the question of its impact on climate. Anthropogenic release of carbon dioxide is an extra source in the complex carbon cycle involving the ocean, the atmosphere and the biosphere. Three-dimensional general circulation models have been used world-wide over the last decade to perform climate research. Complete global change experiments need to couple an atmospheric model with an oceanic one and a thermodynamical and dynamical sea-ice model. Therefore realistic scenarios of greenhouse gas increases can be studied. These computer-time expensive experiments cannot be reproduced as often as necessary. A commonly used approach is to perform time-slice experiments at the equilibrium with an atmospheric GCM forced by Sea Surface Temperature (SST) anomalies. Several sensitivity experiments using higher resolutions or more sophisticated physical parameterisations can be performed. As the resolution increases, one can study the result over special areas of interest, such as Europe

  1. Global precipitation measurements for validating climate models

    Science.gov (United States)

    Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

    2017-11-01

    The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

  2. Sensitivity Analysis of a Physiochemical Interaction Model ...

    African Journals Online (AJOL)

    The mathematical modelling of physiochemical interactions in the framework of industrial and environmental physics usually relies on an initial value problem which is described by a single first order ordinary differential equation. In this analysis, we will study the sensitivity analysis due to a variation of the initial condition ...

  3. Numerical modeling of shock-sensitivity experiments

    Energy Technology Data Exchange (ETDEWEB)

    Bowman, A.L.; Forest, C.A.; Kershner, J.D.; Mader, C.L.; Pimbley, G.H.

    1981-01-01

    The Forest Fire rate model of shock initiation of heterogeneous explosives has been used to study several experiments commonly performed to measure the sensitivity of explosives to shock and to study initiation by explosive-formed jets. The minimum priming charge test, the gap test, the shotgun test, sympathetic detonation, and jet initiation have been modeled numerically using the Forest Fire rate in the reactive hydrodynamic codes SIN and 2DE.

  4. Learning About Climate and Atmospheric Models Through Machine Learning

    Science.gov (United States)

    Lucas, D. D.

    2017-12-01

    From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  5. Stochastic sensitivity analysis of nitrogen pollution to climate change in a river basin with complex pollution sources.

    Science.gov (United States)

    Yang, Xiaoying; Tan, Lit; He, Ruimin; Fu, Guangtao; Ye, Jinyin; Liu, Qun; Wang, Guoqing

    2017-12-01

    It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by - 10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 °C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the sub-daily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of

  6. Climate change in Germany. Vulnerability and adaption of climate sensitive sectors; Klimawandel in Deutschland. Vulnerabilitaet und Anpassungsstrategien klimasensitiver Systeme

    Energy Technology Data Exchange (ETDEWEB)

    Zebisch, Marc; Grothmann, Torsten; Schroeter, Dagmar; Hasse, Clemens; Fritsch, Uta; Cramer, Wolfgang [Potsdam Institut fuer Klimaforschung, Potsdam (Germany)

    2005-08-15

    The objectives of this study were the following: documentation of existing knowledge on global change (and particularly climate change) in Germany and to analysis of its current and potential future impacts on seven climate-sensitive sectors (water management, agriculture, forestry, biodiversity/nature conservation, health, tourism and transport).; the evaluation of the present degree of adaptation and the adaptive capacity of these climate-sensitive sectors to global change; conclusions on the vulnerability to global change of sectors and regions in Germany by considering potential global change impacts, degrees of adaptation and adaptive capacity; and the discussion of the results of the study with decision-makers from government, administration, economy and society, in order to develop a basis for the development of strategies of adaptation to global change in Germany.

  7. Sensitivity of the carbon cycle in the Arctic to climate change

    Science.gov (United States)

    McGuire, A. David; Anderson, Leif G.; Christensen, Torben R.; Dallimore, Scott; Guo, Laodong; Hayes, Daniel J.; Heimann, Martin; Lorenson, T.D.; Macdonald, Robie W.; Roulet, Nigel

    2009-01-01

    The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO2 and CH4. Studies suggest that the Arctic has been a sink for atmospheric CO2 of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH4 to the atmosphere (between 32 and 112 Tg CH4/yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon–climate

  8. Lake heat content and stability variation due to climate change: coupled regional climate model (REMO-lake model (DYRESM analysis

    Directory of Open Access Journals (Sweden)

    Stefan Weinberger

    2014-02-01

    Full Text Available Climate change-derived higher air temperatures and the resulting increase in lake surface temperatures are known to influence the physical, biological and chemical processes of water bodies. By using hydrodynamic lake models coupled with regional climate models the potential future impact of a changing climate can be investigated. The present study hence elucidates limno-physical changes at the peri-Alpine, 83-m deep, currently dimictic Ammersee in southeastern Germany, both to underline the role of lakes as sentinels of climate change and provide a sound basis for further limnological investigations. This was realised by using water temperatures simulated with the hydrodynamic model DYRESM for the period 2041-2050, based on the results of the regional climate model REMO (IPCC A1B emission scenario. Modelling of future heat content resulted in a projected increase in the upper 3 m of the epilimnion from end of March to mid-November, whereas a decrease in future total heat content (January-December of the entire water column was simulated compared to that observed in 1997-2007. Lake thermal stability is projected to be higher in the period 2041-2050 than in 1985-2007. Stratification is expected to occur earlier and to last longer in the future than the pattern observed in 1985-2007. The future mean May-June depth of the thermocline is simulated to be situated above its past average vertical position, whereas an increase of mean thermocline depth is projected for the beginning of August to October. Furthermore, the mean May-October thickness of the metalimnion is simulated to increase. Additionally, we investigated the sensitivity of these limno-physical results to changes in the model parameter light extinction coefficient which determines how the solar radiation is absorbed by the lake water. The elucidation of physical changes at Ammersee by means of a regional climate model provides a sound basis on which to face the new challenges of lake

  9. Selecting, weeding, and weighting biased climate model ensembles

    Science.gov (United States)

    Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.

    2012-12-01

    In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model ensembles with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member ensemble CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the base state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this ensemble to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the ensemble using this knowledge does a relatively poor job of adjusting the ensemble mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model ensembles created by a selection process that does not emphasize the priorities of your log-likelihood.

  10. Climate response to the meltwater runoff from Greenland ice sheet: evolving sensitivity to discharging locations

    Science.gov (United States)

    Liu, Yonggang; Hallberg, Robert; Sergienko, Olga; Samuels, Bonnie L.; Harrison, Matthew; Oppenheimer, Michael

    2017-11-01

    Greenland Ice Sheet (GIS) might have lost a large amount of its volume during the last interglacial and may do so again in the future due to climate warming. In this study, we test whether the climate response to the glacial meltwater is sensitive to its discharging location. Two fully coupled atmosphere-ocean general circulation models, CM2G and CM2M, which have completely different ocean components are employed to do the test. In each experiment, a prescribed freshwater flux of 0.1 Sv is discharged from one of the four locations around Greenland—Petermann, 79 North, Jacobshavn and Helheim glaciers. The results from both models show that the AMOC weakens more when the freshwater is discharged from the northern GIS (Petermann and 79 North) than when it is discharged from the southern GIS (Jacobshavn and Helheim), by 15% (CM2G) and 31% (CM2M) averaged over model year 50-300 (CM2G) and 70-300 (CM2M), respectively. This is due to easier access of the freshwater from northern GIS to the deepwater formation site in the Nordic Seas. In the long term (> 300 year), however, the AMOC change is nearly the same for freshwater discharged from any location of the GIS. The East Greenland current accelerates with time and eventually becomes significantly faster when the freshwater is discharged from the north than from the south. Therefore, freshwater from the north is transported efficiently towards the south first and then circulates back to the Nordic Seas, making its impact to the deepwater formation there similar to the freshwater discharged from the south. The results indicate that the details of the location of meltwater discharge matter if the short-term ( 300 years) climate response is focused upon.

  11. On coupling global biome models with climate models

    International Nuclear Information System (INIS)

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992), which predicts global vegetation patterns in equilibrium with climate, is coupled with the ECHAM climate model of the Max-Planck-Institut fuer Meteorologie, Hamburg. It is found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only between the initial biome distribution and the biome distribution computed after the first simulation period, provided that the climate-biome model is started from a biome distribution that resembles the present-day distribution. After the first simulation period, there is no significant shrinking, expanding, or shifting of biomes. Likewise, no trend is seen in global averages of land-surface parameters and climate variables. (orig.)

  12. Chinese insurance agents in "bad barrels": a multilevel analysis of the relationship between ethical leadership, ethical climate and business ethical sensitivity.

    Science.gov (United States)

    Zhang, Na; Zhang, Jian

    2016-01-01

    The moral hazards and poor public image of the insurance industry, arising from insurance agents' unethical behavior, affect both the normal operation of an insurance company and decrease applicants' confidence in the company. Contrarily, these scandals may demonstrate that the organizations were "bad barrels" in which insurance agents' unethical decisions were supported or encouraged by the organization's leadership or climate. The present study brings two organization-level factors (ethical leadership and ethical climate) together and explores the role of ethical climate on the relationship between the ethical leadership and business ethical sensitivity of Chinese insurance agents. Through the multilevel analysis of 502 insurance agents from 56 organizations, it is found that organizational ethical leadership is positively related to the organizational ethical climate; organizational ethical climate is positively related to business ethical sensitivity, and organizational ethical climate fully mediates the relationship between organizational ethical leadership and business ethical sensitivity. Organizational ethical climate plays a completely mediating role in the relationship between organizational ethical leadership and business ethical sensitivity. The integrated model of ethical leadership, ethical climate and business ethical sensitivity makes several contributions to ethics theory, research and management.

  13. Formulation of an ocean model for global climate simulations

    Directory of Open Access Journals (Sweden)

    S. M. Griffies

    2005-01-01

    Full Text Available This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL climate model used for the 4th IPCC Assessment (AR4 of global climate change. In particular, it reviews the numerical schemes and physical parameterizations that make up an ocean climate model and how these schemes are pieced together for use in a state-of-the-art climate model. Features of the model described here include the following: (1 tripolar grid to resolve the Arctic Ocean without polar filtering, (2 partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3 more accurate equation of state, (4 three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5 incorporation of regional climatological variability in shortwave penetration, (6 neutral physics parameterization for representation of the pathways of tracer transport, (7 staggered time stepping for tracer conservation and numerical efficiency, (8 anisotropic horizontal viscosities for representation of equatorial currents, (9 parameterization of exchange with marginal seas, (10 incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11 transport of water across the ocean free surface to eliminate unphysical ``virtual tracer flux' methods, (12 parameterization of tidal mixing on continental shelves. We also present preliminary analyses of two particularly important sensitivities isolated during the development process, namely the details of how parameterized subgridscale eddies transport momentum and tracers.

  14. Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China.

    Science.gov (United States)

    Hou, Lan-Gong; Zou, Song-Bing; Xiao, Hong-Lang; Yang, Yong-Gang

    2013-01-01

    The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

  15. Sensitivity of the Greenland Ice Sheet to Interglacial Climate Forcing: MIS 5e Versus MIS 11

    Science.gov (United States)

    Rachmayani, Rima; Prange, Matthias; Lunt, Daniel J.; Stone, Emma J.; Schulz, Michael

    2017-11-01

    The Greenland Ice Sheet (GrIS) is thought to have contributed substantially to high global sea levels during the interglacials of Marine Isotope Stage (MIS) 5e and 11. Geological evidence suggests that the mass loss of the GrIS was greater during the peak interglacial of MIS 11 than MIS 5e, despite a weaker boreal summer insolation. We address this conundrum by using the three-dimensional thermomechanical ice sheet model Glimmer forced by Community Climate System Model version 3 output for MIS 5e and MIS 11 interglacial time slices. Our results suggest a stronger sensitivity of the GrIS to MIS 11 climate forcing than to MIS 5e forcing. Besides stronger greenhouse gas radiative forcing, the greater MIS 11 GrIS mass loss relative to MIS 5e is attributed to a larger oceanic heat transport toward high latitudes by a stronger Atlantic meridional overturning circulation. The vigorous MIS 11 ocean overturning, in turn, is related to a stronger wind-driven salt transport from low to high latitudes promoting North Atlantic Deep Water formation. The orbital insolation forcing, which causes the ocean current anomalies, is discussed.

  16. Anticipating the uncertain: economic modeling and climate change policy

    Energy Technology Data Exchange (ETDEWEB)

    Jensen, Svenn

    2012-11-01

    With this thesis I wish to contribute to the understanding of how uncertainty and the anticipation of future events by economic actors affect climate policies. The thesis consists of four papers. Two papers are analytical models which explicitly consider that emissions are caused by extracting scarce fossil fuels which in the future must be replaced by clean technologies. The other two are so called numerical integrated assessment models. Such models represent the world economy, the climate system and the interactions between those two quantitatively, complementing more abstract theoretical work. Should policy makers discriminate between subsidizing renewable energy sources such as wind or solar power, and technologies such as carbon capture and storage (CCS)? Focusing only on the dynamic supply of fossil fuels and hence Co{sub 2}, we find here that cheaper future renewables cause extraction to speed up, lower costs of CCS may delay it. CCS hence may dampen the dynamic inefficiency caused by the absence of comprehensive climate policies today. Does it matter whether uncertainty about future damage assessment is due to scientific complexities or stems from the political process? In paper two, I find that political and scientific uncertainties have opposing effects on the incentives to investment in renewables and the extraction of fossil fuels: The prospect of scientific learning about the climate system increases investment incentives and, ceteris paribus, slows extraction down; uncertainty about future political constellations does the opposite. The optimal carbon tax under scientific uncertainty equals expected marginal damages, whereas political uncertainty demands a tax below marginal damages that decreases over time. Does uncertainty about economic growth impact optimal climate policy today? Here we are the first to consistently analyze how uncertainty about future economic growth affects optimal emission reductions and the optimal social cost of carbon. We

  17. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    Science.gov (United States)

    1997-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

  18. Screening design for model sensitivity studies

    Science.gov (United States)

    Welsh, James P.; Koenig, George G.; Bruce, Dorothy

    1997-07-01

    This paper describes a different approach to sensitivity studies for environmental, including atmospheric, physics models. The sensitivity studies were performed on a multispectral environmental data and scene generation capability. The capability includes environmental physics models that are used to generate data and scenes for simulation of environmental materials, features, and conditions, such as trees, clouds, soils, and snow. These studies were performed because it is difficult to obtain input data for many of the environmental variables. The problem to solve is to determine which of the 100 or so input variables, used by the generation capability, are the most important. These sensitivity studies focused on the generation capabilities needed to predict and evaluate the performance of sensor systems operating in the infrared portions of the electromagnetic spectrum. The sensitivity study approach described uses a screening design. Screening designs are analytical techniques that use a fraction of all of the combinations of the potential input variables and conditions to determine which are the most important. Specifically a 20-run Plackett-Burman screening design was used to study the sensitivity of eight data and scene generation capability computed response variables to 11 selected input variables. This is a two-level design, meaning that the range of conditions is represented by two different values for each of the 11 selected variables. The eight response variables used were maximum, minimum, range, and mode of the model-generated temperature and radiance values. The result is that six of the 11 input variables (soil moisture, solar loading, roughness length, relative humidity, surface albedo, and surface emissivity) had a statistically significant effect on the response variables.

  19. Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing

    Science.gov (United States)

    Samset, B. H.; Myhre, G.; Forster, P. M.; Hodnebrog, O.; Andrews, T.; Boucher, O.; Faluvegi, G.; Flaeschner, D.; Kasoar, M.; Kharin, V.; hide

    2018-01-01

    We present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from ten climate models, we show how modeled global mean precipitation increases by 2-3% per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature-driven (slow) ocean HS of 3-5%/K, while the slow land HS is only 0-2%/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. We identify a particular need for model investigations and observational constraints on convective precipitation in the Arctic, and large-scale precipitation around the Equator.

  20. Sensitivities in global scale modeling of isoprene

    Directory of Open Access Journals (Sweden)

    R. von Kuhlmann

    2004-01-01

    Full Text Available A sensitivity study of the treatment of isoprene and related parameters in 3D atmospheric models was conducted using the global model of tropospheric chemistry MATCH-MPIC. A total of twelve sensitivity scenarios which can be grouped into four thematic categories were performed. These four categories consist of simulations with different chemical mechanisms, different assumptions concerning the deposition characteristics of intermediate products, assumptions concerning the nitrates from the oxidation of isoprene and variations of the source strengths. The largest differences in ozone compared to the reference simulation occured when a different isoprene oxidation scheme was used (up to 30-60% or about 10 nmol/mol. The largest differences in the abundance of peroxyacetylnitrate (PAN were found when the isoprene emission strength was reduced by 50% and in tests with increased or decreased efficiency of the deposition of intermediates. The deposition assumptions were also found to have a significant effect on the upper tropospheric HOx production. Different implicit assumptions about the loss of intermediate products were identified as a major reason for the deviations among the tested isoprene oxidation schemes. The total tropospheric burden of O3 calculated in the sensitivity runs is increased compared to the background methane chemistry by 26±9  Tg( O3 from 273 to an average from the sensitivity runs of 299 Tg(O3. % revised Thus, there is a spread of ± 35% of the overall effect of isoprene in the model among the tested scenarios. This range of uncertainty and the much larger local deviations found in the test runs suggest that the treatment of isoprene in global models can only be seen as a first order estimate at present, and points towards specific processes in need of focused future work.

  1. Applying incentive sensitization models to behavioral addiction

    DEFF Research Database (Denmark)

    Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne

    2014-01-01

    The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...... symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment....

  2. Precipitates/Salts Model Sensitivity Calculation

    International Nuclear Information System (INIS)

    Mariner, P.

    2001-01-01

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO 2 ) on the chemical evolution of water in the drift

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

    Science.gov (United States)

    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.

  4. VEMAP vs VINCERA: a DGVM sensitivity to differences in climate scenarios

    Science.gov (United States)

    Dominique Bachelet; James Lenihan; Ray Drapek; Ronald. Neilson

    2008-01-01

    The MCI DGVM has been used in two international model comparison projects, VEMAP (Vegetation Ecosystem Modeling and Analysis Project) and VINCERA (Vulnerability and Impacts of North American forests to Climate Change: Ecosystem Responses and Adaptation). The latest version of MC1 was run on both VINCERA and VEMAP climate and soil input data to document how a change in...

  5. Assessing the sensitivity of avian species abundance to land cover and climate

    Science.gov (United States)

    LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.

    2016-01-01

    Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

  6. Improved Analysis of Earth System Models and Observations using Simple Climate Models

    Science.gov (United States)

    Nadiga, B. T.; Urban, N. M.

    2016-12-01

    Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using

  7. Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

    Science.gov (United States)

    Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

    2015-01-15

    Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014

  8. Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size

    Science.gov (United States)

    Kiehl, J. T.

    1994-01-01

    Extensive observations indicate a distinct difference between maritime and continental effective drop size, r(sub e), for warm clouds. The latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2) is used to explore the sensitivity of differentiating between continental and maritime r(sub e) on the simulated climate. The results of this study indicate that the smaller drop size over continents leads to a reduction of surface-absorbed solar radiation from 20 to 60 W/sq m. This reduction in surface solar flux leads to a cooling of the continents by up to -3.5 K. The reduction in surface solar flux and temperature also leads to a reduction in latent heat flux and precipitation over land. In the January simulation, there is a significant shift in tropical precipitation associated with the Australian monsoon. This shift leads to a response in the extra tropical geopotential height field over the western United States. All of these changes reduce biases in the current version of CCM2.

  9. Improved Analysis of Earth System Models and Observations using Simple Climate Models

    Science.gov (United States)

    Nadiga, Balasubramanya; Urban, Nathan

    2017-04-01

    First-principles-based Earth System Models (ESMs) are central to both improving our understanding of the climate system and developing climate projections. Nevertheless, given the diversity of climate simulated by the various ESMs and the intense computational burden associated with running such models, simple climate models (SCMs) are key to being able to compare ESMs and the climates they simulate in a dynamically meaningful fashion. We present some preliminary work along these lines. In an application of an SCM to compare different ESMs and observations, we demonstrate a deficiency in the commonly-used upwelling-diffusion (UD) energy balance model (EBM). When we consider the vertical distribution of ocean heat uptake, the lack of representation of processes such as deep water formation and subduction in the UD-EBM precludes a reasonable representation of the vertical distribution of heat uptake in that model. We then demonstrate how the problem can be remedied by introducing a parameterization of such processes in the UD-EBM. With further development, it is anticipated that this approach of ESM inter-comparison using simple physics-based models will lead to further insights into aspects of the climate response such as its stability and sensitivity, uncertainty and predictability, and underlying flow structure and topology.

  10. Climate impact of transportation A model comparison

    NARCIS (Netherlands)

    Girod, B.; Vuuren, D.P. van; Grahn, M.; Kitous, A.; Kim, S.H.; Kyle, P.

    2013-01-01

    Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global

  11. Modelling the wind climate of Ireland

    DEFF Research Database (Denmark)

    Frank, H.P.; Landberg, L.

    1997-01-01

    The wind climate of Ireland has been calculated using the Karlsruhe Atmospheric Mesoscale Model KAMM. The climatology is represented by 65 frequency classes of geostrophic wind that were selected as equiangular direction sectors and speed intervals with equal frequency in a sector. The results ar...

  12. Global comparison of three greenhouse climate models

    NARCIS (Netherlands)

    Bavel, van C.H.M.; Takakura, T.; Bot, G.P.A.

    1985-01-01

    Three dynamic simulation models for calculating the greenhouse climate and its energy requirements for both heating and cooling were compared by making detailed computations for each of seven sets of data. The data sets ranged from a cold winter day, requiring heating, to a hot summer day, requiring

  13. Large diurnal temperature range increases bird sensitivity to climate change.

    Science.gov (United States)

    Briga, Michael; Verhulst, Simon

    2015-11-13

    Climate variability is changing on multiple temporal scales, and little is known of the consequences of increases in short-term variability, particularly in endotherms. Using mortality data with high temporal resolution of zebra finches living in large outdoor aviaries (5 years, 359.220 bird-days), we show that mortality rate increases almost two-fold per 1°C increase in diurnal temperature range (DTR). Interestingly, the DTR effect differed between two groups with low versus high experimentally manipulated foraging costs, reflecting a typical laboratory 'easy' foraging environment and a 'hard' semi-natural environment respectively. DTR increased mortality on days with low minimum temperature in the easy foraging environment, but on days with high minimum temperature in the semi-natural environment. Thus, in a natural environment DTR effects will become increasingly important in a warming world, something not detectable in an 'easy' laboratory environment. These effects were particularly apparent at young ages. Critical time window analyses showed that the effect of DTR on mortality is delayed up to three months, while effects of minimum temperature occurred within a week. These results show that daily temperature variability can substantially impact the population viability of endothermic species.

  14. Sensitivity of the climate simulations to update of Plant Functional Type distributions

    Science.gov (United States)

    Georgievski, Goran; Hagemann, Stefan; Khlystova, Iryna

    2015-04-01

    In the frame of the European Space Agency (ESA) Climate Change Initiative (CCI), a new global land cover (LC) data set is produced. Land cover is classified as one of Essential Climate Variables (ECV), and defined as the physical material at the surface of the earth (for example: trees, grass, bare soil, water). The ESA-CCI-LC product complies with the United Nations Land Cover Classification Scheme (UNLCCS). However, the UNLCCS set of rules is not suitable for climate modelling. Therefore, ESA-CCI-LC categorical classes need to be converted to model specific plant functional types (PFT) distributions. Here we present a conversion method of ESA-CCI-LC classes to PFT fractions and the impact of the new PFT distributions to climate simulations using the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and its land surface component (JSBACH). The main features of the updated PFT distributions are less trees and more herbaceous types. We conducted SST driven climate simulations with MPI-ESM and offline JSBACH simulations driven by WATCH forcing data based on ERA-Interim (WFDEI) at T63 resolution. These simulations are evaluated for the 1981-2010 period. Sensitivities of the hydrological, energy and carbon cycles are investigated. The following variables are compared between simulations with the new ESA-CCI-LC and the old reference PFT distributions: (i) evapotranspiration and runoff as an indicator of changes in hydrological cycle, (ii) temperature and albedo as an indicator of energy cycle and (iii) gross primary production (GPP) as an indicator of carbon cycle sensitivity. First results indicate increased annual mean albedo in northern extra tropical latitudes and therefore cooling at those latitudes. Furthermore, the annual cycle of albedo is in better agreement with satellite observation (GLOBALBEDO-DHR and GLOBALBEDO-BHR). GPP is slightly decreased in the annual mean, while evapotranspiration shows slight increase in southern tropical latitudes

  15. Study of tropical clouds feedback to a climate warming as simulated by climate models

    International Nuclear Information System (INIS)

    Brient, Florent

    2012-01-01

    The last IPCC report affirms the predominant role of low cloud-radiative feedbacks in the inter-model spread of climate sensitivity. Understanding the mechanisms that control the behavior of low-level clouds is thus crucial. However, the complexity of coupled ocean-atmosphere models and the large number of processes potentially involved make the analysis of this response difficult. To simplify the analysis and to identify the most critical controls of cloud feedbacks, we analyze the cloud response to climate change simulated by the IPSL-CM5A model in a hierarchy of configurations. A comparison between three model configurations (coupled, atmospheric and aqua-planet) using the same physical parametrizations shows that the cloud response to global warming is dominated by a decrease of low clouds in regimes of moderate subsidence. Using a Single Column Model, forced by weak subsidence large-scale forcing, allows us to reproduce the vertical cloud profile predicted in the 3D model, as well as its response to climate change (if a stochastic forcing is added on vertical velocity). We analyze the sensitivity of this low-cloud response to external forcing and also to uncertain parameters of physical parameterizations involved on the atmospheric model. Through a moist static energy (MSE) budget, we highlight several mechanisms: (1) Robust: Over weak subsidence regimes, the Clausius-Clapeyron relationship predicts that a warmer atmosphere leads to a increase of the vertical MSE gradient, resulting on a strengthening of the import of low-MSE from the free atmosphere into the cloudy boundary layer. The MSE budget links changes of vertical advection and cloud radiative effects. (2) Physics Model Dependent: The coupling between shallow convection, turbulence and cloud schemes allows the intensification of low-MSE transport so that cloud radiative cooling becomes 'less necessary' to balance the energy budget (Robust positive low cloud-radiative feedback for the model). The

  16. The climate impact of energy peat utilisation - comparison and sensitivity analysis of Finnish and Swedish results

    Energy Technology Data Exchange (ETDEWEB)

    Holmgren, Kristina; Kirkinen, Johanna; Savolainen, Ilkka

    2006-06-15

    The climate impact of energy peat utilisation have been studied both in Finland by VTT Technical Research Centre and in Sweden by IVL Swedish Environmental Research Institute Ltd. The main objective of this study is to compare the results of earlier studies by VTT and IVL and to perform a sensitivity analysis of previous and new results. The scientific approach of the two studies is very similar. The climate impact of peat utilisation is considered from a life-cycle point of view by taking into account all phases of the peat utilisation chain. Peat reserves can be both sinks and sources of greenhouse gas emissions as well as there are both uptake and emissions of greenhouse gases during the utilisation chain. The net impact of the utilisation chain is assessed as the climate impact due to the utilisation chain minus the climate impact of non-utilisation chain. The instantaneous radiative forcing and accumulated radiative forcing are used in both studies as the indicator of the climate impact. Radiative forcing is calculated on the basis of the concentration changes due to emissions and uptake of greenhouse gases. The differences in the models for calculating concentrations and radiative forcing are minor. There are some differences in the definitions and boundaries of the considered peat utilisation chains, although the differences in the results due to differences in the chain definitions are small. The main reason for the differences in results between the two studies is differences in emission (and uptake) estimates for the after-treatment phase and the non-utilisation chain. Both Swedish and Finnish studies show that the use of cultivated peatland for energy peat utilisation results in lower climate impact than using coal (within 100 years). Both studies show that the use of pristine mires for peat production will result in larger climate impact than the use of already drained peatlands. The climate impact of peat utilisation chains where fens and forestry

  17. The climate impact of energy peat utilisation - comparison and sensitivity analysis of Finnish and Swedish results

    International Nuclear Information System (INIS)

    Holmgren, Kristina; Kirkinen, Johanna; Savolainen, Ilkka

    2006-06-01

    The climate impact of energy peat utilisation have been studied both in Finland by VTT Technical Research Centre and in Sweden by IVL Swedish Environmental Research Institute Ltd. The main objective of this study is to compare the results of earlier studies by VTT and IVL and to perform a sensitivity analysis of previous and new results. The scientific approach of the two studies is very similar. The climate impact of peat utilisation is considered from a life-cycle point of view by taking into account all phases of the peat utilisation chain. Peat reserves can be both sinks and sources of greenhouse gas emissions as well as there are both uptake and emissions of greenhouse gases during the utilisation chain. The net impact of the utilisation chain is assessed as the climate impact due to the utilisation chain minus the climate impact of non-utilisation chain. The instantaneous radiative forcing and accumulated radiative forcing are used in both studies as the indicator of the climate impact. Radiative forcing is calculated on the basis of the concentration changes due to emissions and uptake of greenhouse gases. The differences in the models for calculating concentrations and radiative forcing are minor. There are some differences in the definitions and boundaries of the considered peat utilisation chains, although the differences in the results due to differences in the chain definitions are small. The main reason for the differences in results between the two studies is differences in emission (and uptake) estimates for the after-treatment phase and the non-utilisation chain. Both Swedish and Finnish studies show that the use of cultivated peatland for energy peat utilisation results in lower climate impact than using coal (within 100 years). Both studies show that the use of pristine mires for peat production will result in larger climate impact than the use of already drained peatlands. The climate impact of peat utilisation chains where fens and forestry

  18. Conceptual modelling of evapotranspiration for simulations of climate change effects

    Energy Technology Data Exchange (ETDEWEB)

    Lindstroem, G.; Gardelin, M.; Persson, Magnus

    1994-09-01

    The evapotranspiration routines in existing conceptual hydrological models have been identified as one of the weaknesses which appear when these models are used for the simulation of hydrological effects of a changing climate. The hydrological models in operational use today usually have a very superficial description of evapotranspiration. They have, nevertheless, been able to yield reasonable results. The objective of this paper is to analyse and suggest modifications of existing evapotranspiration routines in conceptual hydrological models to make them more appropriate for use in simulation of the effects of a changing climate on water resources. The following modifications of the evapotranspiration routine were formulated and tested in the HBV model: Temperature anomaly correction of evapotranspiration, potential evapotranspiration by a simplified Thornthwaite type formula, interception submodel, spatially distributed evapotranspiration routine and alternative formulations of lake evapotranspiration. Sensitivity analyses were thereafter made to illustrate the effects of uncertainty in the hydrological model structure versus those of the uncertainty in the climate change predictions. 34 refs, 15 figs, 6 tabs

  19. Aerosols and clouds in chemical transport models and climate models.

    Energy Technology Data Exchange (ETDEWEB)

    Lohmann,U.; Schwartz, S. E.

    2008-03-02

    Clouds exert major influences on both shortwave and longwave radiation as well as on the hydrological cycle. Accurate representation of clouds in climate models is a major unsolved problem because of high sensitivity of radiation and hydrology to cloud properties and processes, incomplete understanding of these processes, and the wide range of length scales over which these processes occur. Small changes in the amount, altitude, physical thickness, and/or microphysical properties of clouds due to human influences can exert changes in Earth's radiation budget that are comparable to the radiative forcing by anthropogenic greenhouse gases, thus either partly offsetting or enhancing the warming due to these gases. Because clouds form on aerosol particles, changes in the amount and/or composition of aerosols affect clouds in a variety of ways. The forcing of the radiation balance due to aerosol-cloud interactions (indirect aerosol effect) has large uncertainties because a variety of important processes are not well understood precluding their accurate representation in models.

  20. Modeling the climatic response to orbital variations.

    Science.gov (United States)

    Imbrie, J; Imbrie, J Z

    1980-02-29

    According to the astronomical theory of climate, variations in the earth's orbit are the fundamental cause of the succession of Pleistocene ice ages. This article summarizes how the theory has evolved since the pioneer studies of James Croll and Milutin Milankovitch, reviews recent evidence that supports the theory, and argues that a major opportunity is at hand to investigate the physical mechanisms by which the climate system responds to orbital forcing. After a survey of the kinds of models that have been applied to this problem, a strategy is suggested for building simple, physically motivated models, and a time-dependent model is developed that simulates the history of planetary glaciation for the past 500,000 years. Ignoring anthropogenic and other possible sources of variation acting at frequencies higher than one cycle per 19,000 years, this model predicts that the long-term cooling trend which began some 6000 years ago will continue for the next 23,000 years.

  1. Photovoltaic System Modeling. Uncertainty and Sensitivity Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, Clifford W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Martin, Curtis E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-08-01

    We report an uncertainty and sensitivity analysis for modeling AC energy from ph otovoltaic systems . Output from a PV system is predicted by a sequence of models. We quantify u ncertainty i n the output of each model using empirical distribution s of each model's residuals. We propagate uncertainty through the sequence of models by sampli ng these distributions to obtain a n empirical distribution of a PV system's output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane - of - array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power ; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power . O ur analysis consider s a notional PV system com prising an array of FirstSolar FS - 387 modules and a 250 kW AC inverter ; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV syste m output to be relatively small, on the order of 1% for daily energy. We found that unce rtainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.

  2. Modeling climate and fuel reduction impacts on mixed-conifer forest carbon stocks in the Sierra Nevada, California

    Science.gov (United States)

    Matthew D. Hurteau; Timothy A. Robards; Donald Stevens; David Saah; Malcolm North; George W. Koch

    2014-01-01

    Quantifying the impacts of changing climatic conditions on forest growth is integral to estimating future forest carbon balance. We used a growth-and-yield model, modified for climate sensitivity, to quantify the effects of altered climate on mixed-conifer forest growth in the Lake Tahoe Basin, California. Estimates of forest growth and live tree carbon stocks were...

  3. Objectively combining AR5 instrumental period and paleoclimate climate sensitivity evidence

    Science.gov (United States)

    Lewis, Nicholas; Grünwald, Peter

    2017-06-01

    Combining instrumental period evidence regarding equilibrium climate sensitivity with largely independent paleoclimate proxy evidence should enable a more constrained sensitivity estimate to be obtained. Previous, subjective Bayesian approaches involved selection of a prior probability distribution reflecting the investigators' beliefs about climate sensitivity. Here a recently developed approach employing two different statistical methods—objective Bayesian and frequentist likelihood-ratio—is used to combine instrumental period and paleoclimate evidence based on data presented and assessments made in the IPCC Fifth Assessment Report. Probabilistic estimates from each source of evidence are represented by posterior probability density functions (PDFs) of physically-appropriate form that can be uniquely factored into a likelihood function and a noninformative prior distribution. The three-parameter form is shown accurately to fit a wide range of estimated climate sensitivity PDFs. The likelihood functions relating to the probabilistic estimates from the two sources are multiplicatively combined and a prior is derived that is noninformative for inference from the combined evidence. A posterior PDF that incorporates the evidence from both sources is produced using a single-step approach, which avoids the order-dependency that would arise if Bayesian updating were used. Results are compared with an alternative approach using the frequentist signed root likelihood ratio method. Results from these two methods are effectively identical, and provide a 5-95% range for climate sensitivity of 1.1-4.05 K (median 1.87 K).

  4. Objectively combining AR5 instrumental period and paleoclimate climate sensitivity evidence

    Science.gov (United States)

    Lewis, Nicholas; Grünwald, Peter

    2018-03-01

    Combining instrumental period evidence regarding equilibrium climate sensitivity with largely independent paleoclimate proxy evidence should enable a more constrained sensitivity estimate to be obtained. Previous, subjective Bayesian approaches involved selection of a prior probability distribution reflecting the investigators' beliefs about climate sensitivity. Here a recently developed approach employing two different statistical methods—objective Bayesian and frequentist likelihood-ratio—is used to combine instrumental period and paleoclimate evidence based on data presented and assessments made in the IPCC Fifth Assessment Report. Probabilistic estimates from each source of evidence are represented by posterior probability density functions (PDFs) of physically-appropriate form that can be uniquely factored into a likelihood function and a noninformative prior distribution. The three-parameter form is shown accurately to fit a wide range of estimated climate sensitivity PDFs. The likelihood functions relating to the probabilistic estimates from the two sources are multiplicatively combined and a prior is derived that is noninformative for inference from the combined evidence. A posterior PDF that incorporates the evidence from both sources is produced using a single-step approach, which avoids the order-dependency that would arise if Bayesian updating were used. Results are compared with an alternative approach using the frequentist signed root likelihood ratio method. Results from these two methods are effectively identical, and provide a 5-95% range for climate sensitivity of 1.1-4.05 K (median 1.87 K).

  5. The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity: OCEAN'S ACTIVE ROLE

    Energy Technology Data Exchange (ETDEWEB)

    Garuba, Oluwayemi A. [Pacific Northwest National Laboratory, Richland WA USA; Lu, Jian [Pacific Northwest National Laboratory, Richland WA USA; Liu, Fukai [Physical Oceanography Laboratory/CIMST, Ocean University of China and National Laboratory for Marine Science and Technology, Qinqdao China; Singh, Hansi A. [Pacific Northwest National Laboratory, Richland WA USA

    2018-01-08

    Transient climate sensitivity has been shown to be influenced by the changing pattern of SST and Ocean Heat Uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully-coupled CO2-quadrupling CESM simulation against a partially-coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is the main factor responsible for the reduced transient climate sensitivity and weaker surface warming response in the fully-coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO2 forcing in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the non-unitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully-and partially-coupled responses.

  6. A Practical Philosophy of Complex Climate Modelling

    Science.gov (United States)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

  7. Climate Modeling Computing Needs Assessment

    Science.gov (United States)

    Petraska, K. E.; McCabe, J. D.

    2011-12-01

    This paper discusses early findings of an assessment of computing needs for NASA science, engineering and flight communities. The purpose of this assessment is to document a comprehensive set of computing needs that will allow us to better evaluate whether our computing assets are adequately structured to meet evolving demand. The early results are interesting, already pointing out improvements we can make today to get more out of the computing capacity we have, as well as potential game changing innovations for the future in how we apply information technology to science computing. Our objective is to learn how to leverage our resources in the best way possible to do more science for less money. Our approach in this assessment is threefold: Development of use case studies for science workflows; Creating a taxonomy and structure for describing science computing requirements; and characterizing agency computing, analysis, and visualization resources. As projects evolve, science data sets increase in a number of ways: in size, scope, timelines, complexity, and fidelity. Generating, processing, moving, and analyzing these data sets places distinct and discernable requirements on underlying computing, analysis, storage, and visualization systems. The initial focus group for this assessment is the Earth Science modeling community within NASA's Science Mission Directorate (SMD). As the assessment evolves, this focus will expand to other science communities across the agency. We will discuss our use cases, our framework for requirements and our characterizations, as well as our interview process, what we learned and how we plan to improve our materials after using them in the first round of interviews in the Earth Science Modeling community. We will describe our plans for how to expand this assessment, first into the Earth Science data analysis and remote sensing communities, and then throughout the full community of science, engineering and flight at NASA.

  8. Modelling middle pliocene warm climates of the USA

    Science.gov (United States)

    Haywood, A.M.; Valdes, P.J.; Sellwood, B.W.; Kaplan, J.O.; Dowsett, H.J.

    2001-01-01

    The middle Pliocene warm period represents a unique time slice in which to model and understand climatic processes operating under a warm climatic regime. Palaeoclimatic model simulations, focussed on the United States of America (USA), for the middle Pliocene (ca 3 Ma) were generated using the USGS PRISM2 2?? ?? 2?? data set of boundary conditions and the UK Meteorological Office's HadAMS General Circulation Model (GCM). Model results suggest that conditions in the USA during the middle Pliocene can be characterised as annually warmer (by 2?? to 4??C), less seasonal, wetter (by a maximum of 4 to 8 mm/day) and with an absence of freezing winters over the central and southern Great Plains. A sensitivity experiment suggests that the main forcing mechanisms for surface temperature changes in near coastal areas are the imposed Pliocene sea surface temperatures (SST's). In interior regions, reduced Northern Hemisphere terrestrial ice, combined with less snow cover and a reduction in the elevation of the western cordillera of North America, generate atmospheric circulation changes and positive albedo feedbacks that raise surface temperatures. A complex set of climatic feedback mechanisms cause an enhancement of the hydrological cycle magnifying the moisture bearing westerly wind belt during the winter season (Dec., Jan., Feb.). Predictions produced by the model are in broad agreement with available geological evidence. However, the GCM appears to underestimate precipitation levels in the interior and central regions of the southern USA. Copyright: Palaeontological Association, 22 June 2001.

  9. Sensitivity Study of Stochastic Walking Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2010-01-01

    is to employ a stochastic load model accounting for mean values and standard deviations for the walking load parameters, and to use this as a basis for estimation of structural response. This, however, requires decisions to be made in terms of statistical istributions and their parameters, and the paper...... investigates whether statistical distributions of bridge response are sensitive to some of the decisions made by the engineer doing the analyses. For the paper a selected part of potential influences are examined and footbridge responses are extracted using Monte-Carlo simulations and focus is on estimating...

  10. Applying incentive sensitization models to behavioral addiction.

    Science.gov (United States)

    Rømer Thomsen, Kristine; Fjorback, Lone O; Møller, Arne; Lou, Hans C

    2014-09-01

    The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. High resolution experiments with the ALADIN-Climate regional climate model

    Science.gov (United States)

    Csima, G.

    2009-09-01

    The global climate models are able to describe the climate of the Earth at a rather coarse resolution providing realistic projections only for the synoptic scale characteristics of the climate. For this reason, they are insufficient for detailed regional or local scale estimations. However, impact studies and policy makers need simulations including all the effects caused by local features. Consequently, techniques for downscaling global climate model simulations - such as regional climate modelling - are essential. The ALADIN-Climate regional climate model (developed by Météo France on the basis of the internationally developed ALADIN modelling system) was adapted at the Hungarian Meteorological Service a few years ago. In the framework of the CECILIA project (www.cecilia-eu.org), the ALADIN-Climate regional climate model runs at high (10 km) horizontal resolution. Therefore, it is anticipated to give more realistic climate estimation for this century than either the global models or the lower resolution regional climate models. The ALADIN-Climate model was coupled to both ERA-40 re-analysis data and the ARPEGE/OPA global atmosphere-ocean general circulation model for the past - 1961-1990 - as the reference period. For the future time slices of 2021-2050 and 2071-2100, the lateral boundary conditions were provided by the same global model with the use of A1B SRES scenario. The results have been validated against different observational datasets for the past, and have been compared to the results of the ARPEGE-Climat global model in order to expose the added value of the regional climate model. The ALADIN-Climate model has also been evaluated for the future to give an estimation of climate change in the Carpathian Basin.

  12. Climate simulations for the last interglacial period by means of climate models of different complexity

    Energy Technology Data Exchange (ETDEWEB)

    Montoya, M.L. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    1999-07-01

    Climatic conditions during the lst interglacial (125,000 years before present) are investigated with two climate models of different complexity: The atmosphere-ocean general circulation model ECHAM-1/LSG and the climate system model of intermediate complexity CLIMBER-2. In particular the role of vegetation at the last interglacial maximum, and its importance for a consistent simulation of the Mid-Holocene climate, has been investigated (EU project ASPEN: Air-Sea Wave Processes in Climate Change Models). Comparison of the results of the two models reveals a broad agreement in most large-scale features. Nevertheless, discrepancies are also detected. Essentially, the models differ in their ocean circulation responses. Profiting of the fast turnaround time of CLIMBER-2, a number of sensitivity experiments have been performed to try to explain the possible reasons for these differences, and to analyze additional effects not included in the previous simulations. In particular, the role of vegetation at the last interglacial maximum has been investigated. Comparison of the simulated responses against CLIMAP reconstructed SSTs for Marine Isotope Stage 5e shows a satisfactory agreement within the data uncertainties. (orig.) [German] Die klimatischen Bedingungen waehrend der letzten interglazialen Periode (vor 125 000 Jahren) werden anhand zweier Klimamodelle unterschiedlicher Komplexitaet untersucht: Dem Ozean-Atmosphaere gekoppelten allgemeinen Zirkulationsmodell ECHAM-1/LSG und dem Klimasystemmodell mittlerer Komplexitaet CLIMBER-2. Inbesondere wurde die Rolle der Vegetation in der letzten interglazialen Periode und ihre Bedeutung fuer eine konsistente Simulation des mittelholozaenischen Klimas untersucht (EU-Projekt ASPEN: Air-Sea Wave Processes in Climate Change Models - 'Klimavariationen in historischen Zeiten'). Der Vergleich der Ergebnisse beider Modelle zeigt eine gute Uebereinstimmung der meisten der grossskaligen Eigenschaften, allerdings zeigen sich

  13. Climate models with delay differential equations

    Science.gov (United States)

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  14. Possible role of climate changes in variations in pollen seasons and allergic sensitizations during 27 years.

    Science.gov (United States)

    Ariano, Renato; Canonica, Giorgio Walter; Passalacqua, Giovanni

    2010-03-01

    Climate changes may affect the quality and amount of airborne allergenic pollens. The direct assessment of such an effect requires long observation periods and a restricted geographic area. To assess variations in pollens and allergic sensitizations across 27 years in relation to climate change in a specific region. We recorded pollen counts, season durations, and prevalences of sensitizations for 5 major pollens (birch, cypress, olive, grass, and Parietaria) in western Liguria between 1981 and 2007. Pollen counts were performed using a Hirst-type trap, and sensitizations were assessed by means of skin prick testing. Meteorologic data for the same period included average temperatures, direct radiation, humidity, number of sunny days, and rainfall. There was a progressive increase in the duration of the pollen seasons for Parietaria (+85 days), olive (+18 days), and cypress (+18 days), with an overall advance of their start dates. For Parietaria, there was an advance of 2 months in 2006 vs 1981. Also, the total pollen load progressively increased for the considered species (approximately 25% on average) except for grasses. Percentages of patients sensitized to the pollens increased throughout the years, whereas the percentage of individuals sensitized to house dust mite remained stable. These behaviors paralleled the constant increase in direct radiation, temperature, and number of days with a temperature greater than 30 degrees C. The progressive climate changes, with increased temperatures, may modify the global pollen load and affect the rate of allergic sensitization across long periods.

  15. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

    Sloth Madsen, M; Fox Maule, C; MacKellar, N

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

  16. Handling Uncertainty in Palaeo-Climate Models and Data

    Science.gov (United States)

    Voss, J.; Haywood, A. M.; Dolan, A. M.; Domingo, D.

    2017-12-01

    The study of palaeoclimates can provide data on the behaviour of the Earth system with boundary conditions different from the ones we observe in the present. One of the main challenges in this approach is that data on past climates comes with large uncertainties, since quantities of interest cannot be observed directly, but must be derived from proxies instead. We consider proxy-derived data from the Pliocene (around 3 millions years ago; the last interval in Earth history when CO2 was at modern or near future levels) and contrast this data to the output of complex climate models. In order to perform a meaningful data-model comparison, uncertainties must be taken into account. In this context, we discuss two examples of complex data-model comparison problems. Both examples have in common that they involve fitting a statistical model to describe how the output of the climate simulations depends on various model parameters, including atmospheric CO2 concentration and orbital parameters (obliquity, excentricity, and precession). This introduces additional uncertainties, but allows to explore a much larger range of model parameters than would be feasible by only relying on simulation runs. The first example shows how Gaussian process emulators can be used to perform data-model comparison when simulation runs only differ in the choice of orbital parameters, but temperature data is given in the (somewhat inconvenient) form of "warm peak averages". The second example shows how a simpler approach, based on linear regression, can be used to analyse a more complex problem where we use a larger and more varied ensemble of climate simulations with the aim to estimate Earth System Sensitivity.

  17. Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

    Science.gov (United States)

    Haywood, A. M.; Hill, D.J.; Dolan, A. M.; Otto-Bliesner, B. L.; Bragg, F.; Chan, W.-L.; Chandler, M. A.; Contoux, C.; Dowsett, H. J.; Jost, A.; hide

    2013-01-01

    Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied.Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-mode data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

  18. Supercomputing for weather and climate modelling: convenience or necessity

    CSIR Research Space (South Africa)

    Landman, WA

    2009-12-01

    Full Text Available Weather and climate modelling require dedicated computer infrastructure in order to generate high-resolution, large ensemble, various models with different configurations, etc. in order to optimise operational forecasts and climate projections. High...

  19. Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

    Science.gov (United States)

    Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

    2018-01-01

    Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

  20. Tree Rings in the Tropics: Insights into the Ecology and Climate Sensitivity of Tropical Trees

    NARCIS (Netherlands)

    Brienen, R.J.W.; Schöngart, J.; Zuidema, P.A.

    2016-01-01

    Tree-ring studies provide important contributions to understanding the climate sensitivity of tropical trees and the effects of global change on tropical forests. This chapter reviews recent advances in tropical tree-ring research. In tropical lowlands, tree ring formation is mainly driven by

  1. Can feedback analysis be used to uncover the physical origin of climate sensitivity and efficacy differences?

    Science.gov (United States)

    Rieger, Vanessa S.; Dietmüller, Simone; Ponater, Michael

    2017-10-01

    Different strengths and types of radiative forcings cause variations in the climate sensitivities and efficacies. To relate these changes to their physical origin, this study tests whether a feedback analysis is a suitable approach. For this end, we apply the partial radiative perturbation method. Combining the forward and backward calculation turns out to be indispensable to ensure the additivity of feedbacks and to yield a closed forcing-feedback-balance at top of the atmosphere. For a set of CO2-forced simulations, the climate sensitivity changes with increasing forcing. The albedo, cloud and combined water vapour and lapse rate feedback are found to be responsible for the variations in the climate sensitivity. An O3-forced simulation (induced by enhanced NOx and CO surface emissions) causes a smaller efficacy than a CO2-forced simulation with a similar magnitude of forcing. We find that the Planck, albedo and most likely the cloud feedback are responsible for this effect. Reducing the radiative forcing impedes the statistical separability of feedbacks. We additionally discuss formal inconsistencies between the common ways of comparing climate sensitivities and feedbacks. Moreover, methodical recommendations for future work are given.

  2. A method for climate and vegetation reconstruction through the inversion of a dynamic vegetation model

    Energy Technology Data Exchange (ETDEWEB)

    Garreta, Vincent; Guiot, Joel; Hely, Christelle [CEREGE, UMR 6635, CNRS, Universite Aix-Marseille, Europole de l' Arbois, Aix-en-Provence (France); Miller, Paul A.; Sykes, Martin T. [Lund University, Department of Physical Geography and Ecosystems Analysis, Geobiosphere Science Centre, Lund (Sweden); Brewer, Simon [Universite de Liege, Institut d' Astrophysique et de Geophysique, Liege (Belgium); Litt, Thomas [University of Bonn, Paleontological Institute, Bonn (Germany)

    2010-08-15

    Climate reconstructions from data sensitive to past climates provide estimates of what these climates were like. Comparing these reconstructions with simulations from climate models allows to validate the models used for future climate prediction. It has been shown that for fossil pollen data, gaining estimates by inverting a vegetation model allows inclusion of past changes in carbon dioxide values. As a new generation of dynamic vegetation model is available we have developed an inversion method for one model, LPJ-GUESS. When this novel method is used with high-resolution sediment it allows us to bypass the classic assumptions of (1) climate and pollen independence between samples and (2) equilibrium between the vegetation, represented as pollen, and climate. Our dynamic inversion method is based on a statistical model to describe the links among climate, simulated vegetation and pollen samples. The inversion is realised thanks to a particle filter algorithm. We perform a validation on 30 modern European sites and then apply the method to the sediment core of Meerfelder Maar (Germany), which covers the Holocene at a temporal resolution of approximately one sample per 30 years. We demonstrate that reconstructed temperatures are constrained. The reconstructed precipitation is less well constrained, due to the dimension considered (one precipitation by season), and the low sensitivity of LPJ-GUESS to precipitation changes. (orig.)

  3. Natural climate variability in a coupled model

    International Nuclear Information System (INIS)

    Zebiak, S.E.; Cane, M.A.

    1990-01-01

    Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions

  4. OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

    Science.gov (United States)

    Erickson, T. A.; Koziol, B. W.; Rood, R. B.

    2011-12-01

    The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

  5. A State-Dependent Quantification of Climate Sensitivity Based on Paleodata of the Last 2.1 Million Years

    Science.gov (United States)

    Köhler, Peter; Stap, Lennert B.; von der Heydt, Anna S.; de Boer, Bas; van de Wal, Roderik S. W.; Bloch-Johnson, J.

    2017-11-01

    The evidence from both data and models indicates that specific equilibrium climate sensitivity S[X]—the global annual mean surface temperature change (ΔTg) as a response to a change in radiative forcing X (ΔR[X])—is state dependent. Such a state dependency implies that the best fit in the scatterplot of ΔTg versus ΔR[X] is not a linear regression but can be some nonlinear or even nonsmooth function. While for the conventional linear case the slope (gradient) of the regression is correctly interpreted as the specific equilibrium climate sensitivity S[X], the interpretation is not straightforward in the nonlinear case. We here explain how such a state-dependent scatterplot needs to be interpreted and provide a theoretical understanding—or generalization—how to quantify S[X] in the nonlinear case. Finally, from data covering the last 2.1 Myr we show that—due to state dependency—the specific equilibrium climate sensitivity which considers radiative forcing of CO2 and land ice sheet (LI) albedo, S[CO2,LI], is larger during interglacial states than during glacial conditions by more than a factor 2.

  6. Sensitivity of climate change mitigation estimates to assumptions about technical change

    International Nuclear Information System (INIS)

    Dowlatabadi, H.

    1998-01-01

    With greater certainty in anthropogenic influence on observed changes in climate there is increasing pressure for agreements to control emissions of greenhouse gases ([HOUGHTON]). While it is difficult to assess the appropriate level of mitigation, it has been argued that flexibility in meeting emission targets offers significant economic savings. Such flexibility can be exercised in terms of timing of mitigation (i.e. delay) or geographic location of the intervention (e.g. permit trading and Joint-Implementation). Much of this insight is based on standard models of technical change in energy supply and demand. However, standard model formulations rarely consider: (i) a link between the pattern of technical change and policy interventions; (ii) economies of learning; and (iii) technical progress in discovery and recovery of oil and gas. While there is evidence to support the importance of these factors in historic patterns of technical progress, the data necessary to calibrate internally consistent economic models of these phenomena have not been available. In this paper simple representations of endogenous and induced technical change have been used to explore the sensitivity of mitigation cost estimates to how technical change is represented in energy economics models. The scenarios involve control of CO 2 emissions to limit its concentration to no more than 550 ppm(v), starting in the year 2000, and delayed to 2025. This sensitivity analysis has revealed four robust insights: (i) If endogenous technical change is assumed, expected business as usual emissions are higher than otherwise estimated - nevertheless, while 25% greater CO 2 control is required for meeting the CO 2 concentration target, the cost of mitigation is 40% lower; (ii) If technical progress in oil and gas discovery and recovery is assumed, energy use and CO 2 emissions increase by 75% and 65%, respectively above the standard estimates; (iii) If the economies of learning exhibited in various

  7. Regional climate model performance and prediction of seasonal ...

    African Journals Online (AJOL)

    Knowledge about future climate provides valuable insights into how the challenges posed by climate change and variability can be addressed. ... Impacts Studies) in simulating rainfall and temperature over Uganda and also assess future impacts of climate when forced by an ensemble of two Global Climate Models (GCMs) ...

  8. Sensitivities of the hydrologic cycle to model physics, grid resolution, and ocean type in the aquaplanet Community Atmosphere Model

    Science.gov (United States)

    Benedict, James J.; Medeiros, Brian; Clement, Amy C.; Pendergrass, Angeline G.

    2017-06-01

    Precipitation distributions and extremes play a fundamental role in shaping Earth's climate and yet are poorly represented in many global climate models. Here, a suite of idealized Community Atmosphere Model (CAM) aquaplanet simulations is examined to assess the aquaplanet's ability to reproduce hydroclimate statistics of real-Earth configurations and to investigate sensitivities of precipitation distributions and extremes to model physics, horizontal grid resolution, and ocean type. Little difference in precipitation statistics is found between aquaplanets using time-constant sea-surface temperatures and those implementing a slab ocean model with a 50 m mixed-layer depth. In contrast, CAM version 5.3 (CAM5.3) produces more time mean, zonally averaged precipitation than CAM version 4 (CAM4), while CAM4 generates significantly larger precipitation variance and frequencies of extremely intense precipitation events. The largest model configuration-based precipitation sensitivities relate to choice of horizontal grid resolution in the selected range 1-2°. Refining grid resolution has significant physics-dependent effects on tropical precipitation: for CAM4, time mean zonal mean precipitation increases along the Equator and the intertropical convergence zone (ITCZ) narrows, while for CAM5.3 precipitation decreases along the Equator and the twin branches of the ITCZ shift poleward. Increased grid resolution also reduces light precipitation frequencies and enhances extreme precipitation for both CAM4 and CAM5.3 resulting in better alignment with observational estimates. A discussion of the potential implications these hydrologic cycle sensitivities have on the interpretation of precipitation statistics in future climate projections is also presented.Plain Language SummaryPrecipitation plays a fundamental role in shaping Earth's climate. Global climate models predict the average precipitation reasonably well but often struggle to accurately represent how often it

  9. LINKING MICROBES TO CLIMATE: INCORPORATING MICROBIAL ACTIVITY INTO CLIMATE MODELS COLLOQUIUM

    Energy Technology Data Exchange (ETDEWEB)

    DeLong, Edward; Harwood, Caroline; Reid, Ann

    2011-01-01

    This report explains the connection between microbes and climate, discusses in general terms what modeling is and how it applied to climate, and discusses the need for knowledge in microbial physiology, evolution, and ecology to contribute to the determination of fluxes and rates in climate models. It recommends with a multi-pronged approach to address the gaps.

  10. Comparison of two potato simulation models under climate change. II Application of climate change scenarios.

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

    The effects of climate change (for the year 2050 compared to ambient climate) and change in climatic variability on potato growth and production at 6 sites in Europe were calculated. These calculations were done with both a simple growth model, POTATOS, and a comprehensive model, NPOTATO. Comparison

  11. Comparison of two soya bean simulation models under climate change : II Application of climate change scenarios

    NARCIS (Netherlands)

    Wolf, J.

    2002-01-01

    The effects of climate change (for 2050 compared to ambient climate) and change in climatic variability on soya bean growth and production at 3 sites in the EU have been calculated. These calculations have been done with both a simple growth model, SOYBEANW, and a comprehensive model, CROPGRO.

  12. Modeling climate change impacts on water trading.

    Science.gov (United States)

    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.

  13. Nonlinear climatic sensitivity to greenhouse gases over past 4 glacial/interglacial cycles.

    Science.gov (United States)

    Lo, Li; Chang, Sheng-Pu; Wei, Kuo-Yen; Lee, Shih-Yu; Ou, Tsong-Hua; Chen, Yi-Chi; Chuang, Chih-Kai; Mii, Horng-Sheng; Burr, George S; Chen, Min-Te; Tung, Ying-Hung; Tsai, Meng-Chieh; Hodell, David A; Shen, Chuan-Chou

    2017-07-04

    The paleoclimatic sensitivity to atmospheric greenhouse gases (GHGs) has recently been suggested to be nonlinear, however a GHG threshold value associated with deglaciation remains uncertain. Here, we combine a new sea surface temperature record spanning the last 360,000 years from the southern Western Pacific Warm Pool with records from five previous studies in the equatorial Pacific to document the nonlinear relationship between climatic sensitivity and GHG levels over the past four glacial/interglacial cycles. The sensitivity of the responses to GHG concentrations rises dramatically by a factor of 2-4 at atmospheric CO 2 levels of >220 ppm. Our results suggest that the equatorial Pacific acts as a nonlinear amplifier that allows global climate to transition from deglacial to full interglacial conditions once atmospheric CO 2 levels reach threshold levels.

  14. Current analogues of future climate indicate the likely response of a sensitive montane tropical avifauna to a warming world.

    Science.gov (United States)

    Anderson, Alexander S; Storlie, Collin J; Shoo, Luke P; Pearson, Richard G; Williams, Stephen E

    2013-01-01

    Among birds, tropical montane species are likely to be among the most vulnerable to climate change, yet little is known about how climate drives their distributions, nor how to predict their likely responses to temperature increases. Correlative models of species' environmental niches have been widely used to predict changes in distribution, but direct tests of the relationship between key variables, such as temperature, and species' actual distributions are few. In the absence of historical data with which to compare observations and detect shifts, space-for-time substitutions, where warmer locations are used as analogues of future conditions, offer an opportunity to test for species' responses to climate. We collected density data for rainforest birds across elevational gradients in northern and southern subregions within the Australian Wet Tropics (AWT). Using environmental optima calculated from elevational density profiles, we detected a significant elevational difference between the two regions in ten of 26 species. More species showed a positive (19 spp.) than negative (7 spp.) displacement, with a median difference of ∼80.6 m across the species analysed that is concordant with that expected due to latitudinal temperature differences (∼75.5 m). Models of temperature gradients derived from broad-scale climate surfaces showed comparable performance to those based on in-situ measurements, suggesting the former is sufficient for modeling impacts. These findings not only confirm temperature as an important factor driving elevational distributions of these species, but also suggest species will shift upslope to track their preferred environmental conditions. Our approach uses optima calculated from elevational density profiles, offering a data-efficient alternative to distribution limits for gauging climate constraints, and is sensitive enough to detect distribution shifts in this avifauna in response to temperature changes of as little as 0.4 degrees. We

  15. Current analogues of future climate indicate the likely response of a sensitive montane tropical avifauna to a warming world.

    Directory of Open Access Journals (Sweden)

    Alexander S Anderson

    Full Text Available Among birds, tropical montane species are likely to be among the most vulnerable to climate change, yet little is known about how climate drives their distributions, nor how to predict their likely responses to temperature increases. Correlative models of species' environmental niches have been widely used to predict changes in distribution, but direct tests of the relationship between key variables, such as temperature, and species' actual distributions are few. In the absence of historical data with which to compare observations and detect shifts, space-for-time substitutions, where warmer locations are used as analogues of future conditions, offer an opportunity to test for species' responses to climate. We collected density data for rainforest birds across elevational gradients in northern and southern subregions within the Australian Wet Tropics (AWT. Using environmental optima calculated from elevational density profiles, we detected a significant elevational difference between the two regions in ten of 26 species. More species showed a positive (19 spp. than negative (7 spp. displacement, with a median difference of ∼80.6 m across the species analysed that is concordant with that expected due to latitudinal temperature differences (∼75.5 m. Models of temperature gradients derived from broad-scale climate surfaces showed comparable performance to those based on in-situ measurements, suggesting the former is sufficient for modeling impacts. These findings not only confirm temperature as an important factor driving elevational distributions of these species, but also suggest species will shift upslope to track their preferred environmental conditions. Our approach uses optima calculated from elevational density profiles, offering a data-efficient alternative to distribution limits for gauging climate constraints, and is sensitive enough to detect distribution shifts in this avifauna in response to temperature changes of as little as 0

  16. Current Analogues of Future Climate Indicate the Likely Response of a Sensitive Montane Tropical Avifauna to a Warming World

    Science.gov (United States)

    Anderson, Alexander S.; Storlie, Collin J.; Shoo, Luke P.; Pearson, Richard G.; Williams, Stephen E.

    2013-01-01

    Among birds, tropical montane species are likely to be among the most vulnerable to climate change, yet little is known about how climate drives their distributions, nor how to predict their likely responses to temperature increases. Correlative models of species’ environmental niches have been widely used to predict changes in distribution, but direct tests of the relationship between key variables, such as temperature, and species’ actual distributions are few. In the absence of historical data with which to compare observations and detect shifts, space-for-time substitutions, where warmer locations are used as analogues of future conditions, offer an opportunity to test for species’ responses to climate. We collected density data for rainforest birds across elevational gradients in northern and southern subregions within the Australian Wet Tropics (AWT). Using environmental optima calculated from elevational density profiles, we detected a significant elevational difference between the two regions in ten of 26 species. More species showed a positive (19 spp.) than negative (7 spp.) displacement, with a median difference of ∼80.6 m across the species analysed that is concordant with that expected due to latitudinal temperature differences (∼75.5 m). Models of temperature gradients derived from broad-scale climate surfaces showed comparable performance to those based on in-situ measurements, suggesting the former is sufficient for modeling impacts. These findings not only confirm temperature as an important factor driving elevational distributions of these species, but also suggest species will shift upslope to track their preferred environmental conditions. Our approach uses optima calculated from elevational density profiles, offering a data-efficient alternative to distribution limits for gauging climate constraints, and is sensitive enough to detect distribution shifts in this avifauna in response to temperature changes of as little as 0.4 degrees

  17. Sensitivity of leaf size and shape to climate: Global patterns and paleoclimatic applications

    Science.gov (United States)

    Peppe, D.J.; Royer, D.L.; Cariglino, B.; Oliver, S.Y.; Newman, S.; Leight, E.; Enikolopov, G.; Fernandez-Burgos, M.; Herrera, F.; Adams, J.M.; Correa, E.; Currano, E.D.; Erickson, J.M.; Hinojosa, L.F.; Hoganson, J.W.; Iglesias, A.; Jaramillo, C.A.; Johnson, K.R.; Jordan, G.J.; Kraft, N.J.B.; Lovelock, E.C.; Lusk, C.H.; Niinemets, U.; Penuelas, J.; Rapson, G.; Wing, S.L.; Wright, I.J.

    2011-01-01

    Paleobotanists have long used models based on leaf size and shape to reconstruct paleoclimate. However, most models incorporate a single variable or use traits that are not physiologically or functionally linked to climate, limiting their predictive power. Further, they often underestimate paleotemperature relative to other proxies. Here we quantify leaf-climate correlations from 92 globally distributed, climatically diverse sites, and explore potential confounding factors. Multiple linear regression models for mean annual temperature (MAT) and mean annual precipitation (MAP) are developed and applied to nine well-studied fossil floras. We find that leaves in cold climates typically have larger, more numerous teeth, and are more highly dissected. Leaf habit (deciduous vs evergreen), local water availability, and phylogenetic history all affect these relationships. Leaves in wet climates are larger and have fewer, smaller teeth. Our multivariate MAT and MAP models offer moderate improvements in precision over univariate approaches (??4.0 vs 4.8??C for MAT) and strong improvements in accuracy. For example, our provisional MAT estimates for most North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence. Our study demonstrates that the inclusion of additional leaf traits that are functionally linked to climate improves paleoclimate reconstructions. This work also illustrates the need for better understanding of the impact of phylogeny and leaf habit on leaf-climate relationships. ?? 2011 The Authors. New Phytologist ?? 2011 New Phytologist Trust.

  18. Sensitivity of the Amazon biome to high resolution climate change projections

    OpenAIRE

    LYRA,Andre de Arruda; CHOU,Sin Chan; SAMPAIO,Gilvan de Oliveira

    2016-01-01

    ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was f...

  19. Potential Influence of Climate Change on the Acid-Sensitivity of High-Elevation Lakes in the Georgia Basin, British Columbia

    OpenAIRE

    Strang, Donna; Aherne, Julian

    2015-01-01

    Global climate models predict increased temperature and precipitation in the Georgia Basin, British Colmbia; however, little is known about the impacts on high-elevation regions. In the current study, fifty-four high-elevation lakes (754–2005 m a.s.l.) were studied to investigate the potential influence of climate change on surface water acid-sensitivity. Redundancy analysis indicated that the concentration of nitrate, dissolved organic carbon, and associated metals was significantly influe...

  20. Tackifier Mobility in Model Pressure Sensitive Adhesives

    Science.gov (United States)

    Paiva, Adriana; Li, Xiaoqing

    1997-03-01

    A systematic study of the molecular mobility of tackifier in a pressure sensitive adhesive (PSA) has been done for the first time. The objective is to relate changes in adhesive performance with tackifier loading to tackifier mobility. Study focused first on a model PSA consisting of anionically polymerized polyisoprene (PI) (Mw=300,000 Mw/Mn 1.05) and a single simple tackifier, n-butyl ester of abietic acid. This model system is fully miscible at room temperature, and its tack performance has been studied. Tackifier mobility was measured using Pulsed-Gradient Spin-Echo NMR as a function of tackifier concentration and temperature. The concentration dependence observed for this adhesive with modestly enhanced performance was weak, indicating the tackifier neither acts to plasticize or antiplasticize appreciably. Diffusion in a two-phase system of hydrogenated PI with the same tackifier is similar, though the tack of that adhesive varies much more markedly with composition. In contrast, tackifier mobility varies strongly with composition in a PSA composed of PI with a commercial tackifier chemically similar to the model tackifier, but having a higher molecular weight and glass transition temperature. * Supported in part by US DOD: ARO(DAAH04-93-G-0410)

  1. Pozebe v Primorju z vidika uspevanja mediteranskih kultur = Frosts in Primorska region from the aspect of climatically more sensitive cultures

    Directory of Open Access Journals (Sweden)

    Darko Ogrin

    2002-01-01

    Full Text Available Climatic characteristics in south-west Slovenia are akin to the Mediterranean ones,therefore some more sensitive cultures still grow there; by far the most important isolive which is otherwise typical of the central Mediterranean. These cultures growat their northern climatic borders, therefore they are periodically affected by severefrosts. The development of olive growing, and other climatically more sensitive culturesas well, has also been fostered by both the climatic trends of the last decadesand the forecasts for the 21st century prognosticating further warming of the climate.

  2. Downscaling GISS ModelE Boreal Summer Climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  3. Downscaling GISS ModelE boreal summer climate over Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew

    2016-12-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June-September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2° latitude by 2.5° longitude and the RM3 grid spacing is 0.44°. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  4. Potential Sensitivity of Québec's Breeding Birds to Climate Change

    Directory of Open Access Journals (Sweden)

    Jean-Luc DesGranges

    2010-12-01

    Full Text Available We examined the relationship between climatic factors and the distribution of breeding birds in southern Québec, Canada to identify the species whose distribution renders them potentially sensitive to climate change in the study area. We determined the degree of association between the distribution of 65 breeding bird species (601 presence-absence squares of the Atlas of the Breeding Birds of Québec and climate variables (212 climatological stations in operation for at least 20 years over the period 1953–1984 by statistically correcting for the effects of several factors that are correlated with bird distribution. Factors considered were the nature and scale of land cover patterns that included vegetation types and landscape characterization, geographical coordinates, and elevation. Canonical Correspondence Analysis (CCA was used to investigate the effect of climatic variables on breeding bird distribution. Independent variables accounted for a total of 29.1% of the variation in the species matrix. A very large portion of the variance explained by climate variables was shared with spatial variables, reflecting the relationships among latitude, longitude, elevation, and climate. After correcting for the effect of land cover variables, climatic variables still explained 11.4% of the variation in the species matrix, with temperature, i.e., warmer summers and milder winters, having a greater influence than precipitation, i.e., wetter summers. Of the 65 species, 14 appeared to be particularly climate-sensitive. Eight are insectivorous neotropical migrants and six species are at the northern limit of their range in the study area. The opposite is largely true for the eight others; they are practically absent from the southern part of the study area, except for the Dark-eyed Junco (Junco hyemalis, which is widespread there. The White-breasted Nuthatch (Sitta carolinensis is the only resident species that seemed responsive to climatic variables, i

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

    Science.gov (United States)

    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

  6. Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

    Directory of Open Access Journals (Sweden)

    M. Eby

    2013-05-01

    Full Text Available Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there

  7. Evaluating the Hydrologic Sensitivities of Three Land Surface Models to Bound Uncertainties in Runoff Projections

    Science.gov (United States)

    Chiao, T.; Nijssen, B.; Stickel, L.; Lettenmaier, D. P.

    2013-12-01

    Hydrologic modeling is often used to assess the potential impacts of climate change on water availability and quality. A common approach in these studies is to calibrate the selected model(s) to reproduce historic stream flows prior to the application of future climate projections. This approach relies on the implicit assumptions that the sensitivities of these models to meteorological fluctuations will remain relatively constant under climate change and that these sensitivities are similar among models if all models are calibrated to the same historic record. However, even if the models are able to capture the historic variability in hydrological variables, differences in model structure and parameter estimation contribute to the uncertainties in projected runoff, which confounds the incorporation of these results into water resource management decision-making. A better understanding of the variability in hydrologic sensitivities between different models can aid in bounding this uncertainty. In this research, we characterized the hydrologic sensitivities of three watershed-scale land surface models through a case study of the Bull Run watershed in Northern Oregon. The Distributed Hydrology Soil Vegetation Model (DHSVM), Precipitation-Runoff Modeling System (PRMS), and Variable Infiltration Capacity model (VIC) were implemented and calibrated individually to historic streamflow using a common set of long-term, gridded forcings. In addition to analyzing model performances for a historic period, we quantified the temperature sensitivity (defined as change in runoff in response to change in temperature) and precipitation elasticity (defined as change in runoff in response to change in precipitation) of these three models via perturbation of the historic climate record using synthetic experiments. By comparing how these three models respond to changes in climate forcings, this research aims to test the assumption of constant and similar hydrologic sensitivities. Our

  8. Modeling Bird Migration under Climate Change: A Mechanistic Approach

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this

  9. MECCA coordinated research program: analysis of climate models uncertainties used for climatic changes study

    International Nuclear Information System (INIS)

    Caneill, J.Y.; Hakkarinen, C.

    1992-01-01

    An international consortium, called MECCA, (Model Evaluation Consortium for Climate Assessment) has been created in 1991 by different partners including electric utilities, government and academic groups to make available to the international scientific community, a super-computer facility for climate evolution studies. The first phase of the program consists to assess uncertainties of climate model simulations in the framework of global climate change studies. Fourteen scientific projects have been accepted on an international basis in this first phase. The second phase of the program will consist in the evaluation of a set of long climate simulations realized with coupled ocean/atmosphere models, in order to study the transient aspects of climate changes and the associated uncertainties. A particular attention will be devoted, on the consequences of these assessments on climate impact studies, and on the regional aspects of climate changes

  10. The atmospheric bridge linking AMV and summer European climate in a climate model

    Science.gov (United States)

    Ghosh, Rohit; Müller, Wolfgang A.; Eichhorn, Astrid; Baehr, Johanna; Bader, Jürgen

    2017-04-01

    By using the 20th Century reanalysis, the summer Atlantic Multidecadal Variability (AMV) has been shown to affect the European climate through an associated atmospheric baroclinic response which has been called North-Atlantic-European East West (NEW) mode(Ghosh et. al. 2016). Here, we continue this analysis, by using control simulations and AMIP-type of sensitivity experiments with the Max-Planck Institute Earth System Model (MPI-ESM) and investigate the model response to AMV type SST and its similarities and differences from the response in the reanalysis. In the control simulations of the coupled model version MPI-ESM, both low resolution (LR, approx. 200km in the atmosphere) and high (HR, approx. 100km) resolution can simulate a similar AMV type of SST pattern likewise the 20th century reanalysis. The AMV response of the LR, however, is found more sensitive to tropical branch of the SST and thus the North-Atlantic-European (NAE) climate is mainly influenced by the stationary Rossby wave response from the tropics. In HR, the impact of the tropical SST variations on extra-tropics is weaker due to lesser eddy-mean flow interactions. However the NEW mode is not found in any of these control simulations which could be due to a relatively strong SST bias over the extra-tropical North Atlantic in the model. Hence, we further conducted AMIP-like sensitivity experiments with the observed AMV type SST pattern on the atmospheric component of the LR, the ECHAM version 6.3. The results from the experiments underlines that in the positive phase of the AMV, the NAE climate is mainly influenced by the tropical branch of the AMV. Here, again a stationary Rossby wave response is associated with negative surface air temperature (SAT) anomalies over the C-E Europe; which is opposite to what is found in the re-analysis. However, in the case of the negative phase of AMV, the NAE climate is mainly governed by the extra-tropical branch of SST through a baroclinic-like response, which

  11. Embedding complex hydrology in the climate system - Towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, Michael; Rasmussen, Søren H.; Ridler, Marc

    2013-01-01

    Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....

  12. Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models

    DEFF Research Database (Denmark)

    Butts, M.; Rasmussen, S.H.; Ridler, M.

    2013-01-01

    Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....

  13. Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

    Science.gov (United States)

    West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

    2016-01-01

    Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

  14. Tsunami propagation modelling – a sensitivity study

    Directory of Open Access Journals (Sweden)

    P. Tkalich

    2007-12-01

    Full Text Available Indian Ocean (2004 Tsunami and following tragic consequences demonstrated lack of relevant experience and preparedness among involved coastal nations. After the event, scientific and forecasting circles of affected countries have started a capacity building to tackle similar problems in the future. Different approaches have been used for tsunami propagation, such as Boussinesq and Nonlinear Shallow Water Equations (NSWE. These approximations were obtained assuming different relevant importance of nonlinear, dispersion and spatial gradient variation phenomena and terms. The paper describes further development of original TUNAMI-N2 model to take into account additional phenomena: astronomic tide, sea bottom friction, dispersion, Coriolis force, and spherical curvature. The code is modified to be suitable for operational forecasting, and the resulting version (TUNAMI-N2-NUS is verified using test cases, results of other models, and real case scenarios. Using the 2004 Tsunami event as one of the scenarios, the paper examines sensitivity of numerical solutions to variation of different phenomena and parameters, and the results are analyzed and ranked accordingly.

  15. Observed forest sensitivity to climate implies large changes in 21st century North American forest growth.

    Science.gov (United States)

    Charney, Noah D; Babst, Flurin; Poulter, Benjamin; Record, Sydne; Trouet, Valerie M; Frank, David; Enquist, Brian J; Evans, Margaret E K

    2016-09-01

    Predicting long-term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree-ring observations spanning North America and a space-for-time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water-use efficiency (WUE) due to CO2 -fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high-latitude forests, leaving no evidence for continued 'boreal greening'; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change. © 2016 John Wiley & Sons Ltd/CNRS.

  16. Selecting a climate model subset to optimise key ensemble properties

    Directory of Open Access Journals (Sweden)

    N. Herger

    2018-02-01

    Full Text Available End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  17. Selecting a climate model subset to optimise key ensemble properties

    Science.gov (United States)

    Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

    2018-02-01

    End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  18. Modeling lakes and reservoirs in the climate system

    NARCIS (Netherlands)

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L.N.; Fang, X.; Gal, G.; Jöhnk, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere–land surface–lake climate models that could be used for both of these types of study

  19. Assessing climate change effects on long-term forest development: adjusting growth, phenology, and seed production in a gap model

    NARCIS (Netherlands)

    Meer, van der P.J.; Jorritsma, I.T.M.; Kramer, K.

    2002-01-01

    The sensitivity of forest development to climate change is assessed using a gap model. Process descriptions in the gap model of growth, phenology, and seed production were adjusted for climate change effects using a detailed process-based growth modeland a regression analysis. Simulation runs over

  20. Possible impact of climate change on meningitis in northwest Nigeria: an assessment using CMIP5 climate model simulations

    Science.gov (United States)

    Abdussalam, Auwal; Monaghan, Andrew; Steinhoff, Daniel; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Thornes, John; Leckebusch, Gregor

    2014-05-01

    Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily-populated northwest Nigeria. Cases exhibit strong sensitivity to intra- and inter-annual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations from an ensemble of thirteen statistically downscaled global climate model projections from the Coupled Model Intercomparison Experiment Phase 5 (CMIP5) for RCPs 2.6, 6.0 and 8.5 scenarios. The results suggest future temperature increases due to climate change has the potential to significantly increase meningitis cases in both the early and late 21st century, and to increase the length of the meningitis season in the late century. March cases may increase from 23 per 100,000 people for present day (1990-2005), to 29-30 per 100,000 (p<0.01) in the early century (2020-2035) and 31-42 per 100,000 (p<0.01) in the late century (2060-2075), the range being dependent on the emissions scenario. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as we assume current prevention and treatment strategies remain similar in the future.

  1. The Impact of Subsidies on the Prevalence of Climate-Sensitive Residential Buildings in Malaysia

    Directory of Open Access Journals (Sweden)

    David T. Tan

    2017-12-01

    Full Text Available Dependence on air-conditioning (AC for residential cooling and ventilation is a health and sustainability challenge. In hot temperatures, climate-sensitive buildings (CSB can complement and/or substitute for AC usage in achieving thermal comfort. Many countries facing such conditions—particularly in tropical climates—are developing quickly, with rising populations and income creating demand for new housing and AC. This presents a window for adoption of CSB but could also result in long term lock-in of AC-dependent buildings. Here, a simple system dynamics model is used to explore the potential and limitations of subsidies to affect futures of housing stock and night-time AC usage in Malaysia. The effectiveness of subsidies in achieving high uptake of CSB and resulting health benefits is highly dependent on homebuyer willingness to pay (WTP. A detailed understanding of WTP in the Malaysian context and factors that can shift WTP is necessary to determine if CSB subsidies can be a good policy mechanism for achieving CSB uptake.

  2. Climate-signal changes in a temperature-sensitive dendroclimatic network: the influence of site aspect

    Science.gov (United States)

    Leonelli, Giovanni; Pelfini, Manuela; Battipaglia, Giovanna; Cherubini, Paolo

    2010-05-01

    especially for S- and W-facing site chronologies). On the other hand, trees from N-facing sites showed an increasing sensitivity to July temperatures, especially since the period 1911-1970. Our results underline that some climatic factors related to slope aspect (e.g. temperature regime, snow-cover persistence or growing season length) play a key role in limiting P. cembra tree-ring growth at high altitudes, especially in N-facing sites. Moreover, it is evident at all sites that at high altitudes, low temperatures at the beginning of the growing season no longer limit growth as they did in earlier decades. Stronger changes are involving especially the S- and W-facing sites that in the past were more limited by June temperature, whereas trees on N-facing slopes are generally less adapted to warmer conditions at the beginning of the growing season (June) and therefore respond less to an increasing air temperature. We point out the importance of testing growth-climate relationships over time to detect possible trends in climate sensitivity. In fact, wide variation in climate sensitivity over time could lead to over- or underestimations of past temperatures. Moreover, our findings showed that site ecology can affect dendroclimatic reconstructions.

  3. Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

    Science.gov (United States)

    Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

    2017-08-16

    Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate