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. Regional climate model sensitivity to domain size

    Energy Technology Data Exchange (ETDEWEB)

    Leduc, Martin [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada); UQAM/Ouranos, Montreal, QC (Canada); Laprise, Rene [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada)

    2009-05-15

    Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the ''perfect model'' approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 x 100 grid points). The permanent ''spatial spin-up'' corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere. (orig.)

  3. Regional climate model sensitivity to domain size

    Science.gov (United States)

    Leduc, Martin; Laprise, René

    2009-05-01

    Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

  4. Climate and climate change sensitivity to model configuration in the Canadian RCM over North America

    Energy Technology Data Exchange (ETDEWEB)

    De Elia, Ramon [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada); Centre ESCER, Univ. du Quebec a Montreal (Canada); Cote, Helene [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada)

    2010-06-15

    Climate simulations performed with Regional Climate Models (RCMs) have been found to show sensitivity to parameter settings. The origin, consequences and interpretations of this sensitivity are varied, but it is generally accepted that sensitivity studies are very important for a better understanding and a more cautious manipulation of RCM results. In this work we present sensitivity experiments performed on the simulated climate produced by the Canadian Regional Climate Model (CRCM). In addition to climate sensitivity to parameter variation, we analyse the impact of the sensitivity on the climate change signal simulated by the CRCM. These studies are performed on 30-year long simulated present and future seasonal climates, and we have analysed the effect of seven kinds of configuration modifications: CRCM initial conditions, lateral boundary condition (LBC), nesting update interval, driving Global Climate Model (GCM), driving GCM member, large-scale spectral nudging, CRCM version, and domain size. Results show that large changes in both the driving model and the CRCM physics seem to be the main sources of sensitivity for the simulated climate and the climate change. Their effects dominate those of configuration issues, such as the use or not of large-scale nudging, domain size, or LBC update interval. Results suggest that in most cases, differences between simulated climates for different CRCM configurations are not transferred to the estimated climate change signal: in general, these tend to cancel each other out. (orig.)

  5. 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.)

  6. Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Bruce T. [Boston University, Department of Geography and Environment, Boston, MA (United States); Knight, Jeff R.; Ringer, Mark A. [Met Office Hadley Centre, Exeter (United Kingdom); Deser, Clara; Phillips, Adam S. [National Center for Atmospheric Research, Boulder, CO (United States); Yoon, Jin-Ho [University of Maryland, Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, College Park, MD (United States); Cherchi, Annalisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici, and Istituto Nazionale di Geofisica e Vulcanologia, Bologna (Italy)

    2010-12-15

    Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed. (orig.)

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

    KAUST Repository

    Merlis, Timothy M.; Held, Isaac M.; Stenchikov, Georgiy L.; Zeng, Fanrong; Horowitz, Larry W.

    2014-01-01

    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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model

    Science.gov (United States)

    Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue

    2015-10-01

    In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.

  13. 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

  14. 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.

  15. Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

    Science.gov (United States)

    Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

    2011-12-01

    Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

  16. Eocene climate and Arctic paleobathymetry: A tectonic sensitivity study using GISS ModelE-R

    Science.gov (United States)

    Roberts, C. D.; Legrande, A. N.; Tripati, A. K.

    2009-12-01

    The early Paleogene (65-45 million years ago, Ma) was a ‘greenhouse’ interval with global temperatures warmer than any other time in the last 65 Ma. This period was characterized by high levels of CO2, warm high-latitudes, warm surface-and-deep oceans, and an intensified hydrological cycle. Sediments from the Arctic suggest that the Eocene surface Arctic Ocean was warm, brackish, and episodically enabled the freshwater fern Azolla to bloom. The precise mechanisms responsible for the development of these conditions remain uncertain. We present equilibrium climate conditions derived from a fully-coupled, water-isotope enabled, general circulation model (GISS ModelE-R) configured for the early Eocene. We also present model-data comparison plots for key climatic variables (SST and δ18O) and analyses of the leading modes of variability in the tropical Pacific and North Atlantic regions. Our tectonic sensitivity study indicates that Northern Hemisphere climate would have been very sensitive to the degree of oceanic exchange through the seaways connecting the Arctic to the Atlantic and Tethys. By restricting these seaways, we simulate freshening of the surface Arctic Ocean to ~6 psu and warming of sea-surface temperatures by 2°C in the North Atlantic and 5-10°C in the Labrador Sea. Our results may help explain the occurrence of low-salinity tolerant taxa in the Arctic Ocean during the Eocene and provide a mechanism for enhanced warmth in the north western Atlantic. We also suggest that the formation of a volcanic land-bridge between Greenland and Europe could have caused increased ocean convection and warming of intermediate waters in the Atlantic. If true, this result is consistent with the theory that bathymetry changes may have caused thermal destabilisation of methane clathrates in the Atlantic.

  17. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    Science.gov (United States)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  18. Tuning the climate sensitivity of a global model to match 20th Century warming

    Science.gov (United States)

    Mauritsen, T.; Roeckner, E.

    2015-12-01

    A climate models ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons historical warming cannot be considered a purely empirical result of the modelling efforts because the desired result is known in advance and so is a potential target of tuning. Here we explain how the latest edition of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) atmospheric model (ECHAM6.3) had its climate sensitivity systematically tuned to about 3 K; the MPI model to be used during CMIP6. This was deliberately done in order to improve the match to observed 20th Century warming over the previous model generation (MPI-ESM, ECHAM6.1) which warmed too much and had a sensitivity of 3.5 K. In the process we identified several controls on model cloud feedback that confirm recently proposed hypotheses concerning trade-wind cumulus and high-latitude mixed-phase clouds. We then evaluate the model fidelity with centennial global warming and discuss the relative importance of climate sensitivity, forcing and ocean heat uptake efficiency in determining the response as well as possible systematic biases. The activity of targeting historical warming during model development is polarizing the modeling community with 35 percent of modelers stating that 20th Century warming was rated very important to decisive, whereas 30 percent would not consider it at all. Likewise, opinions diverge as to which measures are legitimate means for improving the model match to observed warming. These results are from a survey conducted in conjunction with the first WCRP Workshop on Model Tuning in fall 2014 answered by 23 modelers. We argue that tuning or constructing models to match observed warming to some extent is practically unavoidable, and as such, in many cases might as well be done explicitly. For modeling groups that have the capability to tune both their aerosol forcing and climate sensitivity there is now a unique

  19. Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

    Energy Technology Data Exchange (ETDEWEB)

    Wan, Hui; Rasch, Philip J.; Zhang, Kai; Qian, Yun; Yan, Huiping; Zhao, Chun

    2014-09-08

    This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.

  20. 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

  1. Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, T. (Yale Univ., New Haven, CT (United States))

    1994-06-01

    A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.

  2. 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

  3. 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.

  4. 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

  5. Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models

    Directory of Open Access Journals (Sweden)

    H. Wan

    2014-09-01

    Full Text Available This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model, version 5. In the first example, the method is used to characterize sensitivities of the simulated clouds to time-step length. Results show that 3-day ensembles of 20 to 50 members are sufficient to reproduce the main signals revealed by traditional 5-year simulations. A nudging technique is applied to an additional set of simulations to help understand the contribution of physics–dynamics interaction to the detected time-step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol life cycle are perturbed simultaneously in order to find out which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. It turns out that 12-member ensembles of 10-day simulations are able to reveal the same sensitivities as seen in 4-year simulations performed in a previous study. In both cases, the ensemble method reduces the total computational time by a factor of about 15, and the turnaround time by a factor of several hundred. The efficiency of the method makes it particularly useful for the development of

  6. The influence of cirrus cloud-radiative forcing on climate and climate sensitivity in a general circulation model

    International Nuclear Information System (INIS)

    Lohmann, U.; Roeckner, E.

    1994-01-01

    Six numerical experiments have been performed with a general circulation model (GCM) to study the influence of high-level cirrus clouds and global sea surface temperature (SST) perturbations on climate and climate sensitivity. The GCM used in this investigation is the third-generation ECHAM3 model developed jointly by the Max-Planck-Institute for Meteorology and the University of Hamburg. It is shown that the model is able to reproduce many features of the observed cloud-radiative forcing with considerable skill, such as the annual mean distribution, the response to seasonal forcing and the response to observed SST variations in the equatorial Pacific. In addition to a reference experiment where the cirrus emissivity is computed as a function of the cloud water content, two sensitivity experiments have been performed in which the cirrus emissivity is either set to zero everywhere above 400 hPa ('transparent cirrus') or set to one ('black cirrus'). These three experiments are repeated identically, except for prescribing a globally uniform SST warming of 4 K. (orig.)

  7. 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

  8. 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

  9. 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

  10. 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

  11. Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration

    International Nuclear Information System (INIS)

    Schwalm, Christopher R; Huntinzger, Deborah N; Michalak, Anna M; Fisher, Joshua B; Kimball, John S; Mueller, Brigitte; Zhang, Ke; Zhang Yongqiang

    2013-01-01

    Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill. (letter)

  12. Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

    Science.gov (United States)

    Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

    2017-12-01

    The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at

  13. Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

    Science.gov (United States)

    Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

    2016-02-01

    The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

  14. 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.

  15. Response to the eruption of Mount Pinatubo in relation to climate sensitivity in the CMIP3 models

    Energy Technology Data Exchange (ETDEWEB)

    Bender, Frida A.M.; Ekman, Annica M.L.; Rodhe, Henning [Stockholm University, Department of Meteorology, Stockholm (Sweden)

    2010-10-15

    The radiative flux perturbations and subsequent temperature responses in relation to the eruption of Mount Pinatubo in 1991 are studied in the ten general circulation models incorporated in the Coupled Model Intercomparison Project, phase 3 (CMIP3), that include a parameterization of volcanic aerosol. Models and observations show decreases in global mean temperature of up to 0.5 K, in response to radiative perturbations of up to 10 W m{sup -2}, averaged over the tropics. The time scale representing the delay between radiative perturbation and temperature response is determined by the slow ocean response, and is estimated to be centered around 4 months in the models. Although the magnitude of the temperature response to a volcanic eruption has previously been used as an indicator of equilibrium climate sensitivity in models, we find these two quantities to be only weakly correlated. This may partly be due to the fact that the size of the volcano-induced radiative perturbation varies among the models. It is found that the magnitude of the modelled radiative perturbation increases with decreasing climate sensitivity, with the exception of one outlying model. Therefore, we scale the temperature perturbation by the radiative perturbation in each model, and use the ratio between the integrated temperature perturbation and the integrated radiative perturbation as a measure of sensitivity to volcanic forcing. This ratio is found to be well correlated with the model climate sensitivity, more sensitive models having a larger ratio. Further, if this correspondence between ''volcanic sensitivity'' and sensitivity to CO{sub 2} forcing is a feature not only among the models, but also of the real climate system, the alleged linear relation can be used to estimate the real climate sensitivity. The observational value of the ratio signifying volcanic sensitivity is hereby estimated to correspond to an equilibrium climate sensitivity, i.e. equilibrium temperature

  16. 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...... a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast....

  17. Constraining climate sensitivity and continental versus seafloor weathering using an inverse geological carbon cycle model.

    Science.gov (United States)

    Krissansen-Totton, Joshua; Catling, David C

    2017-05-22

    The relative influences of tectonics, continental weathering and seafloor weathering in controlling the geological carbon cycle are unknown. Here we develop a new carbon cycle model that explicitly captures the kinetics of seafloor weathering to investigate carbon fluxes and the evolution of atmospheric CO 2 and ocean pH since 100 Myr ago. We compare model outputs to proxy data, and rigorously constrain model parameters using Bayesian inverse methods. Assuming our forward model is an accurate representation of the carbon cycle, to fit proxies the temperature dependence of continental weathering must be weaker than commonly assumed. We find that 15-31 °C (1σ) surface warming is required to double the continental weathering flux, versus 3-10 °C in previous work. In addition, continental weatherability has increased 1.7-3.3 times since 100 Myr ago, demanding explanation by uplift and sea-level changes. The average Earth system climate sensitivity is  K (1σ) per CO 2 doubling, which is notably higher than fast-feedback estimates. These conclusions are robust to assumptions about outgassing, modern fluxes and seafloor weathering kinetics.

  18. Inferring climate sensitivity from volcanic events

    Energy Technology Data Exchange (ETDEWEB)

    Boer, G.J. [Environment Canada, University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Stowasser, M.; Hamilton, K. [University of Hawaii, International Pacific Research Centre, Honolulu, HI (United States)

    2007-04-15

    The possibility of estimating the equilibrium climate sensitivity of the earth-system from observations following explosive volcanic eruptions is assessed in the context of a perfect model study. Two modern climate models (the CCCma CGCM3 and the NCAR CCSM2) with different equilibrium climate sensitivities are employed in the investigation. The models are perturbed with the same transient volcano-like forcing and the responses analysed to infer climate sensitivities. For volcano-like forcing the global mean surface temperature responses of the two models are very similar, despite their differing equilibrium climate sensitivities, indicating that climate sensitivity cannot be inferred from the temperature record alone even if the forcing is known. Equilibrium climate sensitivities can be reasonably determined only if both the forcing and the change in heat storage in the system are known very accurately. The geographic patterns of clear-sky atmosphere/surface and cloud feedbacks are similar for both the transient volcano-like and near-equilibrium constant forcing simulations showing that, to a considerable extent, the same feedback processes are invoked, and determine the climate sensitivity, in both cases. (orig.)

  19. Amazon collapse in the next century: exploring the sensitivity to climate and model formulation uncertainties

    Science.gov (United States)

    Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.

    2007-12-01

    A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.

  20. A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence

    Directory of Open Access Journals (Sweden)

    Edlund Stefan

    2012-09-01

    Full Text Available Abstract Background The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. Methods This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data. The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation’s Spatiotemporal Epidemiological Modeller (STEM. Results Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166–2

  1. An investigation of the sensitivity of a land surface model to climate change using a reduced form model

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, A.H.; McIlwaine, S. [PAOS/CIRES, Univ. of Colorado, Boulder, CO (United States); Beringer, J. [Inst. of Arctic Biology, Univ. of Alaska, Fairbanks (United States); Bonan, G.B. [National Center for Atmospheric Research, Boulder, CO (United States)

    2001-05-01

    In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. (orig.)

  2. Using a Mechanistic Reactive Transport Model to Represent Soil Organic Matter Dynamics and Climate Sensitivity

    Science.gov (United States)

    Guerry, N.; Riley, W. J.; Maggi, F.; Torn, M. S.; Kleber, M.

    2011-12-01

    substantial uncertainty in how these relationships should be represented. We also developed several other model formulations, including one that represents SOM in pools of varying decomposability, but lacking explicit protection mechanisms. We tested the model against several observational and experimental datasets. An important conclusion of our analysis is that although several of the model structural formulations were able to represent the bulk SOM observations, including 14C vertical profiles, the temperature, moisture, and soil chemistry sensitivity of decomposition varied strongly between each formulation. Finally, we applied the model to design observations that would be required to better constrain process representation and improve predictions of changes in SOM under changing climate.

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

    OpenAIRE

    Angelen, J. H.; Lenaerts, J. T. M.; Lhermitte, S.; Fettweis, X.; Kuipers Munneke, P.; Broeke, M. R.; Meijgaard, E.; Smeets, C. J. P. P.

    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, 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...

  5. The Influence of Climate Change on Atmospheric Deposition of Mercury in the Arctic—A Model Sensitivity Study

    Science.gov (United States)

    Hansen, Kaj M.; Christensen, Jesper H.; Brandt, Jørgen

    2015-01-01

    Mercury (Hg) is a global pollutant with adverse health effects on humans and wildlife. It is of special concern in the Arctic due to accumulation in the food web and exposure of the Arctic population through a rich marine diet. Climate change may alter the exposure of the Arctic population to Hg. We have investigated the effect of climate change on the atmospheric Hg transport to and deposition within the Arctic by making a sensitivity study of how the atmospheric chemistry-transport model Danish Eulerian Hemispheric Model (DEHM) reacts to climate change forcing. The total deposition of Hg to the Arctic is 18% lower in the 2090s compared to the 1990s under the applied Special Report on Emissions Scenarios (SRES-A1B) climate scenario. Asia is the major anthropogenic source area (25% of the deposition to the Arctic) followed by Europe (6%) and North America (5%), with the rest arising from the background concentration, and this is independent of the climate. DEHM predicts between a 6% increase (Status Quo scenario) and a 37% decrease (zero anthropogenic emissions scenario) in Hg deposition to the Arctic depending on the applied emission scenario, while the combined effect of future climate and emission changes results in up to 47% lower Hg deposition. PMID:26378551

  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. Process based model sheds light on climate sensitivity of Mediterranean tree-ring width

    Directory of Open Access Journals (Sweden)

    R. Touchan

    2012-03-01

    Full Text Available We use the process-based VS (Vaganov-Shashkin model to investigate whether a regional Pinus halepensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004 from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982–2004 and the model is applied to generate tree-ring indices for 1959–1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (r=0.76 p<0.0001, n=23. The model shows that the average duration of the growing season is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model.

  8. 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.

  9. 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

  10. 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

  11. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2018-06-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  12. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2017-08-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  13. Climate sensitivity of marine energy

    International Nuclear Information System (INIS)

    Harrison, G.P.; Wallace, A.R.

    2005-01-01

    Marine energy has a significant role to play in lowering carbon emissions within the energy sector. Paradoxically, it may be susceptible to changes in climate that will result from rising carbon emissions. Wind patterns are expected to change and this will alter wave regimes. Despite a lack of definite proof of a link to global warming, wind and wave conditions have been changing over the past few decades. Changes in the wind and wave climate will affect offshore wind and wave energy conversion: where the resource is constrained, production and economic performance may suffer; alternatively, stormier climates may create survival issues. Here, a relatively simple sensitivity study is used to quantify how changes in mean wind speed - as a proxy for wider climate change - influence wind and wave energy production and economics. (author)

  14. High-Latitude Stratospheric Sensitivity to QBO Width in a Chemistry-Climate Model with Parameterized Ozone Chemistry

    Science.gov (United States)

    Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

    2010-01-01

    In a pair of idealized simulations with a simplified chemistry-climate model, the sensitivity of the wintertime Arctic stratosphere to variability in the width of the quasi-biennial oscillation (QBO) is assessed. The width of the QBO appears to have equal influence on the Arctic stratosphere as does the phase (i.e. the Holton-Tan mechanism). In the model, a wider QBO acts like a preferential shift toward the easterly phase of the QBO, where zonal winds at 60 N tend to be relatively weaker, while 50 hPa geopotential heights and polar ozone values tend to be higher.

  15. The Role of Sea Ice in 2 x CO2 Climate Model Sensitivity. Part 2; Hemispheric Dependencies

    Science.gov (United States)

    Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.

    1997-01-01

    How sensitive are doubled CO2 simulations to GCM control-run sea ice thickness and extent? This issue is examined in a series of 10 control-run simulations with different sea ice and corresponding doubled CO2 simulations. Results show that with increased control-run sea ice coverage in the Southern Hemisphere, temperature sensitivity with climate change is enhanced, while there is little effect on temperature sensitivity of (reasonable) variations in control-run sea ice thickness. In the Northern Hemisphere the situation is reversed: sea ice thickness is the key parameter, while (reasonable) variations in control-run sea ice coverage are of less importance. In both cases, the quantity of sea ice that can be removed in the warmer climate is the determining factor. Overall, the Southern Hemisphere sea ice coverage change had a larger impact on global temperature, because Northern Hemisphere sea ice was sufficiently thick to limit its response to doubled CO2, and sea ice changes generally occurred at higher latitudes, reducing the sea ice-albedo feedback. In both these experiments and earlier ones in which sea ice was not allowed to change, the model displayed a sensitivity of -0.02 C global warming per percent change in Southern Hemisphere sea ice coverage.

  16. 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

  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

    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, and

  19. 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.

  20. 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

  1. 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

  2. Climate-sensitive feedbacks between hillslope processes and fluvial erosion in sediment-driven incision models

    Science.gov (United States)

    Skov, Daniel S.; Egholm, David L.

    2016-04-01

    Surface erosion and sediment production seem to have accelerated globally as climate cooled in the Late Cenozoic, [Molnar, P. 2004, Herman et al 2013]. Glaciers emerged in many high mountain ranges during the Quaternary, and glaciation therefore represents a likely explanation for faster erosion in such places. Still, observations and measurements point to increases in erosion rates also in landscapes where erosion is driven mainly by fluvial processes [Lease and Ehlers (2013), Reusser (2004)]. Flume experiments and fieldwork have shown that rates of incision are to a large degree controlled by the sediment load of streams [e.g. Sklar and Dietrich (2001), Beer and Turowski (2015)]. This realization led to the formulation of sediment-flux dependent incision models [Sklar and Dietrich (2004)]. The sediment-flux dependence links incision in the channels to hillslope processes that supply sediment to the channels. The rates of weathering and soil transport on the hillslopes are processes that are likely to respond to changing temperatures, e.g. because of vegetation changes or the occurrence of frost. In this study, we perform computational landscape evolution experiments, where the coupling between fluvial incision and hillslope processes is accounted for by coupling a sediment-flux-dependent model for fluvial incision to a climate-dependent model for weathering and hillslope sediment transport. The computational experiments first of all demonstrate a strong positive feedback between channel and hillslope processes. In general, faster weathering leads to higher rates of channel incision, which further increases the weathering rates, mainly because of hillslope steepening. Slower weathering leads to the opposite result. The experiments also demonstrate, however, that the feedbacks vary significantly between different parts of a drainage network. For example, increasing hillslope sediment production may accelerate incision in the upper parts of the catchment, while at

  3. 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

  4. 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.

  5. 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

    2018-05-01

    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), [CO 2 ] (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 [CO 2 ] 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 CO 2 .

  6. 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.

  7. 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.

    2018-05-01

    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.

  8. 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.)

  9. The importance of mixed-phase clouds for climate sensitivity in the global aerosol-climate model ECHAM6-HAM2

    OpenAIRE

    Lohmann, Ulrike; Neubauer, David

    2018-01-01

    Clouds are important in the climate system because of their large influence on the radiation budget. On the one hand, they scatter solar radiation and with that cool the climate. On the other hand, they absorb and re-emit terrestrial radiation, which causes a warming. How clouds change in a warmer climate is one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that also mi...

  10. 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.

  11. Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-12

    Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We looked for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.

  12. 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

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

    KAUST Repository

    Umakanth, U.; Kesarkar, Amit P.; Attada, Raju; Vijaya Bhaskar Rao, S.

    2015-01-01

    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

  14. 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

  15. 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.

  16. 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...

  17. Sensitivity of a coupled climate-carbon cycle model to large volcanic eruptions during the last millennium

    Energy Technology Data Exchange (ETDEWEB)

    Brovkin, Victor; Lorenz, Stephan J.; Jungclaus, Johann; Raddatz, Thomas; Timmreck, Claudia; Reick, Christian H.; Segschneider, Joachim; Six, Katharina (Max Planck Inst. for Meteorology Hamburg (Germany))

    2010-11-15

    The sensitivity of the climate-biogeochemistry system to volcanic eruptions is investigated using the comprehensive Earth System Model developed at the Max Planck Institute for Meteorology. The model includes an interactive carbon cycle with modules for terrestrial biosphere as well as ocean biogeochemistry. The volcanic forcing is based on a recent reconstruction for the last 1200 yr. An ensemble of five simulations is performed and the averaged response of the system is analysed in particular for the largest eruption of the last millennium in the year 1258. After this eruption, the global annual mean temperature drops by 1 K and recovers slowly during 10 yr. Atmospheric CO{sub 2} concentration declines during 4 yr after the eruption by ca. 2 ppmv to its minimum value and then starts to increase towards the pre-eruption level. This CO{sub 2} decrease is explained mainly by reduced heterotrophic respiration on land in response to the surface cooling, which leads to increased carbon storage in soils, mostly in tropical and subtropical regions. The ocean acts as a weak carbon sink, which is primarily due to temperature-induced solubility. This sink saturates 2 yr after the eruption, earlier than the land uptake.

  18. Sensitivity of a coupled climate-carbon cycle model to large volcanic eruptions during the last millennium

    International Nuclear Information System (INIS)

    Brovkin, Victor; Lorenz, Stephan J.; Jungclaus, Johann; Raddatz, Thomas; Timmreck, Claudia; Reick, Christian H.; Segschneider, Joachim; Six, Katharina

    2010-01-01

    The sensitivity of the climate-biogeochemistry system to volcanic eruptions is investigated using the comprehensive Earth System Model developed at the Max Planck Institute for Meteorology. The model includes an interactive carbon cycle with modules for terrestrial biosphere as well as ocean biogeochemistry. The volcanic forcing is based on a recent reconstruction for the last 1200 yr. An ensemble of five simulations is performed and the averaged response of the system is analysed in particular for the largest eruption of the last millennium in the year 1258. After this eruption, the global annual mean temperature drops by 1 K and recovers slowly during 10 yr. Atmospheric CO 2 concentration declines during 4 yr after the eruption by ca. 2 ppmv to its minimum value and then starts to increase towards the pre-eruption level. This CO 2 decrease is explained mainly by reduced heterotrophic respiration on land in response to the surface cooling, which leads to increased carbon storage in soils, mostly in tropical and subtropical regions. The ocean acts as a weak carbon sink, which is primarily due to temperature-induced solubility. This sink saturates 2 yr after the eruption, earlier than the land uptake.

  19. Thermodynamics of climate change: generalized sensitivities

    Directory of Open Access Journals (Sweden)

    V. Lucarini

    2010-10-01

    Full Text Available Using a recent theoretical approach, we study how global warming impacts the thermodynamics of the climate system by performing experiments with a simplified yet Earth-like climate model. The intensity of the Lorenz energy cycle, the Carnot efficiency, the material entropy production, and the degree of irreversibility of the system change monotonically with the CO2 concentration. Moreover, these quantities feature an approximately linear behaviour with respect to the logarithm of the CO2 concentration in a relatively wide range. These generalized sensitivities suggest that the climate becomes less efficient, more irreversible, and features higher entropy production as it becomes warmer, with changes in the latent heat fluxes playing a predominant role. These results may be of help for explaining recent findings obtained with state of the art climate models regarding how increases in CO2 concentration impact the vertical stratification of the tropical and extratropical atmosphere and the position of the storm tracks.

  20. 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.)

  1. Climate sensitivity of glaciers in southern Norway: application of an energy-balance model to Nigardsbreen, Hellstugubreen and Alfotbreen

    NARCIS (Netherlands)

    Oerlemans, J.

    1992-01-01

    Three glaciers in southern Norway, with very different massbalance characteristics, are studied with an energy-balance model of the ice/snow surface. The model simulates the observed mass-balance profiles in a satisfactory way, and can thus be used with some confidence in a study of climate

  2. The role of soil moisture in land surface-atmosphere coupling: climate model sensitivity experiments over India

    Science.gov (United States)

    Williams, Charles; Turner, Andrew

    2015-04-01

    It is generally acknowledged that anthropogenic land use changes, such as a shift from forested land into irrigated agriculture, may have an impact on regional climate and, in particular, rainfall patterns in both time and space. India provides an excellent example of a country in which widespread land use change has occurred during the last century, as the country tries to meet its growing demand for food. Of primary concern for agriculture is the Indian summer monsoon (ISM), which displays considerable seasonal and subseasonal variability. Although it is evident that changing rainfall variability will have a direct impact on land surface processes (such as soil moisture variability), the reverse impact is less well understood. However, the role of soil moisture in the coupling between the land surface and atmosphere needs to be properly explored before any potential impact of changing soil moisture variability on ISM rainfall can be understood. This paper attempts to address this issue, by conducting a number of sensitivity experiments using a state-of-the-art climate model from the UK Meteorological Office Hadley Centre: HadGEM2. Several experiments are undertaken, with the only difference between them being the extent to which soil moisture is coupled to the atmosphere. Firstly, the land surface is fully coupled to the atmosphere, globally (as in standard model configurations); secondly, the land surface is entirely uncoupled from the atmosphere, again globally, with soil moisture values being prescribed on a daily basis; thirdly, the land surface is uncoupled from the atmosphere over India but fully coupled elsewhere; and lastly, vice versa (i.e. the land surface is coupled to the atmosphere over India but uncoupled elsewhere). Early results from this study suggest certain 'hotspot' regions where the impact of soil moisture coupling/uncoupling may be important, and many of these regions coincide with previous studies. Focusing on the third experiment, i

  3. Climate sensitivity of marine energy

    OpenAIRE

    Harrison, Gareth; Wallace, Robin

    2005-01-01

    Marine energy has a significant role to play in lowering carbon emissions within the energy sector. Paradoxically, it may be susceptible to changes in climate that will result from rising carbon emissions. Wind patterns are expected to change and this will alter wave regimes. Despite a lack of definite proof of a link to global warming, wind and wave conditions have been changing over the past few decades. Changes in the wind and wave climate will affect offshore wind and wave energy conversi...

  4. The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations

    Directory of Open Access Journals (Sweden)

    K. Zhang

    2012-10-01

    Full Text Available This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Nudged simulations of the year 2000 are carried out to compare the aerosol properties and global distribution in HAM1 and HAM2, and to evaluate them against various observations. Sensitivity experiments are performed to help identify the impact of each individual update in model formulation.

    Results indicate that from HAM1 to HAM2 there is a marked weakening of aerosol water uptake in the lower troposphere, reducing the total aerosol water burden from 75 Tg to 51 Tg. The main reason is the newly introduced κ-Köhler-theory-based water uptake scheme uses a lower value for the maximum relative humidity cutoff. Particulate organic matter loading in HAM2 is considerably higher in the upper troposphere, because the explicit treatment of secondary organic aerosols allows highly volatile oxidation products of the precursors to be vertically transported to regions of very low temperature and to form aerosols there. Sulfate, black carbon, particulate organic matter and mineral dust in HAM2 have longer lifetimes than in HAM1 because of weaker in-cloud scavenging, which is in turn related to lower autoconversion efficiency in the newly introduced two-moment cloud microphysics scheme. Modification in the sea salt emission scheme causes a significant increase in the ratio (from 1.6 to 7.7 between accumulation mode and coarse mode emission fluxes of

  5. 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

  6. Lessons on climate sensitivity from past climate changes

    NARCIS (Netherlands)

    von der Heydt, A.S.; Dijkstra, H.A.; van de Wal, R.S.W.; Caballero, R.; Crucifix, M.; Foster, G.L.; Huber, M.; Kohler, P.; Rohling, E.; Valdes, P.J.; Ashwin, P.; Bathiany, S.; Berends, T.; van Bree, L.G.J.; Ditlevsen, P.; Ghil, M.; Haywood, A.; Katzav, J.K.; Lohmann, G.; Lohmann, J.; Lucarini, V.; Marzocchi, A.; Palike, H.; Ruvalcaba Baroni, I.; Simon, D.; Sluijs, A.; Stap, L.B.; Tantet, A.; Viebahn, J.; Ziegler, M.

    2016-01-01

    Over the last decade, our understanding of climate sensitivity has improved considerably. The climate system shows variability on many timescales, is subject to non-stationary forcing and it is most likely out of equilibrium with the changes in the radiative forcing. Slow and fast feedbacks

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

    Science.gov (United States)

    Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam

    2011-03-01

    This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

  14. 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

  15. 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

    1997-12-31

    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

  16. 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.

  17. 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

  18. Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

    Science.gov (United States)

    Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

    2014-12-01

    Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

  19. Sensitivity of wave energy to climate change

    OpenAIRE

    Harrison, Gareth; Wallace, Robin

    2005-01-01

    Wave energy will have a key role in meeting renewable energy targets en route to a low carbon economy. However, in common with other renewables, it may be sensitive to changes in climate resulting from rising carbon emissions. Changes in wind patterns are widely anticipated and this will ultimately alter wave regimes. Indeed, evidence indicates that wave heights have been changing over the last 40 years, although there is no proven link to global warming. Changes in the wave climate will impa...

  20. 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

  1. 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

  2. Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Jerez, Sonia; Montavez, Juan P.; Gomez-Navarro, Juan J.; Jimenez-Guerrero, Pedro [Dept. de Fisica, Univ. de Murcia (Spain); Jimenez, Jose M.; Gonzalez-Rouco, Jesus F. [Dept. de Astrofisica y CC. de la Atmosfera, Univ. Complutense de Madrid (Spain)

    2010-06-15

    Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim and Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results. (orig.)

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. Deep time evidence for climate sensitivity increase with warming

    DEFF Research Database (Denmark)

    Shaffer, Gary; Huber, Matthew; Rondanelli, Roberto

    2016-01-01

    warming analogue. We obtain constrained estimates of CO2 and climate sensitivity before and during the PETM and of the PETM carbon input amount and nature. Sensitivity increased from 3.3-5.6 to 3.7-6.5K (Kelvin) into the PETM. When taken together with Last Glacial Maximum and modern estimates, this result...... 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...

  10. Modelling Interglacial Climate

    DEFF Research Database (Denmark)

    Pedersen, Rasmus Anker

    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......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......, with maximum warming occurring in winter. The three scenarios all affect the climate beyond the Arctic, especially the mid-latitude circulation which is sensitive to the location of the ice loss. Together, the results presented in this thesis illustrate that the changes in the Arctic sea ice cover...

  11. 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

  12. A sensitivity study to global desertification in cold and warm climates: results from the IPSL OAGCM model

    Energy Technology Data Exchange (ETDEWEB)

    Alkama, Ramdane [GAME/CNRM, CNRS/Meteo-France, Toulouse (France); Kageyama, Masa; Ramstein, Gilles [LSCE/IPSL UMR CEA-CNRS-UVSQ 8212, Gif sur Yvette (France)

    2012-04-15

    Many simulations have been devoted to study the impact of global desertification on climate, but very few have quantified this impact in very different climate contexts. Here, the climatic impacts of large-scale global desertification in warm (2100 under the SRES A2 scenario forcing), modern and cold (Last Glacial Maximum, 21 thousand years ago) climates are assessed by using the IPSL OAGCM. For each climate, two simulations have been performed, one in which the continents are covered by modern vegetation, the other in which global vegetation is changed to desert i.e. bare soil. The comparison between desert and present vegetation worlds reveals that the prevailing signal in terms of surface energy budget is dominated by the reduction of upward latent heat transfer. Replacing the vegetation by bare soil has similar impacts on surface air temperature South of 20 N in all three climatic contexts, with a warming over tropical forests and a slight cooling over semi-arid and arid areas, and these temperature changes are of the same order of magnitude. North of 20 N, the difference between the temperatures simulated with present day vegetation and in a desert world is mainly due to the change in net radiation related to the modulation of the snow albedo by vegetation, which is obviously absent in the desert world simulations. The enhanced albedo in the desert world simulations induces a large temperature decrease, especially during summer in the cold and modern climatic contexts, whereas the largest difference occurs during winter in the warm climate. This temperature difference requires a larger heat transport to the northern high latitudes. Part of this heat transport increase is achieved through an intensification of the Atlantic Meridional Overturning Circulation. This intensification reduces the sea-ice extent and causes a warming over the North Atlantic and Arctic oceans in the warm climate context. In contrast, the large cooling North of 20 N in both the modern

  13. 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

  14. 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.

  15. 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.

  16. Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  17. The Sensitivity of Evapotranspiration Models to Errors in Model ...

    African Journals Online (AJOL)

    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 based on the ...

  18. Sensitivity analysis of a coupled hydro-mechanical paleo-climate model of density-dependent groundwater flow in discretely fractured crystalline rock

    International Nuclear Information System (INIS)

    Normani, S.D.; Sykes, J.F.

    2011-01-01

    A high resolution three-dimensional sub-regional scale (104 km 2 ) density-dependent, discretely fractured groundwater flow model with hydro-mechanical coupling and pseudo-permafrost was developed from a larger 5734 km 2 regional-scale groundwater flow model of a Canadian Shield setting. The objective of the work is to determine the sensitivity of modelled groundwater system evolution to the hydro-mechanical parameters. The discrete fracture dual continuum numerical model FRAC3DVS-OPG was used for all simulations. A discrete fracture network model delineated from surface features was superimposed onto an approximate 790 000 element domain mesh with approximately 850 000 nodes. Orthogonal fracture faces (between adjacent finite element grid blocks) were used to best represent the irregular discrete fracture zone network. Interconnectivity of the permeable fracture zones is an important pathway for the possible migration and subsequent reduction in groundwater and contaminant residence times. The crystalline rock matrix between these structural discontinuities was assigned mechanical and flow properties characteristic of those reported for the Canadian Shield. The variation of total dissolved solids with depth was assigned using literature data for the Canadian Shield. Performance measures for the sensitivity analysis include equivalent freshwater heads, environmental heads, linear velocities, and depth of penetration by conservative non-decaying tracers released at the surface. A 121 000 year North American continental scale paleo-climate simulation was applied to the domain with ice-sheet histories estimated by the University of Toronto Glacial Systems Model (UofT GSM). Hydro-mechanical coupling between the rock matrix and the pore fluid, due to the ice sheet normal stress, was included in the simulations. The flow model included the influence of vertical strain and assumed that areal loads were homogeneous. Permafrost depth was applied as a permeability reduction

  19. Model confirmation in climate economics

    Science.gov (United States)

    Millner, Antony; McDermott, Thomas K. J.

    2016-01-01

    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. PMID:27432964

  20. Animating climate model data

    Science.gov (United States)

    DaPonte, John S.; Sadowski, Thomas; Thomas, Paul

    2006-05-01

    This paper describes a collaborative project conducted by the Computer Science Department at Southern Connecticut State University and NASA's Goddard Institute for Space Science (GISS). Animations of output from a climate simulation math model used at GISS to predict rainfall and circulation have been produced for West Africa from June to September 2002. These early results have assisted scientists at GISS in evaluating the accuracy of the RM3 climate model when compared to similar results obtained from satellite imagery. The results presented below will be refined to better meet the needs of GISS scientists and will be expanded to cover other geographic regions for a variety of time frames.

  1. Climate of the last millennium: a sensitivity study

    Energy Technology Data Exchange (ETDEWEB)

    Bertrand, Cedric [Royal Meterological Inst. of Belgium, Brussels (Belgium); Loutre, Marie-France; Crucifix, Michel; Berger, Andre [Univ. catholique de Louvain, Louvain la-neuve (Belgium). Inst. d' Astronomie et de Geophysique G. Lemaitre

    2002-05-01

    Seventy-one sensitivity experiments have been performed using a two-dimensional sector-averaged global climate model to assess the potential impact of six different factors on the last millennium climate and in particular on the surface air temperature evolution. Both natural (i.e. solar and volcanism) and anthropogenically-induced (i.e. deforestation, additional greenhouse gases, and tropospheric aerosol burden) climate forcings have been considered. Comparisons of climate reconstructions with model results indicate that all the investigated forcings are needed to simulate the surface air temperature evolution. Due to uncertainties in historical climate forcings and temperature reconstructions, the relative importance of a particular forcing in the explanation of the recorded temperature variance is largely function of the forcing time series used. Nevertheless, our results indicate that whatever the historical solar and volcanic reconstructions may be, these externally driven natural climate forcings are unable to give climate responses comparable in magnitude and time to the late-2Oth-century temperature warming while for earlier periods combination of solar and volcanic forcings can explain the Little Ice Age and the Medieval Warm Period. Only the greenhouse gas forcing allows the model to simulate an accelerated warming rate during the last three decades. The best guess simulation (largest similarity with the reconstruction) for the period starting 1850 AD requires however to include anthropogenic sulphate forcing as well as the impact of deforestation to constrain the magnitude of the greenhouse gas twentieth century warming to better fit the observation. On the contrary, prior to 1850 AD mid-latitude land clearance tends to reinforce the Little Ice age in our simulations.

  2. 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

  3. 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

  4. 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.

  5. 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

  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. 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

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

    Science.gov (United States)

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

    2018-01-17

    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 (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . 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.

  9. 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.

  10. 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

  11. 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

  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

  13. Regional climate simulations over South America: sensitivity to model physics and to the treatment of lateral boundary conditions using the MM5 model

    Energy Technology Data Exchange (ETDEWEB)

    Solman, Silvina A. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina); Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos. Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Pessacg, Natalia L. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina)

    2012-01-15

    In this study the capability of the MM5 model in simulating the main mode of intraseasonal variability during the warm season over South America is evaluated through a series of sensitivity experiments. Several 3-month simulations nested into ERA40 reanalysis were carried out using different cumulus schemes and planetary boundary layer schemes in an attempt to define the optimal combination of physical parameterizations for simulating alternating wet and dry conditions over La Plata Basin (LPB) and the South Atlantic Convergence Zone regions, respectively. The results were compared with different observational datasets and model evaluation was performed taking into account the spatial distribution of monthly precipitation and daily statistics of precipitation over the target regions. Though every experiment was able to capture the contrasting behavior of the precipitation during the simulated period, precipitation was largely underestimated particularly over the LPB region, mainly due to a misrepresentation in the moisture flux convergence. Experiments using grid nudging of the winds above the planetary boundary layer showed a better performance compared with those in which no constrains were imposed to the regional circulation within the model domain. Overall, no single experiment was found to perform the best over the entire domain and during the two contrasting months. The experiment that outperforms depends on the area of interest, being the simulation using the Grell (Kain-Fritsch) cumulus scheme in combination with the MRF planetary boundary layer scheme more adequate for subtropical (tropical) latitudes. The ensemble of the sensitivity experiments showed a better performance compared with any individual experiment. (orig.)

  14. 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.

  15. 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

  16. Sensitivity of ring growth and carbon allocation to climatic variation vary within ponderosa pine trees.

    Science.gov (United States)

    Kerhoulas, Lucy P; Kane, Jeffrey M

    2012-01-01

    Most dendrochronological studies focus on cores sampled from standard positions (main stem, breast height), yet vertical gradients in hydraulic constraints and priorities for carbon allocation may contribute to different growth sensitivities with position. Using cores taken from five positions (coarse roots, breast height, base of live crown, mid-crown branch and treetop), we investigated how radial growth sensitivity to climate over the period of 1895-2008 varies by position within 36 large ponderosa pines (Pinus ponderosa Dougl.) in northern Arizona. The climate parameters investigated were Palmer Drought Severity Index, water year and monsoon precipitation, maximum annual temperature, minimum annual temperature and average annual temperature. For each study tree, we generated Pearson correlation coefficients between ring width indices from each position and six climate parameters. We also investigated whether the number of missing rings differed among positions and bole heights. We found that tree density did not significantly influence climatic sensitivity to any of the climate parameters investigated at any of the sample positions. Results from three types of analyses suggest that climatic sensitivity of tree growth varied with position height: (i) correlations of radial growth and climate variables consistently increased with height; (ii) model strength based on Akaike's information criterion increased with height, where treetop growth consistently had the highest sensitivity and coarse roots the lowest sensitivity to each climatic parameter; and (iii) the correlation between bole ring width indices decreased with distance between positions. We speculate that increased sensitivity to climate at higher positions is related to hydraulic limitation because higher positions experience greater xylem tensions due to gravitational effects that render these positions more sensitive to climatic stresses. The low sensitivity of root growth to all climatic variables

  17. Sensitivity of regional climate to global temperature and forcing

    International Nuclear Information System (INIS)

    Tebaldi, Claudia; O’Neill, Brian; Lamarque, Jean-François

    2015-01-01

    The sensitivity of regional climate to global average radiative forcing and temperature change is important for setting global climate policy targets and designing scenarios. Setting effective policy targets requires an understanding of the consequences exceeding them, even by small amounts, and the effective design of sets of scenarios requires the knowledge of how different emissions, concentrations, or forcing need to be in order to produce substantial differences in climate outcomes. Using an extensive database of climate model simulations, we quantify how differences in global average quantities relate to differences in both the spatial extent and magnitude of climate outcomes at regional (250–1250 km) scales. We show that differences of about 0.3 °C in global average temperature are required to generate statistically significant changes in regional annual average temperature over more than half of the Earth’s land surface. A global difference of 0.8 °C is necessary to produce regional warming over half the land surface that is not only significant but reaches at least 1 °C. As much as 2.5 to 3 °C is required for a statistically significant change in regional annual average precipitation that is equally pervasive. Global average temperature change provides a better metric than radiative forcing for indicating differences in regional climate outcomes due to the path dependency of the effects of radiative forcing. For example, a difference in radiative forcing of 0.5 W m −2 can produce statistically significant differences in regional temperature over an area that ranges between 30% and 85% of the land surface, depending on the forcing pathway. (letter)

  18. The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

    Directory of Open Access Journals (Sweden)

    M. Keller

    2018-04-01

    Full Text Available Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM and 2 km grid spacing (convection-resolving model, CRM are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW using a vertically uniform warming and the other with vertically dependent warming (VW that enables changes in lapse rate.The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.

  19. The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

    Science.gov (United States)

    Keller, Michael; Kröner, Nico; Fuhrer, Oliver; Lüthi, Daniel; Schmidli, Juerg; Stengel, Martin; Stöckli, Reto; Schär, Christoph

    2018-04-01

    Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM) and 2 km grid spacing (convection-resolving model, CRM) are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW) using a vertically uniform warming and the other with vertically dependent warming (VW) that enables changes in lapse rate. The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.

  20. 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.)

  1. 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.

  2. Sensitivity study of heavy precipitation in Limited Area Model climate simulations: influence of the size of the domain and the use of the spectral nudging technique

    Science.gov (United States)

    Colin, Jeanne; Déqué, Michel; Radu, Raluca; Somot, Samuel

    2010-10-01

    We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment.

  3. Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

    Science.gov (United States)

    Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

    2018-01-01

    The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

  4. 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...

  5. Runoff sensitivity to climate change in the Nile River Basin

    Science.gov (United States)

    Hasan, Emad; Tarhule, Aondover; Kirstetter, Pierre-Emmanuel; Clark, Race; Hong, Yang

    2018-06-01

    In data scarce basins, such as the Nile River Basin (NRB) in Africa, constraints related to data availability, quality, and access often complicate attempts to estimate runoff sensitivity using conventional methods. In this paper, we show that by integrating the concept of the aridity index (AI) (derived from the Budyko curve) and climate elasticity, we can obtain the first order response of the runoff sensitivity using minimal data input and modeling expertise or experience. The concept of runoff elasticity relies on the fact that the energy available for evapotranspiration plays a major role in determining whether the precipitation received within a drainage basin generates runoff. The approach does not account for human impacts on runoff modification and or diversions. By making use of freely available gauge-corrected satellite data for precipitation, temperature, runoff, and potential evapotranspiration, we derived the sensitivity indicator (β) to determine the runoff response to changes in precipitation and temperature for four climatic zones in the NRB, namely, tropical, subtropical, semiarid and arid zones. The proposed sensitivity indicator can be partitioned into different elasticity components i.e: precipitation (εp), potential evapotranspiration (εETp), temperature (εT) and the total elasticity (εtot) . These elasticities allow robust quantification of the runoff response to the potential changes in precipitation and temperature with a high degree of accuracy. Results indicate that the tropical zone is energy-constrained with low sensitivity, (β 1.0) . The subtropical-highland zone moves between energy-limited to water-limited conditions during periods of wet and dry spells with varying sensitivity. The semiarid and arid zones are water limited, with high sensitivity, (β > 1.0) . The calculated runoff elasticities show that a 10% decrease in precipitation leads to a decrease in runoff of between 19% in the tropical zone and 30% in the arid zones

  6. Economics of climate change : sensitivity analysis of social cost of carbon

    OpenAIRE

    Torniainen, Sami

    2016-01-01

    Social cost of carbon (SCC) is the key concept in the economics of climate change. It measures the economic cost of climate impacts. SCC has influence on how beneficial it is to prevent climate change: if the value of SCC increases, investments to low-carbon technology become more attractive and profitable. This paper examines the sensitivity of two important assumptions that affect to SCC: the choice of a discount rate and time horizon. Using the integrated assessment model, ...

  7. Sensitivity of tropical climate to low-level clouds in the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Zeng-Zhen [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); NCEP/NWS/NOAA, Climate Prediction Center, Camp Springs, MD (United States); Huang, Bohua; Schneider, Edwin K. [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); George Mason University, Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, Fairfax, VA (United States); Hou, Yu-Tai; Yang, Fanglin [NCEP/NWS/NOAA, Environmental Modeling Center, Camp Springs, MD (United States); Wang, Wanqiu [NCEP/NWS/NOAA, Climate Prediction Center, Camp Springs, MD (United States); Stan, Cristiana [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States)

    2011-05-15

    In this work, we examine the sensitivity of tropical mean climate and seasonal cycle to low clouds and cloud liquid water path (CLWP) by prescribing them in the NCEP climate forecast system (CFS). It is found that the change of low cloud cover alone has a minor influence on the amount of net shortwave radiation reaching the surface and on the warm biases in the southeastern Atlantic. In experiments where CLWP is prescribed using observations, the mean climate in the tropics is improved significantly, implying that shortwave radiation absorption by CLWP is mainly responsible for reducing the excessive surface net shortwave radiation over the southern oceans in the CFS. Corresponding to large CLWP values in the southeastern oceans, the model generates large low cloud amounts. That results in a reduction of net shortwave radiation at the ocean surface and the warm biases in the sea surface temperature in the southeastern oceans. Meanwhile, the cold tongue and associated surface wind stress in the eastern oceans become stronger and more realistic. As a consequence of the overall improvement of the tropical mean climate, the seasonal cycle in the tropical Atlantic is also improved. Based on the results from these sensitivity experiments, we propose a model bias correction approach, in which CLWP is prescribed only in the southeastern Atlantic by using observed annual mean climatology of CLWP. It is shown that the warm biases in the southeastern Atlantic are largely eliminated, and the seasonal cycle in the tropical Atlantic Ocean is significantly improved. Prescribing CLWP in the CFS is then an effective interim technique to reduce model biases and to improve the simulation of seasonal cycle in the tropics. (orig.)

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

    2015-02-01

    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.

  15. 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.

  16. 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)

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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...... of multi-decadal time series of annual shrub growth provide an underused resource to explore climate–growth relationships. Here, we analyse circumpolar data from 37 Arctic and alpine sites in 9 countries, including 25 species, and 42,000 annual growth records from 1,821 individuals. Our analyses...... demonstrate that the sensitivity of shrub growth to climate was: (1) heterogeneous, with European sites showing greater summer temperature sensitivity than North American sites, and (2) higher at sites with greater soil moisture and for taller shrubs (for example, alders and willows) growing at their northern...

  2. Climate sensitivity to Arctic seaway restriction during the early Paleogene

    Science.gov (United States)

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

    2009-09-01

    The opening and closing of ocean gateways affects the global distribution of heat, salt, and moisture, potentially driving climatic change on regional to global scales. Between 65 and 45 million years ago (Ma), during the early Paleogene, exchange between the Arctic and global oceans occurred through two narrow and shallow seaways, the Greenland-Norway seaway and the Turgai Strait. Sediments from the Arctic Ocean suggest that, during this interval, the surface ocean was warm, brackish, and episodically enabled the freshwater fern Azolla to bloom. The precise mechanisms responsible for the development of these conditions in the Paleogene Arctic remain uncertain. Here we show results from an isotope-enabled, atmosphere-ocean general circulation model, which indicate that Northern Hemisphere climate would have been very sensitive to the degree of oceanic exchange through the Arctic seaways. We also present modelled estimates of seawater and calcite δ18O for the Paleogene. By restricting these seaways, we simulate freshening of the surface Arctic Ocean to ~ 6 psu and warming of sea-surface temperatures by 2 °C in the North Atlantic and 5-10 °C in the Labrador Sea. Our results may help explain the occurrence of low-salinity tolerant taxa in the Arctic Ocean during the Eocene and provide a mechanism for enhanced warmth in the north western Atlantic. We propose that the formation of a volcanic land-bridge between Greenland and Europe could have caused increased ocean convection and warming of intermediate waters in the Atlantic. If true, this result is consistent with the theory that bathymetry changes may have caused thermal destabilisation of methane clathrates and supports a tectonic trigger hypothesis for the Paleocene Eocene Thermal Maximum (PETM).

  3. 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

  4. 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.

  5. 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

  6. Climate Change Sensitivity of Multi-Species Afforestation in Semi-Arid Benin

    Directory of Open Access Journals (Sweden)

    Florent Noulèkoun

    2018-06-01

    Full Text Available The early growth stage is critical in the response of trees to climate change and variability. It is not clear, however, what climate metrics are best to define the early-growth sensitivity in assessing adaptation strategies of young forests to climate change. Using a combination of field experiments and modelling, we assessed the climate sensitivity of two promising afforestation species, Jatropha curcas L. and Moringa oleifera Lam., by analyzing their predicted climate–growth relationships in the initial two years after planting on degraded cropland in the semi-arid zone of Benin. The process-based WaNuLCAS model (version 4.3, World Agroforestry Centre, Bogor, Indonesia was used to simulate aboveground biomass growth for each year in the climate record (1981–2016, either as the first or as the second year of tree growth. Linear mixed models related the annual biomass growth to climate indicators, and climate sensitivity indices quantified climate–growth relationships. In the first year, the length of dry spells had the strongest effect on tree growth. In the following year, the annual water deficit and length of dry season became the strongest predictors. Simulated rooting depths greater than those observed in the experiments enhanced biomass growth under extreme dry conditions and reduced sapling sensitivity to drought. Projected increases in aridity implied significant growth reduction, but a multi-species approach to afforestation using species that are able to develop deep-penetrating roots should increase the resilience of young forests to climate change. The results illustrate that process-based modelling, combined with field experiments, can be effective in assessing the climate–growth relationships of tree species.

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

    KAUST Repository

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

    2017-01-01

    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/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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Sensitivity of simulated maize crop yields to regional climate in the Southwestern United States

    Science.gov (United States)

    Kim, S.; Myoung, B.; Stack, D.; Kim, J.; Hatzopoulos, N.; Kafatos, M.

    2013-12-01

    The sensitivity of maize yield to the regional climate in the Southwestern United States (SW US) has been investigated by using a crop-yield simulation model (APSIM) in conjunction with meteorological forcings (daily minimum and maximum temperature, precipitation, and radiation) from the North American Regional Reanalysis (NARR) dataset. The primary focus of this study is to look at the effects of interannual variations of atmospheric components on the crop productivity in the SW US over the 21-year period (1991 to 2011). First of all, characteristics and performance of APSIM was examined by comparing simulated maize yields with observed yields from United States Department of Agriculture (USDA) and the leaf-area index (LAI) from MODIS satellite data. Comparisons of the simulated maize yield with the available observations show that the crop model can reasonably reproduce observed maize yields. Sensitivity tests were performed to assess the relative contribution of each climate driver to regional crop yield. Sensitivity experiments show that potential crop production responds nonlinearly to climate drivers and the yield sensitivity varied among geographical locations depending on their mean climates. Lastly, a detailed analysis of both the spatial and temporal variations of each climate driver in the regions where maize is actually grown in three states (CA, AZ, and NV) in the SW US was performed.

  14. 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.

  15. 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.

  16. Marine low cloud sensitivity to an idealized climate change : The CGILS LES intercomparison

    NARCIS (Netherlands)

    Blossey, P.N.; Bretherton, C.S.; Zhang, M.; Cheng, A.; Endo, S.; Heus, T.; Liu, Y.; Lock, A.P.; De Roode, S.R.; Xu, K.M.

    2013-01-01

    Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large-eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs)

  17. Sensitivity of intermittent streams to climate variations in the USA

    Science.gov (United States)

    Eng, Kenny; Wolock, David M.; Dettinger, Mike

    2015-01-01

    There is a great deal of interest in the literature on streamflow changes caused by climate change because of the potential negative effects on aquatic biota and water supplies. Most previous studies have primarily focused on perennial streams, and there have been only a few studies examining the effect of climate variability on intermittent streams. Our objectives in this study were to (1) identify regions of similar zero-flow behavior, and (2) evaluate the sensitivity of intermittent streams to historical variability in climate in the United States. This study was carried out at 265 intermittent streams by evaluating: (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with climate (magnitudes, durations and intensity), and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results identified five distinct seasonality patterns in the zero-flow events. In addition, strong associations between the low-flow metrics and historical changes in climate were found. The decadal analysis suggested no significant seasonal shifts or decade-to-decade trends in the low-flow metrics. The lack of trends or changes in seasonality is likely due to unchanged long-term patterns in precipitation over the time period examined.

  18. 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

  19. 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

  20. Sensitivity of groundwater recharge using climatic analogues and HYDRUS-1D

    Directory of Open Access Journals (Sweden)

    B. Leterme

    2012-08-01

    Full Text Available The sensitivity of groundwater recharge to different climate conditions was simulated using the approach of climatic analogue stations, i.e. stations presently experiencing climatic conditions corresponding to a possible future climate state. The study was conducted in the context of a safety assessment of a future near-surface disposal facility for low and intermediate level short-lived radioactive waste in Belgium; this includes estimation of groundwater recharge for the next millennia. Groundwater recharge was simulated using the Richards based soil water balance model HYDRUS-1D and meteorological time series from analogue stations. This study used four analogue stations for a warmer subtropical climate with changes of average annual precipitation and potential evapotranspiration from −42% to +5% and from +8% to +82%, respectively, compared to the present-day climate. Resulting water balance calculations yielded a change in groundwater recharge ranging from a decrease of 72% to an increase of 3% for the four different analogue stations. The Gijon analogue station (Northern Spain, considered as the most representative for the near future climate state in the study area, shows an increase of 3% of groundwater recharge for a 5% increase of annual precipitation. Calculations for a colder (tundra climate showed a change in groundwater recharge ranging from a decrease of 97% to an increase of 32% for four different analogue stations, with an annual precipitation change from −69% to −14% compared to the present-day climate.

  1. Variations in the Sensitivity of Shrub Growth to Climate Change along Arctic Environmental and Biotic Gradients

    Science.gov (United States)

    Beck, P. S. A.; Myers-Smith, I. H.; Elmendorf, S.; Georges, D.

    2015-12-01

    Despite evidence of rapid shrub expansion at many Arctic sites and the profound effects this has on ecosystem structure, biogeochemical cycling, and land-atmosphere feedbacks in the Arctic, the drivers of shrub growth remain poorly understood. The compilation of 41,576 annual shrub growth measurements made around the Arctic, allowed for the first systematic evaluation of the climate sensitivity of Arctic shrub growth, i.e. the strength of the relationship between annual shrub growth and monthly climate variables. The growth measurements were taken on 1821 plants of 25 species at 37 arctic and alpine sites, either as annual ring widths or as stem increments. We evaluated climate sensitivity of shrub growth for each genus-by-site combination in this data set based on the performance and parameters of linear mixed models that used CRU TS3.21 climate data as predictors of shrub growth between 1950 and 2010. 76% of genus-by-site combinations showed climate sensitive growth, but climate-growth relationships varied with soil moisture, species canopy height, and geographic position within the species ranges. Shrubs growing at sites with more soil moisture showed greater climate sensitivity, suggesting that water availability might limit shrub growth if continued warming isn't matched by a steady increase in soil moisture. Tall shrub species growing at their northern range limit were particularly climate sensitive causing climate sensitivity of shrubs to peak at the transition between Low and High Arctic, where carbon storage in permafrost is greatest. Local and regional studies have documented matching spatial and temporal patterns in dendrochronological measurements and satellite observations of vegetation indices both in boreal and Arctic regions. Yet the circumarctic comparison of patterns in dendrochronological and remote sensing data sets yielded poor levels of agreement. In much of the Arctic, steep environmental gradients generate fine spatial patterns of vegetation

  2. 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 those present in the astronomical forcing. We shall do this in terms of a general framework of conceptual dynamical models, which may or may not exhibit internal self-sustained oscillations. We introduce and discuss two distinct mechanisms for a periodic response at a dierent period to a periodic...

  3. 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.

  4. 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...

  5. Sensitivity of climate mitigation strategies to natural disturbances

    International Nuclear Information System (INIS)

    Le Page, Y; Hurtt, G; Thomson, A M; Bond-Lamberty, B; Patel, P; Wise, M; Calvin, K; Kyle, P; Clarke, L; Edmonds, J; Janetos, A

    2013-01-01

    The present and future concentration of atmospheric carbon dioxide depends on both anthropogenic and natural sources and sinks of carbon. Most proposed climate mitigation strategies rely on a progressive transition to carbon-efficient technologies to reduce industrial emissions, substantially supported by policies to maintain or enhance the terrestrial carbon stock in forests and other ecosystems. This strategy may be challenged if terrestrial sequestration capacity is affected by future climate feedbacks, but how and to what extent is little understood. Here, we show that climate mitigation strategies are highly sensitive to future natural disturbance rates (e.g. fires, hurricanes, droughts), because of the potential effect of disturbances on the terrestrial carbon balance. Generally, altered disturbance rates affect the pace of societal and technological transitions required to achieve the mitigation target, with substantial consequences on the energy sector and the global economy. An understanding of the future dynamics and consequences of natural disturbances on terrestrial carbon balance is thus essential for developing robust climate mitigation strategies and policies. (letter)

  6. 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.

  7. 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.

  8. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    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...... 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 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...

  9. 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.

  10. Climate Change Modelling and Its Roles to Chinese Crops Yield

    Institute of Scientific and Technical Information of China (English)

    JU Hui; LIN Er-da; Tim Wheeler; Andrew Challinor; JIANG Shuai

    2013-01-01

    Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10%for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. Reconstructing Holocene climate using a climate model: Model strategy and preliminary results

    Science.gov (United States)

    Haberkorn, K.; Blender, R.; Lunkeit, F.; Fraedrich, K.

    2009-04-01

    An Earth system model of intermediate complexity (Planet Simulator; PlaSim) is used to reconstruct Holocene climate based on proxy data. The Planet Simulator is a user friendly general circulation model (GCM) suitable for palaeoclimate research. Its easy handling and the modular structure allow for fast and problem dependent simulations. The spectral model is based on the moist primitive equations conserving momentum, mass, energy and moisture. Besides the atmospheric part, a mixed layer-ocean with sea ice and a land surface with biosphere are included. The present-day climate of PlaSim, based on an AMIP II control-run (T21/10L resolution), shows reasonable agreement with ERA-40 reanalysis data. Combining PlaSim with a socio-technological model (GLUES; DFG priority project INTERDYNAMIK) provides improved knowledge on the shift from hunting-gathering to agropastoral subsistence societies. This is achieved by a data assimilation approach, incorporating proxy time series into PlaSim to initialize palaeoclimate simulations during the Holocene. For this, the following strategy is applied: The sensitivities of the terrestrial PlaSim climate are determined with respect to sea surface temperature (SST) anomalies. Here, the focus is the impact of regionally varying SST both in the tropics and the Northern Hemisphere mid-latitudes. The inverse of these sensitivities is used to determine the SST conditions necessary for the nudging of land and coastal proxy climates. Preliminary results indicate the potential, the uncertainty and the limitations of the method.

  16. Climate Ocean Modeling on Parallel Computers

    Science.gov (United States)

    Wang, P.; Cheng, B. N.; Chao, Y.

    1998-01-01

    Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

  17. Increased sensitivity to climate change in disturbed ecosystems

    DEFF Research Database (Denmark)

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

    2015-01-01

    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 relatio......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...

  18. A sensitivity analysis of hazardous waste disposal site climatic and soil design parameters using HELP3

    International Nuclear Information System (INIS)

    Adelman, D.D.; Stansbury, J.

    1997-01-01

    The Resource Conservation and Recovery Act (RCRA) Subtitle C, Comprehensive Environmental Response, Compensation, And Liability Act (CERCLA), and subsequent amendments have formed a comprehensive framework to deal with hazardous wastes on the national level. Key to this waste management is guidance on design (e.g., cover and bottom leachate control systems) of hazardous waste landfills. The objective of this research was to investigate the sensitivity of leachate volume at hazardous waste disposal sites to climatic, soil cover, and vegetative cover (Leaf Area Index) conditions. The computer model HELP3 which has the capability to simulate double bottom liner systems as called for in hazardous waste disposal sites was used in the analysis. HELP3 was used to model 54 combinations of climatic conditions, disposal site soil surface curve numbers, and leaf area index values to investigate how sensitive disposal site leachate volume was to these three variables. Results showed that leachate volume from the bottom double liner system was not sensitive to these parameters. However, the cover liner system leachate volume was quite sensitive to climatic conditions and less sensitive to Leaf Area Index and curve number values. Since humid locations had considerably more cover liner system leachate volume than and locations, different design standards may be appropriate for humid conditions than for and conditions

  19. 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.

  20. 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.

  1. Regional model simulations of New Zealand climate

    Science.gov (United States)

    Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

    1998-03-01

    Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

  2. 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. [...

  3. 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.

  4. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

  5. Tropical interannual variability in a global coupled GCM: Sensitivity to mean climate state

    Energy Technology Data Exchange (ETDEWEB)

    Moore, A.M. [Bureau of Meterology Research Centre, Melbourne, Victoria (Australia)

    1995-04-01

    A global coupled ocean-atmosphere-sea ice general circulation model is used to study interannual variability in the Tropics. Flux correction is used to control the mean climate of the coupled system, and in one configuration of the coupled model, interannual variability in the tropical Pacific is dominated by westward moving anomalies. Through a series of experiments in which the equatorial ocean wave speeds and ocean-atmosphere coupling strength are varied, it is demonstrated that these westward moving disturbances are probably some manifestation of what Neelin describes as an {open_quotes}SST mode.{close_quotes} By modifying the flux correction procedure, the mean climate of the coupled model can be changed. A fairly modest change in the mean climate is all that is required to excite eastward moving anomalies in place of the westward moving SST modes found previously. The apparent sensitivity of the nature of tropical interannual variability to the mean climate state in a coupled general circulation model such as that used here suggests that caution is advisable if we try to use such models to answer questions relating to changes in ENSO-like variability associated with global climate change. 41 refs., 23 figs., 1 tab.

  6. The ice-core record - Climate sensitivity and future greenhouse warming

    Science.gov (United States)

    Lorius, C.; Raynaud, D.; Jouzel, J.; Hansen, J.; Le Treut, H.

    1990-01-01

    The prediction of future greenhouse-gas-warming depends critically on the sensitivity of earth's climate to increasing atmospheric concentrations of these gases. Data from cores drilled in polar ice sheets show a remarkable correlation between past glacial-interglacial temperature changes and the inferred atmospheric concentration of gases such as carbon dioxide and methane. These and other palaeoclimate data are used to assess the role of greenhouse gases in explaining past global climate change, and the validity of models predicting the effect of increasing concentrations of such gases in the atmosphere.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    KAUST Repository

    Imbers, Jara; Lopez, Ana; Huntingford, Chris; Allen, Myles

    2014-01-01

    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.

  12. 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

  13. Using Impact-Relevant Sensitivities to Efficiently Evaluate and Select Climate Change Scenarios

    Science.gov (United States)

    Vano, J. A.; Kim, J. B.; Rupp, D. E.; Mote, P.

    2014-12-01

    We outline an efficient approach to help researchers and natural resource managers more effectively use global climate model information in their long-term planning. The approach provides an estimate of the magnitude of change of a particular impact (e.g., summertime streamflow) from a large ensemble of climate change projections prior to detailed analysis. These estimates provide both qualitative information as an end unto itself (e.g., the distribution of future changes between emissions scenarios for the specific impact) and a judicious, defensible evaluation structure that can be used to qualitatively select a sub-set of climate models for further analysis. More specifically, the evaluation identifies global climate model scenarios that both (1) span the range of possible futures for the variable/s most important to the impact under investigation, and (2) come from global climate models that adequately simulate historical climate, providing plausible results for the future climate in the region of interest. To identify how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an impact variable (e.g., streamflow magnitude, vegetation carbon) responds locally to projected regional temperature and precipitation changes. We demonstrate our technique over the Pacific Northwest, focusing on two types of impacts each in three distinct geographic settings: (a) changes in streamflow magnitudes in critical seasons for water management in the Willamette, Yakima, and Upper Columbia River basins; and (b) changes in annual vegetation carbon in the Oregon and Washington Coast Ranges, Western Cascades, and Columbia Basin ecoregions.

  14. 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

  15. Comparison of winter wheat yield sensitivity to climate variables under irrigated and rain-fed conditions

    Science.gov (United States)

    Xiao, Dengpan; Shen, Yanjun; Zhang, He; Moiwo, Juana P.; Qi, Yongqing; Wang, Rende; Pei, Hongwei; Zhang, Yucui; Shen, Huitao

    2016-09-01

    Crop simulation models provide alternative, less time-consuming, and cost-effective means of determining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat ( Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (CO2) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCP. The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCP. There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2°C was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1°C decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rainfed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to 560 ppm, and yield under YY increased linearly by ≈7.0% for the same increase in CO2 concentration.

  16. 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

  17. Modeling the uncertain impacts of climate change

    International Nuclear Information System (INIS)

    Liebetrau, A.M.

    1992-08-01

    Human and earth systems are extremely complex processes. The modeling of these systems to assess the effects of climate change is an activity fraught with uncertainty. System models typically involve the linking of a series of computer codes, each of which is a detailed model of some physical or social process in its own right. In such system models, the output from one process model is the input to another. Traditional methods for dealing with uncertainty are inadequate because of the sheer complexity of the modeling effort: Monte Carlo methods and the exhaustive evaluation of ''what if?'' scenarios estimate sensitivities fail because of the heavy computational burden. More efficient methods are required for learning about system models that are constructed from a collection of computer codes. A two-tiered modeling approach is being developed to estimate the distribution of outcomes from a series of nested models. The basic strategy is to develop a simplified executive, or simplified system code (SSC), that is analogous to the more complex underlying code. An essential feature of the SSC is that it uses information abstracted from the detailed underlying process codes in a manner that preserves their essential features and interactions among them. Of course, to be useful, the SSC must be much faster to run than its complex counterpart. The success of the SSC modeling strategy depends on the methods used to extract essential features of the complex underlying codes

  18. Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

    Science.gov (United States)

    Ali, H.; Mishra, V.

    2017-12-01

    Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

  19. Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

    Science.gov (United States)

    Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

    2011-12-01

    Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

  20. 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.

  1. Climate Modeling and Causal Identification for Sea Ice Predictability

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-12

    This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments in which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.

  2. 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.

  3. Tropical-extratropical climate interaction as revealed in idealized coupled climate model experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Haijun [Peking University, Department of Atmospheric Science and Laboratory for Severe Storm and Flood Disasters, School of Physics, Beijing (China); Liu, Zhengyu [University of Wisconsin-Madison, Center for Climatic Research and Department of the Atmospheric and Oceanic Sciences, Madison, WI (United States)

    2005-06-01

    Tropical-extratropical climate interactions are studied by idealized experiments with a prescribed 2 C SST anomaly at different latitude bands in a coupled climate model. Instead of focusing on intrinsic climate variability, this work investigates the mean climate adjustment to remote external forcing. The extratropical impact on tropical climate can be as strong as the tropical impact on extratropical climate, with the remote sea surface temperature (SST) response being about half the magnitude of the imposed SST change in the forcing region. The equatorward impact of extratropical climate is accomplished by both the atmospheric bridge and the oceanic tunnel. About two-thirds of the tropical SST change comes from the atmospheric bridge, while the remaining one-third comes from the oceanic tunnel. The equatorial SST increase is first driven by the reduced latent heat flux and the weakened poleward surface Ekman transport, and then enhanced by the decrease in subtropical cells' strength and the equatorward subduction of warm anomalies. In contrast, the poleward impact of tropical climate is accomplished mainly by the atmospheric bridge, which is responsible for extratropical temperature changes in both the surface and subsurface. Sensitivity experiments also show the dominant role of the Southern Hemisphere oceans in the tropical climate change. (orig.)

  4. 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...

  5. 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.|info:eu-repo/dai/nl/290472113

    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

  6. 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

  7. Estimating daily climatologies for climate indices derived from climate model data and observations

    Science.gov (United States)

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

  8. 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

  9. 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.

  10. Estimating option values of solar radiation management assuming that climate sensitivity is uncertain.

    Science.gov (United States)

    Arino, Yosuke; Akimoto, Keigo; Sano, Fuminori; Homma, Takashi; Oda, Junichiro; Tomoda, Toshimasa

    2016-05-24

    Although solar radiation management (SRM) might play a role as an emergency geoengineering measure, its potential risks remain uncertain, and hence there are ethical and governance issues in the face of SRM's actual deployment. By using an integrated assessment model, we first present one possible methodology for evaluating the value arising from retaining an SRM option given the uncertainty of climate sensitivity, and also examine sensitivities of the option value to SRM's side effects (damages). Reflecting the governance challenges on immediate SRM deployment, we assume scenarios in which SRM could only be deployed with a limited degree of cooling (0.5 °C) only after 2050, when climate sensitivity uncertainty is assumed to be resolved and only when the sensitivity is found to be high (T2x = 4 °C). We conduct a cost-effectiveness analysis with constraining temperature rise as the objective. The SRM option value is originated from its rapid cooling capability that would alleviate the mitigation requirement under climate sensitivity uncertainty and thereby reduce mitigation costs. According to our estimates, the option value during 1990-2049 for a +2.4 °C target (the lowest temperature target level for which there were feasible solutions in this model study) relative to preindustrial levels were in the range between $2.5 and $5.9 trillion, taking into account the maximum level of side effects shown in the existing literature. The result indicates that lower limits of the option values for temperature targets below +2.4 °C would be greater than $2.5 trillion.

  11. Generating evidence on gender sensitive climate-smart agriculture ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Specifically, it is important to understand how gender dynamics influence ... for CSA to buffer or mitigate the negative effects of climate change, promote equality, ... long-term climate action to reduce social inequality, promote greater gender ...

  12. 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.

  13. 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...

  14. 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.

  15. Model Driven Development of Data Sensitive Systems

    DEFF Research Database (Denmark)

    Olsen, Petur

    2014-01-01

    storage systems, where the actual values of the data is not relevant for the behavior of the system. For many systems the values are important. For instance the control flow of the system can be dependent on the input values. We call this type of system data sensitive, as the execution is sensitive...... 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...

  16. 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.

  17. Climate change sensitivity of multi-species afforestation in semi-arid Benin

    NARCIS (Netherlands)

    Noulèkoun, Florent; Khamzina, Asia; Naab, Jesse B.; Khasanah, N.; Noordwijk, van Meine; Lamers, John P.A.

    2018-01-01

    The early growth stage is critical in the response of trees to climate change and variability. It is not clear, however, what climate metrics are best to define the early-growth sensitivity in assessing adaptation strategies of young forests to climate change. Using a combination of field

  18. 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

  19. 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)

  20. Mixing parametrizations for ocean climate modelling

    Science.gov (United States)

    Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir

    2016-04-01

    The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model

  1. 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.

  2. 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

  3. 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

  4. Climate: Policy, Modeling, and Federal Priorities (Invited)

    Science.gov (United States)

    Koonin, S.; Department Of Energy Office Of The Under SecretaryScience

    2010-12-01

    The Administration has set ambitious national goals to reduce our dependence on fossil fuels and reduce anthropogenic greenhouse gas (GHG) emissions. The US and other countries involved in the U.N. Framework Convention on Climate Change continue to work toward a goal of establishing a viable treaty that would encompass limits on emissions and codify actions that nations would take to reduce emissions. These negotiations are informed by the science of climate change and by our understanding of how changes in technology and the economy might affect the overall climate in the future. I will describe the present efforts within the U.S. Department of Energy, and the federal government more generally, to address issues related to climate change. These include state-of-the-art climate modeling and uncertainty assessment, economic and climate scenario planning based on best estimates of different technology trajectories, adaption strategies for climate change, and monitoring and reporting for treaty verification.

  5. Future directions in climate modeling: A climate impacts perspective

    International Nuclear Information System (INIS)

    Mearns, L.O.

    1990-01-01

    One of the most serious impediments to further progress on the determination of specific impacts of climate change on relevant earth systems is the lack of precise and accurate scenarios of regional change. Spatial resolution of models is generally coarse (5-10 degree, corresponding to 550-1,100 km), and the modeling of physical processes is quite crude. Three main areas in which improvements in the modeling of physical processes are being made are modeling of surface processes, modeling of oceans and coupling of oceans and atmospheric models, and modeling of clouds. Improvements are required in the modeling of surface hydrology and vegetative effects, which have significant impact on the albedo scheme used. Oceans are important in climate modeling for the following reasons: delay of warming due to oceanic heat absorption; effect of mean meridional circulation; control of regional patterns of sea surface temperatures and sea ice by wind driven currents; absorption of atmospheric carbon dioxide by the oceans; and determination of interannual climatic variability via variability in sea surface temperature. The effects of clouds on radiation balance is highly significant. Clouds both reflect shortwave radiation and trap longwave radiation. Most cloud properties are sub-grid scale and thus difficult to include explicitly in models. 25 refs., 1 tab

  6. 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.

  7. Climate change sensitivity index for Pacific salmon habitat in southeast Alaska.

    Directory of Open Access Journals (Sweden)

    Colin S Shanley

    Full Text Available Global climate change may become one of the most pressing challenges to Pacific Salmon conservation and management for southeast Alaska in the 21st Century. Predicted hydrologic change associated with climate change will likely challenge the ability of specific stocks to adapt to new flow regimes and resulting shifts in spawning and rearing habitats. Current research suggests egg-to-fry survival may be one of the most important freshwater limiting factors in Pacific Salmon's northern range due to more frequent flooding events predicted to scour eggs from mobile spawning substrates. A watershed-scale hydroclimatic sensitivity index was developed to map this hypothesis with an historical stream gauge station dataset and monthly multiple regression-based discharge models. The relative change from present to future watershed conditions predicted for the spawning and incubation period (September to March was quantified using an ensemble global climate model average (ECHAM5, HadCM3, and CGCM3.1 and three global greenhouse gas emission scenarios (B1, A1B, and A2 projected to the year 2080. The models showed the region's diverse physiography and climatology resulted in a relatively predictable pattern of change: northern mainland and steeper, snow-fed mountainous watersheds exhibited the greatest increases in discharge, an earlier spring melt, and a transition into rain-fed hydrologic patterns. Predicted streamflow increases for all watersheds ranged from approximately 1-fold to 3-fold for the spawning and incubation period, with increased peak flows in the spring and fall. The hydroclimatic sensitivity index was then combined with an index of currently mapped salmon habitat and species diversity to develop a research and conservation priority matrix, highlighting potentially vulnerable to resilient high-value watersheds. The resulting matrix and observed trends are put forth as a framework to prioritize long-term monitoring plans, mitigation

  8. 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.

  9. 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 Institutional support: RVO:86652079 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 Subject RIV: GC - Agronomy OBOR OECD: Agronomy, plant breeding and plant protection Impact factor: 2.571, year: 2016

  10. 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

  11. A review on regional convection permitting climate modeling

    Science.gov (United States)

    van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

    2016-04-01

    With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies

  12. 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

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

    Institute of Scientific and Technical Information of China (English)

    WANG Shuang-Jing; CAO Long; LI Na

    2014-01-01

    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 by4.5 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.

  15. Mean versus extreme climate in the Mediterranean region and its sensitivity to future global warming conditions

    Energy Technology Data Exchange (ETDEWEB)

    Paeth, H.; Hense, A. [Meteorological Inst., Univ. Bonn (Germany)

    2005-06-01

    The Mediterranean region (MTR) has been supposed to be very sensitive to changes in land surface and atmospheric greenhouse-gas (GHG) concentrations. Particularly, an intensification of climate extremes may be associated with severe socio-economic implications. Here, we present an analysis of climate mean and extreme conditions in this subtropical area based on regional climate model experiments, simulating the present-day and possible future climate. The analysis of extreme values (EVs) is based on the assumption that the extremes of daily precipitation and near-surface temperature are well fitted by the Generalized Pareto distribution (GPD). Return values of extreme daily events are determined using the method of L-moments. Particular emphasis is laid on the evaluation of the return values with respect to the uncertainty range of the estimate as derived from a Monte Carlo sampling approach. During the most recent 25 years the MTR has become dryer in spring but more humid especially in the western part in autumn and winter. At the same time, the whole region has been subject to a substantial warming. The strongest rainfall extremes are simulated in autumn over the Mediterranean Sea around Italy. Temperature extremes are most pronounced over the land masses, especially over northern Africa. Given the large uncertainty of the EV estimate, only 1-year return values are further analysed. During recent decades, statistically significant changes in extremes are only found for temperature. Future climate conditions may come along with a decrease in mean and extreme precipitation during the cold season, whereas an intensification of the hydrological cycle is predicted in summer and autumn. Temperature is predominantly affected over the Iberian Peninsula and the eastern part of the MTR. In many grid boxes, the signals are blurred out due to the large amount of uncertainty in the EV estimate. Thus, a careful analysis is required when making inferences about the future

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Compositional Stability of the Bacterial Community in a Climate-Sensitive Sub-Arctic Peatland.

    Science.gov (United States)

    Weedon, James T; Kowalchuk, George A; Aerts, Rien; Freriks, Stef; Röling, Wilfred F M; van Bodegom, Peter M

    2017-01-01

    The climate sensitivity of microbe-mediated soil processes such as carbon and nitrogen cycling offers an interesting case for evaluating the corresponding sensitivity of microbial community composition to environmental change. Better understanding of the degree of linkage between functional and compositional stability would contribute to ongoing efforts to build mechanistic models aiming at predicting rates of microbe-mediated processes. We used an amplicon sequencing approach to test if previously observed large effects of experimental soil warming on C and N cycle fluxes (50-100% increases) in a sub-arctic Sphagnum peatland were reflected in changes in the composition of the soil bacterial community. We found that treatments that previously induced changes to fluxes did not associate with changes in the phylogenetic composition of the soil bacterial community. For both DNA- and RNA-based analyses, variation in bacterial communities could be explained by the hierarchy: spatial variation (12-15% of variance explained) > temporal variation (7-11%) > climate treatment (4-9%). We conclude that the bacterial community in this environment is stable under changing conditions, despite the previously observed sensitivity of process rates-evidence that microbe-mediated soil processes can alter without concomitant changes in bacterial communities. We propose that progress in linking soil microbial communities to ecosystem processes can be advanced by further investigating the relative importance of community composition effects versus physico-chemical factors in controlling biogeochemical process rates in different contexts.

  1. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  2. Understanding National Models for Climate Assessments

    Science.gov (United States)

    Dave, A.; Weingartner, K.

    2017-12-01

    National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.

  3. 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.

  4. 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.

  5. Climate change due to greenhouse effects in China as simulated by a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gao, X.J.; Zhao, Z.C.; Ding, Y.H.; Huang, R.H.; Giorgi, F. [National Climate Centre, Beijing (China)

    2001-07-01

    Impacts of greenhouse effects (2 x CO{sub 2}) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 x CO{sub 2}) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 x CO{sub 2} showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO{sub 2} doubling.

  6. On coupling global biome models with climate models

    OpenAIRE

    Claussen, M.

    1994-01-01

    The BIOME model of Prentice et al. (1992; J. Biogeogr. 19: 117-134), which predicts global vegetation patterns in equilibrium with climate, was coupled with the ECHAM climate model of the Max-Planck-Institut fiir Meteorologie, Hamburg, Germany. It was 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 betw...

  7. The transferability of hydrological models under nonstationary climatic conditions

    Directory of Open Access Journals (Sweden)

    C. Z. Li

    2012-04-01

    Full Text Available This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET, and streamflow data. Nash-Sutcliffe efficiency (NSE, modified index of agreement (d1 and water balance error (WBE were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to

  8. Modelling of anthropogenic and natural climate changes

    Energy Technology Data Exchange (ETDEWEB)

    Grassl, H; Mikolajewicz, U; Bakan, S [Max Planck Institute of Meteorology, Hamburg (Germany)

    1993-06-01

    The delay of anthropogenic climate change caused by oceans and other slowly reacting climate system components forces us to numerical modeling as the basis of decisions. For three three-dimensional numerical examples, namely transient coupled ocean-atmosphere models for the additional greenhouse effect, internal ocean-atmosphere variability, and disturbance by soot particles from burning oil wells, the present-day status is described. From all anthropogenic impacts on the radiative balance, the contribution from trace gases is the most important.

  9. 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

  10. 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

  11. Assessing climate change impact by integrated hydrological modelling

    Science.gov (United States)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  12. 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

  13. 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...

  14. 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...

  15. 78 FR 13874 - Watershed Modeling To Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to...

    Science.gov (United States)

    2013-03-01

    ... EPA's policy to include all comments it receives in the public docket without change and to make the... Modeling To Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to Climate Change and Urban... Loads to Climate Change and Urban Development in 20 U.S. Watersheds (EPA/600/R-12/058). EPA also is...

  16. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  17. 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),

  18. Community vulnerability to climate change in the context of other exposure-sensitivities in Kugluktuk, Nunavut

    Directory of Open Access Journals (Sweden)

    Laura Tozer

    2011-07-01

    Full Text Available Climate change in the Canadian north is, and will be, managed by communities that are already experiencing social, political, economic and other environmental changes. Hence, there is a need to understand vulnerability to climate change in the context of multiple exposure-sensitivities at the community level. This article responds to this perceived knowledge need based on a case study of the community of Kugluktuk in Nunavut, Canada. An established approach for vulnerability assessment is used to identify current climatic and non-climatic exposure-sensitivities along with their associated contemporary adaptation strategies. This assessment of current vulnerability is used as a basis to consider Kugluktuk's possible vulnerability to climatic change in the future. Current climate-related exposure-sensitivities in Kugluktuk relate primarily to subsistence harvesting and community infrastructure. Thinner and less stable ice conditions and unpredictable weather patterns are making travel and harvesting more dangerous and some community infrastructure is sensitive to permafrost melt and extreme weather events (e.g., flash floods. The ability of individuals and households to adapt to these and other climatic exposure-sensitivities is influenced by non-climatic factors that condition adaptive capacity including substance abuse, the erosion of traditional knowledge and youth suicide. These and other non-climatic factors often underpin adaptive capacity to deal with and adapt to changing conditions and must be considered in an assessment of vulnerability. This research argues that Northern communities are challenged by multiple exposure-sensitivities—beyond just those posed by climate—and effective adaptation to climate change requires consideration if not resolution of socio-economic and other issues in communities.

  19. 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.

  20. 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.

  1. 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.

  2. 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)

  3. 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)

    1996-12-31

    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

  4. 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

  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. 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.

  7. Climate effects of a hypothetical regional nuclear war: Sensitivity to emission duration and particle composition

    Science.gov (United States)

    Pausata, Francesco S. R.; Lindvall, Jenny; Ekman, Annica M. L.; Svensson, Gunilla

    2016-11-01

    Here, we use a coupled atmospheric-ocean-aerosol model to investigate the plume development and climate effects of the smoke generated by fires following a regional nuclear war between emerging third-world nuclear powers. We simulate a standard scenario where 5 Tg of black carbon (BC) is emitted over 1 day in the upper troposphere-lower stratosphere. However, it is likely that the emissions from the fires ignited by bomb detonations include a substantial amount of particulate organic matter (POM) and that they last more than 1 day. We therefore test the sensitivity of the aerosol plume and climate system to the BC/POM ratio (1:3, 1:9) and to the emission length (1 day, 1 week, 1 month). We find that in general, an emission length of 1 month substantially reduces the cooling compared to the 1-day case, whereas taking into account POM emissions notably increases the cooling and the reduction of precipitation associated with the nuclear war during the first year following the detonation. Accounting for POM emissions increases the particle size in the short-emission-length scenarios (1 day/1 week), reducing the residence time of the injected particle. While the initial cooling is more intense when including POM emission, the long-lasting effects, while still large, may be less extreme compared to the BC-only case. Our study highlights that the emission altitude reached by the plume is sensitive to both the particle type emitted by the fires and the emission duration. Consequently, the climate effects of a nuclear war are strongly dependent on these parameters.

  8. 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

  9. Representation of Northern Hemisphere winter storm tracks in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Greeves, C.Z.; Pope, V.D.; Stratton, R.A.; Martin, G.M. [Met Office Hadley Centre for Climate Prediction and Research, Exeter (United Kingdom)

    2007-06-15

    Northern Hemisphere winter storm tracks are a key element of the winter weather and climate at mid-latitudes. Before projections of climate change are made for these regions, it is necessary to be sure that climate models are able to reproduce the main features of observed storm tracks. The simulated storm tracks are assessed for a variety of Hadley Centre models and are shown to be well modelled on the whole. The atmosphere-only model with the semi-Lagrangian dynamical core produces generally more realistic storm tracks than the model with the Eulerian dynamical core, provided the horizontal resolution is high enough. The two models respond in different ways to changes in horizontal resolution: the model with the semi-Lagrangian dynamical core has much reduced frequency and strength of cyclonic features at lower resolution due to reduced transient eddy kinetic energy. The model with Eulerian dynamical core displays much smaller changes in frequency and strength of features with changes in horizontal resolution, but the location of the storm tracks as well as secondary development are sensitive to resolution. Coupling the atmosphere-only model (with semi-Lagrangian dynamical core) to an ocean model seems to affect the storm tracks largely via errors in the tropical representation. For instance a cold SST bias in the Pacific and a lack of ENSO variability lead to large changes in the Pacific storm track. Extratropical SST biases appear to have a more localised effect on the storm tracks. (orig.)

  10. The mobilisation model and parameter sensitivity

    International Nuclear Information System (INIS)

    Blok, B.M.

    1993-12-01

    In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

  11. Time to refine key climate policy models

    Science.gov (United States)

    Barron, Alexander R.

    2018-05-01

    Ambition regarding climate change at the national level is critical but is often calibrated with the projected costs — as estimated by a small suite of energy-economic models. Weaknesses in several key areas in these models will continue to distort policy design unless collectively addressed by a diversity of researchers.

  12. 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.

  13. Attributing the effects of climate on phenology change suggests high sensitivity in coastal zones

    Science.gov (United States)

    Seyednasrollah, B.; Clark, J. S.

    2015-12-01

    The impact of climate change on spring phenology depends on many variables that cannot be separated using current models. Phenology can influence carbon sequestration, plant nutrition, forest health, and species distributions. Leaf phenology is sensitive to changes of environmental factors, including climate, species composition, latitude, and solar radiation. The many variables and their interactions frustrate efforts to attribute variation to climate change. We developed a Bayesian framework to quantify the influence of environment on the speed of forest green-up. This study presents a state-space hierarchical model to infer and predict change in forest greenness over time using satellite observations and ground measurements. The framework accommodates both observation and process errors and it allows for main effects of variables and their interactions. We used daily spaceborne remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify temporal variability in the enhanced vegetation index (EVI) along a habitat gradient in the Southeastern United States. The ground measurements of meteorological parameters are obtained from study sites located in the Appalachian Mountains, the Piedmont and the Atlantic Coastal Plain between years 2000 and 2015. Results suggest that warming accelerates spring green-up in the Coastal Plain to a greater degree than in the Piedmont and Appalachian. In other words, regardless of variation in the timing of spring onset, the rate of greenness in non-coastal zones decreases with increasing temperature and hence with time over the spring transitional period. However, in coastal zones, as air temperature increases, leaf expansion becomes faster. This may indicate relative vulnerability to warming in non-coastal regions where moisture could be a limiting factor, whereas high temperatures in regions close to the coast enhance forest physiological activities. Model predictions agree with the remotely

  14. 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.)

  15. 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.

  16. 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.

  17. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  18. 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.

  19. The influence of internal variability on Earth's energy balance framework and implications for estimating climate sensitivity

    Science.gov (United States)

    Dessler, Andrew E.; Mauritsen, Thorsten; Stevens, Bjorn

    2018-04-01

    Our climate is constrained by the balance between solar energy absorbed by the Earth and terrestrial energy radiated to space. This energy balance has been widely used to infer equilibrium climate sensitivity (ECS) from observations of 20th-century warming. Such estimates yield lower values than other methods, and these have been influential in pushing down the consensus ECS range in recent assessments. Here we test the method using a 100-member ensemble of the Max Planck Institute Earth System Model (MPI-ESM1.1) simulations of the period 1850-2005 with known forcing. We calculate ECS in each ensemble member using energy balance, yielding values ranging from 2.1 to 3.9 K. The spread in the ensemble is related to the central assumption in the energy budget framework: that global average surface temperature anomalies are indicative of anomalies in outgoing energy (either of terrestrial origin or reflected solar energy). We find that this assumption is not well supported over the historical temperature record in the model ensemble or more recent satellite observations. We find that framing energy balance in terms of 500 hPa tropical temperature better describes the planet's energy balance.

  20. Sensitivity of the global submarine hydrate inventory to scenarios of future climate change

    Science.gov (United States)

    Hunter, S. J.; Goldobin, D. S.; Haywood, A. M.; Ridgwell, A.; Rees, J. G.

    2013-04-01

    The global submarine inventory of methane hydrate is thought to be considerable. The stability of marine hydrates is sensitive to changes in temperature and pressure and once destabilised, hydrates release methane into sediments and ocean and potentially into the atmosphere, creating a positive feedback with climate change. Here we present results from a multi-model study investigating how the methane hydrate inventory dynamically responds to different scenarios of future climate and sea level change. The results indicate that a warming-induced reduction is dominant even when assuming rather extreme rates of sea level rise (up to 20 mm yr-1) under moderate warming scenarios (RCP 4.5). Over the next century modelled hydrate dissociation is focussed in the top ˜100m of Arctic and Subarctic sediments beneath business-as-usual scenario (RCP 8.5), upper estimates of resulting global sea-floor methane fluxes could exceed estimates of natural global fluxes by 2100 (>30-50TgCH4yr-1), although subsequent oxidation in the water column could reduce peak atmospheric release rates to 0.75-1.4 Tg CH4 yr-1.

  1. 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

  2. Sensitivity of very small glaciers in the Swiss Alps to future climate change

    Directory of Open Access Journals (Sweden)

    Matthias eHuss

    2016-04-01

    Full Text Available Very small glaciers (<0.5 km2 account for more than 80% of the total number of glaciers in mid- to low-latitude mountain ranges. Although their total area and volume is small compared to larger glaciers, they are a relevant component of the cryosphere, contributing to landscape formation, local hydrology and sea-level rise. Worldwide glacier monitoring mostly focuses on medium-sized to large glaciers leaving us with a limited understanding of the response of dwarf glaciers to climate change. In this study, we present a comprehensive modeling framework to assess past and future changes of very small glaciers at the mountain-range scale. Among other processes our model accounts for snow redistribution, changes in glacier geometry and the time-varying effect of supraglacial debris. It computes the mass balance distribution, the englacial temperature regime and proglacial runoff. The evolution of 1,133 individual glaciers in the Swiss Alps is modeled in detail until 2060 based on new distributed data sets. Our results indicate that 52% of all very small glaciers in Switzerland will completely disappear within the next 25 years. However, a few avalanche-fed glaciers at low elevation might be able to survive even substantial atmospheric warming. We find highly variable sensitivities of very small glaciers to air temperature change, with gently-sloping, low-elevation, and debris-covered glaciers being most sensitive.

  3. 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.

  4. ATLAS MDT neutron sensitivity measurement and modeling

    International Nuclear Information System (INIS)

    Ahlen, S.; Hu, G.; Osborne, D.; Schulz, A.; Shank, J.; Xu, Q.; Zhou, B.

    2003-01-01

    The sensitivity of the ATLAS precision muon detector element, the Monitored Drift Tube (MDT), to fast neutrons has been measured using a 5.5 MeV Van de Graaff accelerator. The major mechanism of neutron-induced signals in the drift tubes is the elastic collisions between the neutrons and the gas nuclei. The recoil nuclei lose kinetic energy in the gas and produce the signals. By measuring the ATLAS drift tube neutron-induced signal rate and the total neutron flux, the MDT neutron signal sensitivities were determined for different drift gas mixtures and for different neutron beam energies. We also developed a sophisticated simulation model to calculate the neutron-induced signal rate and signal spectrum for ATLAS MDT operation configurations. The calculations agree with the measurements very well. This model can be used to calculate the neutron sensitivities for different gaseous detectors and for neutron energies above those available to this experiment

  5. Can model weighting improve probabilistic projections of climate change?

    Energy Technology Data Exchange (ETDEWEB)

    Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

    2012-10-15

    Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)

  6. The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

    Energy Technology Data Exchange (ETDEWEB)

    Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

    2000-06-01

    A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

  7. 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.

  8. Identifying misbehaving models using baseline climate variance

    Science.gov (United States)

    Schultz, Colin

    2011-06-01

    The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

  9. 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.

  10. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    Science.gov (United States)

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

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

    Science.gov (United States)

    1998-01-01

    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 GISS 8 deg x lO deg atmospheric 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.

  12. The sensitivity of the ESA DELTA model

    Science.gov (United States)

    Martin, C.; Walker, R.; Klinkrad, H.

    Long-term debris environment models play a vital role in furthering our understanding of the future debris environment, and in aiding the determination of a strategy to preserve the Earth orbital environment for future use. By their very nature these models have to make certain assumptions to enable informative future projections to be made. Examples of these assumptions include the projection of future traffic, including launch and explosion rates, and the methodology used to simulate break-up events. To ensure a sound basis for future projections, and consequently for assessing the effectiveness of various mitigation measures, it is essential that the sensitivity of these models to variations in key assumptions is examined. The DELTA (Debris Environment Long Term Analysis) model, developed by QinetiQ for the European Space Agency, allows the future projection of the debris environment throughout Earth orbit. Extensive analyses with this model have been performed under the auspices of the ESA Space Debris Mitigation Handbook and following the recent upgrade of the model to DELTA 3.0. This paper draws on these analyses to present the sensitivity of the DELTA model to changes in key model parameters and assumptions. Specifically the paper will address the variation in future traffic rates, including the deployment of satellite constellations, and the variation in the break-up model and criteria used to simulate future explosion and collision events.

  13. 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

  14. 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

  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. 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

  19. The Software Architecture of Global Climate Models

    Science.gov (United States)

    Alexander, K. A.; Easterbrook, S. M.

    2011-12-01

    It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

  20. Modeling the effect of climate change on the indoor climate

    NARCIS (Netherlands)

    Schijndel, van A.W.M.; Schellen, H.L.

    2010-01-01

    Within the new EU project ‘Climate for Culture’ researchers are investigating climate change impacts on UNESCO World Heritage Sites. Simulation results are expected to give information on the possible impact of climate change on the built cultural heritage and its indoor environment. This paper

  1. Sensitivity analysis of a modified energy model

    International Nuclear Information System (INIS)

    Suganthi, L.; Jagadeesan, T.R.

    1997-01-01

    Sensitivity analysis is carried out to validate model formulation. A modified model has been developed to predict the future energy requirement of coal, oil and electricity, considering price, income, technological and environmental factors. The impact and sensitivity of the independent variables on the dependent variable are analysed. The error distribution pattern in the modified model as compared to a conventional time series model indicated the absence of clusters. The residual plot of the modified model showed no distinct pattern of variation. The percentage variation of error in the conventional time series model for coal and oil ranges from -20% to +20%, while for electricity it ranges from -80% to +20%. However, in the case of the modified model the percentage variation in error is greatly reduced - for coal it ranges from -0.25% to +0.15%, for oil -0.6% to +0.6% and for electricity it ranges from -10% to +10%. The upper and lower limit consumption levels at 95% confidence is determined. The consumption at varying percentage changes in price and population are analysed. The gap between the modified model predictions at varying percentage changes in price and population over the years from 1990 to 2001 is found to be increasing. This is because of the increasing rate of energy consumption over the years and also the confidence level decreases as the projection is made far into the future. (author)

  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. 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...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that......, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis pressure data. The spatial correlation of REMO surface winds in Europe...

  4. 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.

  5. 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).

  6. Modelling recent and future climatic suitability for fasciolosis in Europe.

    Science.gov (United States)

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

    2015-03-19

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

  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. The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

    Science.gov (United States)

    Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

    2004-06-01

    The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

  9. Sensitivity of health sector indicators' response to climate change in Ghana.

    Science.gov (United States)

    Dovie, Delali B K; Dzodzomenyo, Mawuli; Ogunseitan, Oladele A

    2017-01-01

    There is accumulating evidence that the emerging burden of global climate change threatens the fidelity of routine indicators for disease detection and management of risks to public health. The threat partially reflects the conservative character of the health sector and the reluctance to adopt new indicators, despite the growing awareness that existing environmental health indicators were developed to respond to risks that may no longer be relevant, and are too simplistic to also act as indicators for newer global-scale risk factors. This study sought to understand the scope of existing health indicators, while aiming to discover new indicators for building resilience against three climate sensitive diseases (cerebro spinal meningitis, malaria and diarrhea). Therefore, new potential indicators derived from human and biophysical origins were developed to complement existing health indicators, thereby creating climate-sensitive battery of robust composite indices of resilience in health planning. Using Ghana's health sector as a case study systematic international literature review, national expert consultation, and focus group outcomes yielded insights into the relevance, sensitivity and impacts of 45 indicators in 11 categories in responding to climate change. In total, 65% of the indicators were sensitive to health impacts of climate change; 24% acted directly; 31% synergistically; and 45% indirectly, with indicator relevance strongly associated with type of health response. Epidemiological indicators (e.g. morbidity) and health demographic indicators (e.g. population structure) require adjustments with external indicators (e.g. biophysical, policy) to be resilient to climate change. Therefore, selective integration of social and ecological indicators with existing public health indicators improves the fidelity of the health sector to adopt more robust planning of interdependent systems to build resilience. The study highlights growing uncertainties in

  10. 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

  11. 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 auch

  12. 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.

  13. 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....

  14. On the mechanisms of warming the mid-Pliocene and the inference of a hierarchy of climate sensitivities with relevance to the understanding of climate futures

    Directory of Open Access Journals (Sweden)

    D. Chandan

    2018-06-01

    timescale as the ice–albedo feedback becomes active, and then sensitivity further increases to 7.0 °C per doubling of CO2 on long timescales due to the feedback from the glacial isostatic adjustment of the Earth's surface in response to the melting of the polar ice sheets. Finally, once the slow feedbacks have stabilized, the sensitivity of the system drops to 3.35 °C per doubling of CO2. Our inference of the intermediate-timescale climate sensitivity suggests that the projected warming by 2300 CE, inferred using Earth system models of intermediate complexity on the basis of an extension to the RCP4.5 emission scenario in which atmospheric pCO2 stabilizes at roughly twice the PI level in year 2150 CE, could be underestimated by  ∼ 1 °C due to the absence of ice-sheet-based feedbacks in those models.

  15. 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

  16. 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.

  17. 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.

  18. 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...

  19. A potato model intercomparison across varying climates and productivity levels.

    Science.gov (United States)

    Fleisher, David H; Condori, Bruno; Quiroz, Roberto; Alva, Ashok; Asseng, Senthold; Barreda, Carolina; Bindi, Marco; Boote, Kenneth J; Ferrise, Roberto; Franke, Angelinus C; Govindakrishnan, Panamanna M; Harahagazwe, Dieudonne; Hoogenboom, Gerrit; Naresh Kumar, Soora; Merante, Paolo; Nendel, Claas; Olesen, Jorgen E; Parker, Phillip S; Raes, Dirk; Raymundo, Rubi; Ruane, Alex C; Stockle, Claudio; Supit, Iwan; Vanuytrecht, Eline; Wolf, Joost; Woli, Prem

    2017-03-01

    A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be

  20. 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.

  1. 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...

  2. Sensitivity of pine flatwoods hydrology to climate change and forest management in Florida, USA

    Science.gov (United States)

    Jianbiao Lu; Ge Sun; Steven G. McNulty; Nicholas B. Comerford

    2009-01-01

    Pine flatwoods (a mixture of cypress wetlands and managed pine uplands) is an important ecosystem in the southeastern U.S. However, long-term hydrologic impacts of forest management and climate change on this heterogeneous landscape are not well understood. Therefore, this study examined the sensitivity of cypress-pine flatwoods...

  3. 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.

  4. Energy partitioning at treeline forest and tundra sites and its sensitivity to climate change

    Energy Technology Data Exchange (ETDEWEB)

    Lafleur, P.M. [Trent Univ., Peterborough, ON (Canada); Rouse, W.R. [McMaster Univ., Hamilton, ON (Canada)

    1995-12-31

    A study was conducted to examine the inter-annual variability in energy fluxes of treeline tundra and forest and to investigate the sensitivity of forest and tundra energy balances to climatic changes. A five year record of energy balance data from contiguous wetland tundra and subarctic forest sites near Churchill, Manitoba was analyzed. The data included snow free periods only. Wind direction was used as an analogue for changing climatic conditions where onshore winds are cooler and moister than offshore winds. Sensible and latent heat fluxes at both sites varied significantly between onshore and offshore wind regimes. The differences between onshore and offshore fluxes at the tundra site were larger than for the forest. The tundra-to-forest Bowen ratios decreased with increasing vapour pressure deficit and increasing air temperature. Results suggest that energy partitioning in the wetland tundra is more sensitive to climate change than in the treeline forests. 22 refs., 1 tab., 6 figs.

  5. International Space Science Institute Workshop on Shallow Clouds, Water Vapor, Circulation and Climate Sensitivity

    CERN Document Server

    Winker, David; Bony, Sandrine; Stevens, Bjorn

    2018-01-01

    This volume presents a series of overview articles arising from a workshop exploring the links among shallow clouds, water vapor, circulation, and climate sensitivity. It provides a state-of-the art synthesis of understanding about the coupling of clouds and water vapor to the large-scale circulation. The emphasis is on two phenomena, namely the self-aggregation of deep convection and interactions between low clouds and the large-scale environment, with direct links to the sensitivity of climate to radiative perturbations. Each subject is approached using simulations, observations, and synthesizing theory; particular attention is paid to opportunities offered by new remote-sensing technologies, some still prospective. The collection provides a thorough grounding in topics representing one of the World Climate Research Program’s Grand Challenges. Previously published in Surveys in Geophysics, Volume 38, Issue 6, 2017 The articles “Observing Convective Aggregation”, “An Observational View of Relationshi...

  6. 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.

  7. Sensitivity of system stability to model structure

    Science.gov (United States)

    Hosack, G.R.; Li, H.W.; Rossignol, P.A.

    2009-01-01

    A community is stable, and resilient, if the levels of all community variables can return to the original steady state following a perturbation. The stability properties of a community depend on its structure, which is the network of direct effects (interactions) among the variables within the community. These direct effects form feedback cycles (loops) that determine community stability. Although feedback cycles have an intuitive interpretation, identifying how they form the feedback properties of a particular community can be intractable. Furthermore, determining the role that any specific direct effect plays in the stability of a system is even more daunting. Such information, however, would identify important direct effects for targeted experimental and management manipulation even in complex communities for which quantitative information is lacking. We therefore provide a method that determines the sensitivity of community stability to model structure, and identifies the relative role of particular direct effects, indirect effects, and feedback cycles in determining stability. Structural sensitivities summarize the degree to which each direct effect contributes to stabilizing feedback or destabilizing feedback or both. Structural sensitivities prove useful in identifying ecologically important feedback cycles within the community structure and for detecting direct effects that have strong, or weak, influences on community stability. The approach may guide the development of management intervention and research design. We demonstrate its value with two theoretical models and two empirical examples of different levels of complexity. ?? 2009 Elsevier B.V. All rights reserved.

  8. 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.

  9. Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state

    Science.gov (United States)

    Tucker, Colin; Ferrenberg, Scott; Reed, Sasha C.

    2018-01-01

    Arid and semiarid ecosystems make up approximately 41% of Earth’s terrestrial surface and are suggested to regulate the trend and interannual variability of the global terrestrial carbon (C) sink. Biological soil crusts (biocrusts) are common dryland soil surface communities of bryophytes, lichens, and/or cyanobacteria that bind the soil surface together and that may play an important role in regulating the climatic sensitivity of the dryland C cycle. Major uncertainties exist in our understanding of the interacting effects of changing temperature and moisture on CO2 uptake (photosynthesis) and loss (respiration) from biocrust and sub-crust soil, particularly as related to biocrust successional state. Here, we used a mesocosm approach to assess how biocrust successional states related to climate treatments. We subjected bare soil (Bare), early successional lightly pigmented cyanobacterial biocrust (Early), and late successional darkly pigmented moss-lichen biocrust (Late) to either ambient or + 5°C above ambient soil temperature for 84 days. Under ambient temperatures, Late biocrust mesocosms showed frequent net uptake of CO2, whereas Bare soil, Early biocrust, and warmed Late biocrust mesocosms mostly lost CO2 to the atmosphere. The inhibiting effect of warming on CO2 exchange was a result of accelerated drying of biocrust and soil. We used these data to parameterize, via Bayesian methods, a model of ecosystem CO2 fluxes, and evaluated the model with data from an autochamber CO2 system at our field site on the Colorado Plateau in SE Utah. In the context of the field experiment, the data underscore the negative effect of warming on fluxes both biocrust CO2 uptake and loss—which, because biocrusts are a dominant land cover type in this ecosystem, may extend to ecosystem-scale C cycling.

  10. Circulation and oxygen cycling in the Mediterranean Sea: Sensitivity to future climate change

    Science.gov (United States)

    Powley, Helen R.; Krom, Michael D.; Van Cappellen, Philippe

    2016-11-01

    Climate change is expected to increase temperatures and decrease precipitation in the Mediterranean Sea (MS) basin, causing substantial changes in the thermohaline circulation (THC) of both the Western Mediterranean Sea (WMS) and Eastern Mediterranean Sea (EMS). The exact nature of future circulation changes remains highly uncertain, however, with forecasts varying from a weakening to a strengthening of the THC. Here we assess the sensitivity of dissolved oxygen (O2) distributions in the WMS and EMS to THC changes using a mass balance model, which represents the exchanges of O2 between surface, intermediate, and deep water reservoirs, and through the Straits of Sicily and Gibraltar. Perturbations spanning the ranges in O2 solubility, aerobic respiration kinetics, and THC changes projected for the year 2100 are imposed to the O2 model. In all scenarios tested, the entire MS remains fully oxygenated after 100 years; depending on the THC regime, average deep water O2 concentrations fall in the ranges 151-205 and 160-219 µM in the WMS and EMS, respectively. On longer timescales (>1000 years), the scenario with the largest (>74%) decline in deep water formation rate leads to deep water hypoxia in the EMS but, even then, the WMS deep water remains oxygenated. In addition, a weakening of THC may result in a negative feedback on O2 consumption as supply of labile dissolved organic carbon to deep water decreases. Thus, it appears unlikely that climate-driven changes in THC will cause severe O2 depletion of the deep water masses of the MS in the foreseeable future.

  11. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    Science.gov (United States)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  12. 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.)

  13. 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.

  14. Sensitivity of tropospheric heating rates to aerosols: A modeling study

    International Nuclear Information System (INIS)

    Hanna, A.F.; Shankar, U.; Mathur, R.

    1994-01-01

    The effect of aerosols on the radiation balance is critical to the energetics of the atmosphere. Because of the relatively long residence of specific types of aerosols in the atmosphere and their complex thermal and chemical interactions, understanding their behavior is crucial for understanding global climate change. The authors used the Regional Particulate Model (RPM) to simulate aerosols in the eastern United States in order to identify the aerosol characteristics of specific rural and urban areas these characteristics include size, concentration, and vertical profile. A radiative transfer model based on an improved δ-Eddington approximation with 26 spectral intervals spanning the solar spectrum was then used to analyze the tropospheric heating rates associated with these different aerosol distributions. The authors compared heating rates forced by differences in surface albedo associated with different land-use characteristics, and found that tropospheric heating and surface cooling are sensitive to surface properties such as albedo

  15. Sensitivity of the hydrologic cycle in Tana river basin to climate change

    International Nuclear Information System (INIS)

    Mutua, F.M.

    1998-01-01

    The Tana River basin in Kenya has four distinct climates along it's gradient from cool humid in mount Kenya region through arid and semi arid in the lower plains to semi humid coastal climate. From the highlands of mount Kenya to the plateau on the lowlands, the river traverses some sections which have high potential for hydro-electric power generation. The government has constructed water reovirus to collect water for electricity generation. The influence of the reovirus have also caused climate modification. The aim of the study was to investigate the sensitivity of the river flows in the Tana river to climate change. The study indicates that, as long as temperature increment of up to 2 degrees centigrade are accompanied by positive changes (greater than 10%) in rainfall over the basin, then the hydrologic cycle adjust itself accordingly to give a positive response (increased runoff) in terms of the river at the outlet

  16. Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

    Science.gov (United States)

    Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

    2015-04-01

    not so much at medium elevations. (ii) Considering climate change, the variability that is due to the GCM-RCM chains is much greater than the variability induced by the uncertainty in the initial climatic conditions. (iii) The uncertainties caused by the intrinsic stochasticity in the DVMs and by the random generation of the climate time-series are negligible. Overall, our results indicate that DVMs are quite sensitive to the climate data, highlighting particularly (1) the limitations of using one single multi-model average climate change scenario in climate impact studies and (2) the need to better consider the uncertainty in climate model outputs for projecting future vegetation changes.

  17. Infrared radiation parameterizations in numerical climate models

    Science.gov (United States)

    Chou, Ming-Dah; Kratz, David P.; Ridgway, William

    1991-01-01

    This study presents various approaches to parameterizing the broadband transmission functions for utilization in numerical climate models. One-parameter scaling is applied to approximate a nonhomogeneous path with an equivalent homogeneous path, and the diffuse transmittances are either interpolated from precomputed tables or fit by analytical functions. Two-parameter scaling is applied to parameterizing the carbon dioxide and ozone transmission functions in both the lower and middle atmosphere. Parameterizations are given for the nitrous oxide and methane diffuse transmission functions.

  18. 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.

  19. 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

  20. 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

  1. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

    Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  2. 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.

  3. A flexible climate model for use in integrated assessments

    Science.gov (United States)

    Sokolov, A. P.; Stone, P. H.

    Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM

  4. 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

  5. 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

  6. Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?: NUDGING AND MODEL SENSITIVITIES

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Guangxing [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Wan, Hui [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Zhang, Kai [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Ghan, Steven J. [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA

    2016-07-10

    Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

  7. 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

  8. 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....

  9. Coupling Climate Models and Forward-Looking Economic Models

    Science.gov (United States)

    Judd, K.; Brock, W. A.

    2010-12-01

    Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward

  10. Drought Persistence Errors in Global Climate Models

    Science.gov (United States)

    Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

    2018-04-01

    The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

  11. 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

  12. 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.

  13. Precipitates/Salts Model Sensitivity Calculation

    Energy Technology Data Exchange (ETDEWEB)

    P. Mariner

    2001-12-20

    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{sub 2}) on the chemical evolution of water in the drift.

  14. 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.

  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. Abilities and limitations in the use of regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Koeltzov, Morten Andreas Oedegaard

    2012-11-01

    In order to say something about the effect of climate change at the regional level, one takes in use regional climate models. In these models the thesis introduce regional features, which are not included in the global climate models (which are basically in climate research). Regional models can provide good and useful climate projections that add more value than the global climate models, but also introduces an uncertainty in the calculations. How should this uncertainty affect the use of regional climate models?The most common methodology for calculating potential future climate developments are based on different scenarios of possible emissions of greenhouse gases. These scenarios operates as global climate models using physical laws and calculate possible future developments. This is considered mathematical complexed and processes with limited supercomputing capacity calculates the global models for the larger scale of the climate system. To study the effects of climate change are regional details required and the regional models used therefore in a limited area of the climate system. These regional models are driven by data from the global models and refines and improves these data. Impact studies can then use the data from the regional models or data which are further processed to provide more local details using geo-statistical methods. In the preparation of the climate projections is there a minimum of 4 sources of uncertainty. This uncertainty is related to the provision of emission scenarios of greenhouse gases, uncertainties related to the use of global climate models, uncertainty related to the use of regional climate models and the uncertainty of internal variability in the climate system. This thesis discusses the use of regional climate models, and illustrates how the regional climate model adds value to climate projections, and at the same time introduce uncertainty in the calculations. It discusses in particular the importance of the choice of

  17. 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.

  18. Current climate and climate change over India as simulated by the Canadian Regional Climate Model

    Science.gov (United States)

    Alexandru, Adelina; Sushama, Laxmi

    2015-08-01

    The performance of the fifth generation of the Canadian Regional Climate Model (CRCM5) in reproducing the main climatic characteristics over India during the southwest (SW)-, post- and pre-monsoon seasons are presented in this article. To assess the performance of CRCM5, European Centre for Medium- Range Weather Forecasts (ECMWF) Re- Analysis (ERA- 40) and Interim re-analysis (ERA-Interim) driven CRCM5 simulation is compared against independent observations and reanalysis data for the 1971-2000 period. Projected changes for two future periods, 2041-2070 and 2071-2100, with respect to the 1971-2000 current period are assessed based on two transient climate change simulations of CRCM5 spanning the 1950-2100 period. These two simulations are driven by the Canadian Earth System Model version 2 (CanESM2) and the Max Planck Institute for Meteorology's Earth System Low Resolution Model (MPI-ESM-LR), respectively. The boundary forcing errors associated with errors in the driving global climate models are also studied by comparing the 1971-2000 period of the CanESM2 and MPI-ESM-LR driven simulations with that of the CRCM5 simulation driven by ERA-40/ERA-Interim. Results show that CRCM5 driven by ERA-40/ERA-Interim is in general able to capture well the temporal and spatial patterns of 2 m-temperature, precipitation, wind, sea level pressure, total runoff and soil moisture over India in comparison with available reanalysis and observations. However, some noticeable differences between the model and observational data were found during the SW-monsoon season within the domain of integration. CRCM5 driven by ERA-40/ERA-Interim is 1-2 °C colder than CRU observations and generates more precipitation over the Western Ghats and central regions of India, and not enough in the northern and north-eastern parts of India and along the Konkan west coast in comparison with the observed precipitation. The monsoon onset seems to be relatively well captured over the southwestern coast of

  19. 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.

  20. 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.

  1. Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: effect of hydrological model and CH4 model structure

    Directory of Open Access Journals (Sweden)

    J. van Huissteden

    2009-07-01

    Full Text Available Methane (CH4 fluxes from northern wetlands may have influenced atmospheric CH4 concentrations at climate warming phases during the last 800 000 years and during the present global warming. Including these CH4 fluxes in earth system models is essential to understand feedbacks between climate and atmospheric composition. Attempts to model CH4 fluxes from wetlands have previously been undertaken using various approaches. Here, we test a process-based wetland CH4 flux model (PEATLAND-VU which includes details of soil-atmosphere CH4 transport. The model has been used to simulate CH4 emissions from continental Europe in previous glacial climates and the current climate. This paper presents results regarding the sensitivity of modeling glacial terrestrial CH4 fluxes to (a basic tuning parameters of the model, (b different approaches in modeling of the water table, and (c model structure. In order to test the model structure, PEATLAND-VU was compared to a simpler modeling approach based on wetland primary production estimated from a vegetation model (BIOME 3.5. The tuning parameters are the CH4 production rate from labile organic carbon and its temperature sensitivity. The modelled fluxes prove comparatively insensitive to hydrology representation, while sensitive to microbial parameters and model structure. Glacial climate emissions are also highly sensitive to assumptions about the extent of ice cover and exposed seafloor. Wetland expansion over low relief exposed seafloor areas have compensated for a decrease of wetland area due to continental ice cover.

  2. The international coordination of climate model validation and intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gates, W L [Lawrence Livermore National Lab. Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison

    1996-12-31

    Climate modeling, whereby basic physical laws are used to integrate the physics and dynamics of climate into a consistent system, plays a key role in climate research and is the medium through. Depending upon the portion(s) of the climate system being considered, climate models range from those concerned only with the equilibrium globally-averaged surface temperature to those depicting the 3-dimensional time-dependent evolution of the coupled atmosphere, ocean, sea ice and land surface. Here only the latter class of models are considered, which are commonly known as general circulation models (or GCMs). (author)

  3. Construction of a novel economy-climate model

    Institute of Scientific and Technical Information of China (English)

    CHOU JieMing; DONG WenJie; YE DuZheng

    2007-01-01

    An attempt has been made to construct a novel economy-climate model by combining climate change research with agricultural economy research to evaluate the influence of global climate change on grain yields. The insertion of a climate change factor into the economic C-D (Cobb-Dauglas) production function model yields a novel evaluation model, which connects the climate change factor to the economic variation factor, and the performance and reasonableness of the novel evaluation model are also preliminarily simulated and verified.

  4. The international coordination of climate model validation and intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gates, W.L. [Lawrence Livermore National Lab. Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison

    1995-12-31

    Climate modeling, whereby basic physical laws are used to integrate the physics and dynamics of climate into a consistent system, plays a key role in climate research and is the medium through. Depending upon the portion(s) of the climate system being considered, climate models range from those concerned only with the equilibrium globally-averaged surface temperature to those depicting the 3-dimensional time-dependent evolution of the coupled atmosphere, ocean, sea ice and land surface. Here only the latter class of models are considered, which are commonly known as general circulation models (or GCMs). (author)

  5. 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

  6. 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.

  7. Sensitivity of crop yield and N losses in winter wheat to changes in mean and variability of temperature and precipitation in Denmark using the FASSET model

    DEFF Research Database (Denmark)

    Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

    2012-01-01

    Sensitivity of wheat yield and soil nitrogen (N) losses to stepwise changes in means and variances of climatic variables were determined using the FASSET model. The LARS-WG was used to generate climate scenarios using observed climate data (1961–90) from two sites in Denmark, which differed...... loam. This study illustrates the importance of considering effects of changes to mean climatic factors, climatic variability and soil types on both crop yield and soil N losses....

  8. Sensitivity of marine systems to climate and fishing: Concepts, issues and management responses

    DEFF Research Database (Denmark)

    Perry, Ian; Cury, Philippe; Brander, Keith

    2010-01-01

    forcing. Fishing is unlikely to alter the sensitivities of individual finfish and invertebrates to climate forcing. It will remove individuals with specific characteristics from the gene pool, thereby affecting structure and function at higher levels of organisation. Fishing leads to a loss of older age......Modern fisheries research and management must understand and take account of the interactions between climate and fishing, rather than try to disentangle their effects and address each separately. These interactions are significant drivers of change in exploited marine systems and have...... but will be manifest as the accumulation of the interactions between fishing and climate variability — unless threshold limits are exceeded. Marine resource managers need to develop approaches which maintain the resilience of individuals, populations, communities and ecosystems to the combined and interacting effects...

  9. Hydrologic response and watershed sensitivity to climate warming in California's Sierra Nevada.

    Directory of Open Access Journals (Sweden)

    Sarah E Null

    Full Text Available This study focuses on the differential hydrologic response of individual watersheds to climate warming within the Sierra Nevada mountain region of California. We describe climate warming models for 15 west-slope Sierra Nevada watersheds in California under unimpaired conditions using WEAP21, a weekly one-dimensional rainfall-runoff model. Incremental climate warming alternatives increase air temperature uniformly by 2 degrees, 4 degrees, and 6 degrees C, but leave other climatic variables unchanged from observed values. Results are analyzed for changes in mean annual flow, peak runoff timing, and duration of low flow conditions to highlight which watersheds are most resilient to climate warming within a region, and how individual watersheds may be affected by changes to runoff quantity and timing. Results are compared with current water resources development and ecosystem services in each watershed to gain insight into how regional climate warming may affect water supply, hydropower generation, and montane ecosystems. Overall, watersheds in the northern Sierra Nevada are most vulnerable to decreased mean annual flow, southern-central watersheds are most susceptible to runoff timing changes, and the central portion of the range is most affected by longer periods with low flow conditions. Modeling results suggest the American and Mokelumne Rivers are most vulnerable to all three metrics, and the Kern River is the most resilient, in part from the high elevations of the watershed. Our research seeks to bridge information gaps between climate change modeling and regional management planning, helping to incorporate climate change into the development of regional adaptation strategies for Sierra Nevada watersheds.

  10. 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 models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

  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...... are compared with data from the European Wind Atlas which have been analyzed using the Wind Atlas Analysis and Application Program, WA(S)P. The prediction of the areas of higher wind power is fair. Stations with low power are overpredicted....

  12. Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

    Science.gov (United States)

    Veldkamp, T. I. E.; Eisner, S.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.

    2015-01-01

    Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity

  13. The Whole Atmosphere Community Climate Model

    Science.gov (United States)

    Boville, B. A.; Garcia, R. R.; Sassi, F.; Kinnison, D.; Roble, R. G.

    The Whole Atmosphere Community Climate Model (WACCM) is an upward exten- sion of the National Center for Atmospheric Research Community Climate System Model. WACCM simulates the atmosphere from the surface to the lower thermosphere (140 km) and includes both dynamical and chemical components. The salient points of the model formulation will be summarized and several aspects of its performance will be discussed. Comparison with observations indicates that WACCM produces re- alistic temperature and zonal wind distributions. Both the mean state and interannual variability will be summarized. Temperature inversions in the midlatitude mesosphere have been reported by several authors and are also found in WACCM. These inver- sions are formed primarily by planetary wave forcing, but the background state on which they form also requires gravity wave forcing. The response to sea surface temperature (SST) anomalies will be examined by com- paring simulations with observed SSTs for 1950-1998 to a simulation with clima- tological annual cycle of SSTs. The response to ENSO events is found to extend though the winter stratosphere and mesosphere and a signal is also found at the sum- mer mesopause. The experimental framework allows the ENSO signal to be isolated, because no other forcings are included (e.g. solar variability and volcanic eruptions) which complicate the observational record. The temperature and wind variations asso- ciated with ENSO are large enough to generate significant perturbations in the chem- ical composition of the middle atmosphere, which will also be discussed.

  14. Climate models on massively parallel computers

    International Nuclear Information System (INIS)

    Vitart, F.; Rouvillois, P.

    1993-01-01

    First results got on massively parallel computers (Multiple Instruction Multiple Data and Simple Instruction Multiple Data) allow to consider building of coupled models with high resolutions. This would make possible simulation of thermoaline circulation and other interaction phenomena between atmosphere and ocean. The increasing of computers powers, and then the improvement of resolution will go us to revise our approximations. Then hydrostatic approximation (in ocean circulation) will not be valid when the grid mesh will be of a dimension lower than a few kilometers: We shall have to find other models. The expert appraisement got in numerical analysis at the Center of Limeil-Valenton (CEL-V) will be used again to imagine global models taking in account atmosphere, ocean, ice floe and biosphere, allowing climate simulation until a regional scale

  15. Climate-sensitive urban design through Envi-Met simulation: case study in Kemayoran, Jakarta

    Science.gov (United States)

    Kusumastuty, K. D.; Poerbo, H. W.; Koerniawan, M. D.

    2018-03-01

    Indonesia as a tropical country which the character of its climate are hot and humid, the outdoor activity applications are often disrupted due to discomfort in thermal conditions. Massive construction of skyscrapers in urban areas are caused by the increase of human population leads to reduced green and infiltration areas that impact to environmental imbalances and triggering microclimate changes with rising air temperatures on the surface. The area that significantly experiences the rise of temperature in the Central Business District (CBD), which has need an analysis to create thermal comfort conditions to improve the ease of outdoor activities by an approach. This study aims to design the Kemayoran CBD through Climate Sensitive Urban Design especially in hot and humid tropical climate area and analyze thermal comfort level and optimal air conditioning in the outdoor area. This research used a quantitative method by generating the design using Climate Sensitive Urban Design principle through Envi-met 4.1 simulation program to find out the value of PMV, air temperature, wind speed and relative humidity conditions. The design area considers the configuration of buildings such as the distance between buildings, the average height, the orientation of the building, and the width of the road.

  16. Sensitivity of sediment magnetic records to climate change during Holocene for the northern South China Sea

    Science.gov (United States)

    Ouyang, Tingping; Li, Mingkun; Zhao, Xiang; Zhu, Zhaoyu; Tian, Chengjing; Qiu, Yan; Peng, Xuechao; Hu, Qiao

    2016-05-01

    Magnetic property has been proved to be a sensitive proxy to climate change for both terrestrial and marine sediments. Based on the schedule frame established by AMS 14C dating of foraminifera, detail magnetic analyses were performed for core PC24 sediments at sampling intervals of 2 cm to discuss magnetic sensitivity of marine sediment to climate during Holocene for the northern South China Sea. The results indicated that: 1) Concentration dependent magnetic parameters are positive corresponding to variation of temperature. The frequency dependent susceptibility coefficient basically reflected the variation in humidity; 2) XARM/SIRM was more sensitive to detrital magnetite particles and SIRM/X was more effective to biogenic magnetite particles. Variations of XARM/SIRM and SIRM/X are corresponding to precipitation and temperature, respectively; 3) the Holocene Megathermal in the study area was identified as 7.5-3.4 cal. ka BP. The warmest stage of Holocene for the study area should be during 6.1 to 3.9 cal. ka BP; 4) The 8 ka cold event was characterized as cold and dry during 8.55 to 8.25 cal. ka BP; 5) During early and middle Holocene, the climate combinations were warm dry and cold wet. It turned to warm and wet after 2.7 cal. ka BP.

  17. Sensitivity of sediment magnetic records to climate change during Holocene for the northern South China Sea

    Directory of Open Access Journals (Sweden)

    Tingping eOuyang

    2016-05-01

    Full Text Available Magnetic property has been proved to be a sensitive proxy to climate change for both terrestrial and marine sediments. Based on the schedule frame established by AMS 14C dating of foraminifera, detail magnetic analyses were performed for core PC24 sediments at sampling intervals of 2 cm to discuss magnetic sensitivity of marine sediment to climate during Holocene for the northern South China Sea. The results indicated that: 1 Concentration dependent magnetic parameters are positive corresponding to variation of temperature. The frequency dependent susceptibility coefficient basically reflected the variation in humidity; 2 XARM/SIRM was more sensitive to detrital magnetite particles and SIRM/X was more effective to biogenic magnetite particles. Variations of XARM/SIRM and SIRM/X are corresponding to precipitation and temperature, respectively; 3 the Holocene Megathermal in the study area was identified as 7.5-3.4 cal. ka BP. The warmest stage of Holocene for the study area should be during 6.1 to 3.9 cal. ka BP; 4 The 8 ka cold event was characterized as cold and dry during 8.55 to 8.25 cal. ka BP; 5 During early and middle Holocene, the climate combinations were warm dry and cold wet. It turned to warm and wet after 2.7 cal. ka BP.

  18. Last Interglacial climate and sea-level evolution from a coupled ice sheet-climate model

    Science.gov (United States)

    Goelzer, Heiko; Huybrechts, Philippe; Loutre, Marie-France; Fichefet, Thierry

    2016-12-01

    As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG, ˜ 130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate-ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet-climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

  19. Sensitivity of intermittent streams to climate variations in the United States

    Science.gov (United States)

    Eng, K.

    2015-12-01

    There is growing interest in the effects of climate change on streamflows because of the potential negative effects on aquatic biota and water supplies. Previous studies of climate controls on flows have primarily focused on perennial streams, and few studies have examined the effect of climate variability on intermittent streams. Our objectives in this study were to (1) identify regions showing similar patterns of intermittency, and (2) evaluate the sensitivity of intermittent streams to historical variability in climate in the United States. This study was carried out at 265 intermittent streams by evaluating: (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with precipitation (magnitudes, durations and intensity) and temperature, and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results identified five distinct seasonal patterns of flow intermittency: fall, fall-to-winter, non-seasonal, summer, and summer-to-winter intermittent streams. In addition, strong associations between the low-flow metrics and historical climate variability were found. However, the lack of trends in historical variations in precipitation results in no significant seasonal shifts or decade-to-decade trends in the low-flow metrics over the period of record (1950 to 2013).

  20. Sensitivity of intermittent streams to climate variations in the western United States

    Science.gov (United States)

    Eng, K.; Wolock, D.; Dettinger, M. D.

    2014-12-01

    There is a great deal of interest in streamflow changes caused by climate change because of the potential negative effects on aquatic biota and water supplies. Most previous studies have focused on perennial streams, and only a few studies have examined the effect of climate variability on intermittent streams. Our objective in this study was to evaluate the sensitivity of intermittent streams to historical variability in climate in the semi-arid regions of the western United States. This study was carried out at 45 intermittent streams that had a minimum of 45 years of daily-streamgage record by evaluating: (1) correlations among time series of flow metrics (number of zero-flow events, the average of the central 50% and largest 10% of flows) with climate, and (2) decadal changes in the seasonality and long-term trends of these flow metrics. Results showed strong associations between the low-flow metrics and historical changes in climate. The decadal analysis, in contrast, suggested no significant seasonal shifts or decade-to-decade trends in the low-flow metrics. The lack of trends or changes in seasonality is likely due to unchanged long-term patterns in precipitation over the time period examined.

  1. Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

    Science.gov (United States)

    Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

    2018-05-01

    Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

  2. Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography

    DEFF Research Database (Denmark)

    Wu, Minchao; Knorr, Wolfgang; Thonicke, Kirsten

    2015-01-01

    model. Applying a range of future projections that combine different scenarios for climate changes, enhanced CO2 concentrations, and population growth, we investigated the individual and combined effects of these drivers on the total area and regions affected by fire in the 21st century. The two models...

  3. Internal variability in a regional climate model over West Africa

    Energy Technology Data Exchange (ETDEWEB)

    Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)

    2008-02-15

    Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)

  4. A potato model intercomparison across varying climates and productivity levels

    DEFF Research Database (Denmark)

    H. Fleisher, David; Condori, Bruno; Quiroz, Roberto

    2017-01-01

    A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States.......01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach....

  5. A Energy Balance Analysis of the Climate Sensitivity to Variations in the Rate of Upwelling in the World Oceans.

    Science.gov (United States)

    Morantine, Michael Creighton

    -scale to be the source of the dynamic interaction responsible for this abrupt climatic event. The process employed in the dimension reduction used in the formulation of lower-order EBM's will be illustrated through the development of the equations, pointing out the inherent assumptions which must be made when developing one- and two-dimensional models as they are required. One -, two- and three-dimensional energy balance models will be analyzed and the results of climate sensitivity to upwelling variations will be presented graphically for each case.

  6. Conceptual Model of Climate Change Impacts at LANL

    Energy Technology Data Exchange (ETDEWEB)

    Dewart, Jean Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-17

    Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual model of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).

  7. Climate Modeling: Ocean Cavities below Ice Shelves

    Energy Technology Data Exchange (ETDEWEB)

    Petersen, Mark Roger [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Computer, Computational, and Statistical Sciences Division

    2016-09-12

    The Accelerated Climate Model for Energy (ACME), a new initiative by the U.S. Department of Energy, includes unstructured-mesh ocean, land-ice, and sea-ice components using the Model for Prediction Across Scales (MPAS) framework. The ability to run coupled high-resolution global simulations efficiently on large, high-performance computers is a priority for ACME. Sub-ice shelf ocean cavities are a significant new capability in ACME, and will be used to better understand how changing ocean temperature and currents influence glacial melting and retreat. These simulations take advantage of the horizontal variable-resolution mesh and adaptive vertical coordinate in MPAS-Ocean, in order to place high resolution below ice shelves and near grounding lines.

  8. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, M.; Hsiang, S. M.; Schlenker, W.; Sobel, A.

    2013-06-28

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  9. Multi-wheat-model ensemble responses to interannual climatic variability

    DEFF Research Database (Denmark)

    Ruane, A C; Hudson, N I; Asseng, S

    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 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......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 1981–2010 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...

  10. Utilising temperature differences as constraints for estimating parameters in a simple climate model

    International Nuclear Information System (INIS)

    Bodman, Roger W; Karoly, David J; Enting, Ian G

    2010-01-01

    Simple climate models can be used to estimate the global temperature response to increasing greenhouse gases. Changes in the energy balance of the global climate system are represented by equations that necessitate the use of uncertain parameters. The values of these parameters can be estimated from historical observations, model testing, and tuning to more complex models. Efforts have been made at estimating the possible ranges for these parameters. This study continues this process, but demonstrates two new constraints. Previous studies have shown that land-ocean temperature differences are only weakly correlated with global mean temperature for natural internal climate variations. Hence, these temperature differences provide additional information that can be used to help constrain model parameters. In addition, an ocean heat content ratio can also provide a further constraint. A pulse response technique was used to identify relative parameter sensitivity which confirmed the importance of climate sensitivity and ocean vertical diffusivity, but the land-ocean warming ratio and the land-ocean heat exchange coefficient were also found to be important. Experiments demonstrate the utility of the land-ocean temperature difference and ocean heat content ratio for setting parameter values. This work is based on investigations with MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) as the simple climate model.

  11. Modeling technical change in climate analysis: evidence from agricultural crop damages.

    Science.gov (United States)

    Ahmed, Adeel; Devadason, Evelyn S; Al-Amin, Abul Quasem

    2017-05-01

    This study accounts for the Hicks neutral technical change in a calibrated model of climate analysis, to identify the optimum level of technical change for addressing climate changes. It demonstrates the reduction to crop damages, the costs to technical change, and the net gains for the adoption of technical change for a climate-sensitive Pakistan economy. The calibrated model assesses the net gains of technical change for the overall economy and at the agriculture-specific level. The study finds that the gains of technical change are overwhelmingly higher than the costs across the agriculture subsectors. The gains and costs following technical change differ substantially for different crops. More importantly, the study finds a cost-effective optimal level of technical change that potentially reduces crop damages to a minimum possible level. The study therefore contends that the climate policy for Pakistan should consider the role of technical change in addressing climate impacts on the agriculture sector.

  12. Climate implications of carbonaceous aerosols: An aerosol microphysical study using the GISS/MATRIX climate model

    International Nuclear Information System (INIS)

    Bauer, Susanne E.; Menon, Surabi; Koch, Dorothy; Bond, Tami; Tsigaridis, Kostas

    2010-01-01

    Recently, attention has been drawn towards black carbon aerosols as a likely short-term climate warming mitigation candidate. However the global and regional impacts of the direct, cloud-indirect and semi-direct forcing effects are highly uncertain, due to the complex nature of aerosol evolution and its climate interactions. Black carbon is directly released as particle into the atmosphere, but then interacts with other gases and particles through condensation and coagulation processes leading to further aerosol growth, aging and internal mixing. A detailed aerosol microphysical scheme, MATRIX, embedded within the global GISS modelE includes the above processes that determine the lifecycle and climate impact of aerosols. This study presents a quantitative assessment of the impact of microphysical processes involving black carbon, such as emission size distributions and optical properties on aerosol cloud activation and radiative forcing. Our best estimate for net direct and indirect aerosol radiative forcing change is -0.56 W/m 2 between 1750 and 2000. However, the direct and indirect aerosol effects are very sensitive to the black and organic carbon size distribution and consequential mixing state. The net radiative forcing change can vary between -0.32 to -0.75 W/m 2 depending on these carbonaceous particle properties. Assuming that sulfates, nitrates and secondary organics form a coating shell around a black carbon core, rather than forming a uniformly mixed particles, changes the overall net radiative forcing from a negative to a positive number. Black carbon mitigation scenarios showed generally a benefit when mainly black carbon sources such as diesel emissions are reduced, reducing organic and black carbon sources such as bio-fuels, does not lead to reduced warming.

  13. Predicting Future Seed Sourcing of Platycladus orientalis (L. for Future Climates Using Climate Niche Models

    Directory of Open Access Journals (Sweden)

    Xian-Ge Hu

    2017-12-01

    Full Text Available Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L. seed zones (Northwestern; Northern; Central; Southern; and Subtropical covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5. Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.

  14. Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

    Energy Technology Data Exchange (ETDEWEB)

    Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

    2017-01-04

    Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

  15. Atmospheric sulfur and climate changes: a modelling study at mid and high-southern latitudes

    International Nuclear Information System (INIS)

    Castebrunet, H.

    2007-09-01

    The mid and high-southern latitudes are still marginally affected by anthropogenic sulfur emissions. They are the only regions in the world where the natural cycle of the atmospheric sulfur may still be observed. Sulfur aerosols are well-known for their radiative impact, and thus interact with climate. Climate can in turn affect atmospheric sulfur sources, distribution and chemistry. Antarctic ice cores provide information on the evolution of climate and sulfur deposition at the surface of the ice sheet at glacial-interglacial time scales. The aim of this thesis is to develop and use modeling towards a better understanding of the atmospheric sulfur cycle in antarctic and sub-antarctic regions. Ice core data are used to validate model results under glacial climate conditions. An Atmospheric General Circulation Model (AGCM) coupled to a sulfur chemistry module is used: the LMD-ZTSulfur model, version 4. An update of both the physical and chemical parts of the model. The model was first performed. The impact of there changes on modelled sulfur cycle are evaluated for modern climate. Further, boundary conditions are adapted to simulate the atmospheric circulation and sulfur cycle at the Last Glacial Maximum, approximately 20,000 years ago. In the model, sulfur is found to be highly sensitive to antarctic sea-ice coverage, which is still poorly known during the ice age. An original dataset of ice-age sea-ice coverage was developed. Its impact on the oceanic emissions of dimethyl sulfide, main precursor of sulfur aerosols at high-southern latitudes, is discussed. Using the same oceanic sulfur reservoirs as for present day climate, the model broadly reproduces the glacial deposits of sulfur aerosols on the Antarctic plateau, suggesting little impact of climate on oceanic sulfur production in the Antarctic region. Sensitivity tests were carried out to draw an up-to-date status of major uncertainties and difficulties facing future progress in understanding atmospheric

  16. Simulated climate change during the last 1,000 years: comparing the ECHO-G general circulation model with the MAGICC simple climate model

    Energy Technology Data Exchange (ETDEWEB)

    Osborn, Timothy J.; Briffa, Keith R. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Raper, Sarah C.B. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Manchester Metropolitan University, Dalton Research Institute, Manchester (United Kingdom)

    2006-08-15

    An intercomparison of eight climate simulations, each driven with estimated natural and anthropogenic forcings for the last millennium, indicates that the so-called ''Erik'' simulation of the ECHO-G coupled ocean-atmosphere climate model exhibits atypical behaviour. The ECHO-G simulation has a much stronger cooling trend from 1000 to 1700 and a higher rate of warming since 1800 than the other simulations, with the result that the overall amplitude of millennial-scale temperature variations in the ECHO-G simulation is much greater than in the other models. The MAGICC (Model for the Assessment of Greenhouse-gas-Induced Climate Change) simple climate model is used to investigate possible causes of this atypical behaviour. It is shown that disequilibrium in the initial conditions probably contributes spuriously to the cooling trend in the early centuries of the simulation, and that the omission of tropospheric sulphate aerosol forcing is the likely explanation for the anomalously large recent warming. The simple climate model results are used to adjust the ECHO-G Erik simulation to mitigate these effects, which brings the simulation into better agreement with the other seven models considered here and greatly reduces the overall range of temperature variations during the last millennium simulated by ECHO-G. Smaller inter-model differences remain which can probably be explained by a combination of the particular forcing histories and model sensitivities of each experiment. These have not been investigated here, though we have diagnosed the effective climate sensitivity of ECHO-G to be 2.39{+-}0.11 K for a doubling of CO{sub 2}. (orig.)

  17. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2014-12-01

    We have developed a cloud-enabled web-service system that empowers physics-based, multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks. The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the observational datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation, (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs, and (3) ECMWF reanalysis outputs for several environmental variables in order to supplement observational datasets. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, (4) the calculation of difference between two variables, and (5) the conditional sampling of one physical variable with respect to another variable. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use, avoiding the hassle of local software installation and environment incompatibility. CMDA will be used as an educational tool for the summer school organized by JPL's Center for Climate Science in 2014. In order to support 30+ simultaneous users during the school, we have deployed CMDA to the Amazon cloud environment. The cloud-enabled CMDA will provide each student with a virtual machine while the user interaction with the system will remain the same

  18. Evaluating the performance and utility of regional climate models

    DEFF Research Database (Denmark)

    Christensen, Jens H.; Carter, Timothy R.; Rummukainen, Markku

    2007-01-01

    This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design...... of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme...

  19. Sensitivity analysis of Smith's AMRV model

    International Nuclear Information System (INIS)

    Ho, Chih-Hsiang

    1995-01-01

    Multiple-expert hazard/risk assessments have considerable precedent, particularly in the Yucca Mountain site characterization studies. In this paper, we present a Bayesian approach to statistical modeling in volcanic hazard assessment for the Yucca Mountain site. Specifically, we show that the expert opinion on the site disruption parameter p is elicited on the prior distribution, π (p), based on geological information that is available. Moreover, π (p) can combine all available geological information motivated by conflicting but realistic arguments (e.g., simulation, cluster analysis, structural control, etc.). The incorporated uncertainties about the probability of repository disruption p, win eventually be averaged out by taking the expectation over π (p). We use the following priors in the analysis: priors chosen for mathematical convenience: Beta (r, s) for (r, s) = (2, 2), (3, 3), (5, 5), (2, 1), (2, 8), (8, 2), and (1, 1); and three priors motivated by expert knowledge. Sensitivity analysis is performed for each prior distribution. Estimated values of hazard based on the priors chosen for mathematical simplicity are uniformly higher than those obtained based on the priors motivated by expert knowledge. And, the model using the prior, Beta (8,2), yields the highest hazard (= 2.97 X 10 -2 ). The minimum hazard is produced by the open-quotes three-expert priorclose quotes (i.e., values of p are equally likely at 10 -3 10 -2 , and 10 -1 ). The estimate of the hazard is 1.39 x which is only about one order of magnitude smaller than the maximum value. The term, open-quotes hazardclose quotes, is defined as the probability of at least one disruption of a repository at the Yucca Mountain site by basaltic volcanism for the next 10,000 years

  20. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  1. Sensitivity study of reduced models of the activated sludge process ...

    African Journals Online (AJOL)

    The problem of derivation and calculation of sensitivity functions for all parameters of the mass balance reduced model of the COST benchmark activated sludge plant is formulated and solved. The sensitivity functions, equations and augmented sensitivity state space models are derived for the cases of ASM1 and UCT ...

  2. Statistical Compression for Climate Model Output

    Science.gov (United States)

    Hammerling, D.; Guinness, J.; Soh, Y. J.

    2017-12-01

    Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the origi