Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

Energy Technology Data Exchange (ETDEWEB)

Bhatt, Uma S. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Wackerbauer, Renate [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Polyakov, Igor V. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences; Newman, David E. [Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics; Sanchez, Raul E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fusion Energy Division; Univ. Carlos III de Madrid (Spain)

2015-11-13

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.

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

Science.gov (United States)

McCusker, Kelly E.

Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

Toward an ultra-high resolution community climate system model for the BlueGene platform

Energy Technology Data Exchange (ETDEWEB)

Dennis, John M [Computer Science Section, National Center for Atmospheric Research, Boulder, CO (United States); Jacob, Robert [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States); Vertenstein, Mariana [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Craig, Tony [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Loy, Raymond [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States)

2007-07-15

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10{sup 0} resolution for CICE, POP, and CLM models and 1/4{sup 0} resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science.

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

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.

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....

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.

Modelling the effects of climate change on the energy system-A case study of Norway

International Nuclear Information System (INIS)

Seljom, Pernille; Rosenberg, Eva; Fidje, Audun; Haugen, Jan Erik; Meir, Michaela; Rekstad, John; Jarlset, Thore

2011-01-01

The overall objective of this work is to identify the effects of climate change on the Norwegian energy system towards 2050. Changes in the future wind- and hydro-power resource potential, and changes in the heating and cooling demand are analysed to map the effects of climate change. The impact of climate change is evaluated with an energy system model, the MARKAL Norway model, to analyse the future cost optimal energy system. Ten climate experiments, based on five different global models and six emission scenarios, are used to cover the range of possible future climate scenarios and of these three experiments are used for detailed analyses. This study indicate that in Norway, climate change will reduce the heating demand, increase the cooling demand, have a limited impact on the wind power potential, and increase the hydro-power potential. The reduction of heating demand will be significantly higher than the increase of cooling demand, and thus the possible total direct consequence of climate change will be reduced energy system costs and lower electricity production costs. The investments in offshore wind and tidal power will be reduced and electric based vehicles will be profitable earlier. - Highlights: → Climate change will make an impact on the Norwegian energy system towards 2050. → An impact is lower Norwegian electricity production costs and increased electricity export. → Climate change gives earlier profitable investments in electric based vehicles. → Climate change reduces investments in offshore wind and tidal power.

A Scalable and Extensible Earth System Model for Climate Change Science

Energy Technology Data Exchange (ETDEWEB)

Gent, Peter; Lamarque, Jean-Francois; Conley, Andrew; Vertenstein, Mariana; Craig, Anthony

2013-02-13

The objective of this award was to build a scalable and extensible Earth System Model that can be used to study climate change science. That objective has been achieved with the public release of the Community Earth System Model, version 1 (CESM1). In particular, the development of the CESM1 atmospheric chemistry component was substantially funded by this award, as was the development of the significantly improved coupler component. The CESM1 allows new climate change science in areas such as future air quality in very large cities, the effects of recovery of the southern hemisphere ozone hole, and effects of runoff from ice melt in the Greenland and Antarctic ice sheets. Results from a whole series of future climate projections using the CESM1 are also freely available via the web from the CMIP5 archive at the Lawrence Livermore National Laboratory. Many research papers using these results have now been published, and will form part of the 5th Assessment Report of the United Nations Intergovernmental Panel on Climate Change, which is to be published late in 2013.

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.

The DSET Tool Library: A software approach to enable data exchange between climate system models

Energy Technology Data Exchange (ETDEWEB)

McCormick, J. [Lawrence Livermore National Lab., CA (United States)

1994-12-01

Climate modeling is a computationally intensive process. Until recently computers were not powerful enough to perform the complex calculations required to simulate the earth`s climate. As a result standalone programs were created that represent components of the earth`s climate (e.g., Atmospheric Circulation Model). However, recent advances in computing, including massively parallel computing, make it possible to couple the components forming a complete earth climate simulation. The ability to couple different climate model components will significantly improve our ability to predict climate accurately and reliably. Historically each major component of the coupled earth simulation is a standalone program designed independently with different coordinate systems and data representations. In order for two component models to be coupled, the data of one model must be mapped to the coordinate system of the second model. The focus of this project is to provide a general tool to facilitate the mapping of data between simulation components, with an emphasis on using object-oriented programming techniques to provide polynomial interpolation, line and area weighting, and aggregation services.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

DEFF Research Database (Denmark)

Eby, M.; Weaver, A. J.; Alexander, K.

2013-01-01

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...

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.)

Climate Ocean Modeling on a Beowulf Class System

Science.gov (United States)

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

2000-01-01

With the growing power and shrinking cost of personal computers. the availability of fast ethernet interconnections, and public domain software packages, it is now possible to combine them to build desktop parallel computers (named Beowulf or PC clusters) at a fraction of what it would cost to buy systems of comparable power front supercomputer companies. This led as to build and assemble our own sys tem. specifically for climate ocean modeling. In this article, we present our experience with such a system, discuss its network performance, and provide some performance comparison data with both HP SPP2000 and Cray T3E for an ocean Model used in present-day oceanographic research.

Modeling the impact of large-scale energy conversion systems on global climate

International Nuclear Information System (INIS)

Williams, J.

There are three energy options which could satisfy a projected energy requirement of about 30 TW and these are the solar, nuclear and (to a lesser extent) coal options. Climate models can be used to assess the impact of large scale deployment of these options. The impact of waste heat has been assessed using energy balance models and general circulation models (GCMs). Results suggest that the impacts are significant when the heat imput is very high and studies of more realistic scenarios are required. Energy balance models, radiative-convective models and a GCM have been used to study the impact of doubling the atmospheric CO 2 concentration. State-of-the-art models estimate a surface temperature increase of 1.5-3.0 0 C with large amplification near the poles, but much uncertainty remains. Very few model studies have been made of the impact of particles on global climate, more information on the characteristics of particle input are required. The impact of large-scale deployment of solar energy conversion systems has received little attention but model studies suggest that large scale changes in surface characteristics associated with such systems (surface heat balance, roughness and hydrological characteristics and ocean surface temperature) could have significant global climatic effects. (Auth.)

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

2016-10-17

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

The computational future for climate and Earth system models: on the path to petaflop and beyond.

Science.gov (United States)

Washington, Warren M; Buja, Lawrence; Craig, Anthony

2009-03-13

The development of the climate and Earth system models has had a long history, starting with the building of individual atmospheric, ocean, sea ice, land vegetation, biogeochemical, glacial and ecological model components. The early researchers were much aware of the long-term goal of building the Earth system models that would go beyond what is usually included in the climate models by adding interactive biogeochemical interactions. In the early days, the progress was limited by computer capability, as well as by our knowledge of the physical and chemical processes. Over the last few decades, there has been much improved knowledge, better observations for validation and more powerful supercomputer systems that are increasingly meeting the new challenges of comprehensive models. Some of the climate model history will be presented, along with some of the successes and difficulties encountered with present-day supercomputer systems.

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.

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.

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...

Modeling U.S. water resources under climate change

Science.gov (United States)

Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

2014-04-01

Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

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

Climate Science: How Earth System Models are Reshaping the Science Policy Interface.

Science.gov (United States)

Ruane, Alex

2015-01-01

This talk is oriented at a general audience including the largest French utility company, and will describe the basics of climate change before moving into emissions scenarios and agricultural impacts that we can test with our earth system models and impacts models.

Regional climate projection of the Maritime Continent using the MIT Regional Climate Model

Science.gov (United States)

IM, E. S.; Eltahir, E. A. B.

2014-12-01

Given that warming of the climate system is unequivocal (IPCC AR5), accurate assessment of future climate is essential to understand the impact of climate change due to global warming. Modelling the climate change of the Maritime Continent is particularly challenge, showing a high degree of uncertainty. Compared to other regions, model agreement of future projections in response to anthropogenic emission forcings is much less. Furthermore, the spatial and temporal behaviors of climate projections seem to vary significantly due to a complex geographical condition and a wide range of scale interactions. For the fine-scale climate information (27 km) suitable for representing the complexity of climate change over the Maritime Continent, dynamical downscaling is performed using the MIT regional climate model (MRCM) during two thirty-year period for reference (1970-1999) and future (2070-2099) climate. Initial and boundary conditions are provided by Community Earth System Model (CESM) simulations under the emission scenarios projected by MIT Integrated Global System Model (IGSM). Changes in mean climate as well as the frequency and intensity of extreme climate events are investigated at various temporal and spatial scales. Our analysis is primarily centered on the different behavior of changes in convective and large-scale precipitation over land vs. ocean during dry vs. wet season. In addition, we attempt to find the added value to downscaled results over the Maritime Continent through the comparison between MRCM and CESM projection. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

An Overview of the Future Development of Climate and Earth System Models for Scientific and Policy Use (Invited)

Science.gov (United States)

Washington, W. M.

2010-12-01

The development of climate and earth system models has been regarded primarily as the making of scientific tools to study the complex nature of the Earth’s climate. These models have a long history starting with very simple physical models based on fundamental physics in the 1960s and over time they have become much more complex with atmospheric, ocean, sea ice, land/vegetation, biogeochemical, glacial and ecological components. The policy use aspects of these models did not start in the 1960s and 1970s as decision making tools but were used to answer fundamental scientific questions such as what happens when the atmospheric carbon dioxide concentration increases or is doubled. They gave insights into the various interactions and were extensively compared with observations. It was realized that models of the earlier time periods could only give first order answers to many of the fundamental policy questions. As societal concerns about climate change rose, the policy questions of anthropogenic climate change became better defined; they were mostly concerned with the climate impacts of increasing greenhouse gases, aerosols, and land cover change. In the late 1980s, the United Nations set up the Intergovernmental Panel on Climate Change to perform assessments of the published literature. Thus, the development of climate and Earth system models became intimately linked to the need to not only improve our scientific understanding but also answering fundamental policy questions. In order to meet this challenge, the models became more complex and realistic so that they could address these policy oriented science questions such as rising sea level. The presentation will discuss the past and future development of global climate and earth system models for science and policy purposes. Also to be discussed is their interactions with economic integrated assessment models, regional and specialized models such as river transport or ecological components. As an example of one

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

Science.gov (United States)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their

Coupled water-energy modelling to assess climate change impacts on the Iberian Power System

DEFF Research Database (Denmark)

Pereira Cardenal, Silvio Javier; Madsen, H.; Riegels, N.

and marginal costs of the power producers. Two effects of climate change on the power system were studied: changes in the hydropower production caused by changes in precipitation and temperature, and changes in the electricity demand over the year caused by temperature changes. A rainfall-runoff model......Water resources systems and power systems are strongly linked; water is needed for most power generation technologies, and electricity is required in every stage of water usage. In the Iberian Peninsula, climate change is expected to have a negative impact on the power system: changes in runoff...... was established to estimate the impact of precipitation and temperature changes on reservoir inflows. The model was calibrated using observed precipitation, temperature and river discharge time series. Potential evapotranspiration was estimated from temperature data, and snow accumulation/melt was modelled using...

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

Directory of Open Access Journals (Sweden)

Annelie Holzkämper

2017-10-01

Full Text Available Climate change poses a challenge to agricultural production and its impacts vary depending on regional focus and on the type of production system. To avoid production losses and make use of emerging potentials, adaptations in agricultural management will inevitably be required. Adaptation responses can broadly be distinguished into (1 short-term incremental responses that farmers often choose autonomously in response to observed changes and based on local knowledge and experiences, and (2 long-term transformative responses that require strategic planning, and which are usually implemented at a larger spatial scale. Models can be used to support decision making at both response levels; thereby, different features of models prove more or less valuable depending on the type of adaptation response. This paper presents a systematic literature review on the state-of-the-art in modelling for adaptation planning in agricultural production systems, investigating the question of which model types can be distinguished and how these types differ in the way they support decision making in agricultural adaptation planning. Five types of models are distinguished: (1 empirical crop models; (2 regional suitability models; (3 biophysical models; (4 meta-models; and (5 decision models. The potential and limitations of these model types for providing decision-support to short- and long-term adaptation planning are discussed. The risk of maladaptation—adaptation that implies negative consequences either in the long term or in a wider context—is identified as a key challenge of adaptation planning that needs more attention. Maladaptation is not only a risk of decision making in the face of incomplete knowledge of future climate impacts on the agricultural production system; but it can also be a threat if the connectedness of the agroecosystem is not sufficiently acknowledged when management adaptations are implemented. Future research supporting climate change

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

Energy Technology Data Exchange (ETDEWEB)

Fedorov, Alexey V. [Yale Univ., New Haven, CT (United States)

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth system models, to the stability and variability of the AMOC in past climates.

A new synoptic scale resolving global climate simulation using the Community Earth System Model

Science.gov (United States)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

The climate4impact platform: Providing, tailoring and facilitating climate model data access

Science.gov (United States)

Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

2017-04-01

One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

Science.gov (United States)

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

A Semi-empirical Model of the Stratosphere in the Climate System

Science.gov (United States)

Sodergren, A. H.; Bodeker, G. E.; Kremser, S.; Meinshausen, M.; McDonald, A.

2014-12-01

Chemistry climate models (CCMs) currently used to project changes in Antarctic ozone are extremely computationally demanding. CCM projections are uncertain due to lack of knowledge of future emissions of greenhouse gases (GHGs) and ozone depleting substances (ODSs), as well as parameterizations within the CCMs that have weakly constrained tuning parameters. While projections should be based on an ensemble of simulations, this is not currently possible due to the complexity of the CCMs. An inexpensive but realistic approach to simulate changes in stratospheric ozone, and its coupling to the climate system, is needed as a complement to CCMs. A simple climate model (SCM) can be used as a fast emulator of complex atmospheric-ocean climate models. If such an SCM includes a representation of stratospheric ozone, the evolution of the global ozone layer can be simulated for a wide range of GHG and ODS emissions scenarios. MAGICC is an SCM used in previous IPCC reports. In the current version of the MAGICC SCM, stratospheric ozone changes depend only on equivalent effective stratospheric chlorine (EESC). In this work, MAGICC is extended to include an interactive stratospheric ozone layer using a semi-empirical model of ozone responses to CO2and EESC, with changes in ozone affecting the radiative forcing in the SCM. To demonstrate the ability of our new, extended SCM to generate projections of global changes in ozone, tuning parameters from 19 coupled atmosphere-ocean general circulation models (AOGCMs) and 10 carbon cycle models (to create an ensemble of 190 simulations) have been used to generate probability density functions of the dates of return of stratospheric column ozone to 1960 and 1980 levels for different latitudes.

An Integrated Modelling System to Predict Hydrological Processes under Climate and Land-Use/Cover Change Scenarios

Directory of Open Access Journals (Sweden)

Babak Farjad

2017-10-01

Full Text Available This study proposes an integrated modeling system consisting of the physically-based MIKE SHE/MIKE 11 model, a cellular automata model, and general circulation models (GCMs scenarios to investigate the independent and combined effects of future climate and land-use/land-cover (LULC changes on the hydrology of a river system. The integrated modelling system is applied to the Elbow River watershed in southern Alberta, Canada in conjunction with extreme GCM scenarios and two LULC change scenarios in the 2020s and 2050s. Results reveal that LULC change substantially modifies the river flow regime in the east sub-catchment, where rapid urbanization is occurring. It is also shown that the change in LULC causes an increase in peak flows in both the 2020s and 2050s. The impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence and leads to a significant rise in streamflow, and, subsequently, increases the vulnerability of the watershed to spring floods. This study highlights the importance of using an integrated modeling approach to investigate both the independent and combined impacts of climate and LULC changes on the future of hydrology to improve our understanding of how watersheds will respond to climate and LULC changes.

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.

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.

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)

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)

COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

Energy Technology Data Exchange (ETDEWEB)

Gutowski, William J.

2013-02-07

The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

Science.gov (United States)

Bailey, D. A.; Holland, M. M.; DuVivier, A. K.

2017-12-01

The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.

The CSIRO Mk3L climate system model version 1.0 – Part 1: Description and evaluation

Directory of Open Access Journals (Sweden)

S. J. Phipps

2011-06-01

Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulations and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. This paper describes the model physics and software, analyses the control climatology, and evaluates the ability of the model to simulate the modern climate.

Mk3L incorporates a spectral atmospheric general circulation model, a z-coordinate ocean general circulation model, a dynamic-thermodynamic sea ice model and a land surface scheme with static vegetation. The source code is highly portable, and has no dependence upon proprietary software. The model distribution is freely available to the research community. A 1000-yr climate simulation can be completed in around one-and-a-half months on a typical desktop computer, with greater throughput being possible on high-performance computing facilities.

Mk3L produces realistic simulations of the larger-scale features of the modern climate, although with some biases on the regional scale. The model also produces reasonable representations of the leading modes of internal climate variability in both the tropics and extratropics. The control state of the model exhibits a high degree of stability, with only a weak cooling trend on millennial timescales. Ongoing development work aims to improve the model climatology and transform Mk3L into a comprehensive earth system model.

Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.

Science.gov (United States)

Bonan, Gordon B; Doney, Scott C

2018-02-02

Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.

Study on the climate system and mass transport by a climate model

International Nuclear Information System (INIS)

Numaguti, A.; Sugata, S.; Takahashi, M.; Nakajima, T.; Sumi, A.

1997-01-01

The Center for Global Environmental Research (CGER), an organ of the National Institute for Environmental Studies of the Environment Agency of Japan, was established in October 1990 to contribute broadly to the scientific understanding of global change, and to the elucidation of and solution for our pressing environmental problems. CGER conducts environmental research from interdisciplinary, multiagency, and international perspective, provides research support facilities such as a supercomputer and databases, and offers its own data from long-term monitoring of the global environment. In March 1992, CGER installed a supercomputer system (NEC SX-3, Model 14) to facilitate research on global change. The system is open to environmental researchers worldwide. Proposed research programs are evaluated by the Supercomputer Steering Committee which consists of leading scientists in climate modeling, atmospheric chemistry, oceanic circulation, and computer science. After project approval, authorization for system usage is provided. In 1995 and 1996, several research proposals were designated as priority research and allocated larger shares of computer resources. The CGER supercomputer monograph report Vol. 3 is a report of priority research of CGER's supercomputer. The report covers the description of CCSR-NIES atmospheric general circulation model, lagragian general circulation based on the time-scale of particle motion, and ability of the CCSR-NIES atmospheric general circulation model in the stratosphere. The results obtained from these three studies are described in three chapters. We hope this report provides you with useful information on the global environmental research conducted on our supercomputer

Climate change induced transformations of agricultural systems: insights from a global model

Science.gov (United States)

Leclère, D.; Havlík, P.; Fuss, S.; Schmid, E.; Mosnier, A.; Walsh, B.; Valin, H.; Herrero, M.; Khabarov, N.; Obersteiner, M.

2014-12-01

Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis.

Climate change induced transformations of agricultural systems: insights from a global model

International Nuclear Information System (INIS)

Leclère, D; Havlík, P; Mosnier, A; Walsh, B; Valin, H; Khabarov, N; Obersteiner, M; Fuss, S; Schmid, E; Herrero, M

2014-01-01

Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis. (letter)

Climate change impacts on food system

Science.gov (United States)

Zhang, X.; Cai, X.; Zhu, T.

2014-12-01

Food system includes biophysical factors (climate, land and water), human environments (production technologies and food consumption, distribution and marketing), as well as the dynamic interactions within them. Climate change affects agriculture and food systems in various ways. Agricultural production can be influenced directly by climatic factors such as mean temperature rising, change in rainfall patterns, and more frequent extreme events. Eventually, climate change could cause shift of arable land, alteration of water availability, abnormal fluctuation of food prices, and increase of people at risk of malnutrition. This work aims to evaluate how climate change would affect agricultural production biophysically and how these effects would propagate to social factors at the global level. In order to model the complex interactions between the natural and social components, a Global Optimization model of Agricultural Land and Water resources (GOALW) is applied to the analysis. GOALW includes various demands of human society (food, feed, other), explicit production module, and irrigation water availability constraint. The objective of GOALW is to maximize global social welfare (consumers' surplus and producers' surplus).Crop-wise irrigation water use in different regions around the world are determined by the model; marginal value of water (MVW) can be obtained from the model, which implies how much additional welfare benefit could be gained with one unit increase in local water availability. Using GOALW, we will analyze two questions in this presentation: 1) how climate change will alter irrigation requirements and how the social system would buffer that by price/demand adjustment; 2) how will the MVW be affected by climate change and what are the controlling factors. These results facilitate meaningful insights for investment and adaptation strategies in sustaining world's food security under climate change.

Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

Science.gov (United States)

Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

2017-04-01

The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

Science.gov (United States)

Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

2008-01-01

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5

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

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

Adapting Nyando smallholder farming systems to climate change and variability through modelling

NARCIS (Netherlands)

Recha, T.O.; Gachene, C.K.K.; Claessens, L.F.G.

2017-01-01

This study was done in Nyando, Kenya to model maize production under different climate scenarios and project the yields up to 2030 and 2050 using Decision Support System for Agrotechnology Transfer (DSSAT) under rain fed conditions. Three maize varieties were used; Katumani Comp B as early maturing

Regional decadal predictions of coupled climate-human systems

Science.gov (United States)

Curchitser, E. N.; Lawrence, P.; Felder, F.; Large, W.; Bacmeister, J. T.; Andrews, C.; Kopp, R. E.

2016-12-01

We present results from a project to develop a framework for investigating the interactions between human activity and the climate system using state-of-the-art multi-scale, climate and economic models. The model is applied to the highly industrialized and urbanized coastal region of the northeast US with an emphasis on New Jersey. The framework is developed around the NCAR Community Earth System Model (CESM). The CESM model capabilities are augmented with enhanced resolution of the atmosphere (25 km), land surface (I km) and ocean models (7 km) in our region of interest. To the climate model, we couple human activity models for the utility sector and a 300-equation econometric model with sectorial details of an input-output model for the New Jersey economy. We will present results to date showing the potential impact of climate change on electricity markets on its consequences on economic activity in the region.

Assessing climate change impact by integrated hydrological modelling

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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

System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

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Pervin, Lia; Islam, Md Saiful

2015-02-01

The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

GLOBAL CLIMATE MODEL:A COMPREHENSIVE TOOL IN CLIMATE CHANGE IMPACT STUDIES

Directory of Open Access Journals (Sweden)

Dharmaveer Singh

2015-01-01

Full Text Available There is growing concern, how and to what extent future changes in climate will affect human society and natural environments. Continuous emissions of Green House Gasses (GHGs at or above current rates will cause further warming. This, in turn, may modify global climate system during 21st century that very likely would have larger impacts than those observed during 20th century. At present, Global Climate Models (GCMs are only the most reliable tools available for studying behaviour of the climate system. This paper presents a comprehensive review of GCMs including their development and applications in climate change impacts studies. Following a discussion of the limitations of GCMs at regional and local scales, different approaches of downscaling are discussed in detail.

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

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

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and

Next-Generation Climate Modeling Science Challenges for Simulation, Workflow and Analysis Systems

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Koch, D. M.; Anantharaj, V. G.; Bader, D. C.; Krishnan, H.; Leung, L. R.; Ringler, T.; Taylor, M.; Wehner, M. F.; Williams, D. N.

2016-12-01

We will present two examples of current and future high-resolution climate-modeling research that are challenging existing simulation run-time I/O, model-data movement, storage and publishing, and analysis. In each case, we will consider lessons learned as current workflow systems are broken by these large-data science challenges, as well as strategies to repair or rebuild the systems. First we consider the science and workflow challenges to be posed by the CMIP6 multi-model HighResMIP, involving around a dozen modeling groups performing quarter-degree simulations, in 3-member ensembles for 100 years, with high-frequency (1-6 hourly) diagnostics, which is expected to generate over 4PB of data. An example of science derived from these experiments will be to study how resolution affects the ability of models to capture extreme-events such as hurricanes or atmospheric rivers. Expected methods to transfer (using parallel Globus) and analyze (using parallel "TECA" software tools) HighResMIP data for such feature-tracking by the DOE CASCADE project will be presented. A second example will be from the Accelerated Climate Modeling for Energy (ACME) project, which is currently addressing challenges involving multiple century-scale coupled high resolution (quarter-degree) climate simulations on DOE Leadership Class computers. ACME is anticipating production of over 5PB of data during the next 2 years of simulations, in order to investigate the drivers of water cycle changes, sea-level-rise, and carbon cycle evolution. The ACME workflow, from simulation to data transfer, storage, analysis and publication will be presented. Current and planned methods to accelerate the workflow, including implementing run-time diagnostics, and implementing server-side analysis to avoid moving large datasets will be presented.

Representation of the West African Monsoon System in the aerosol-climate model ECHAM6-HAM2

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Stanelle, Tanja; Lohmann, Ulrike; Bey, Isabelle

2017-04-01

The West African Monsoon (WAM) is a major component of the global monsoon system. The temperature contrast between the Saharan land surface in the North and the sea surface temperature in the South dominates the WAM formation. The West African region receives most of its precipitation during the monsoon season between end of June and September. Therefore the existence of the monsoon is of major social and economic importance. We discuss the ability of the climate model ECHAM6 as well as the coupled aerosol climate model ECHAM6-HAM2 to simulate the major features of the WAM system. The north-south temperature gradient is reproduced by both model versions but all model versions fail in reproducing the precipitation amount south of 10° N. A special focus is on the representation of the nocturnal low level jet (NLLJ) and the corresponding enhancement of low level clouds (LLC) at the Guinea Coast, which are a crucial factor for the regional energy budget. Most global climate models have difficulties to represent these features. The pure climate model ECHAM6 is able to simulate the existence of the NLLJ and LLC, but the model does not represent the pronounced diurnal cycle. Overall, the representation of LLC is worse in the coupled model. We discuss the model behaviors on the basis of outputted temperature and humidity tendencies and try to identify potential processes responsible for the model deficiencies.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

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Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Influence of the management strategy model on estimating water system performance under climate change

Science.gov (United States)

Francois, Baptiste; Hingray, Benoit; Creutin, Jean-Dominique; Hendrickx, Frederic

2015-04-01

The performance of water systems used worldwide for the management of water resources is expected to be influenced by future changes in regional climates and water uses. Anticipating possible performance changes of a given system requires a modeling chain simulating its management. Operational management is usually not trivial especially when several conflicting objectives have to be accounted for. Management models are therefore often a crude representation of the real system and they only approximate its performance. Estimated performance changes are expected to depend on the management model used, but this is often not assessed. This communication analyzes the influence of the management strategy representation on the performance of an Alpine reservoir (Serre-Ponçon, South-East of France) for which irrigation supply, hydropower generation and recreational activities are the main objectives. We consider three ways to construct the strategy named as clear-, short- and far-sighted management. They are based on different forecastability degrees of seasonal inflows into the reservoir. The strategies are optimized using a Dynamic Programming algorithm (deterministic for clear-sighted and implicit stochastic for short- and far-sighted). System performance is estimated for an ensemble of future hydro-meteorological projections obtained in the RIWER2030 research project (http://www.lthe.fr/RIWER2030/) from a suite of climate experiments from the EU - ENSEMBLES research project. Our results show that changes in system performance is much more influenced by changes in hydro-meteorological variables than by the choice of strategy modeling. They also show that a simple strategy representation (i.e. clear-sighted management) leads to similar estimates of performance modifications than those obtained with a representation supposedly closer to real world (i.e. the far-sighted management). The Short-Sighted management approach lead to significantly different results, especially

The Earth System Model

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Schoeberl, Mark; Rood, Richard B.; Hildebrand, Peter; Raymond, Carol

2003-01-01

The Earth System Model is the natural evolution of current climate models and will be the ultimate embodiment of our geophysical understanding of the planet. These models are constructed from components - atmosphere, ocean, ice, land, chemistry, solid earth, etc. models and merged together through a coupling program which is responsible for the exchange of data from the components. Climate models and future earth system models will have standardized modules, and these standards are now being developed by the ESMF project funded by NASA. The Earth System Model will have a variety of uses beyond climate prediction. The model can be used to build climate data records making it the core of an assimilation system, and it can be used in OSSE experiments to evaluate. The computing and storage requirements for the ESM appear to be daunting. However, the Japanese ES theoretical computing capability is already within 20% of the minimum requirements needed for some 2010 climate model applications. Thus it seems very possible that a focused effort to build an Earth System Model will achieve succcss.

Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system

Directory of Open Access Journals (Sweden)

H. T. Hewitt

2011-04-01

Full Text Available This paper describes the development of a technically robust climate modelling system, HadGEM3, which couples the Met Office Unified Model atmosphere component, the NEMO ocean model and the Los Alamos sea ice model (CICE using the OASIS coupler. Details of the coupling and technical solutions of the physical model (HadGEM3-AO are documented, in addition to a description of the configurations of the individual submodels. The paper demonstrates that the implementation of the model has resulted in accurate conservation of heat and freshwater across the model components. The model performance in early versions of this climate model is briefly described to demonstrate that the results are scientifically credible. HadGEM3-AO is the basis for a number of modelling efforts outside of the Met Office, both within the UK and internationally. This documentation of the HadGEM3-AO system provides a detailed reference for developers of HadGEM3-based climate configurations.

Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

Science.gov (United States)

Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

2017-12-01

Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the

Arctic melt ponds and bifurcations in the climate system

Science.gov (United States)

Sudakov, I.; Vakulenko, S. A.; Golden, K. M.

2015-05-01

Understanding how sea ice melts is critical to climate projections. In the Arctic, melt ponds that develop on the surface of sea ice floes during the late spring and summer largely determine their albedo - a key parameter in climate modeling. Here we explore the possibility of a conceptual sea ice climate model passing through a bifurcation point - an irreversible critical threshold as the system warms, by incorporating geometric information about melt pond evolution. This study is based on a bifurcation analysis of the energy balance climate model with ice-albedo feedback as the key mechanism driving the system to bifurcation points.

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

Safety climate and culture: Integrating psychological and systems perspectives.

Science.gov (United States)

Casey, Tristan; Griffin, Mark A; Flatau Harrison, Huw; Neal, Andrew

2017-07-01

Safety climate research has reached a mature stage of development, with a number of meta-analyses demonstrating the link between safety climate and safety outcomes. More recently, there has been interest from systems theorists in integrating the concept of safety culture and to a lesser extent, safety climate into systems-based models of organizational safety. Such models represent a theoretical and practical development of the safety climate concept by positioning climate as part of a dynamic work system in which perceptions of safety act to constrain and shape employee behavior. We propose safety climate and safety culture constitute part of the enabling capitals through which organizations build safety capability. We discuss how organizations can deploy different configurations of enabling capital to exert control over work systems and maintain safe and productive performance. We outline 4 key strategies through which organizations to reconcile the system control problems of promotion versus prevention, and stability versus flexibility. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Java Climate Model: a tool for interaction between science, policy and citizens, to avoid dangerous anthropogenic interference in the climate system

Science.gov (United States)

Matthews, B.

2003-04-01

To reach an effective global agreement to help avoid "dangerous anthropogenic interference in the climate system" (UNFCCC article 2) we must balance many complex interacting issues, and also inspire the active engagement of citizens around the world. So we have to transfer understanding back from computers and experts, into the ultimate "integrated assessment model" which remains the global network of human heads. The Java Climate Model (JCM) tries to help provide a quantitative framework for this global dialogue, by enabling anybody to explore many mitigation policy options and scientific uncertainties simply by adjusting parameter controls with a mouse in a web browser. The instant response on linked plots helps to demonstrate cause and effect, and the sensitivity to various assumptions, risk and value judgements. JCM implements the same simple models and formulae as used by IPCC for the TAR projections, in efficient modular structure, including carbon cycle and atmospheric chemistry, radiative forcing, changes in temperature and sealevel, including some feedbacks. As well as explore the SRES scenarios, the user can create a wide variety of inverse scenarios for stabilising CO2, forcing, or temperature. People ask how local emissions which they can control, may influence the vast global natural and human systems, and change local climate impacts which affect them directly. JCM includes regional emissions and socioeconomic data, and scaled climate impact maps. However to complete this loop in a fast interactive model is a challenge! For transparency and accessibility, pop-up information is provided in ten languages, and documentation ranges from key cross-cutting questions, to them details of the model formulae, including all source code.

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

Climate change projections for Greek viticulture as simulated by a regional climate model

Science.gov (United States)

Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

2017-07-01

Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

Modeling of the climate system and of its response to a greenhouse effect increase

International Nuclear Information System (INIS)

Li, L.

2005-01-01

The anthropic disturbance of the Earth's greenhouse effect is already visible and will enhance in the coming years or decades. In front of the rapidity and importance of the global warming effect, the socio-economical management of this change will rise problems and must be studied by the scientific community. At the modeling level, finding a direct strategy for the validation of climate models is not easy: many uncertainties exist because energy transformations take place at a low level and several processes take place at the same time. The variability observed at the seasonal, inter-annual or paleo- scales allows to validate the models at the process level but not the evolution of the whole system. The management of these uncertainties is an integral part of the global warming problem. Thus, several scenarios can be proposed and their risk of occurrence must be estimated. This paper presents first the greenhouse effect, the climatic changes during geologic times, the anthropic disturbance of the greenhouse effect, the modeling of climate and the forecasting of its evolution. (J.S.)

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.

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.

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.

Reconstructing Climate Change: The Model-Data Ping-Pong

Science.gov (United States)

Stocker, T. F.

2017-12-01

When Cesare Emiliani, the father of paleoceanography, made the first attempts at a quantitative reconstruction of Pleistocene climate change in the early 1950s, climate models were not yet conceived. The understanding of paleoceanographic records was therefore limited, and scientists had to resort to plausibility arguments to interpret their data. With the advent of coupled climate models in the early 1970s, for the first time hypotheses about climate processes and climate change could be tested in a dynamically consistent framework. However, only a model hierarchy can cope with the long time scales and the multi-component physical-biogeochemical Earth System. There are many examples how climate models have inspired the interpretation of paleoclimate data on the one hand, and conversely, how data have questioned long-held concepts and models. In this lecture I critically revisit a few examples of this model-data ping-pong, such as the bipolar seesaw, the mid-Holocene greenhouse gas increase, millennial and rapid CO2 changes reconstructed from polar ice cores, and the interpretation of novel paleoceanographic tracers. These examples also highlight many of the still unsolved questions and provide guidance for future research. The combination of high-resolution paleoceanographic data and modeling has never been more relevant than today. It will be the key for an appropriate risk assessment of impacts on the Earth System that are already underway in the Anthropocene.

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

A control-oriented model for combined building climate comfort and aquifer thermal energy storage system

NARCIS (Netherlands)

Rostampour Samarin, Vahab; Bloemendal, J.M.; Jaxa-Rozen, M.; Keviczky, T.

2016-01-01

This paper presents a control-oriented model for combined building climate comfort and aquifer thermal energy storage (ATES) system. In particular, we first provide a description of building operational systems together with control framework variables. We then focus on the derivation of an

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

Science.gov (United States)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

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...

[Lake eutrophication modeling in considering climatic factors change: a review].

Science.gov (United States)

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

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.

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

Science.gov (United States)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

Modeling Multi-Reservoir Hydropower Systems in the Sierra Nevada with Environmental Requirements and Climate Warming

Science.gov (United States)

Rheinheimer, David Emmanuel

Hydropower systems and other river regulation often harm instream ecosystems, partly by altering the natural flow and temperature regimes that ecosystems have historically depended on. These effects are compounded at regional scales. As hydropower and ecosystems are increasingly valued globally due to growing values for clean energy and native species as well as and new threats from climate warming, it is important to understand how climate warming might affect these systems, to identify tradeoffs between different water uses for different climate conditions, and to identify promising water management solutions. This research uses traditional simulation and optimization to explore these issues in California's upper west slope Sierra Nevada mountains. The Sierra Nevada provides most of the water for California's vast water supply system, supporting high-elevation hydropower generation, ecosystems, recreation, and some local municipal and agricultural water supply along the way. However, regional climate warming is expected to reduce snowmelt and shift runoff to earlier in the year, affecting all water uses. This dissertation begins by reviewing important literature related to the broader motivations of this study, including river regulation, freshwater conservation, and climate change. It then describes three substantial studies. First, a weekly time step water resources management model spanning the Feather River watershed in the north to the Kern River watershed in the south is developed. The model, which uses the Water Evaluation And Planning System (WEAP), includes reservoirs, run-of-river hydropower, variable head hydropower, water supply demand, and instream flow requirements. The model is applied with a runoff dataset that considers regional air temperature increases of 0, 2, 4 and 6 °C to represent historical, near-term, mid-term and far-term (end-of-century) warming. Most major hydropower turbine flows are simulated well. Reservoir storage is also

The origins of computer weather prediction and climate modeling

International Nuclear Information System (INIS)

Lynch, Peter

2008-01-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

Chemistry and Climate in Asia - An Earth System Modeling Project

Science.gov (United States)

Barth, M. C.; Emmons, L. K.; Massie, S. T.; Pfister, G.; Romero Lankao, P.; Lamarque, J.; Carmichael, G. R.

2011-12-01

Asia is one of the most highly populated and economically dynamic regions in the world, with much of the population located in growing mega-cities. It is a region with significant emissions of greenhouse gases, aerosols and other pollutants, which pose high health risks to urban populations. Emissions of these aerosols and gases increased drastically over the last decade due to economic growth and urbanization and are expected to rise further in the near future. As such, the continent plays a role in influencing climate change via its effluent of aerosols and gaseous pollutants. Asia is also susceptible to adverse climate change through interactions between aerosols and clouds, which potentially can have serious implications for freshwater resources. We are developing an integrated inter-disciplinary program to focus on Asia, its climate, air quality, and impact on humans that will include connections with hydrology, ecosystems, extreme weather events, and human health. The primary goal of this project is to create a team to identify key scientific questions and establish networks of specialists to create a plan for future studies to address these questions. A second goal is to establish research facilities and a framework for investigating chemistry and climate over Asia. These facilities include producing high resolution Earth System Model simulations that have been evaluated with meteorological and chemical measurements, producing high-resolution emission inventories, analyzing satellite data, and analyzing the vulnerability of humans to air quality and extreme natural events. In this presentation we will describe in more detail these activities and discuss a future workshop on the impact of chemistry in climate on air quality and human health.

Teaching Climate Change Using System Models: An Understanding Global Change Project Pilot Study

Science.gov (United States)

Bean, J. R.; Stuhlsatz, M.; Bracey, Z. B.; Marshall, C. R.

2017-12-01

Teaching and learning about historical and anthropogenic climate change in the classroom requires integrating instructional resources that address physical, chemical, and biological processes. The Understanding Global Change (UGC) framework and system models developed at the University of California Museum of Paleontology (UCMP) provide visualizations of the relationships and feedbacks between Earth system processes, and the consequences of anthropogenic activities on global climate. This schema provides a mechanism for developing pedagogic narratives that are known to support comprehension and retention of information and relationships. We designed a nine-day instructional unit for middle and high school students that includes a sequence of hands-on, inquiry-based, data rich activities combined with conceptual modeling exercises intended to foster students' development of systems thinking and their understanding of human influences on Earth system processes. The pilot unit, Sea Level Rise in the San Francisco Bay Area, addresses the human causes and consequences of sea level rise and related Earth system processes (i.e., the water cycle and greenhouse effect). Most of the content is not Bay Area specific, and could be used to explore sea level rise in any coastal region. Students completed pre and post assessments, which included questions about the connectedness of components of the Earth system and probed their attitudes towards participating in environmental stewardship activities. Students sequentially drew models representing the content explored in the activities and wrote short descriptions of their system diagrams that were collected by teachers for analysis. We also randomly assigned classes to engage in a very short additional intervention that asked students to think about the role that humans play in the Earth system and to draw themselves into the models. The study will determine if these students have higher stewardship scores and more frequently

Collaborative Proposal: Transforming How Climate System Models are Used: A Global, Multi-Resolution Approach

Energy Technology Data Exchange (ETDEWEB)

Estep, Donald

2013-04-15

Despite the great interest in regional modeling for both weather and climate applications, regional modeling is not yet at the stage that it can be used routinely and effectively for climate modeling of the ocean. The overarching goal of this project is to transform how climate models are used by developing and implementing a robust, efficient, and accurate global approach to regional ocean modeling. To achieve this goal, we will use theoretical and computational means to resolve several basic modeling and algorithmic issues. The first task is to develop techniques for transitioning between parameterized and high-fidelity regional ocean models as the discretization grid transitions from coarse to fine regions. The second task is to develop estimates for the error in scientifically relevant quantities of interest that provide a systematic way to automatically determine where refinement is needed in order to obtain accurate simulations of dynamic and tracer transport in regional ocean models. The third task is to develop efficient, accurate, and robust time-stepping schemes for variable spatial resolution discretizations used in regional ocean models of dynamics and tracer transport. The fourth task is to develop frequency-dependent eddy viscosity finite element and discontinuous Galerkin methods and study their performance and effectiveness for simulation of dynamics and tracer transport in regional ocean models. These four projects share common difficulties and will be approach using a common computational and mathematical toolbox. This is a multidisciplinary project involving faculty and postdocs from Colorado State University, Florida State University, and Penn State University along with scientists from Los Alamos National Laboratory. The completion of the tasks listed within the discussion of the four sub-projects will go a long way towards meeting our goal of developing superior regional ocean models that will transform how climate system models are used.

The Transformation of Climate Models to Earth System Models and their Role in Policy Development and Decision Support

Science.gov (United States)

Washington, W. M.

2012-12-01

We have seen over the last few decades continued improvement in climate models such that they are becoming Earth system models (ESMs). Usually climate models use specified concentrations of greenhouse gases whereas ESMs allow carbon, water, biochemical and other cycles to be fully interactive between various model components. Typically ESMs have atmospheric, ocean, land/vegetation, sea ice, urbanization components and some are starting to include glacier change which can directly affect sea level change. Steve Schneider, for whom this lecture is named after, strongly encouraged the development of such models and he went further to strongly suggest that these tools be developed beyond just the climate science questions. The modeling community needs to be interacting with the social, behavioral, and economic science communities. This would allow for realistic humankind interactions with the Earth system. In 2012, the federal government with advice from the National Academies developed a new strategic plan for the U. S. Global Change Research Program entitled The National Global Change Research Plan 2012-2021. This new plan has added the social, behavioral, and economic sciences to the mix of research expertise. It should be pointed out that the Global Change Research Act of 1990 passed by Congress specified strategic goals: advance science, inform decisions, conduct assessments, and communicate and educate. In order to carry out these goals an implementation plan is being put together by the 13 federal agencies and departments. Throughout Steve's professional life, he knew that to make global change understood required this broad community of sciences to work together to answer the questions that the public and policymakers had about environmental change. This talk will not only be about the historical developments in the field but also about the future research challenges. As part of the talk I will show several unpublished video segments of Steve explaining what

Is the climate system an anticipatory system that minimizes free energy?

Science.gov (United States)

Rubin, Sergio; Crucifix, Michel

2017-04-01

All systems, whether they are alive or not are structured determined systems, i.e. their present states [x (t)] depends of past states [x (t - α)]. However it has been suggested [Rosen, 1985; Friston, 2013] that systems that contain life are capable of anticipation and active inference. The underlying principle is that state changes in living systems are best modelled as a function of past and future states [ x(t) = f (x (t - α), x(t), x (t + β)) ]. The reason for this is that living systems contain a predictive model of their ambiance on which they are active: they appear to model their ambiance to preserve their integrity and homeorhesis. We therefore formulate the following hypothesis: can the climate system be interpreted as an anticipatory system that minimizes free energy? Can its variability (catastrophe, bifurcation and/or tipping points) be interpreted in terms of active inference and anticipation failure? Here we present a mathematical formulation of the climate system as an anticipatory system that minimizes free energy and its possible implication in the future climate predictability. References Rosen, R. (1985). Anticipatory systems. In Anticipatory systems (pp. 313-370). Springer New York. Friston, K. (2013). Life as we know it. Journal of the Royal Society Interface, 10(86), 20130475.

Integrated assessment of water-power grid systems under changing climate

Science.gov (United States)

Yan, E.; Zhou, Z.; Betrie, G.

2017-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. In this presentation, we are focusing on recent improvement in model development of thermoelectric power plant water use simulator, power grid operation and cost optimization model, and model integration that facilitate interaction among water and electricity generation under extreme climate events. A process based thermoelectric power water use simulator includes heat-balance, climate, and cooling system modules that account for power plant characteristics, fuel types, and cooling technology. The model is validated with more than 800 power plants of fossil-fired, nuclear and gas-turbine power plants with different cooling systems. The power grid operation and cost optimization model was implemented for a selected regional in the Midwest. The case study will be demonstrated to evaluate the sensitivity and resilience of thermoelectricity generation and power grid under various climate and hydrologic extremes and potential economic consequences.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

Science.gov (United States)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

Reconstruction of the Eemian climate using a fully coupled Earth system model

Science.gov (United States)

Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Huybrechts, Philippe

2017-04-01

Climate of the Last Interglacial (LIG) between ca. 130 and 115 kyr BP is thought to be a good analogue for future climate warming. Though the driving mechanisms of the past and current climate evolution differ, analysis of the LIG climate may provide important insights for projections of future environmental changes. We do not know properly what was spatial distribution and magnitude of surface air temperature and precipitation anomalies with respect to present. Sparse proxy data are attributed mostly to the continental margins, internal areas of ice sheets and particular regions of the World Ocean. Combining mathematical modeling and indirect evidence can help to identify driving mechanisms and feed-backs which formed climatic conditions of the LIG. In order to reproduce the LIG climate, we carried out transient numerical experiments using a fully coupled Earth System Model (ESM) consisting of an AO GCM, which includes decription of the biosphere, atmospheric and oceanic chemistry ets. (INMCM), developed in the Institute of Numerical Mathematics (Moscow, Russia) and the models of Greenland and Antarctic ice sheets (GrISM and AISM, Vrije Uninersiteit Brussel, Belgium). Though the newest version of the INMCM has rather high spatial resolution, it canot be used in long transient numerical experimemts because of high computational demand. Coupling of the GrISM and AISM to the low resolution version of the INMCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmosphere and the ocean components of the ESM (spatial resolution 5˚×4˚, 21 vertical layers in the atmospheric block, 2.5°×2°, 6 min. temporal resolution; 33 vertical layers in the oceanic block; 20×20 km, 51 vertical layers and 1 yr temporal resolution in the GrISM and AISM). We apply two different coupling strategies. AISM is incorporated into the ESM via using procedures of resampling and interpolation of the input fields of annually averaged air surface

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

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

A dynamical stabilizer in the climate system: a mechanism suggested by a simple model

Science.gov (United States)

Bates, J. R.

1999-05-01

A simple zonally averaged hemispheric model of the climate system is constructed, based on energy equations for two ocean basins separated at 30° latitude with the surface fluxes calculated explicitly. A combination of empirical input and theoretical calculation is used to determine an annual mean equilibrium climate for the model and to study its stability with respect to small perturbations. The insolation, the mean albedos and the equilibrium temperatures for the two model zones are prescribed from observation. The principal agent of interaction between the zones is the vertically integrated poleward transport of atmospheric angular momentum across their common boundary. This is parameterized using an empirical formula derived from a multiyear atmospheric data set. The surface winds are derived from the angular momentum transport assuming the atmosphere to be in a state of dynamic balance on the climatic timescales of interest. A further assumption that the air sea temperature difference and low level relative humidity remain fixed at their mean observed values then allows the surface fluxes of latent and sensible heat to be calculated. Results from a radiative model, which show a positive lower tropospheric water vapour/infrared radiative feedback on SST perturbations in both zones, are used to calculate the net upward infrared radiative fluxes at the surface. In the model's equilibrium climate, the principal processes balancing the solar radiation absorbed at the surface are evaporation in the tropical zone and net infrared radiation in the extratropical zone. The stability of small perturbations about the equilibrium is studied using a linearized form of the ocean energy equations. Ice-albedo and cloud feedbacks are omitted and attention is focussed on the competing effects of the water vapour/infrared radiative feedback and the turbulent surface flux and oceanic heat transport feedbacks associated with the angular momentum cycle. The perturbation equations

Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

Science.gov (United States)

Taner, M. U.; Wi, S.; Brown, C.

2017-12-01

The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

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

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.

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.

Modeling future flows of the Volta River system: Impacts of climate change and socio-economic changes.

Science.gov (United States)

Jin, Li; Whitehead, Paul G; Appeaning Addo, Kwasi; Amisigo, Barnabas; Macadam, Ian; Janes, Tamara; Crossman, Jill; Nicholls, Robert J; McCartney, Matthew; Rodda, Harvey J E

2018-05-14

As the scientific consensus concerning global climate change has increased in recent decades, research on potential impacts of climate change on water resources has been given high importance. However in Sub-Saharan Africa, few studies have fully evaluated the potential implications of climate change to their water resource systems. The Volta River is one of the major rivers in Africa covering six riparian countries (mainly Ghana and Burkina Faso). It is a principal water source for approximately 24 million people in the region. The catchment is primarily agricultural providing food supplies to rural areas, demonstrating the classic water, food, energy nexus. In this study an Integrated Catchment Model (INCA) was applied to the whole Volta River system to simulate flow in the rivers and at the outlet of the artificial Lake Volta. High-resolution climate scenarios downscaled from three different Global Climate Models (CNRM-CM5, HadGEM2-ES and CanESM2), have been used to drive the INCA model and to assess changes in flow by 2050s and 2090s under the high climate forcing scenario RCP8.5. Results show that peak flows during the monsoon months could increase into the future. The duration of high flow could become longer compared to the recent condition. In addition, we considered three different socio-economic scenarios. As an example, under the combined impact from climate change from downscaling CNRM-CM5 and medium+ (high economic growth) socio-economic changes, the extreme high flows (Q5) of the Black Volta River are projected to increase 11% and 36% at 2050s and 2090s, respectively. Lake Volta outflow would increase +1% and +5% at 2050s and 2090s, respectively, under the same scenario. The effects of changing socio-economic conditions on flow are minor compared to the climate change impact. These results will provide valuable information assisting future water resource development and adaptive strategies in the Volta Basin. Copyright © 2018 Elsevier B.V. All rights

Orbital Noise in the Earth System and Climate Fluctuations

Science.gov (United States)

Liu, Han-Shou; Smith, David E. (Technical Monitor)

2001-01-01

Frequency noise in the variations of the Earth's obliquity (tilt) can modulate the insolation signal for climate change. Including this frequency noise effect on the incoming solar radiation, we have applied an energy balance climate model to calculate the climate fluctuations for the past one million years. Model simulation results are in good agreement with the geologically observed paleoclimate data. We conclude that orbital noise in the Earth system may be the major cause of the climate fluctuation cycles.

Integrating components of the earth system to model global climate changes: implications for the simulation of the climate of the next million years

International Nuclear Information System (INIS)

Duplessy, J.C.

2009-01-01

The climate system is complex because it is made up of several components (atmosphere, ocean, sea ice, continental surface, ice sheets), each of which has its own response time. The paleo-climate record provides ample evidence that these components interact nonlinearly with each other and also with global biogeochemical cycles, which drive greenhouse gas concentration in the atmosphere. Forecasting the evolution of future climate is therefore an extremely complex problem. In addition, since the nineteenth century, human activities are releasing great quantities of greenhouse gases (CO 2 , CH 4 , CFC, etc.) into the atmosphere. As a consequence, the atmospheric content of these gases has tremendously increased. As they have a strong greenhouse effect, their concentration is now large enough to perturb the natural evolution of the earth's climate. In this paper, we shall review the strategy which has been used to develop and validate tools that would allow to simulate the future long-term behaviour of the Earth's climate. This strategy rests on two complementary approaches: developing numerical models of the climate system and validating them by comparing their output with present-day meteorological data and paleo-climatic reconstructions. We shall then evaluate the methods available to simulate climate at the regional scale and the major uncertainties that must be solved to reasonable estimate the long-term evolution of a region, which would receive a geological repository for nuclear wastes. (author)

Integrated numerical modeling of a landslide early warning system in a context of adaptation to future climatic pressures

Science.gov (United States)

Khabarov, Nikolay; Huggel, Christian; Obersteiner, Michael; Ramírez, Juan Manuel

2010-05-01

Mountain regions are typically characterized by rugged terrain which is susceptible to different types of landslides during high-intensity precipitation. Landslides account for billions of dollars of damage and many casualties, and are expected to increase in frequency in the future due to a projected increase of precipitation intensity. Early warning systems (EWS) are thought to be a primary tool for related disaster risk reduction and climate change adaptation to extreme climatic events and hydro-meteorological hazards, including landslides. An EWS for hazards such as landslides consist of different components, including environmental monitoring instruments (e.g. rainfall or flow sensors), physical or empirical process models to support decision-making (warnings, evacuation), data and voice communication, organization and logistics-related procedures, and population response. Considering this broad range, EWS are highly complex systems, and it is therefore difficult to understand the effect of the different components and changing conditions on the overall performance, ultimately being expressed as human lives saved or structural damage reduced. In this contribution we present a further development of our approach to assess a landslide EWS in an integral way, both at the system and component level. We utilize a numerical model using 6 hour rainfall data as basic input. A threshold function based on a rainfall-intensity/duration relation was applied as a decision criterion for evacuation. Damage to infrastructure and human lives was defined as a linear function of landslide magnitude, with the magnitude modelled using a power function of landslide frequency. Correct evacuation was assessed with a ‘true' reference rainfall dataset versus a dataset of artificially reduced quality imitating the observation system component. Performance of the EWS using these rainfall datasets was expressed in monetary terms (i.e. damage related to false and correct evacuation). We

Multi crop model climate risk country-level management design: case study on the Tanzanian maize production system

Science.gov (United States)

Chavez, E.

2015-12-01

Future climate projections indicate that a very serious consequence of post-industrial anthropogenic global warming is the likelihood of the greater frequency and intensity of extreme hydrometeorological events such as heat waves, droughts, storms, and floods. The design of national and international policies targeted at building more resilient and environmentally sustainable food systems needs to rely on access to robust and reliable data which is largely absent. In this context, the improvement of the modelling of current and future agricultural production losses using the unifying language of risk is paramount. In this study, we use a methodology that allows the integration of the current understanding of the various interacting systems of climate, agro-environment, crops, and the economy to determine short to long-term risk estimates of crop production loss, in different environmental, climate, and adaptation scenarios. This methodology is applied to Tanzania to assess optimum risk reduction and maize production increase paths in different climate scenarios. The simulations carried out use inputs from three different crop models (DSSAT, APSIM, WRSI) run in different technological scenarios and thus allowing to estimate crop model-driven risk exposure estimation bias. The results obtained also allow distinguishing different region-specific optimum climate risk reduction policies subject to historical as well as RCP2.5 and RCP8.5 climate scenarios. The region-specific risk profiles obtained provide a simple framework to determine cost-effective risk management policies for Tanzania and allow to optimally combine investments in risk reduction and risk transfer.

Oscillations in a simple climate-vegetation model

Science.gov (United States)

Rombouts, J.; Ghil, M.

2015-05-01

We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.

A Standardized Evaluation System for Decadal Climate Prediction

Science.gov (United States)

Kadow, C.; Cubasch, U.

2012-12-01

The evaluation of decadal prediction systems is a scientific challenge as well as a technical challenge in the climate research. The major project MiKlip (www.fona-miklip.de) for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. The model system to be developed will be novel in several aspects, with great challenges for the methodology development. This concerns especially the determination of the initial conditions, the inclusion into the model of processes relevant to decadal predictions, the increase of the spatial resolution through regionalisation, the improvement or adjustment of statistical post-processing, and finally the synthesis and validation of the entire model system. Therefore, a standardized evaluation system will be part of the MiKlip system to validate it - developed by the project 'Integrated data and evaluation system for decadal scale prediction' (INTEGRATION). The presentation gives an overview of the different linkages of such a project, shows the different development stages and gives an outlook for users and possible end users in climate service. The technical interface combines all projects inside of MiKlip and invites them to participate in a common evaluation system. The system design and the validation strategy from a standalone tool in the beginning to a user friendly web based system using GRID technologies to an integrated part of the operational MiKlip system for industry and society will give the opportunity to enhance the MiKlip strategy. First results of different possibilities of such a system will be shown to present the scientific background through Taylor diagrams, ensemble skill scores and e.g. climatological means to show the usability and possibilities of MiKlip and the INTEGRATION project.

A Web-Based Geovisual Analytical System for Climate Studies

Directory of Open Access Journals (Sweden)

Zhenlong Li

2012-12-01

Full Text Available Climate studies involve petabytes of spatiotemporal datasets that are produced and archived at distributed computing resources. Scientists need an intuitive and convenient tool to explore the distributed spatiotemporal data. Geovisual analytical tools have the potential to provide such an intuitive and convenient method for scientists to access climate data, discover the relationships between various climate parameters, and communicate the results across different research communities. However, implementing a geovisual analytical tool for complex climate data in a distributed environment poses several challenges. This paper reports our research and development of a web-based geovisual analytical system to support the analysis of climate data generated by climate model. Using the ModelE developed by the NASA Goddard Institute for Space Studies (GISS as an example, we demonstrate that the system is able to (1 manage large volume datasets over the Internet; (2 visualize 2D/3D/4D spatiotemporal data; (3 broker various spatiotemporal statistical analyses for climate research; and (4 support interactive data analysis and knowledge discovery. This research also provides an example for managing, disseminating, and analyzing Big Data in the 21st century.

Using a Global Climate Model in an On-line Climate Change Course

Science.gov (United States)

Randle, D. E.; Chandler, M. A.; Sohl, L. E.

2012-12-01

Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

Representation of deforestation impacts on climate, water, and nutrient cycles in the ACME earth system model

Science.gov (United States)

Cai, X.; Riley, W. J.; Zhu, Q.

2017-12-01

Deforestation causes a series of changes to the climate, water, and nutrient cycles. Employing a state-of-the-art earth system model—ACME (Accelerated Climate Modeling for Energy), we comprehensively investigate the impacts of deforestation on these processes. We first assess the performance of the ACME Land Model (ALM) in simulating runoff, evapotranspiration, albedo, and plant productivity at 42 FLUXNET sites. The single column mode of ACME is then used to examine climate effects (temperature cooling/warming) and responses of runoff, evapotranspiration, and nutrient fluxes to deforestation. This approach separates local effects of deforestation from global circulation effects. To better understand the deforestation effects in a global context, we use the coupled (atmosphere, land, and slab ocean) mode of ACME to demonstrate the impacts of deforestation on global climate, water, and nutrient fluxes. Preliminary results showed that the land component of ACME has advantages in simulating these processes and that local deforestation has potentially large impacts on runoff and atmospheric processes.

The CSIRO Mk3L climate system model version 1.0 – Part 2: Response to external forcings

Directory of Open Access Journals (Sweden)

S. J. Phipps

2012-05-01

Full Text Available The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulation and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. It is freely available to the research community. This paper evaluates the response of the model to external forcings which correspond to past and future changes in the climate system.

A simulation of the mid-Holocene climate is performed, in which changes in the seasonal and meridional distribution of incoming solar radiation are imposed. Mk3L correctly simulates increased summer temperatures at northern mid-latitudes and cooling in the tropics. However, it is unable to capture some of the regional-scale features of the mid-Holocene climate, with the precipitation over Northern Africa being deficient. The model simulates a reduction of between 7 and 15% in the amplitude of El Niño-Southern Oscillation, a smaller decrease than that implied by the palaeoclimate record. However, the realism of the simulated ENSO is limited by the model's relatively coarse spatial resolution.

Transient simulations of the late Holocene climate are then performed. The evolving distribution of insolation is imposed, and an acceleration technique is applied and assessed. The model successfully captures the temperature changes in each hemisphere and the upward trend in ENSO variability. However, the lack of a dynamic vegetation scheme does not allow it to simulate an abrupt desertification of the Sahara.

To assess the response of Mk3L to other forcings, transient simulations of the last millennium are performed. Changes in solar irradiance, atmospheric greenhouse gas concentrations and volcanic emissions are applied to the model. The model is again broadly successful at simulating larger-scale changes in the

DESYCO: a Decision Support System to provide climate services for coastal stakeholders dealing with climate change impacts.

Science.gov (United States)

Torresan, S.; Gallina, V.; Giannini, V.; Rizzi, J.; Zabeo, A.; Critto, A.; Marcomini, A.

2012-04-01

At the international level climate services are recognized as innovative tools aimed at providing and distributing climate data and information according to the needs of end-users. Furthermore, needs-based climate services are extremely effective to manage climate risks and take advantage of the opportunities associated with climate change impacts. To date, climate services are mainly related to climate models that supply climate data (e.g. temperature, precipitations) at different spatial and time scales. However, there is a significant gap of tools aimed at providing information about risks and impacts induced by climate change and allowing non-expert stakeholders to use both climate-model and climate-impact data. DESYCO is a GIS-Decision Support System aimed at the integrated assessment of multiple climate change impacts on vulnerable coastal systems (e.g. beaches, river deltas, estuaries and lagoons, wetlands, agricultural and urban areas). It is an open source software that manages different input data (e.g. raster or shapefiles) coming from climate models (e.g. global and regional climate projections) and high resolution impact models (e.g. hydrodynamic, hydrological and biogeochemical simulations) in order to provide hazard, exposure, susceptibility, risk and damage maps for the identification and prioritization of hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies. Within the CLIM-RUN project (FP7) DESYCO is proposed as an helpful tool to bridge the gap between climate data and stakeholder needs and will be applied to the coastal area of the North Adriatic Sea (Italy) in order to provide climate services for local authorities involved in coastal zone management. Accordingly, a first workshop was held in Venice (Italy) with coastal authorities, climate experts and climate change risk experts, in order to start an iterative exchange of information about the knowledge related to climate change, climate

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.

Anticipating Vulnerability to Climate Change in Dryland Pastoral Systems: Using Dynamic Systems Models for the Kalahari

Directory of Open Access Journals (Sweden)

Andrew J. Dougill

2010-06-01

Full Text Available It is vitally important to identify agroecosystems that may cease functioning because of changing climate or land degradation. However, identifying such systems is confounded on both conceptual and methodological grounds, especially in systems that are moving toward thresholds, a common trait of dryland environments. This study explores these challenges by analyzing how a range of external pressures affect the vulnerability of dryland pastoral systems in the Kalahari. This is achieved by employing dynamic systems modeling approaches to understand the pathways by which communities became vulnerable to drought. Specifically, we evaluate how external pressures have changed: (1 different agroecosystems' abilities to tolerate drought, i.e., ecosystem resilience; (2 rural communities' abilities to adapt to drought, mediated via their access to assets; and (3 the ability of institutions and policy interventions to play a role in mediating drought-related crises, i.e., socio-political governance. This is done by reanalyzing ecological and participatory research findings along with farm-scale livestock offtake data from across the Kalahari in Botswana. An iterative process was followed to establish narratives exploring how external drivers led to changes in agroecosystem resilience, access to assets, and the institutional capacity to buffer the system. We use "causal loop diagrams" and statistical dynamic system models to express key quantitative relationships and establish future scenarios to help define where uncertainties lie by showing where the system is most sensitive to change. We highlight how that greater sharing of land management knowledge and practices between private and communal land managers can provide 'win-win-win' benefits of reducing system vulnerability, increasing economic income, and building social capital. We use future scenario analyses to identify key areas for future studies of climate change adaptation across the Kalahari.

Energy policies avoiding a tipping point in the climate system

Energy Technology Data Exchange (ETDEWEB)

Bahn, Olivier [GERAD and Department of Management Sciences, HEC Montreal, Montreal (Qc) (Canada); Edwards, Neil R. [Earth and Environmental Sciences, CEPSAR, Open University, Milton Keynes MK7 6AA (United Kingdom); Knutti, Reto [Institute for Atmospheric and Climate Science, ETH Zurich, CH-8092 Zurich (Switzerland); Stocker, Thomas F. [Climate and Environmental Physics, Physics Institute, and Oeschger Centre for Climate Change Research, University of Bern, CH-3012 Bern (Switzerland)

2011-01-15

Paleoclimate evidence and climate models indicate that certain elements of the climate system may exhibit thresholds, with small changes in greenhouse gas emissions resulting in non-linear and potentially irreversible regime shifts with serious consequences for socio-economic systems. Such thresholds or tipping points in the climate system are likely to depend on both the magnitude and rate of change of surface warming. The collapse of the Atlantic thermohaline circulation (THC) is one example of such a threshold. To evaluate mitigation policies that curb greenhouse gas emissions to levels that prevent such a climate threshold being reached, we use the MERGE model of Manne, Mendelsohn and Richels. Depending on assumptions on climate sensitivity and technological progress, our analysis shows that preserving the THC may require a fast and strong greenhouse gas emission reduction from today's level, with transition to nuclear and/or renewable energy, possibly combined with the use of carbon capture and sequestration systems. (author)

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.)

Energy policies avoiding a tipping point in the climate system

International Nuclear Information System (INIS)

Bahn, Olivier; Edwards, Neil R.; Knutti, Reto; Stocker, Thomas F.

2011-01-01

Paleoclimate evidence and climate models indicate that certain elements of the climate system may exhibit thresholds, with small changes in greenhouse gas emissions resulting in non-linear and potentially irreversible regime shifts with serious consequences for socio-economic systems. Such thresholds or tipping points in the climate system are likely to depend on both the magnitude and rate of change of surface warming. The collapse of the Atlantic thermohaline circulation (THC) is one example of such a threshold. To evaluate mitigation policies that curb greenhouse gas emissions to levels that prevent such a climate threshold being reached, we use the MERGE model of Manne, Mendelsohn and Richels. Depending on assumptions on climate sensitivity and technological progress, our analysis shows that preserving the THC may require a fast and strong greenhouse gas emission reduction from today's level, with transition to nuclear and/or renewable energy, possibly combined with the use of carbon capture and sequestration systems. - Research Highlights: → Preserving the THC may require a fast and strong greenhouse gas emission reduction. → This could be achieved through strong changes in the energy mix. → Similar results would apply to any climate system tipping points.

Paladin Enterprises: Monolithic particle physics models global climate.

CERN Multimedia

2002-01-01

Paladin Enterprises presents a monolithic particle model of the universe which will be used by them to build an economical fusion energy system. The model is an extension of the work done by James Clerk Maxwell. Essentially, gravity is unified with electro-magnetic forces and shown to be a product of a closed loop current system, i.e. a particle - monolithic or sub atomic. This discovery explains rapid global climate changes which are evident in the geological record and also provides an explanation for recent changes in the global climate.

High-resolution integration of water, energy, and climate models to assess electricity grid vulnerabilities to climate change

Science.gov (United States)

Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.

2017-12-01

The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50

Interactions of Vegetation and Climate: Remote Observations, Earth System Models, and the Amazon Forest

Science.gov (United States)

Quetin, Gregory R.

transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm/yr/°C, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall, and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate. In Chapter 2, we use observations of vegetation interaction with the physical environment to identify where ecosystem functioning is well simulated in an ensemble of Earth system models. We leverage this data-model comparison to hypothesize which physiological mechanisms--photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability--dominate the ecosystem response in places with different climates. The models are generally successful in reproducing the broad sign and shape of ecosystem function across climate space except for simulating generally lower leaf area during warmer years in places with hot wet climates. 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 global warming, and feedbacks between vegetation and climate, are too strong in the models. Finally, models and observations share an abrupt threshold between dry regions and wet regions where strong positive vegetation response to precipitation falls to nearly zero in places receiving around 1000 mm/year. In Chapter 3, we investigate how ecoclimate interactions change

Modelling sequential Biosphere systems under Climate change for radioactive waste disposal. Project BIOCLIM

International Nuclear Information System (INIS)

Texier, D.; Degnan, P.; Loutre, M.F.; Lemaitre, G.; Paillard, D.; Thorne, M.

2000-01-01

The BIOCLIM project (Modelling Sequential Biosphere systems under Climate change for Radioactive Waste Disposal) is part of the EURATOM fifth European framework programme. The project was launched in October 2000 for a three-year period. It is coordinated by ANDRA, the French national radioactive waste management agency. The project brings together a number of European radioactive waste management organisations that have national responsibilities for the safe disposal of radioactive wastes, and several highly experienced climate research teams. Waste management organisations involved are: NIREX (UK), GRS (Germany), ENRESA (Spain), NRI (Czech Republic) and ANDRA (France). Climate research teams involved are: LSCE (CEA/CNRS, France), CIEMAT (Spain), UPMETSIMM (Spain), UCL/ASTR (Belgium) and CRU (UEA, UK). The Environmental Agency for England and Wales provides a regulatory perspective. The consulting company Enviros Consulting (UK) assists ANDRA by contributing to both the administrative and scientific aspects of the project. This paper describes the project and progress to date. (authors)

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

Science.gov (United States)

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

2003-12-01

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

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.

Variance decomposition shows the importance of human-climate feedbacks in the Earth system

Science.gov (United States)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.

2017-12-01

The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.

Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

DEFF Research Database (Denmark)

Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle-climate simulations

Science.gov (United States)

Strassmann, Kuno M.; Joos, Fortunat

2018-05-01

The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

Science.gov (United States)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Vulnerability of ecological systems for nuclear war climatic consequences

International Nuclear Information System (INIS)

Kharuehll, M.; Khatchinson, T.; Kropper, U.; Kharuehll, K.

1988-01-01

Vulnerability of ecological systems of Northern hemisphere (terrestrial, aquatic and tropical) as well as Southern one in relation to climatic changes following large nuclear war is considered. When analyzing potential sensitivity of ecological systems to climatic changes, possible consequences are considered for different stress categories under various war scenarios. The above-mentioned stresses correspond to those adopted in published work by Pittok and others. To estimate the less important climatic disturbances a few additional computer-simulated models are developed

Climate Forecast System

Science.gov (United States)

Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

Investigating the Role of Biogeochemical Processes in the Northern High Latitudes on Global Climate Feedbacks Using an Efficient Scalable Earth System Model

Energy Technology Data Exchange (ETDEWEB)

Jain, Atul K. [Univ. of Illinois, Urbana-Champaign, IL (United States)

2016-09-14

The overall objectives of this DOE funded project is to combine scientific and computational challenges in climate modeling by expanding our understanding of the biogeophysical-biogeochemical processes and their interactions in the northern high latitudes (NHLs) using an earth system modeling (ESM) approach, and by adopting an adaptive parallel runtime system in an ESM to achieve efficient and scalable climate simulations through improved load balancing algorithms.

Regional-Scale Climate Change: Observations and Model Simulations

Energy Technology Data Exchange (ETDEWEB)

Bradley, Raymond S; Diaz, Henry F

2010-12-14

This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, and we conducted studies of changes in phonological indicators based on various climatic thresholds.

Modeling and Analysis Compute Environments, Utilizing Virtualization Technology in the Climate and Earth Systems Science domain

Science.gov (United States)

Michaelis, A.; Nemani, R. R.; Wang, W.; Votava, P.; Hashimoto, H.

2010-12-01

Given the increasing complexity of climate modeling and analysis tools, it is often difficult and expensive to build or recreate an exact replica of the software compute environment used in past experiments. With the recent development of new technologies for hardware virtualization, an opportunity exists to create full modeling, analysis and compute environments that are “archiveable”, transferable and may be easily shared amongst a scientific community or presented to a bureaucratic body if the need arises. By encapsulating and entire modeling and analysis environment in a virtual machine image, others may quickly gain access to the fully built system used in past experiments, potentially easing the task and reducing the costs of reproducing and verify past results produced by other researchers. Moreover, these virtual machine images may be used as a pedagogical tool for others that are interested in performing an academic exercise but don't yet possess the broad expertise required. We built two virtual machine images, one with the Community Earth System Model (CESM) and one with Weather Research Forecast Model (WRF), then ran several small experiments to assess the feasibility, performance overheads costs, reusability, and transferability. We present a list of the pros and cons as well as lessoned learned from utilizing virtualization technology in the climate and earth systems modeling domain.

Advancing coupled human-earth system models: The integrated Earth System Model Project

Science.gov (United States)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

Science.gov (United States)

Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong

2017-12-01

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

The impact of climate change on the European energy system

International Nuclear Information System (INIS)

Dowling, Paul

2013-01-01

Climate change can affect the economy via many different channels in many different sectors. The POLES global energy model has been modified to widen the coverage of climate change impacts on the European energy system. The impacts considered are changes in heating and cooling demand in the residential and services sector, changes in the efficiency of thermal power plants, and changes in hydro, wind (both on- and off-shore) and solar PV electricity output. Results of the impacts of six scenarios on the European energy system are presented, and the implications for European energy security and energy imports are presented. Main findings include: demand side impacts (heating and cooling in the residential and services sector) are larger than supply side impacts; power generation from fossil-fuel and nuclear sources decreases and renewable energy increases; and impacts are larger in Southern Europe than in Northern Europe. There remain many more climate change impacts on the energy sector that cannot currently be captured due to a variety of issues including: lack of climate data, difficulties translating climate data into energy-system-relevant data, lack of detail in energy system models where climate impacts act. This paper does not attempt to provide an exhaustive analysis of climate change impacts in the energy sector, it is rather another step towards an increasing coverage of possible impacts. - Highlights: • Expanded coverage of climate change impacts on European energy system. • Demand side impacts are larger than supply side impacts. • Power from fossil and nuclear sources decreases, renewable energy increases. • Impacts are larger in Southern Europe than in Northern Europe. • Synergies exist between climate change mitigation and climate change adaptation

Parameterization of clouds and radiation in climate models

Energy Technology Data Exchange (ETDEWEB)

Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

1995-09-01

Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

Science.gov (United States)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Flexible climate modeling systems: Lessons from Snowball Earth, Titan and Mars

Science.gov (United States)

Pierrehumbert, R. T.

2007-12-01

Climate models are only useful to the extent that real understanding can be extracted from them. Most leading- edge problems in climate change, paleoclimate and planetary climate require a high degree of flexibility in terms of incorporating model physics -- for example in allowing methane or CO2 to be a condensible substance instead of water vapor. This puts a premium on model design that allows easy modification, and on physical parameterizations that are close to fundamentals with as little empirical ad-hoc formulation as possible. I will provide examples from two approaches to this problem we have been using at the University of Chicago. The first is the FOAM general circulation model, which is a clean single-executable Fortran-77/c code supported by auxiliary applications in Python and Java. The second is a new approach based on using Python as a shell for assembling building blocks in compiled-code into full models. Applications to Snowball Earth, Titan and Mars, as well as pedagogical uses, will be discussed. One painful lesson we have learned is that Fortran-95 is a major impediment to portability and cross-language interoperability; in this light the trend toward Fortran-95 in major modelling groups is seen as a significant step backwards. In this talk, I will focus on modeling projects employing a full representation of atmospheric fluid dynamics, rather than "intermediate complexity" models in which the associated transports are parameterized.

The EC BIOCLIM Project (2000-2003), 5. Euratom Framework Programme - Modelling sequential biosphere systems under climate change for radioactive waste disposal

International Nuclear Information System (INIS)

Calvez, Marianne

2002-01-01

Marianne Calvez (ANDRA, France) presented the new EC BIOCLIM project that started in 2001. Its main objective is to provide a scientific basis and practical methodology for assessing the possible long-term impacts on the safety of radioactive waste repositories in deep formations due to climate driven changes. She explained that BIOCLIM objective is not to predict what will be the future but will correspond to an illustration of how people could use the knowledge. The BIOCLIM project will use the outcomes from the Biomass project. Where Biomass considered discrete biospheres, the BIOCLIM project will consider the evolution of climate with a focus on the European climate for three regions in the United Kingdom, France and Spain. The consortium of BIOCLIM participants consists of various experts in climate modelling and various experts and organisations in performance assessment. The intent is to build an integrated dynamic climate model that represents all the important mechanisms for long-term climate evolution. The modelling will primarily address the next 200000 years. The final outcome will be an enhancement of the state-of-the-art treatment of biosphere system change over long periods of time through the use of a number of innovative climate modelling approaches and the application of the climate model outputs in performance assessments

System and Method for Providing a Climate Data Persistence Service

Science.gov (United States)

Schnase, John L. (Inventor); Ripley, III, William David (Inventor); Duffy, Daniel Q. (Inventor); Thompson, John H. (Inventor); Strong, Savannah L. (Inventor); McInerney, Mark (Inventor); Sinno, Scott (Inventor); Tamkin, Glenn S. (Inventor); Nadeau, Denis (Inventor)

2018-01-01

A system, method and computer-readable storage devices for providing a climate data persistence service. A system configured to provide the service can include a climate data server that performs data and metadata storage and management functions for climate data objects, a compute-storage platform that provides the resources needed to support a climate data server, provisioning software that allows climate data server instances to be deployed as virtual climate data servers in a cloud computing environment, and a service interface, wherein persistence service capabilities are invoked by software applications running on a client device. The climate data objects can be in various formats, such as International Organization for Standards (ISO) Open Archival Information System (OAIS) Reference Model Submission Information Packages, Archive Information Packages, and Dissemination Information Packages. The climate data server can enable scalable, federated storage, management, discovery, and access, and can be tailored for particular use cases.

What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

Science.gov (United States)

Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

2009-12-01

“…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility

Linking models of human behaviour and climate alters projected climate change

Science.gov (United States)

Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

2018-01-01

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

Science.gov (United States)

Rummukainen, M.; Räisänen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willén, U.; Hansson, U.; Jones, C.

This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results.

A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M.; Raeisaenen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willen, U.; Hansson, U.; Jones, C. [Rossby Centre, Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)

2001-03-01

This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results. (orig.)

Decision- rather than scenario-centred downscaling: Towards smarter use of climate model outputs

Science.gov (United States)

Wilby, Robert L.

2013-04-01

Climate model output has been used for hydrological impact assessments for at least 25 years. Scenario-led methods raise awareness about risks posed by climate variability and change to the security of supplies, performance of water infrastructure, and health of freshwater ecosystems. However, it is less clear how these analyses translate into actionable information for adaptation. One reason is that scenario-led methods typically yield very large uncertainty bounds in projected impacts at regional and river catchment scales. Consequently, there is growing interest in vulnerability-based frameworks and strategies for employing climate model output in decision-making contexts. This talk begins by summarising contrasting perspectives on climate models and principles for testing their utility for water sector applications. Using selected examples it is then shown how water resource systems may be adapted with varying levels of reliance on climate model information. These approaches include the conventional scenario-led risk assessment, scenario-neutral strategies, safety margins and sensitivity testing, and adaptive management of water systems. The strengths and weaknesses of each approach are outlined and linked to selected water management activities. These cases show that much progress can be made in managing water systems without dependence on climate models. Low-regret measures such as improved forecasting, better inter-agency co-operation, and contingency planning, yield benefits regardless of the climate outlook. Nonetheless, climate model scenarios are useful for evaluating adaptation portfolios, identifying system thresholds and fixing weak links, exploring the timing of investments, improving operating rules, or developing smarter licensing regimes. The most problematic application remains the climate change safety margin because of the very low confidence in extreme precipitation and river flows generated by climate models. In such cases, it is necessary to

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

Science.gov (United States)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize

Educational and Scientific Applications of Climate Model Diagnostic Analyzer

Science.gov (United States)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

2016-12-01

Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of

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

Science.gov (United States)

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

2012-01-01

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

Numerical climate modeling and verification of selected areas for heat waves of Pakistan using ensemble prediction system

International Nuclear Information System (INIS)

Amna, S; Samreen, N; Khalid, B; Shamim, A

2013-01-01

Depending upon the topography, there is an extreme variation in the temperature of Pakistan. Heat waves are the Weather-related events, having significant impact on the humans, including all socioeconomic activities and health issues as well which changes according to the climatic conditions of the area. The forecasting climate is of prime importance for being aware of future climatic changes, in order to mitigate them. The study used the Ensemble Prediction System (EPS) for the purpose of modeling seasonal weather hind-cast of three selected areas i.e., Islamabad, Jhelum and Muzaffarabad. This research was purposely carried out in order to suggest the most suitable climate model for Pakistan. Real time and simulated data of five General Circulation Models i.e., ECMWF, ERA-40, MPI, Meteo France and UKMO for selected areas was acquired from Pakistan Meteorological Department. Data incorporated constituted the statistical temperature records of 32 years for the months of June, July and August. This study was based on EPS to calculate probabilistic forecasts produced by single ensembles. Verification was done out to assess the quality of the forecast t by using standard probabilistic measures of Brier Score, Brier Skill Score, Cross Validation and Relative Operating Characteristic curve. The results showed ECMWF the most suitable model for Islamabad and Jhelum; and Meteo France for Muzaffarabad. Other models have significant results by omitting particular initial conditions.

Deriving user-informed climate information from climate model ensemble results

Science.gov (United States)

Huebener, Heike; Hoffmann, Peter; Keuler, Klaus; Pfeifer, Susanne; Ramthun, Hans; Spekat, Arne; Steger, Christian; Warrach-Sagi, Kirsten

2017-07-01

Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

Science.gov (United States)

Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

2017-04-01

Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

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.

The non-linear paradigm: The climate system as an egg box''

International Nuclear Information System (INIS)

Iversen, Trond

2000-01-01

The article is the last of three dealing with the problems of climatic forecasting. It presents various ways of applying models and points out that regarding the climate system as non-linear and chaotic may be useful for interpreting observations and models. Some applications of the paradigm are presented. The emphasis is on climatic changes due to energy and human activities

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

Science.gov (United States)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

Historical and idealized climate model experiments: an EMIC intercomparison

DEFF Research Database (Denmark)

Eby, M.; Weaver, A. J.; Alexander, K.

2012-01-01

Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE......, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...

Developing a National Climate Indicators System to Track Climate Changes, Impacts, Vulnerabilities, and Preparedness

Science.gov (United States)

Kenney, M. A.; Janetos, A. C.; Arndt, D.; Chen, R. S.; Pouyat, R.; Anderson, S. M.

2013-12-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. Part of the vision, which is now under development, for the sustained National Climate Assessment (NCA) process is a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public with scientifically valid information that is useful to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region. These indicators will be tracked as a part of ongoing assessment activities, with adjustments as necessary to adapt to changing conditions and understanding. The indicators will be reviewed and updated so that the system adapts to new information. The NCA indicator system is not intended to serve as a vehicle for documenting rigorous cause and effect relationships. It is reasonable, however, for it to serve as a guide to those factors that affect the evolution of variability and change in the climate system, the resources and sectors of concern that are affected by it, and how society chooses to respond. Different components of the end-to-end climate issue serve as categories within which to organize an end-to-end system of indicators: Greenhouse Gas Emissions and Sinks, Atmospheric Composition, Physical Climate Variability and Change, Sectors and Resources of Concern, and Adaptation and Mitigation Responses. This framing has several advantages. It can be used to identify the different components of the end-to-end climate issue that both decision-makers and researchers are interested in. It is independent of scale, and therefore allows the indicators themselves to be described at spatial

A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period

Directory of Open Access Journals (Sweden)

Florence Sevault

2014-11-01

Full Text Available A fully coupled regional climate system model (CNRM-RCSM4 dedicated to the Mediterranean region is described and evaluated using a multidecadal hindcast simulation (1980–2012 driven by global atmosphere and ocean reanalysis. CNRM-RCSM4 includes the regional representation of the atmosphere (ALADIN-Climate model, land surface (ISBA model, rivers (TRIP model and the ocean (NEMOMED8 model, with a daily coupling by the OASIS coupler. This model aims to reproduce the regional climate system with as few constraints as possible: there is no surface salinity, temperature relaxation, or flux correction; the Black Sea budget is parameterised and river runoffs (except for the Nile are fully coupled. The atmospheric component of CNRM-RCSM4 is evaluated in a companion paper; here, we focus on the air–sea fluxes, river discharges, surface ocean characteristics, deep water formation phenomena and the Mediterranean thermohaline circulation. Long-term stability, mean seasonal cycle, interannual variability and decadal trends are evaluated using basin-scale climatologies and in-situ measurements when available. We demonstrate that the simulation shows overall good behaviour in agreement with state-of-the-art Mediterranean RCSMs. An overestimation of the shortwave radiation and latent heat loss as well as a cold Sea Surface Temperature (SST bias and a slight trend in the bottom layers are the primary current deficiencies. Further, CNRM-RCSM4 shows high skill in reproducing the interannual to decadal variability for air–sea fluxes, river runoffs, sea surface temperature and salinity as well as open-sea deep convection, including a realistic simulation of the Eastern Mediterranean Transient. We conclude that CNRM-RCSM4 is a mature modelling tool allowing the climate variability of the Mediterranean regional climate system to be studied and understood. It is used in hindcast and scenario modes in the HyMeX and Med-CORDEX programs.

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.)

The Bern Simple Climate Model (BernSCM v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle–climate simulations

Directory of Open Access Journals (Sweden)

K. M. Strassmann

2018-05-01

Full Text Available The Bern Simple Climate Model (BernSCM is a free open-source re-implementation of a reduced-form carbon cycle–climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs. The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate–carbon cycle response simulated by more complex and detailed models. Model code (in Fortran was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle–climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs, for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

Performance investigation of solid desiccant evaporative cooling system configurations in different climatic zones

International Nuclear Information System (INIS)

Ali, Muzaffar; Vukovic, Vladimir; Sheikh, Nadeem Ahmed; Ali, Hafiz M.

2015-01-01

Highlights: • Five configurations of a DEC system are analyzed in five climate zones. • DEC system model configurations are developed in Dymola/Modelica. • Performance analysis predicted a suitable DEC system configuration for each climate zone. • Results show that climate of Vienna, Sao Paulo, and Adelaide favors the ventilated-dunkle cycle. • While ventilation cycle configuration suits the climate of Karachi and Shanghai. - Abstract: Performance of desiccant evaporative cooling (DEC) system configurations is strongly influenced by the climate conditions and varies widely in different climate zones. Finding the optimal configuration of DEC systems for a specific climatic zone is tedious and time consuming. This investigation conducts performance analysis of five DEC system configurations under climatic conditions of five cities from different zones: Vienna, Karachi, Sao Paulo, Shanghai, and Adelaide. On the basis of operating cycle, three standard and two modified system configurations (ventilation, recirculation, dunkle cycles; ventilated-recirculation and ventilated-dunkle cycles) are analyzed in these five climate zones. Using an advance equation-based object-oriented (EOO) modeling and simulation approach, optimal configurations of a DEC system are determined for each climate zone. Based on the hourly climate data of each zone for its respective design cooling day, performance of each system configuration is estimated using three performance parameters: cooling capacity, COP, and cooling energy delivered. The results revealed that the continental/micro-thermal climate of Vienna, temperate/mesothermal climate of Sao Paulo, and dry-summer subtropical climate of Adelaide favor the use of ventilated-dunkle cycle configuration with average COP of 0.405, 0.89 and 1.01 respectively. While ventilation cycle based DEC configuration suits arid and semiarid climate of Karachi and another category of temperate/mesothermal climate of Shanghai with average COP of

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

7th International Seminar on Climate System and Climate Change(ISCS) through the Eyes of a Trainee

Institute of Scientific and Technical Information of China (English)

Karen K.Y.Shum

2010-01-01

@@ At the invitation of Dr.Dahe Qin,the president of ISCS and the Co-Chair of IPCC WGI,the Hong Kong Observatory has been obliged to participate and benefit from the International Seminar in Beijing,China on 19-30 July 2010.Seminar topics included atmospheric chemistry and climate effects of aerosol biogeochemical cycles,cryosphere and its role in the climate system and climate change,climate models and its application in climate change research,climate change adaptation and mitigation.Data is a common ground for these multi-disciplinary studies around the globe.

Model based climate information on drought risk in Africa

Science.gov (United States)

Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

2012-04-01

The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

Long-term climate monitoring by the global climate observing system

International Nuclear Information System (INIS)

Karl, T.R.

1995-12-01

Is the climate warming? Is the hydrologic cycle changing? Is the atmospheric/oceanic circulation changing? Is the climate becoming more variable or extreme? Is radiative forcing of the climate changing? are complex questions not only from the standpoint of a multi-variate problem, but because of the various aspects of spatial and temporal sampling that must be considered on a global scale. The development of a Global Climate Observing System (GCOS) offers the opportunity for scientists to do something about existing observing deficiencies in light of the importance of documenting long-term climate changes that may already be affected by anthropogenic changes of atmospheric composition and land use as well as other naturally occurring changes. As an important step toward improving the present inadequacies, a workshop was held to help define the long-term monitoring requirements minimally needed to address the five questions posed above, with special emphasis on detecting anthropogenic climate change and its potential impact on managed and unmanaged systems The workshop focussed on three broad areas related to long-term climate monitoring: (a) the scientific rationale for the long-term climate products (including their accuracy, resolution, and homogeneity) required from our observing systems as related to climate monitoring and climate change detection and attribution; (b) the status of long-term climate products and the observing systems from which these data are derived; and (c) implementation strategies necessary to fulfill item (a) in light of existing systems. Item (c) was treated more in terms of feasibility rather than as a specific implementation plan. figs., tabs., refs

A characteristics of East Asian climate using high-resolution regional climate model

Science.gov (United States)

Yhang, Y.

2013-12-01

Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Cassano, John J. [Univ. of Colorado, Boulder, CO (United States); Gutowski, Jr., William J. [Iowa State Univ., Ames, IA (United States); Lipscomb, William H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nijssen, Bart [Univ. of Washington, Seattle, WA (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Robertson, William [Univ. of Texas, El Paso, TX (United States); Tulaczyk, Slawek [Univ. of California, Santa Cruz, CA (United States); Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States)

2011-05-15

The primary outcome of the project was the development of the Regional Arctic System Model (RASM) and evaluation of its individual model components, coupling among them and fully coupled model results. Overall, we have demonstrated that RASM produces realistic mean and seasonal surface climate as well as its interannual and decadal variability and trends.

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.

Software Testing and Verification in Climate Model Development

Science.gov (United States)

Clune, Thomas L.; Rood, RIchard B.

2011-01-01

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

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

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Directory of Open Access Journals (Sweden)

K. Steffens

2014-02-01

Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

Evaluating the impacts of climate change on diurnal wind power cycles using multiple regional climate models

KAUST Repository

Goddard, Scott D.

2015-05-01

Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind-generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high-resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi-parametric mixed model is fit using cubic B-splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production.

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.

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.

A Systems Approach to Climate, Water and Diarrhea in Hubli-Dharward, India

Science.gov (United States)

Mellor, J. E.; Zimmerman, J.

2014-12-01

Although evidence suggests that climate change will negatively impact water resources and hence diarrheal disease rates in the developing world, there is uncertainty surrounding prior studies. This is due to the complexity of the pathways by which climate impacts diarrhea rates making it difficult to develop interventions. Therefore, our goal was to develop a mechanistic systems approach that incorporates the complex climate, human, engineered and water systems to relate climate change to diarrhea rates under future climate scenarios.To do this, we developed an agent-based model (ABM). Our agents are households and children living in Hubli-Dharward, India. The model was informed with 15 months of weather, water quality, ethnographic and diarrhea incidence data. The model's front end is a stochastic weather simulator incorporating 15 global climate models to simulate rainfall and temperature. The water quality available to agents (residents) on a model "day" is a function of the simulated day's weather and is fully validated with field data. As with the field data, as the ambient temperature increases or it rains, the quality of water available to residents in the model deteriorates. The propensity for an resident to get diarrhea is calculated with an integrated Quantitative Microbial Risk Assessment model with uncertainty simulated with a bootstrap method. Other factors include hand-washing, improved water sources, household water treatment and improved sanitation.The benefits of our approach are as follows: Our mechanistic method allows us to develop scientifically derived adaptation strategies. We can quantitatively link climate scenarios with diarrhea incidence over long time periods. We can explore the complex climate and water system dynamics, rank risk factor importance, examine a broad range of scenarios and identify tipping points. Our approach is modular and expandable such that new datasets can be integrated to study climate impacts on a larger scale. Our

Stress testing hydrologic models using bottom-up climate change assessment

Science.gov (United States)

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

2017-12-01

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

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...

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

Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

Science.gov (United States)

Leckebusch, G. C.; Ulbrich, U.

2003-04-01

More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

Comments on Current Space Systems Observing the Climate

Science.gov (United States)

Fisk, L. A.

2016-07-01

The Global Climate Observing System (GCOS), which was established in 1992, has been effective in specifying the observations needed for climate studies, and advocating that these observations be made. As a result, there are essential climate variables being observed, particularly from space, and these have formed the basis for our ever-improving models of how the Earth system functions and the human impact on it. We cannot conclude, however, that the current observing system in space is adequate. Climate change is accelerating, and we need to ensure that our observations capture, with completeness and with proper resolution and cadence, the most important changes. Perhaps of most significance, we need to use observations from space to guide the mitigation and adaptation strategies on which at last our civilization seems prepared to embark. And we need to use our observations to educate particularly policy makers on the reality of climate change, so that none deny the need to act. COSPAR is determined to play its part in highlighting the need to strengthen the climate observing system and notably its research component. This is being accomplished through events like the present roundtable, through the work of its Scientific Commission A, its Task Group on GEO (where COSPAR is serving as a member of its Program Board), and by promoting among space agencies and policy-makers the recently released scientific roadmap on Integrated Earth System Science for the period 2016-2025.

Building Systems from Scratch: an Exploratory Study of Students Learning About Climate Change

Science.gov (United States)

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual programming environment, Scratch, to design games to teach others about climate change. The experience was carefully constructed so that girls of widely differing levels of experience were able to engage in a cycle of game design. This qualitative study aimed to explore the representational choices the girls made as they took up aspects of climate change systems and modeled them in their games. Evidence points to the ways in which designing games about climate science fostered emergent systems thinking and engagement in modeling practices as learners chose what to represent in their games, grappled with the realism of their respective representations, and modeled interactions among systems components. Given the girls' levels of programming skill, parts of systems were more tractable to create than others. The educational purpose of the games was important to the girls' overall design experience, since it influenced their choice of topic, and challenged their emergent understanding of climate change as a systems problem.

IIASA's climate-vegetation-biogeochemical cycle module as a part of an integrated model for climate change

International Nuclear Information System (INIS)

Ganopolski, A.V.; Jonas, M.; Krabec, J.; Olendrzynski, K.; Petoukhov, V.K.; Venevsky, S.V.

1994-01-01

The main objective of this study is the development of a hierarchy of coupled climate biosphere models with a full description of the global biogeochemical cycles. These models are planned for use as the core of a set of integrated models of climate change and they will incorporate the main elements of the Earth system (atmosphere, hydrosphere, pedosphere and biosphere) linked with each other (and eventually with the antroposphere) through the fluxes of heat, momentum, water and through the global biogeochemical cycles of carbon and nitrogen. This set of integrated models can be considered to fill the gap between highly simplified integrated models of climate change and very sophisticated and computationally expensive coupled models, developed on the basis of general circulation models (GCMs). It is anticipated that this range of integrated models will be an effective tool for investigating the broad spectrum of problems connected with the coexistence of human society and biosphere

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

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.

Climate simulations for 1880-2003 with GISS modelE

International Nuclear Information System (INIS)

Hansen, J.; Lacis, A.; Miller, R.; Schmidt, G.A.; Russell, G.; Canuto, V.; Del Genio, A.; Hall, T.; Hansen, J.; Sato, M.; Kharecha, P.; Nazarenko, L.; Aleinov, I.; Bauer, S.; Chandler, M.; Faluvegi, G.; Jonas, J.; Ruedy, R.; Lo, K.; Cheng, Y.; Lacis, A.; Schmidt, G.A.; Del Genio, A.; Miller, R.; Cairns, B.; Hall, T.; Baum, E.; Cohen, A.; Fleming, E.; Jackman, C.; Friend, A.; Kelley, M.

2007-01-01

We carry out climate simulations for 1880-2003 with GISS modelE driven by ten measured or estimated climate forcing. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcing, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcing are due to model deficiencies, inaccurate or incomplete forcing, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880-2003 forcing, we aim to provide a benchmark against which the effect of improvements in the model, climate forcing, and observations can be tested. Principal model deficiencies include unrealistic weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcing are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. (authors)

Historical and idealized climate model experiments: an EMIC intercomparison

DEFF Research Database (Denmark)

Eby, M.; Weaver, A. J.; Alexander, K.

2012-01-01

Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures...... the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within...

How Hot was Africa during the Mid-Holocene? Reexamining Africa's Thermal History via integrated Climate and Proxy System Modeling

Science.gov (United States)

Dee, S.; Russell, J. M.; Morrill, C.

2017-12-01

Climate models predict Africa will warm by up to 5°C in the coming century. Reconstructions of African temperature since the Last Glacial Maximum (LGM) have made fundamental contributions to our understanding of past, present, and future climate and can help constrain predictions from general circulation models (GCMs). However, many of these reconstructions are based on proxies of lake temperature, so the confounding influences of lacustrine processes may complicate our interpretations of past changes in tropical climate. These proxy-specific uncertainties require robust methodology for data-model comparison. We develop a new proxy system model (PSM) for paleolimnology to facilitate data-model comparison and to fully characterize uncertainties in climate reconstructions. Output from GCMs are used to force the PSM to simulate lake temperature, hydrology, and associated proxy uncertainties. We compare reconstructed East African lake and air temperatures in individual records and in a stack of 9 lake records to those predicted by our PSM forced with Paleoclimate Model Intercomparison Project (PMIP3) simulations, focusing on the mid-Holocene (6 kyr BP). We additionally employ single-forcing transient climate simulations from TraCE (10 kyr to 4 kyr B.P. and historical), as well as 200-yr time slice simulations from CESM1.0 to run the lake PSM. We test the sensitivity of African climate change during the mid-Holocene to orbital, greenhouse gas, and ice-sheet forcing in single-forcing simulations, and investigate dynamical hypotheses for these changes. Reconstructions of tropical African temperature indicate 1-2ºC warming during the mid-Holocene relative to the present, similar to changes predicted in the coming decades. However, most climate models underestimate the warming observed in these paleoclimate data (Fig. 1, 6kyr B.P.). We investigate this discrepancy using the new lake PSM and climate model simulations, with attention to the (potentially non

Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

Science.gov (United States)

Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

2013-12-01

Sub Saharan African agriculture is dominated by small-scale farmers and is heavily depend on growing season precipitation. Recent studies indicate that anthropogenic- induced warming including the Indian Ocean sea surface significantly influences precipitation in East Africa. East Africa is a useful region to assess impacts of future climate because of its large rainfall gradient, large percentage of its area being sub-humid or semi-arid, complex climatology and topography, varied soils, and because the population is particularly vulnerable to shifts in climate. Agronomic adaptation practices most commonly being considered include include a shift to short season, drought resistant maize varieties, better management practices especially fertilizer use, and irrigation. The effectiveness of these practices with climate change had not previously been tested. We used the WorldClim data set to represent current climate and compared the current and future climate scenarios of 4 Global Climate Models (GCMs) including a wetter (CCSM) and drier (HadCM3) GCM downscaled to 6 km resolution. The climate data was then used in the process-based CERES maize crop model to simulate the current period (representing 1960- 1990) and change in future maize production (from 2000 to 2050s). The effectiveness of agronomic practices, including short duration maize variety, fertilizer use and irrigation, to reduce projected future yield losses due to climate change were simulated. The GCMs project an increase in maximum temperature during growing season ranging from 1.5 to 3°C. Changes in precipitation were dependent on the GCM, with high variability across different topographies land cover types and elevations. Projected warmer temperatures in the future scenarios accelerated plant development and led to a reduction in growing season length and yields even where moisture was sufficient Maize yield changes in 2050 relative to the historical period were highly varied, in excess of +/- 500 kg

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

Science.gov (United States)

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

2017-07-01

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

Future climate scenarios and rainfall-runoff modelling in the Upper Gallego catchment (Spain)

International Nuclear Information System (INIS)

Buerger, C.M.; Kolditz, O.; Fowler, H.J.; Blenkinsop, S.

2007-01-01

Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system. - Future climate change and data-based rainfall-runoff predictions are presented for the Upper Gallego

Towards the development of a climate model evaluation system in the Centre for Australian Weather and climate research

International Nuclear Information System (INIS)

Rikus, Lawrie; Hu, Ben; Dix, Martin; Watterson, Ian; Elliott, Tracey

2010-01-01

The paper describes the philosophy of the climate model evaluation scheme being developed within CAWCR as well as the database of observational data-sets which under-pins it. It argues that model evaluation should measure 'fitness-of-purpose', that it should be objective and that it should be based on the largest possible number of observational data-sets. Time series plots of smoothed observational data and the relevance of the disparity between data from different sources are discussed. The paper calls for active participation of the Australian climate research community in the project.

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

Science.gov (United States)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

A Reusable Framework for Regional Climate Model Evaluation

Science.gov (United States)

Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

Science.gov (United States)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national

Modeling Impacts of Climate Change on Giant Panda Habitat

Directory of Open Access Journals (Sweden)

Melissa Songer

2012-01-01

Full Text Available Giant pandas (Ailuropoda melanoleuca are one of the most widely recognized endangered species globally. Habitat loss and fragmentation are the main threats, and climate change could significantly impact giant panda survival. We integrated giant panda habitat information with general climate models (GCMs to predict future geographic distribution and fragmentation of giant panda habitat. Results support a major general prediction of climate change—a shift of habitats towards higher elevation and higher latitudes. Our models predict climate change could reduce giant panda habitat by nearly 60% over 70 years. New areas may become suitable outside the current geographic range but much of these areas is far from the current giant panda range and only 15% fall within the current protected area system. Long-term survival of giant pandas will require the creation of new protected areas that are likely to support suitable habitat even if the climate changes.

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.

Ecological Assimilation of Land and Climate Observations - the EALCO model

Science.gov (United States)

Wang, S.; Zhang, Y.; Trishchenko, A.

2004-05-01

Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

Dansgaard–Oeschger events: bifurcation points in the climate system

Directory of Open Access Journals (Sweden)

A. A. Cimatoribus

2013-02-01

Full Text Available Dansgaard–Oeschger events are a prominent mode of variability in the records of the last glacial cycle. Various prototype models have been proposed to explain these rapid climate fluctuations, and no agreement has emerged on which may be the more correct for describing the palaeoclimatic signal. In this work, we assess the bimodality of the system, reconstructing the topology of the multi-dimensional attractor over which the climate system evolves. We use high-resolution ice core isotope data to investigate the statistical properties of the climate fluctuations in the period before the onset of the abrupt change. We show that Dansgaard–Oeschger events have weak early warning signals if the ensemble of events is considered. We find that the statistics are consistent with the switches between two different climate equilibrium states in response to a changing external forcing (e.g. solar, ice sheets, either forcing directly the transition or pacing it through stochastic resonance. These findings are most consistent with a model that associates Dansgaard–Oeschger with changing boundary conditions, and with the presence of a bifurcation point.

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

Avoiding Dangerous Anthropogenic Interference with the Climate System

Energy Technology Data Exchange (ETDEWEB)

Keller, K. [Department of Geosciences, Penn State, PA (United States); Hall, M. [Brookings Institution, Washington, DC (United States); Kim, Seung-Rae [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ (United States); Bradford, D.F. [Department of Economics, Princeton University, Princeton, NJ (United States); Oppenheimer, M. [Woodrow Wilson School and Department of Geosciences, Princeton University, Robertson Hall 448, Princeton, NJ, 08544 (United States)

2005-12-01

The UN Framework Convention on Climate Change calls for the avoidance of 'dangerous anthropogenic interference with the climate system'. Among the many plausible choices, dangerous interference with the climate system may be interpreted as anthropogenic radiative forcing causing distinct and widespread climate change impacts such as a widespread demise of coral reefs or a disintegration of the West Antarctic ice sheet. The geological record and numerical models suggest that limiting global warming below critical temperature thresholds significantly reduces the likelihood of these eventualities. Here we analyze economically optimal policies that may ensure this risk-reduction. Reducing the risk of a widespread coral reef demise implies drastic reductions in greenhouse gas emissions within decades. Virtually unchecked greenhouse gas emissions to date (combined with the inertia of the coupled natural and human systems) may have already committed future societies to a widespread demise of coral reefs. Policies to reduce the risk of a West Antarctic ice sheet disintegration allow for a smoother decarbonization of the economy within a century and may well increase consumption in the long run.

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.

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

Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

Science.gov (United States)

Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

2017-04-01

Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V

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

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

Science.gov (United States)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

Development of climate data storage and processing model

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Okladnikov, I. G.; Gordov, E. P.; Titov, A. G.

2016-11-01

We present a storage and processing model for climate datasets elaborated in the framework of a virtual research environment (VRE) for climate and environmental monitoring and analysis of the impact of climate change on the socio-economic processes on local and regional scales. The model is based on a «shared nothings» distributed computing architecture and assumes using a computing network where each computing node is independent and selfsufficient. Each node holds a dedicated software for the processing and visualization of geospatial data providing programming interfaces to communicate with the other nodes. The nodes are interconnected by a local network or the Internet and exchange data and control instructions via SSH connections and web services. Geospatial data is represented by collections of netCDF files stored in a hierarchy of directories in the framework of a file system. To speed up data reading and processing, three approaches are proposed: a precalculation of intermediate products, a distribution of data across multiple storage systems (with or without redundancy), and caching and reuse of the previously obtained products. For a fast search and retrieval of the required data, according to the data storage and processing model, a metadata database is developed. It contains descriptions of the space-time features of the datasets available for processing, their locations, as well as descriptions and run options of the software components for data analysis and visualization. The model and the metadata database together will provide a reliable technological basis for development of a high- performance virtual research environment for climatic and environmental monitoring.

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...

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

Science.gov (United States)

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

2012-12-01

We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical

21st Century Carbon-Climate Change as Simulated by the Canadian Earth System Model CanESM1

Science.gov (United States)

Curry, C.; Christian, J. R.; Arora, V.; Boer, G. J.; Denman, K. L.; Flato, G. M.; Scinocca, J. F.; Merryfield, W. J.; Lee, W. G.; Yang, D.

2009-12-01

The Canadian Earth System Model CanESM1 is a fully coupled climate/carbon-cycle model with prognostic ocean and terrestrial components. The model has been used to simulate the 1850-2000 climate using historical greenhouse gas emissions, and future climates using IPCC emission scenarios. Modelled globally averaged CO2 concentration, land and ocean carbon uptake compare well with observation-based values at year 2000, as do the annual cycle and latitudinal distribution of CO2, instilling confidence that the model is suitable for future projections of carbon cycle behaviour in a changing climate. Land use change emissions are calculated explicitly using an observation-based time series of fractional coverage of different plant functional types. A more complete description of the model may be found in Arora et al. (2009). Differences in the land-atmosphere CO2 flux from the present to the future period under the SRES A2 emissions scenario show an increase in land sinks by a factor of 7.5 globally, mostly the result of CO2 fertilization. By contrast, the magnitude of the global ocean CO2 sink increases by a factor of only 2.3 by 2100. Expressed as a fraction of total emissions, ocean carbon uptake decreases throughout the 2000-2100 period, while land carbon uptake increases until around 2050, then declines. The result is an increase in airborne CO2 fraction after the mid-21st century, reaching a value of 0.55 by 2100. The simulated decline in ocean carbon uptake over the 21st century occurs despite steadily rising atmospheric CO2. This behaviour is usually attributed to climate-induced changes in surface temperature and salinity that reduce CO2 solubility, and increasing ocean stratification that weakens the biological pump. However, ocean biological processes such as dinitrogen fixation and calcification may also play an important role. Although not well understood at present, improved parameterizations of these processes will increase confidence in projections of

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

Directory of Open Access Journals (Sweden)

Claas Teichmann

2013-06-01

Full Text Available Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs. The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming

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

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

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

DEFF Research Database (Denmark)

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

2016-01-01

Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared...... to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice...

Climate change mitigation through livestock system transitions

Science.gov (United States)

Havlík, Petr; Valin, Hugo; Herrero, Mario; Obersteiner, Michael; Schmid, Erwin; Rufino, Mariana C.; Mosnier, Aline; Thornton, Philip K.; Böttcher, Hannes; Conant, Richard T.; Frank, Stefan; Fritz, Steffen; Fuss, Sabine; Kraxner, Florian; Notenbaert, An

2014-01-01

Livestock are responsible for 12% of anthropogenic greenhouse gas emissions. Sustainable intensification of livestock production systems might become a key climate mitigation technology. However, livestock production systems vary substantially, making the implementation of climate mitigation policies a formidable challenge. Here, we provide results from an economic model using a detailed and high-resolution representation of livestock production systems. We project that by 2030 autonomous transitions toward more efficient systems would decrease emissions by 736 million metric tons of carbon dioxide equivalent per year (MtCO2e⋅y−1), mainly through avoided emissions from the conversion of 162 Mha of natural land. A moderate mitigation policy targeting emissions from both the agricultural and land-use change sectors with a carbon price of US$10 per tCO2e could lead to an abatement of 3,223 MtCO2e⋅y−1. Livestock system transitions would contribute 21% of the total abatement, intra- and interregional relocation of livestock production another 40%, and all other mechanisms would add 39%. A comparable abatement of 3,068 MtCO2e⋅y−1 could be achieved also with a policy targeting only emissions from land-use change. Stringent climate policies might lead to reductions in food availability of up to 200 kcal per capita per day globally. We find that mitigation policies targeting emissions from land-use change are 5 to 10 times more efficient—measured in “total abatement calorie cost”—than policies targeting emissions from livestock only. Thus, fostering transitions toward more productive livestock production systems in combination with climate policies targeting the land-use change appears to be the most efficient lever to deliver desirable climate and food availability outcomes. PMID:24567375

Accelerated Climate Modeling for Energy (ACME) Final Scientific/Technical Report

Energy Technology Data Exchange (ETDEWEB)

Chaudhary, Aashish [Kitware, Inc.

2017-10-17

Seven Department of Energy (DOE) national laboratories, Universities, and Kitware, undertook a coordinated effort to build an Earth system modeling capability tailored to meet the climate change research strategic objectives of the DOE Office of Science, as well as the broader climate change application needs of other DOE programs.

Evaluating Regional Scale Deforestation in the University of Victoria Earth System Climate Model

Science.gov (United States)

Longobardi, P.; Montenegro, A.; Beltrami, H.; Eby, M.

2011-12-01

Forests play a key role in influencing the Earths climate and at the same time are affected by changing climates. At this point it is estimated that 15-30% of Earths natural forests have already been converted to pasture or cropland. With such large amounts of forest being converted to cropland and grassland, it is important to determine the climatic effects of these actions. To date, most modelling efforts towards understanding the climatic effects of deforestation have simulated global deforestation or have been based on experiments where trees were removed from large areas, i.e. the entire Amazon or all forests above 50 N. Here we use the University of Victoria Earth System Climate model which contains a fully coupled carbon cycle, to evaluate the response to deforestation of 10%, 25%, 50% and 100% of the forested areas in three latitude bands: high (above 50°N), mid (above ± 30°) and low (between ± 30°). All simulations were transient simulations, allowing for changes to atmospheric forcings following the A2 emissions scenario. High latitude deforestation lead to cooling (-.05 °C to -0.45 °C) and increase in soil carbon (0.5 to 3 x 1014 kg) for all fractions of deforestation. Due in part to the increase in soil carbon, there was a decrease in atmospheric CO2 in the 50% (-20 ppm) and 100% (-60 ppm) high-latitude deforestation simulations. Low-latitude deforestation initially produced warming in all scenarios (0.1 to 0.25 °C), although all were colder (-0.05 to -0.1 °C) than the control by the end of the simulation. Atmospheric CO2 increased in all simulations (40 to 80 ppm), as well as soil carbon (2 to 16 x 1013 kg). Mid-latitude deforestation also lead to initial warming (0.01 to 0.1 °C) followed by cooling (-0.01 to -0.1 °C). Mid latitude deforestation also produced an increase in soil carbon (2 to 10 x 1013 kg), and atmospheric CO2 (0 to 25ppm). In all three latitude bands forest dieback was observed. Results range from 7% to 37% for high

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.

Integrated Information Systems Across the Weather-Climate Continuum

Science.gov (United States)

Pulwarty, R. S.; Higgins, W.; Nierenberg, C.; Trtanj, J.

2015-12-01

The increasing demand for well-organized (integrated) end-to-end research-based information has been highlighted in several National Academy studies, in IPCC Reports (such as the SREX and Fifth Assessment) and by public and private constituents. Such information constitutes a significant component of the "environmental intelligence" needed to address myriad societal needs for early warning and resilience across the weather-climate continuum. The next generation of climate research in service to the nation requires an even more visible, authoritative and robust commitment to scientific integration in support of adaptive information systems that address emergent risks and inform longer-term resilience strategies. A proven mechanism for resourcing such requirements is to demonstrate vision, purpose, support, connection to constituencies, and prototypes of desired capabilities. In this presentation we will discuss efforts at NOAA, and elsewhere, that: Improve information on how changes in extremes in key phenomena such as drought, floods, and heat stress impact management decisions for resource planning and disaster risk reduction Develop regional integrated information systems to address these emergent challenges, that integrate observations, monitoring and prediction, impacts assessments and scenarios, preparedness and adaptation, and coordination and capacity-building. Such systems, as illustrated through efforts such as NIDIS, have strengthened the integration across the foundational research enterprise (through for instance, RISAs, Modeling Analysis Predictions and Projections) by increasing agility for responding to emergent risks. The recently- initiated Climate Services Information System, in support of the WMO Global Framework for Climate Services draws on the above models and will be introduced during the presentation.

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.

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.

Conceptualizing Climate Change in the Context of a Climate System: Implications for Climate and Environmental Education

Science.gov (United States)

Shepardson, Daniel P.; Niyogi, Dev; Roychoudhury, Anita; Hirsch, Andrew

2012-01-01

Today there is much interest in teaching secondary students about climate change. Much of this effort has focused directly on students' understanding of climate change. We hypothesize, however, that in order for students to understand climate change they must first understand climate as a system and how changes to this system due to both natural…

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

Applying "Climate" system to teaching basic climatology and raising public awareness of climate change issues

Science.gov (United States)

Gordova, Yulia; Okladnikov, Igor; Titov, Alexander; Gordov, Evgeny

2016-04-01

While there is a strong demand for innovation in digital learning, available training programs in the environmental sciences have no time to adapt to rapid changes in the domain content. A joint group of scientists and university teachers develops and implements an educational environment for new learning experiences in basics of climatic science and its applications. This so-called virtual learning laboratory "Climate" contains educational materials and interactive training courses developed to provide undergraduate and graduate students with profound understanding of changes in regional climate and environment. The main feature of this Laboratory is that students perform their computational tasks on climate modeling and evaluation and assessment of climate change using the typical tools of the "Climate" information-computational system, which are usually used by real-life practitioners performing such kind of research. Students have an opportunity to perform computational laboratory works using information-computational tools of the system and improve skills of their usage simultaneously with mastering the subject. We did not create an artificial learning environment to pass the trainings. On the contrary, the main purpose of association of the educational block and computational information system was to familiarize students with the real existing technologies for monitoring and analysis of data on the state of the climate. Trainings are based on technologies and procedures which are typical for Earth system sciences. Educational courses are designed to permit students to conduct their own investigations of ongoing and future climate changes in a manner that is essentially identical to the techniques used by national and international climate research organizations. All trainings are supported by lectures, devoted to the basic aspects of modern climatology, including analysis of current climate change and its possible impacts ensuring effective links between

An Interactive Multi-Model for Consensus on Climate Change

Energy Technology Data Exchange (ETDEWEB)

Kocarev, Ljupco [University of California, San Diego

2014-07-02

This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automated combination of equations from different models in an expert-system-like framework.

Potential energy consumption reduction of automotive climate control systems

International Nuclear Information System (INIS)

Nielsen, Filip; Uddheim, Åsa; Dalenbäck, Jan-Olof

2016-01-01

Highlights: • Twenty-on energy saving measures for vehicle interior climate were evaluated. • Few single energy saving measures could reduce the energy use significantly. • The operation of the system in intermediate conditions determines the energy use. • Required heating/cooling of passenger compartment had small effect on energy use. - Abstract: In recent years fuel consumption of passenger vehicles has received increased attention by customers, the automotive industry, regulatory agencies and academia. One area which affect the fuel consumption is climate control systems. Twenty-one energy saving measures were evaluated regarding the total energy use for vehicle interior climate using simulation. Evaluated properties were heat flow into the passenger compartment, electrical and mechanical work. The simulation model included sub models of the passenger compartment, air-handling unit, Air Conditioning (AC) system, engine and engine cooling system. A real-world representative test cycle, which included tests in cold, intermediate and warm conditions, was used for evaluation. In general, few single energy saving measures could reduce the energy use significantly. The measures with most potential were increased blower efficiency with a reduction of 46% of the electrical work and increased AC-system disengage temperature with a reduction of 27% of the mechanical work. These results show that the operation of the climate control system had a large effect on the energy use, especially compared to the required heating and cooling of the passenger compartment. As a result energy saving measures need to address how heating and cooling is generated before reducing the heat flow into the passenger compartment.

Guiding climate change adaptation within vulnerable natural resource management systems.

Science.gov (United States)

Bardsley, Douglas K; Sweeney, Susan M

2010-05-01

Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

Guiding Climate Change Adaptation Within Vulnerable Natural Resource Management Systems

Science.gov (United States)

Bardsley, Douglas K.; Sweeney, Susan M.

2010-05-01

Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

A simple conceptual model of abrupt glacial climate events

Directory of Open Access Journals (Sweden)

H. Braun

2007-11-01

Full Text Available Here we use a very simple conceptual model in an attempt to reduce essential parts of the complex nonlinearity of abrupt glacial climate changes (the so-called Dansgaard-Oeschger events to a few simple principles, namely (i the existence of two different climate states, (ii a threshold process and (iii an overshooting in the stability of the system at the start and the end of the events, which is followed by a millennial-scale relaxation. By comparison with a so-called Earth system model of intermediate complexity (CLIMBER-2, in which the events represent oscillations between two climate states corresponding to two fundamentally different modes of deep-water formation in the North Atlantic, we demonstrate that the conceptual model captures fundamental aspects of the nonlinearity of the events in that model. We use the conceptual model in order to reproduce and reanalyse nonlinear resonance mechanisms that were already suggested in order to explain the characteristic time scale of Dansgaard-Oeschger events. In doing so we identify a new form of stochastic resonance (i.e. an overshooting stochastic resonance and provide the first explicitly reported manifestation of ghost resonance in a geosystem, i.e. of a mechanism which could be relevant for other systems with thresholds and with multiple states of operation. Our work enables us to explicitly simulate realistic probability measures of Dansgaard-Oeschger events (e.g. waiting time distributions, which are a prerequisite for statistical analyses on the regularity of the events by means of Monte-Carlo simulations. We thus think that our study is an important advance in order to develop more adequate methods to test the statistical significance and the origin of the proposed glacial 1470-year climate cycle.

Statistical surrogate models for prediction of high-consequence climate change.

Energy Technology Data Exchange (ETDEWEB)

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1991-01-01

Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question. 9 refs

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1990-01-01

Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question

Contrasting model complexity under a changing climate in a headwaters catchment.

Science.gov (United States)

Foster, L.; Williams, K. H.; Maxwell, R. M.

2017-12-01

Alpine, snowmelt-dominated catchments are the source of water for more than 1/6th of the world's population. These catchments are topographically complex, leading to steep weather gradients and nonlinear relationships between water and energy fluxes. Recent evidence suggests that alpine systems are more sensitive to climate warming, but these regions are vastly simplified in climate models and operational water management tools due to computational limitations. Simultaneously, point-scale observations are often extrapolated to larger regions where feedbacks can both exacerbate or mitigate locally observed changes. It is critical to determine whether projected climate impacts are robust to different methodologies, including model complexity. Using high performance computing and an integrated model of a representative headwater catchment we determined the hydrologic response from 30 projected climate changes to precipitation, temperature and vegetation for the Rocky Mountains. Simulations were run with 100m and 1km resolution, and with and without lateral subsurface flow in order to vary model complexity. We found that model complexity alters nonlinear relationships between water and energy fluxes. Higher-resolution models predicted larger changes per degree of temperature increase than lower resolution models, suggesting that reductions to snowpack, surface water, and groundwater due to warming may be underestimated in simple models. Increases in temperature were found to have a larger impact on water fluxes and stores than changes in precipitation, corroborating previous research showing that mountain systems are significantly more sensitive to temperature changes than to precipitation changes and that increases in winter precipitation are unlikely to compensate for increased evapotranspiration in a higher energy environment. These numerical experiments help to (1) bracket the range of uncertainty in published literature of climate change impacts on headwater

Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

Science.gov (United States)

Lau, William K. M.

2002-01-01

This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

Toward a consistent modeling framework to assess multi-sectoral climate impacts.

Science.gov (United States)

Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

2018-02-13

Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

The physics and dynamics of the climate system simulation of climate change

International Nuclear Information System (INIS)

Mitchell, J.F.B.

1991-01-01

The use of climate models is described, using examples related to: the greenhouse effect, the principal absorbers, past, present and future, climate feedbacks in CO2 experiments, equilibrium climate change due to increased CO2, modelling the transient response to increases in trace gases, uncertainties in the simulation and detection of the climatic effect of increased trace gas, simulations for 9000 years before present

The fire-vegetation-climate system: how ecology can contribute to earth system science

CSIR Research Space (South Africa)

Archibald, S

2013-05-01

Full Text Available and future state of global vegetation. A key complexity that is currently not well captured by Earth System models is that vegetation is not always deterministically responsive to climate and soils. Feedbacks within the Earth System, top-down controls...

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

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)

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

Modelling the Impacts of Climate Change on Tropospheric Ozone over three Centuries

Science.gov (United States)

Brandt Hedegaard, Gitte; Brandt, Jørgen; Christensen, Jesper H.; Gross, Allan; May, Wihelm; Hansen, Kaj M.; Skjøth, Carsten A.

2010-05-01

So far reduction of the anthropogenic emissions of chemical species to the atmosphere has been profoundly investigated. However, new research indicates that climate change on its own also has a significant impact on the future air pollution levels. Climate Change and its impact on air pollution levels are currently studied by a number of research groups using, global, hemispherical and regional modelling systems. In the Department of Atmospheric Environment, National Environmental Research Institute (NERI), Aarhus University, in Denmark, we have developed a hemispherical model system which is based on the DEHM model (Christensen, 1997; Frohn et al., 2002a; Frohn et al., 2002b). In the DEHM modelling system an option for modelling the impacts of climate change has been included by using meteorological input from global climate models. Here we present results by using climate data that are provided by the ECHAM5/MPI-OM Atmosphere-Ocean General Circulation Model (May, 2008; Roeckner et al., 2003). In the current experiment the anthropogenic emissions in the chemistry model DEHM are kept constant on a 2000 level to separate out the signal of climate change on air pollutants while the meteorological drivers simulated by the ECHAM5/MPI-OM climate model is based on the IPCC SRES A1B Scenario. To save computing time the experiment is carried out in time-slices representing four centuries (1890s, 1990s, 2090s and the 2190s). The results show that the dominating impacts from climate change on a large number of the chemical species are related to the predicted temperature increase. This temperature affects chemistry as well as emissions from nature. The largest changes in both meteorology and air quality is found to happen in the 21st century. However, significant changes are also found in some parameters including tropospheric ozone in the following century. In general the background ozone concentrations is predicted to decrease at surface level however in the densely

Climate variability and predictability associated with the Indo-Pacific Oceanic Channel Dynamics in the CCSM4 Coupled System Model

Science.gov (United States)

Yuan, Dongliang; Xu, Peng; Xu, Tengfei

2017-01-01

An experiment using the Community Climate System Model (CCSM4), a participant of the Coupled Model Intercomparison Project phase-5 (CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole (IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.

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.

Detailed performance analysis of realistic solar photovoltaic systems at extensive climatic conditions

International Nuclear Information System (INIS)

Gupta, Ankit; Chauhan, Yogesh K.

2016-01-01

In recent years, solar energy has been considered as one of the principle renewable energy source for electric power generation. In this paper, single diode photovoltaic (PV) system and double/bypass diode based PV system are designed in MATLAB/Simulink environment based on their mathematical modeling and are validated with a commercially available solar panel. The novelty of the paper is to include the effect of climatic conditions i.e. variable irradiation level, wind speed, temperature, humidity level and dust accumulation in the modeling of both the PV systems to represent a realistic PV system. The comprehensive investigations are made on both the modeled PV systems. The obtained results show the satisfactory performance for realistic models of the PV system. Furthermore, an in depth comparative analysis is carried out for both PV systems. - Highlights: • Modeling of Single diode and Double diode PV systems in MATLAB/Simulink software. • Validation of designed PV systems with a commercially available PV panel. • Acquisition and employment of key climatic factors in modeling of the PV systems. • Evaluation of main model parameters of both the PV systems. • Detailed comparative assessment of both the modeled PV system parameters.

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

Science.gov (United States)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

The MIT Integrated Global System Model: A facility for Assessing and Communicating Climate Change Uncertainty (Invited)

Science.gov (United States)

Prinn, R. G.

2013-12-01

The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

Science.gov (United States)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

Twenty first century climate change as simulated by European climate models

International Nuclear Information System (INIS)

Cubasch, Ulrich

2007-01-01

Full text: Climate change simulation results for seven European state-of-the-art climate models, participating in the European research project ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts), will be presented. Models from Norway, France, Germany, Denmark, and Great Britain, representing a sub-ensemble of the models contributing to the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), are included. Climate simulations are conducted with all the models for present-day climate and for future climate under the SRES A1B, A2, and B1 scenarios. The design of the simulations follows the guidelines of the IPCC AR4. The 21st century projections are compared to the corresponding present-day simulations. The ensemble mean global mean near surface temperature rise for the year 2099 compared to the 1961-1990 period amounts to 3.2Kforthe A1B scenario, to 4.1 K for the A2 scenario, and to 2.1 K for the B1 scenario. The spatial patterns of temperature change are robust among the contributing models with the largest temperature increase over the Arctic in boreal winter, stronger warming overland than over ocean, and little warming over the southern oceans. The ensemble mean globally averaged precipitation increases for the three scenarios (5.6%, 5.7%, and 3.8% for scenarios A1B, A2, and B1, respectively). The precipitation signals of the different models display a larger spread than the temperature signals. In general, precipitation increases in the Intertropical Convergence Zone and the mid- to high latitudes (most pronounced during the hemispheric winter) and decreases in the subtropics. Sea-level pressure decreases over the polar regions in all models and all scenarios, which is mainly compensated by a pressure increase in the subtropical highs. These changes imply an intensification of the Southern and Northern Annular Modes

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.

Formulation of a reduced order model of the climatic system by combining classical simulation methods with artificial intelligence techniques

Science.gov (United States)

Bounceur, Nabila; Crucifix, Michel

2010-05-01

The climate is a multivariable dynamic complex system, governed by equations which are strongly nonlinear. The space-time modes of climatic variability extend on a very broad scale and constitute a major difficulty to represent this variability over long time-scales. It is generally decided to separate the dynamics of the slow components (ice sheets, carbon cycle, deep oceans) which have a time scale of about thousand of years and more, from those of the fast components (atmosphere, mixed layer, earth and ice surface) for which the time scale is for about some years. In this framework, the time-evolution of the slow components depends on the statistics of the fast components, and the latter are controlled by the slow components and the external forcing particularly astronomical ones characterised by the variation of the orbital parameters: Obliquity, precession and eccentricity. The statistics of the fast components of the climate could in principle be estimated with a general circulation model of the atmosphere and ocean. However, the demand on computing resources would be far too excessive. Given the complexity of the climatic system, the great number of dynamic equations which govern it and its degree of nonlinearity we are interested in the statistical reduction rather than an analytical one. The order reduction problem is equivalent to approximator construction. We will focus on neural networks because they constitute very powerful estimators in presence of non-linearity. The training of this network would be done using the output of the climate model of intermediate complexity "LoveClim" developed and available in the Institute of Astronomy and Geophysics G.Lemaître in Belgium as a first step of statistical reduction. The output of the model are first reduced using different methods of reduction order going from linear ones as principal component analysis (PCA) and empirical orthogonal functions (EOF) to non linear ones as Non Linear Principal component

NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

Science.gov (United States)

King, Michael D.; Herring, David D.

1998-01-01

Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data

Dynamics of the larch taiga-permafrost coupled system in Siberia under climate change

Energy Technology Data Exchange (ETDEWEB)

Zhang Ningning [Graduate School of Environmental Studies, Nagoya University, Nagoya, Aichi 464-8601 (Japan); Yasunari, Tetsuzo [Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya 464-8601 (Japan); Ohta, Takeshi, E-mail: zhangningning@lasg.iap.ac.cn [Study Consortium for Earth-Life Interactive Systems (SELIS) of Nagoya University, Nagoya (Japan)

2011-04-15

Larch taiga, also known as Siberian boreal forest, plays an important role in global and regional water-energy-carbon (WEC) cycles and in the climate system. Recent in situ observations have suggested that larch-dominated taiga and permafrost behave as a coupled eco-climate system across a broad boreal zone of Siberia. However, neither field-based observations nor modeling experiments have clarified the synthesized dynamics of this system. Here, using a new dynamic vegetation model coupled with a permafrost model, we reveal the processes of interaction between the taiga and permafrost. The model demonstrates that under the present climate conditions in eastern Siberia, larch trees maintain permafrost by controlling the seasonal thawing of permafrost, which in turn maintains the taiga by providing sufficient water to the larch trees. The experiment without permafrost processes showed that larch would decrease in biomass and be replaced by a dominance of pine and other species that suffer drier hydroclimatic conditions. In the coupled system, fire not only plays a destructive role in the forest, but also, in some cases, preserves larch domination in forests. Climate warming sensitivity experiments show that this coupled system cannot be maintained under warming of about 2 deg. C or more. Under such conditions, a forest with typical boreal tree species (dark conifer and deciduous species) would become dominant, decoupled from the permafrost processes. This study thus suggests that future global warming could drastically alter the larch-dominated taiga-permafrost coupled system in Siberia, with associated changes of WEC processes and feedback to climate.

Dynamics of the larch taiga-permafrost coupled system in Siberia under climate change

International Nuclear Information System (INIS)

Zhang Ningning; Yasunari, Tetsuzo; Ohta, Takeshi

2011-01-01

Larch taiga, also known as Siberian boreal forest, plays an important role in global and regional water-energy-carbon (WEC) cycles and in the climate system. Recent in situ observations have suggested that larch-dominated taiga and permafrost behave as a coupled eco-climate system across a broad boreal zone of Siberia. However, neither field-based observations nor modeling experiments have clarified the synthesized dynamics of this system. Here, using a new dynamic vegetation model coupled with a permafrost model, we reveal the processes of interaction between the taiga and permafrost. The model demonstrates that under the present climate conditions in eastern Siberia, larch trees maintain permafrost by controlling the seasonal thawing of permafrost, which in turn maintains the taiga by providing sufficient water to the larch trees. The experiment without permafrost processes showed that larch would decrease in biomass and be replaced by a dominance of pine and other species that suffer drier hydroclimatic conditions. In the coupled system, fire not only plays a destructive role in the forest, but also, in some cases, preserves larch domination in forests. Climate warming sensitivity experiments show that this coupled system cannot be maintained under warming of about 2 deg. C or more. Under such conditions, a forest with typical boreal tree species (dark conifer and deciduous species) would become dominant, decoupled from the permafrost processes. This study thus suggests that future global warming could drastically alter the larch-dominated taiga-permafrost coupled system in Siberia, with associated changes of WEC processes and feedback to climate.

The UK Earth System Model project

Science.gov (United States)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments

Science.gov (United States)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2013-12-01

Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps

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.

Should we assess climate model predictions in light of severe tests?

Science.gov (United States)

Katzav, Joel

2011-06-01

According to Austro-British philosopher Karl Popper, a system of theoretical claims is scientific only if it is methodologically falsifiable, i.e., only if systematic attempts to falsify or severely test the system are being carried out [Popper, 2005, pp. 20, 62]. He holds that a test of a theoretical system is severe if and only if it is a test of the applicability of the system to a case in which the system's failure is likely in light of background knowledge, i.e., in light of scientific assumptions other than those of the system being tested [Popper, 2002, p. 150]. Popper counts the 1919 tests of general relativity's then unlikely predictions of the deflection of light in the Sun's gravitational field as severe. An implication of Popper's above condition for being a scientific theoretical system is the injunction to assess theoretical systems in light of how well they have withstood severe testing. Applying this injunction to assessing the quality of climate model predictions (CMPs), including climate model projections, would involve assigning a quality to each CMP as a function of how well it has withstood severe tests allowed by its implications for past, present, and nearfuture climate or, alternatively, as a function of how well the models that generated the CMP have withstood severe tests of their suitability for generating the CMP.

The application of a dynamic OpenMI coupling between a regional climate model and a distributed surface water-groundwater model

DEFF Research Database (Denmark)

Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

2014-01-01

To support climate adaptation measures for water resources, we have developed and evaluated a dynamic coupling between a comprehensive distributed hydrological modelling system, MIKE SHE, and a regional climate modelling system, HIRHAM. The coupled model enables two-way interaction between the at......, including local measurements of energy fluxes. The results presented here suggest that there may be important differences in the simulated water balances for this catchment created by introducing an alternative hydrological model into the RCM....

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Directory of Open Access Journals (Sweden)

Rachel D. Cavanagh

2017-09-01

Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

Science.gov (United States)

Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John

2008-01-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system

International Nuclear Information System (INIS)

Gao, Y; Fu, J S; Drake, J B; Liu, Y; Lamarque, J-F

2012-01-01

This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year). (letter)

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

Science.gov (United States)

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Physical-Socio-Economic Modeling of Climate Change

Science.gov (United States)

Chamberlain, R. G.; Vatan, F.

2008-12-01

Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-14

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

The meganism behind internally generated centennial-to-millennial scale climate variability in an earth system model of intermediate complexity

NARCIS (Netherlands)

Friedrich, T.; Timmermann, A.; Menviel, L.; Elison Timm, O.; Mouchet, A.; Roche, D.M.V.A.P.

2010-01-01

The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (∼22.1 )

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...

Progress in modelling agricultural impacts of and adaptations to climate change.

Science.gov (United States)

Rötter, R P; Hoffmann, M P; Koch, M; Müller, C

2018-06-01

Modelling is a key tool to explore agricultural impacts of and adaptations to climate change. Here we report recent progress made especially referring to the large project initiatives MACSUR and AgMIP; in particular, in modelling potential crop impacts from field to global using multi-model ensembles. We identify two main fields where further progress is necessary: a more mechanistic understanding of climate impacts and management options for adaptation and mitigation; and focusing on cropping systems and integrative multi-scale assessments instead of single season and crops, especially in complex tropical and neglected but important cropping systems. Stronger linking of experimentation with statistical and eco-physiological crop modelling could facilitate the necessary methodological advances. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of regional water - power systems under cooling constraints and climate change

DEFF Research Database (Denmark)

Payet-burin, Raphaël; Bertoni, Federica; Davidsen, Claus

2018-01-01

Thermo-electric generation represents 70% of Europe's electricity production and 43% of water withdrawals, and is therefore a key element of the water-energy nexus. In 2003, 2006 and 2009, several thermal power plants had to be switched off in Europe because of heat waves, showing the need...... to assess the impact of climate change on cooling constraints of thermal power plants. An integrated water-power model of the Iberian Peninsula was developed in this study. It includes a physical hydrologic representation, spatially and temporally resolved water demands, management of water infrastructure...... and a simple power system model. The system was evaluated under present and future climatic conditions using different climate change scenarios. The cost of cooling constraints is found to increase by 220–640 million €/year, for the period 2046–2065 depending on the climate change scenario. Average available...

Rainwater catchment system design using simulated future climate data

Science.gov (United States)

Wallace, Corey D.; Bailey, Ryan T.; Arabi, Mazdak

2015-10-01

Rainwater harvesting techniques are used worldwide to augment potable water supply, provide water for small-scale irrigation practices, increase rainwater-use efficiency for sustained crop growth in arid and semi-arid regions, decrease urban stormwater flow volumes, and in general to relieve dependency on urban water resources cycles. A number of methods have been established in recent years to estimate reliability of rainwater catchment systems (RWCS) and thereby properly size the components (roof catchment area, storage tank size) of the system for a given climatic region. These methods typically use historical or stochastically-generated rainfall patterns to quantify system performance and optimally size the system, with the latter accounting for possible rainfall scenarios based on statistical relationships of historical rainfall patterns. To design RWCS systems that can sustainably meet water demand under future climate conditions, this paper introduces a method that employs climatic data from general circulation models (GCMs) to develop a suite of catchment area vs. storage size design curves that capture uncertainty in future climate scenarios. Monthly rainfall data for the 2010-2050 time period is statistically downscaled to daily values using a Markov chain algorithm, with results used only from GCMs that yield rainfall patterns that are statistically consistent with historical rainfall patterns. The process is demonstrated through application to two climatic regions of the Federated States of Micronesia (FSM) in the western Pacific, wherein the majority of the population relies on rainwater harvesting for potable water supply. Through the use of design curves, communities can provide household RWCS that achieve a certain degree of storage reliability. The method described herein can be applied generally to any geographic region. It can be used to first, assess the future performance of existing household systems; and second, to design or modify systems

Which complexity of regional climate system models is essential for downscaling anthropogenic climate change in the Northwest European Shelf?

Science.gov (United States)

Mathis, Moritz; Elizalde, Alberto; Mikolajewicz, Uwe

2018-04-01

Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production.

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

Energy Technology Data Exchange (ETDEWEB)

Boslough, Mark B.; Backus, George A.

2005-12-01

We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3

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.

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.

Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

Science.gov (United States)

Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

2012-12-01

Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

Climate Variability over India and Bangladesh from the Perturbed UK Met Office Hadley Model: Impacts on Flow and Nutrient Fluxes in the Ganges Delta System

Science.gov (United States)

Whitehead, P. G.; Caesar, J.; Crossman, J.; Barbour, E.; Ledesma, J.; Futter, M. N.

2015-12-01

A semi-distributed flow and water quality model (INCA- Integrated Catchments Model) has been set up for the whole of the Ganges- Brahmaputra- Meghna (GBM) River system in India and Bangladesh. These massive rivers transport large fluxes of water and nutrients into the Bay of Bengal via the GBM Delta system in Bangladesh. Future climate change will impact these fluxes with changing rainfall, temperature, evapotranspiration and soil moisture deficits being altered in the catchment systems. In this study the INCA model has been used to assess potential impacts of climate change using the UK Met Office Hadley Centre GCM model linked to a regionally coupled model of South East Asia, covering India and Bangladesh. The Hadley Centre model has been pururbed by varying the parameters in the model to generate 17 realisations of future climates. Some of these reflect expected change but others capture the more extreme potential behaviour of future climate conditions. The 17 realisations have been used to drive the INCA Flow and Nitrogen model inorder to generate downstream times series of hydrology and nitrate- nitrogen. The variability of the climates on these fluxes are investigated and and their likley impact on the Bay of Begal Delta considered. Results indicate a slight shift in the monsoon season with increased wet season flows and increased temperatures which alter nutrient fluxes. Societal Importance to Stakeholders The GBM Delta supports one of the most densely populated regions of people living in poverty, who rely on ecosystem services provided by the Delta for survival. These ecosystem services are dependent upon fluxes of water and nutrients. Freshwater for urban, agriculture, and aquaculture requirements are essential to livelihoods. Nutrient loads stimulate estuarine ecosystems, supporting fishing stocks, which contribute significantly the economy of Bangladesh. Thus the societal importance of upstream climate driven change change in Bangladesh are very

A perspective on sustained marine observations for climate modelling and prediction.

Science.gov (United States)

Dunstone, Nick J

2014-09-28

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow

Comparison of Predictive Models for Photovoltaic Module Performance under Sudanese-Sahelian Climate

Directory of Open Access Journals (Sweden)

Njomo Donatien

2012-06-01

Full Text Available This paper investigates various approaches to the modeling of photovoltaic systems and tests their accuracy under tropical climate. Particularly the single diode model is used to estimate the electrical behavior of the cell with respect changes on environmental parameter of temperature and irradiance. A particular typical MXS60 solar panel is used for models evaluation and results are comparing with points taken directly from the experience made on the same panel in tropical climate of the Sudan type . The accuracy of models was computed and the better model was determined for local conditions. The analysis of the curves shows that the single diode model has the better accuracy whereas the Photovoltaic geographical information system (PVGIS approach seems to be not appropriate for the region.

Climate Forecast System Version 2 (CFSv2) Operational Forecasts

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

Climate Forecast System Version 2 (CFSv2) Operational Analysis

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

SWIFT: Semi-empirical and numerically efficient stratospheric ozone chemistry for global climate models

OpenAIRE

Kreyling, Daniel; Wohltmann, Ingo; Lehmann, Ralph; Rex, Markus

2015-01-01

The SWIFT model is a fast yet accurate chemistry scheme for calculating the chemistry of stratospheric ozone. It is mainly intended for use in Global Climate Models (GCMs), Chemistry Climate Models (CCMs) and Earth System Models (ESMs). For computing time reasons these models often do not employ full stratospheric chem- istry modules, but use prescribed ozone instead. This can lead to insufficient representation between stratosphere and troposphere. The SWIFT stratospheric ozone chem...

Using the CLEAN educational resource collection for building three-dimensional lessons to teach the climate system

Science.gov (United States)

Gold, A. U.; Sullivan, S. M.; Manning, C. L. B.; Ledley, T. S.; Youngman, E.; Taylor, J.; Niepold, F., III; Kirk, K.; Lockwood, J.; Bruckner, M. Z.; Fox, S.

2017-12-01

The impacts of climate change are a critical societal challenge of the 21st century. Educating students about the globally connected climate system is key in supporting the development of mitigation and adaptation strategies. Systems thinking is required for students to understand the complex, dynamic climate systems and the role that humans play within them. The interdisciplinary nature of climate science challenges educators, who often don't have formal training in climate science, to identify resources that are scientifically accurate before weaving them together into units that teach about the climate system. The Climate Literacy and Energy Awareness Network (CLEAN) supports this work by providing over 700 peer-reviewed, classroom-ready resources on climate and energy topics. The resource collection itself provide only limited instructional guidance, so educators need to weave the resources together to build multi-dimensional lessons that develop systems thinking skills. The Next Generation Science Standards (NGSS) science standards encourage educators to teach science in a 3-dimensional approach that trains students in systems thinking. The CLEAN project strives to help educators design NGSS-style, three-dimensional lessons about the climate system. Two approaches are currently being modeled on the CLEAN web portal. The first is described in the CLEAN NGSS "Get Started Guide" which follows a step-by-step process starting with the Disciplinary Core Idea and then interweaves the Cross-Cutting Concepts (CCC) and the Science and Engineering Practices (SEP) based on the teaching strategy chosen for the lesson or unit topic. The second model uses a climate topic as a starting place and the SEP as the guide through a four-step lesson sequence called "Earth Systems Investigations". Both models use CLEAN reviewed lessons as the core activity but provide the necessary framework for classroom implementation. Sample lessons that were developed following these two

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

A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

Science.gov (United States)

Kadow, Christopher; Illing, Sebastian; Kunst, Oliver; Ulbrich, Uwe; Cubasch, Ulrich

2015-04-01

The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced

A method for physically based model analysis of conjunctive use in response to potential climate changes

Science.gov (United States)

Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.

2012-01-01

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.