Climate and Global Change

International Nuclear Information System (INIS)

Duplessy, J.C.; Pons, A.; Fantechi, R.

1991-01-01

The present volume contains the lessons delivered at the course held in Arles, France, on the subject Climate and Global Change: natural variability of the geosphere and biosphere systems, biogeochemical cycles and their perturbation by human activities, monitoring and forecasting global changes (satellite observations, modelling,...). Short presentations of students' own research activities are also proposed (climatic fluctuation in the Mediterranean area, climate/vegetation relations, etc.)

Isotopes as validation tools for global climate models

International Nuclear Information System (INIS)

Henderson-Sellers, A.

2001-01-01

Global Climate Models (GCMs) are the predominant tool with which we predict the future climate. In order that people can have confidence in such predictions, GCMs require validation. As almost every available item of meteorological data has been exploited in the construction and tuning of GCMs to date, independent validation is very difficult. This paper explores the use of isotopes as a novel and fully independent means of evaluating GCMs. The focus is the Amazon Basin which has a long history of isotope collection and analysis and also of climate modelling: both having been reported for over thirty years. Careful consideration of the results of GCM simulations of Amazonian deforestation and climate change suggests that the recent stable isotope record is more consistent with the predicted effects of greenhouse warming, possibly combined with forest removal, than with GCM predictions of the effects of deforestation alone

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.

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

Directory of Open Access Journals (Sweden)

M. S. Mizielinski

2014-08-01

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

Drought Persistence Errors in Global Climate Models

Science.gov (United States)

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

2018-04-01

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

Modeling the global society-biosphere-climate system : Part 2: Computed scenarios

NARCIS (Netherlands)

Alcamo, J.; Van Den Born, G.J.; Bouwman, A.F.; De Haan, B.J.; Klein Goldewijk, K.; Klepper, O.; Krabec, J.; Leemans, R.; Olivier, J.G.J.; Toet, A.M.C.; De Vries, H.J.M.; Van Der Woerd, H.J.

1994-01-01

This paper presents scenarios computed with IMAGE 2.0, an integrated model of the global environment and climate change. Results are presented for selected aspects of the society-biosphere-climate system including primary energy consumption, emissions of various greenhouse gases, atmospheric

Can climate models be tuned to simulate the global mean absolute temperature correctly?

Science.gov (United States)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

Global modelling of river water quality under climate change

Science.gov (United States)

van Vliet, Michelle T. H.; Franssen, Wietse H. P.; Yearsley, John R.

2017-04-01

Climate change will pose challenges on the quality of freshwater resources for human use and ecosystems for instance by changing the dilution capacity and by affecting the rate of chemical processes in rivers. Here we assess the impacts of climate change and induced streamflow changes on a selection of water quality parameters for river basins globally. We used the Variable Infiltration Capacity (VIC) model and a newly developed global water quality module for salinity, temperature, dissolved oxygen and biochemical oxygen demand. The modelling framework was validated using observed records of streamflow, water temperature, chloride, electrical conductivity, dissolved oxygen and biochemical oxygen demand for 1981-2010. VIC and the water quality module were then forced with an ensemble of bias-corrected General Circulation Model (GCM) output for the representative concentration pathways RCP2.6 and RCP8.5 to study water quality trends and identify critical regions (hotspots) of water quality deterioration for the 21st century.

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

Science.gov (United States)

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

2016-01-01

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

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

Science.gov (United States)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

Inter-model variability and biases of the global water cycle in CMIP3 coupled climate models

International Nuclear Information System (INIS)

Liepert, Beate G; Previdi, Michael

2012-01-01

Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 20th century are robust results of coupled general circulation models (CGCMs). In spite of these successes, model-to-model variability and biases that are small in first order climate responses, however, have considerable implications for climate predictability especially when multi-model means are used. We show that most climate simulations of the 20th and 21st century A2 scenario performed with CMIP3 (Coupled Model Inter-comparison Project Phase 3) models have deficiencies in simulating the global atmospheric moisture balance. Large biases of only a few models (some biases reach the simulated global precipitation changes in the 20th and 21st centuries) affect the multi-model mean global moisture budget. An imbalanced flux of −0.14 Sv exists while the multi-model median imbalance is only −0.02 Sv. Moreover, for most models the detected imbalance changes over time. As a consequence, in 13 of the 18 CMIP3 models examined, global annual mean precipitation exceeds global evaporation, indicating that there should be a ‘leaking’ of moisture from the atmosphere whereas for the remaining five models a ‘flooding’ is implied. Nonetheless, in all models, the actual atmospheric moisture content and its variability correctly increases during the course of the 20th and 21st centuries. These discrepancies therefore imply an unphysical and hence ‘ghost’ sink/source of atmospheric moisture in the models whose atmospheres flood/leak. The ghost source/sink of moisture can also be regarded as atmospheric latent heating/cooling and hence as positive/negative perturbation of the atmospheric energy budget or non-radiative forcing in the range of −1 to +6 W m −2 (median +0.1 W m −2 ). The inter-model variability of the global atmospheric moisture transport from oceans to land areas, which impacts the terrestrial water cycle, is also quite high and ranges

Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

Science.gov (United States)

Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

2015-12-01

Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

Adapting Indian Agriculture to Global Climate Change

Indian Academy of Sciences (India)

Adapting Indian Agriculture to Global Climate Change · Climate Change: Generic Implications for Agriculture · Controlled environment facilities at IARI used for evaluating model performance in future climate change scenarios · Slide 4 · Slide 5 · Global studies indicate considerable impact of climate change in tropics.

Global climate change and international security

Energy Technology Data Exchange (ETDEWEB)

Rice, M.

1991-01-01

On May 8--10, 1991, the Midwest Consortium of International Security Studies (MCISS) and Argonne National Laboratory cosponsored a conference on Global Climate Change and International Security. The aim was to bring together natural and social scientists to examine the economic, sociopolitical, and security implications of the climate changes predicted by the general circulation models developed by natural scientists. Five themes emerged from the papers and discussions: (1) general circulation models and predicted climate change; (2) the effects of climate change on agriculture, especially in the Third World; (3) economic implications of policies to reduce greenhouse gas emissions; (4) the sociopolitical consequences of climate change; and (5) the effect of climate change on global security.

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

Science.gov (United States)

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

2011-12-01

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

Global climate change impacts on forests and markets

Science.gov (United States)

Xiaohui Tian; Brent Sohngen; John B Kim; Sara Ohrel; Jefferson Cole

2016-01-01

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, theMC2model. The results suggest that climate change will cause forest outputs (such as timber) to increase...

Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

Science.gov (United States)

Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

2016-01-01

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

Climate change, global warming and coral reefs: modelling the effects of temperature.

Science.gov (United States)

Crabbe, M James C

2008-10-01

Climate change and global warming have severe consequences for the survival of scleractinian (reef-building) corals and their associated ecosystems. This review summarizes recent literature on the influence of temperature on coral growth, coral bleaching, and modelling the effects of high temperature on corals. Satellite-based sea surface temperature (SST) and coral bleaching information available on the internet is an important tool in monitoring and modelling coral responses to temperature. Within the narrow temperature range for coral growth, corals can respond to rate of temperature change as well as to temperature per se. We need to continue to develop models of how non-steady-state processes such as global warming and climate change will affect coral reefs.

Global and Arctic climate engineering: numerical model studies.

Science.gov (United States)

Caldeira, Ken; Wood, Lowell

2008-11-13

We perform numerical simulations of the atmosphere, sea ice and upper ocean to examine possible effects of diminishing incoming solar radiation, insolation, on the climate system. We simulate both global and Arctic climate engineering in idealized scenarios in which insolation is diminished above the top of the atmosphere. We consider the Arctic scenarios because climate change is manifesting most strongly there. Our results indicate that, while such simple insolation modulation is unlikely to perfectly reverse the effects of greenhouse gas warming, over a broad range of measures considering both temperature and water, an engineered high CO2 climate can be made much more similar to the low CO2 climate than would be a high CO2 climate in the absence of such engineering. At high latitudes, there is less sunlight deflected per unit albedo change but climate system feedbacks operate more powerfully there. These two effects largely cancel each other, making the global mean temperature response per unit top-of-atmosphere albedo change relatively insensitive to latitude. Implementing insolation modulation appears to be feasible.

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...

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

NARCIS (Netherlands)

Giesen, R.H.|info:eu-repo/dai/nl/304831603; Oerlemans, J.|info:eu-repo/dai/nl/06833656X

2013-01-01

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century

Lake Representations in Global Climate Models: An End-User Perspective

Science.gov (United States)

Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

2017-12-01

The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

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.)

Detailed Urban Heat Island Projections for Cities Worldwide: Dynamical Downscaling CMIP5 Global Climate Models

Directory of Open Access Journals (Sweden)

Dirk Lauwaet

2015-06-01

Full Text Available A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005 and future (2081–2100 climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban heat island of eight different cities, located on three continents, is quantified and assessed, with an unprecedented horizontal resolution of a few hundred meters. For all cities, urban and rural air temperatures are found to increase strongly, up to 7 °C. However, the urban heat island intensity in most cases increases only slightly, often even below the range of uncertainty. A potential explanation, focusing on the role of increased incoming longwave radiation, is put forth. Finally, an alternative method for generating urban climate projections is proposed, combining the ensemble temperature change statistics and the results of the present-day urban climate.

The Ecological consequences of global climate change

National Research Council Canada - National Science Library

Woodward, F. I

1992-01-01

... & land use - modeling potential responses of vegetation to global climate change - effects of climatic change on population dynamics of crop pests - responses of soils to climate change - predicting...

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Directory of Open Access Journals (Sweden)

B. Schneider

2008-04-01

Full Text Available Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP and export production (EP of particulate organic carbon (POC. Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006 with stronger stratification (higher sea surface temperature; SST being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL also reproduces the inverse relationship between stratification (SST and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Comparison of Explicitly Simulated and Downscaled Tropical Cyclone Activity in a High-Resolution Global Climate Model

Directory of Open Access Journals (Sweden)

Hirofumi Tomita

2010-01-01

Full Text Available The response of tropical cyclone activity to climate change is a matter of great inherent interest and practical importance. Most current global climate models are not, however, capable of adequately resolving tropical cyclones; this has led to the development of downscaling techniques designed to infer tropical cyclone activity from the large-scale fields produced by climate models. Here we compare the statistics of tropical cyclones simulated explicitly in a very high resolution (~14 km grid mesh global climate model to the results of one such downscaling technique driven by the same global model. This is done for a simulation of the current climate and also for a simulation of a climate warmed by the addition of carbon dioxide. The explicitly simulated and downscaled storms are similarly distributed in space, but the intensity distribution of the downscaled events has a somewhat longer high-intensity tail, owing to the higher resolution of the downscaling model. Both explicitly simulated and downscaled events show large increases in the frequency of events at the high-intensity ends of their respective intensity distributions, but the downscaled storms also show increases in low-intensity events, whereas the explicitly simulated weaker events decline in number. On the regional scale, there are large differences in the responses of the explicitly simulated and downscaled events to global warming. In particular, the power dissipation of downscaled events shows a 175% increase in the Atlantic, while the power dissipation of explicitly simulated events declines there.

Formulation of an ocean model for global climate simulations

Directory of Open Access Journals (Sweden)

S. M. Griffies

2005-01-01

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

Using isotopes to improve impact and hydrological predictions of land-surface schemes in global climate models

International Nuclear Information System (INIS)

McGuffie, K.; Henderson-Sellers, A.

2002-01-01

Global climate model (GCM) predictions of the impact of large-scale land-use change date back to 1984 as do the earliest isotopic studies of large-basin hydrology. Despite this coincidence in interest and geography, with both papers focussed on the Amazon, there have been few studies that have tried to exploit isotopic information with the goal of improving climate model simulations of the land-surface. In this paper we analyze isotopic results from the IAEA global data base specifically with the goal of identifying signatures of potential value for improving global and regional climate model simulations of the land-surface. Evaluation of climate model predictions of the impacts of deforestation of the Amazon has been shown to be of significance by recent results which indicate impacts occurring distant from the Amazon i.e. tele-connections causing climate change elsewhere around the globe. It is suggested that these could be similar in magnitude and extent to the global impacts of ENSO events. Validation of GCM predictions associated with Amazonian deforestation are increasingly urgently required because of the additional effects of other aspects of climate change, particularly synergies occurring between forest removal and greenhouse gas increases, especially CO 2 . Here we examine three decades distributions of deuterium excess across the Amazon and use the results to evaluate the relative importance of the fractionating (partial evaporation) and non-fractionating (transpiration) processes. These results illuminate GCM scenarios of importance to the regional climate and hydrology: (i) the possible impact of increased stomatal resistance in the rainforest caused by higher levels of atmospheric CO2 [4]; and (ii) the consequences of the combined effects of deforestation and global warming on the regions climate and hydrology

Does climate directly influence NPP globally?

Science.gov (United States)

Chu, Chengjin; Bartlett, Megan; Wang, Youshi; He, Fangliang; Weiner, Jacob; Chave, Jérôme; Sack, Lawren

2016-01-01

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot ) and stand age (a). The authors of that study concluded that the length of the growing season (lgs ) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re-analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum-likelihood model selection, independent-effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot , both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann ), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale. © 2015 John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2012-09-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon

A multi-model assessment of the co-benefits of climate mitigation for global air quality

Energy Technology Data Exchange (ETDEWEB)

Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Reis, Lara Aleluia; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

2016-12-01

The recent International Panel on Climate change (IPCC) report identifies significant co-benefits from climate policies on near-term ambient air pollution and related human health outcomes [1]. This is increasingly relevant for policy making as the health impacts of air pollution are a major global concern- the Global Burden of Disease (GBD) study identifies outdoor air pollution as the sixth major cause of death globally [2]. Integrated assessment models (IAMs) are an effective tool to evaluate future air pollution outcomes across a wide range of assumptions on socio-economic development and policy regimes. The Representative Concentration Pathways (RCPs) [3] were the first set of long-term global scenarios developed across multiple integrated assessment models that provided detailed estimates of a number of air pollutants until 2100. However these scenarios were primarily designed to cover a defined range of radiative forcing outcomes and thus did not specifically focus on the interactions of long-term climate goals on near-term air pollution impacts. More recently, [4] used the RCP4.5 scenario to evaluate the co-benefits of global GHG reductions on air quality and human health in 2030. [5-7] have further examined the interactions of more diverse pollution control regimes with climate policies. This paper extends the listed studies in a number of ways. Firstly it uses multiple IAMs to look into the co-benefits of a global climate policy for ambient air pollution under harmonized assumptions on near-term air pollution control. Multi-model frameworks have been extensively used in the analysis of climate change mitigation pathways, and the structural uncertainties regarding the underlying mechanisms (see for example [8-10]. This is to our knowledge the first time that a multi-model evaluation has been specifically designed and applied to analyze the co-benefits of climate change policy on ambient air quality, thus enabling a better understanding of at a detailed

Global Water Cycle Agreement in the Climate Models Assessed in the IPCC AR4

Science.gov (United States)

Waliser, D.; Seo, K. -W.; Schubert, S.; Njoku, E.

2007-01-01

This study examines the fidelity of the global water cycle in the climate model simulations assessed in the IPCC Fourth Assessment Report. The results demonstrate good model agreement in quantities that have had a robust global observational basis and that are physically unambiguous. The worst agreement occurs for quantities that have both poor observational constraints and whose model representations can be physically ambiguous. In addition, components involving water vapor (frozen water) typically exhibit the best (worst) agreement, and fluxes typically exhibit better agreement than reservoirs. These results are discussed in relation to the importance of obtaining accurate model representation of the water cycle and its role in climate change. Recommendations are also given for facilitating the needed model improvements.

Conceptual understanding of climate change with a globally resolved energy balance model

Energy Technology Data Exchange (ETDEWEB)

Dommenget, Dietmar [Monash University, School of Mathematical Sciences, Melbourne, VIC (Australia); Floeter, Janine [Leibniz Institute for Marine Sciences, Kiel (Germany)

2011-12-15

The future climate change projections are essentially based on coupled general circulation model (CGCM) simulations, which give a distinct global warming pattern with arctic winter amplification, an equilibrium land-sea warming contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the Intergovernmental Panel on Climate Change (IPCC) predictions, the conceptual understanding of these predicted structures of climate change and the causes of their uncertainties is very difficult to reach if only based on these highly complex CGCM simulations. In the study presented here we will introduce a very simple, globally resolved energy balance (GREB) model, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the strongly simplified energy balance models and the fully coupled 4-dimensional complex CGCMs. It provides a fast tool for the conceptual understanding and development of hypotheses for climate change studies, which shall build a basis or starting point for more detailed studies of observations and CGCM simulations. It is based on the surface energy balance by very simple representations of solar and thermal radiation, the atmospheric hydrological cycle, sensible turbulent heat flux, transport by the mean atmospheric circulation and heat exchange with the deeper ocean. Despite some limitations in the representations of the basic processes, the models climate sensitivity and the spatial structure of the warming pattern are within the uncertainties of the IPCC models simulations. It is capable of simulating aspects of the arctic winter amplification, the equilibrium land-sea warming contrast and the inter-hemispheric warming gradient with good agreement to the IPCC models in amplitude and structure. The results give some insight into the understanding of the land-sea contrast and the polar amplification. The GREB model suggests that the regional inhomogeneous

The extrapolar SWIFT-model: Fast stratospheric ozone chemistry for global climate models

OpenAIRE

Kreyling, Daniel

2016-01-01

The goal of this PhD-thesis was the development of a fast yet accurate chemistry scheme for an interactive calculation of the extrapolar stratospheric ozone layer. The SWIFT-model is mainly intended for use in Global Climate Models (GCMs). For computing-time reasons GCMs often do not employ full stratospheric chemistry modules, but use prescribed ozone instead. This method does not consider the interaction between atmospheric dynamics and the ozone layer and can neither resolve the inter-annu...

Integrating chemistry into 3D climate models: Detailed kinetics in the troposphere and stratosphere of a global climate model

Energy Technology Data Exchange (ETDEWEB)

Kao, C.Y.J.; Elliott, S. [Los Alamos National Lab., NM (United States). Earth and Environmental Sciences Div.; Turco, R.P.; Zhao, X. [Univ. of California, Los Angeles, CA (United States)

1997-11-01

This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). The motivation for the project is to create the first complete, three-dimensional climate model that enfolds atmospheric photochemistry. The LANL chemical global climate model (GCM) not only distributes the trace greenhouse gases and modifies their concentrations within the detailed photochemical web, but also permits them to influence the radiation field and so force their own transport. Both atmospheric chemistry and fluid dynamics are nonlinear and zonally asymmetric phenomena. They can only be adequately modeled in three dimensions on the global grid. The kinetics-augmented GCM is the only program within the atmospheric community capable of investigating interaction involving chemistry and transport. The authors have conducted case studies of timely three-dimensional chemistry issues. Examples include ozone production from biomass burning plumes, kinetic feedbacks in zonally asymmetric transport phenomena with month- to year-long time scales, and volcano sulfate aerosols with respect to their potential effects on tropospheric ozone depletion.

A multi-model assessment of the co-benefits of climate mitigation for global air quality

NARCIS (Netherlands)

Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

2016-01-01

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We

Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model

International Nuclear Information System (INIS)

Cubasch, U.; Santer, B.D.; Hegerl, G.; Hoeck, H.; Maier-Reimer, E.; Mikolajwicz, U.; Stoessel, A.; Voss, R.

1992-01-01

The Monte Carlo approach, which has increasingly been used during the last decade in the field of extended range weather forecasting, has been applied for climate change experiments. Four integrations with a global coupled ocean-atmosphere model have been started from different initial conditions, but with the same greenhouse gas forcing according to the IPCC scenario A. All experiments have been run for a period of 50 years. The results indicate that the time evolution of the global mean warming depends strongly on the initial state of the climate system. It can vary between 6 and 31 years. The Monte Carlo approach delivers information about both the mean response and the statistical significance of the response. While the individual members of the ensemble show a considerable variation in the climate change pattern of temperature after 50 years, the ensemble mean climate change pattern closely resembles the pattern obtained in a 100 year integration and is, at least over most of the land areas, statistically significant. The ensemble averaged sea-level change due to thermal expansion is significant in the global mean and locally over wide regions of the Pacific. The hydrological cycle is also significantly enhanced in the global mean, but locally the changes in precipitation and soil moisture are masked by the variability of the experiments. (orig.)

Automated parameter tuning applied to sea ice in a global climate model

Science.gov (United States)

Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.

2018-01-01

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

Integrated assessment models of global climate change

International Nuclear Information System (INIS)

Parson, E.A.; Fisher-Vanden, K.

1997-01-01

The authors review recent work in the integrated assessment modeling of global climate change. This field has grown rapidly since 1990. Integrated assessment models seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socio-economic and bio-physical processes. They may combine simplified representations of the socio-economic determinants of greenhouse gas emissions, the atmosphere and oceans, impacts on human activities and ecosystems, and potential policies and responses. The authors summarize current projects, grouping them according to whether they emphasize the dynamics of emissions control and optimal policy-making, uncertainty, or spatial detail. They review the few significant insights that have been claimed from work to date and identify important challenges for integrated assessment modeling in its relationships to disciplinary knowledge and to broader assessment seeking to inform policy- and decision-making. 192 refs., 2 figs

An integrated framework to address climate change (ESCAPE) and further developments of the global and regional climate modules (MAGICC)

International Nuclear Information System (INIS)

Hulme, M.; Raper, S.C.B.

1995-01-01

ESCAPE (the Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions) is an integrated climate change assessment model constructed between 1990 and 1992 for DG XI of the Commission of the European Community by a consortium of research institutes headed by the Climatic Research Unit (CRU). It has been designed to enable the user to generate future scenarios of greenhouse gas emissions (through an energy-economic model), examine their impact on global climate and sea level (through two independent global climate models), and illustrate some of the consequences of this global climate change at a regional scale for the European Community (through a regional climate scenario generator and impact models). We provide a very brief overview of the ESCAPE model which, although innovative, suffers from a number of major limitations. Subsequent work in the CRU has concentrated on improvements to the global climate module and work has also commenced on an improved regional climate scenario generating module. These improvements will lead to a new integrated climate change assessment model, MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) which can easily be incorporated into new larger integrated frameworks developed by other institutes. (Author)

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

Evaluation of Global Photosynthesis and BVOC Emission Covariance with Climate in NASA ModelE2-Y

Science.gov (United States)

Unger, N.

2012-12-01

Terrestrial gross primary productivity (GPP), a measure of the total amount of CO2 removed from the atmosphere every year to fuel photosynthesis, is the largest global carbon flux. GPP is vital for human welfare as the basis for food and fiber, and provides the crucial ecosystem service of reducing the accumulation of fossil fuel CO2 in the atmosphere. Land plants emit a significant fraction of the assimilated carbon back to the atmosphere in the form of biogenic volatile organic compounds (BVOCs). Isoprene is the dominant BVOC emission with an estimated global source of 200-660 TgC/yr. Global monoterpene emission estimates range from 30-130 TgC/yr. BVOC photochemical oxidation exerts a profound impact on the distribution and variability of the short-lived climate forcers: ozone, biogenic secondary organic aerosol and methane. Here, we apply multiple observational datasets from a suite of platforms to evaluate an updated global chemistry-climate model that is coupled to a new vegetation biophysics scheme incorporating photosynthesis-dependent BVOC emissions (NASA ModelE2-Y). A fixed vegetation structure dataset based on 8 plant functional types and prescribed phenology including crop planting and harvesting gives GPP of 128 PgC/yr and a global isoprene source of 200TgC/yr. The model GPP captures 85% of the annual average zonal mean variability in a FLUXNET-derived global dataset that was generated by data orientated diagnostic upscaling. We assess model BVOC emission climatology against a comprehensive database of campaign-average above canopy flux measurements and surface concentrations of isoprene and monoterpene collected between 1995-2010 across a wide range of ecosystem types, regions and seasons (> 25 flux estimates; > 22 surface concentration values). We evaluate the diurnal, seasonal and interannual integrity of the model BVOC variability against 9 sites for isoprene and 4 sites for monoterpene. The model captures ~60% of the variability in the time

Impacts of climate change on the global forest sector

Science.gov (United States)

Perez-Garcia, J.; Joyce, L.A.; McGuire, A.D.; Xiao, X.

2002-01-01

The path and magnitude of future anthropogenic emissions of carbon dioxide will likely influence changes in climate that may impact the global forest sector. These responses in the global forest sector may have implications for international efforts to stabilize the atmospheric concentration of carbon dioxide. This study takes a step toward including the role of global forest sector in integrated assessments of the global carbon cycle by linking global models of climate dynamics, ecosystem processes and forest economics to assess the potential responses of the global forest sector to different levels of greenhouse gas emissions. We utilize three climate scenarios and two economic scenarios to represent a range of greenhouse gas emissions and economic behavior. At the end of the analysis period (2040), the potential responses in regional forest growing stock simulated by the global ecosystem model range from decreases and increases for the low emissions climate scenario to increases in all regions for the high emissions climate scenario. The changes in vegetation are used to adjust timber supply in the softwood and hardwood sectors of the economic model. In general, the global changes in welfare are positive, but small across all scenarios. At the regional level, the changes in welfare can be large and either negative or positive. Markets and trade in forest products play important roles in whether a region realizes any gains associated with climate change. In general, regions with the lowest wood fiber production cost are able to expand harvests. Trade in forest products leads to lower prices elsewhere. The low-cost regions expand market shares and force higher-cost regions to decrease their harvests. Trade produces different economic gains and losses across the globe even though, globally, economic welfare increases. The results of this study indicate that assumptions within alternative climate scenarios and about trade in forest products are important factors

Estimation of the global climate effect of brown carbon

Science.gov (United States)

Zhang, A.; Wang, Y.; Zhang, Y.; Weber, R. J.; Song, Y.

2017-12-01

Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The global distribution and climate effect of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning region and that the resulting heating tends to stabilize the atmosphere. Yet current climate models do not include proper treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory from Global Fire Emissions Database 4 (GFED4) and developed a BrC module in the Community Atmosphere Model version 5 (CAM5) of Community Earth System Model (CESM) model. The model simulations compared well to BrC observations of the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC-3) campaigns and includes BrC bleaching. Model results suggested that BrC in the upper troposphere due to convective transport is as important an absorber as BC globally. Upper tropospheric BrC radiative forcing is particularly significant over the tropics, affecting the atmosphere stability and Hadley circulation.

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

Directory of Open Access Journals (Sweden)

A. Arneth

2011-08-01

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

Climate Science's Globally Distributed Infrastructure

Science.gov (United States)

Williams, D. N.

2016-12-01

The Earth System Grid Federation (ESGF) is primarily funded by the Department of Energy's (DOE's) Office of Science (the Office of Biological and Environmental Research [BER] Climate Data Informatics Program and the Office of Advanced Scientific Computing Research Next Generation Network for Science Program), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF), the European Infrastructure for the European Network for Earth System Modeling (IS-ENES), and the Australian National University (ANU). Support also comes from other U.S. federal and international agencies. The federation works across multiple worldwide data centers and spans seven international network organizations to provide users with the ability to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a series of geographically distributed peer nodes that are independently administered and united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP; output used by the Intergovernmental Panel on Climate Change assessment reports), multiple model intercomparison projects (MIPs; endorsed by the World Climate Research Programme [WCRP]), and the Accelerated Climate Modeling for Energy (ACME; ESGF is included in the overarching ACME workflow process to store model output). ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs the global climate science community. Data served by ESGF includes not only model output but also observational data from satellites and instruments, reanalysis, and generated images.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-04

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

A statistical-dynamical downscaling procedure for global climate simulations

International Nuclear Information System (INIS)

Frey-Buness, A.; Heimann, D.; Sausen, R.; Schumann, U.

1994-01-01

A statistical-dynamical downscaling procedure for global climate simulations is described. The procedure is based on the assumption that any regional climate is associated with a specific frequency distribution of classified large-scale weather situations. The frequency distributions are derived from multi-year episodes of low resolution global climate simulations. Highly resolved regional distributions of wind and temperature are calculated with a regional model for each class of large-scale weather situation. They are statistically evaluated by weighting them with the according climate-specific frequency. The procedure is exemplarily applied to the Alpine region for a global climate simulation of the present climate. (orig.)

Global climate feedbacks

Energy Technology Data Exchange (ETDEWEB)

Manowitz, B.

1990-10-01

The important physical, chemical, and biological events that affect global climate change occur on a mesoscale -- requiring high spatial resolution for their analysis. The Department of Energy has formulated two major initiatives under the US Global Change Program: ARM (Atmospheric Radiation Measurements), and CHAMMP (Computer Hardware Advanced Mathematics and Model Physics). ARM is designed to use ground and air-craft based observations to document profiles of atmospheric composition, clouds, and radiative fluxes. With research and models of important physical processes, ARM will delineate the relationships between trace gases, aerosol and cloud structure, and radiative transfer in the atmosphere, and will improve the parameterization of global circulation models. The present GCMs do not model important feedbacks, including those from clouds, oceans, and land processes. The purpose of this workshop is to identify such potential feedbacks, to evaluate the uncertainties in the feedback processes (and, if possible, to parameterize the feedback processes so that they can be treated in a GCM), and to recommend research programs that will reduce the uncertainties in important feedback processes. Individual reports are processed separately for the data bases.

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

Science.gov (United States)

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

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie

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

Directory of Open Access Journals (Sweden)

B. B. B. Booth

2013-04-01

Full Text Available We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM. These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario. A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5 and even under aggressive mitigation (RCP2.6 temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs, the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high

Negotiation and Optimality in an Economic Model of Global Climate Change

International Nuclear Information System (INIS)

Gottinger, H.

2000-03-01

The paper addresses the problem of governmental intervention in a multi-country regime of controlling global climate change. Using a simplified case of a two-country, two-sector general equilibrium model the paper shows that the global optimal time path of economic outputs and temperature will converge to a unique steady state provided that consumers care enough about the future. To answer a set of questions relating to 'what will happen if governments decide to correct the problem of global warming?' we study the equilibrium outcome in a bargaining game where two countries negotiate an agreement on future consumption and production plans for the purpose of correcting the problem of climate change. It is shown that the agreement arising from such a negotiation process achieves the best outcome and that it can be implemented in decentralised economies by a system of taxes, subsidies and transfers. By employing the recent advances in non-cooperative bargaining theory, the agreement between two countries is derived endogenously through a well-specified bargaining procedure

Negotiation and Optimality in an Economic Model of Global Climate Change

Energy Technology Data Exchange (ETDEWEB)

Gottinger, H. [International Institute for Environmental Economics and Management IIEEM, University of Maastricht, Maastricht (Netherlands)

2000-03-01

The paper addresses the problem of governmental intervention in a multi-country regime of controlling global climate change. Using a simplified case of a two-country, two-sector general equilibrium model the paper shows that the global optimal time path of economic outputs and temperature will converge to a unique steady state provided that consumers care enough about the future. To answer a set of questions relating to 'what will happen if governments decide to correct the problem of global warming?' we study the equilibrium outcome in a bargaining game where two countries negotiate an agreement on future consumption and production plans for the purpose of correcting the problem of climate change. It is shown that the agreement arising from such a negotiation process achieves the best outcome and that it can be implemented in decentralised economies by a system of taxes, subsidies and transfers. By employing the recent advances in non-cooperative bargaining theory, the agreement between two countries is derived endogenously through a well-specified bargaining procedure.

Implications of regional improvement in global climate models for agricultural impact research

International Nuclear Information System (INIS)

Ramirez-Villegas, Julian; Thornton, Philip K; Jarvis, Andy; Challinor, Andrew J

2013-01-01

Global climate models (GCMs) have become increasingly important for climate change science and provide the basis for most impact studies. Since impact models are highly sensitive to input climate data, GCM skill is crucial for getting better short-, medium- and long-term outlooks for agricultural production and food security. The Coupled Model Intercomparison Project (CMIP) phase 5 ensemble is likely to underpin the majority of climate impact assessments over the next few years. We assess 24 CMIP3 and 26 CMIP5 simulations of present climate against climate observations for five tropical regions, as well as regional improvements in model skill and, through literature review, the sensitivities of impact estimates to model error. Climatological means of seasonal mean temperatures depict mean errors between 1 and 18 ° C (2–130% with respect to mean), whereas seasonal precipitation and wet-day frequency depict larger errors, often offsetting observed means and variability beyond 100%. Simulated interannual climate variability in GCMs warrants particular attention, given that no single GCM matches observations in more than 30% of the areas for monthly precipitation and wet-day frequency, 50% for diurnal range and 70% for mean temperatures. We report improvements in mean climate skill of 5–15% for climatological mean temperatures, 3–5% for diurnal range and 1–2% in precipitation. At these improvement rates, we estimate that at least 5–30 years of CMIP work is required to improve regional temperature simulations and at least 30–50 years for precipitation simulations, for these to be directly input into impact models. We conclude with some recommendations for the use of CMIP5 in agricultural impact studies. (letter)

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

Science.gov (United States)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-10-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar-Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

Science.gov (United States)

Unger, N.; Harper, K.; Zeng, Y.; Kiang, N. Y.; Alienov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.;

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

Energy Technology Data Exchange (ETDEWEB)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, Almut; Schurgers, G.; Amelynck, C.; Goldstein, Allen H.; Guenther, Alex B.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, Karena A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serca, D.

2013-10-22

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball- Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R² = 64-96 %) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr^-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Comparing Forecasts of the Global Impacts of Climate Change

International Nuclear Information System (INIS)

Mendelsohn, R.; Williams, L.

2004-01-01

This paper utilizes the predictions of several Atmosphere-Ocean General Circulation Models and the Global Impact Model to create forecasts of the global market impacts from climate change. The forecasts of market impacts in 2100 vary considerably depending on climate scenarios and climate impact sensitivity. The models do concur that tropical nations will be hurt, temperate nations will be barely affected, and high latitude nations will benefit. Although the size of these effects varies a great deal across models, the beneficial and harmful effects are offsetting, so that the net impact on the globe is relatively small in almost all outcomes. Looking only at market impacts, the forecasts suggest that while the global net benefits of abatement are small, the distribution of damages suggests a large equity problem that could be addressed through a compensation program. The large uncertainty surrounding these forecasts further suggests that continued monitoring of both the climate and impacts is worthwhile

Global climate convention

International Nuclear Information System (INIS)

Simonis, U.E.

1991-01-01

The effort of negotiate a global convention on climate change is one of mankind's great endeavours - and a challenge to economists and development planners. The inherent linkages between climate and the habitability of the earth are increasingly well recognized, and a convention could help to ensure that conserving the environment and developing the economy in the future must go hand in hand. Due to growing environmental concern the United Nations General Assembly has set into motion an international negotiating process for a framework convention on climate change. One the major tasks in these negotiations is how to share the duties in reducing climate relevant gases, particularly carbon dioxide (CO 2 ), between the industrial and the developing countries. The results and proposals could be among the most far-reaching ever for socio-economic development, indeed for global security and survival itself. While the negotiations will be about climate and protection of the atmosphere, they will be on fundamental global changes in energy policies, forestry, transport, technology, and on development pathways with low greenhouse gas emissions. Some of these aspects of a climate convention, particularly the distributional options and consequences for the North-South relations, are addressed in this chapter. (orig.)

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

Science.gov (United States)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates

DEFF Research Database (Denmark)

Thum, T.; Raisanen, P.; Sevanto, S.

2011-01-01

The response of soil organic carbon to climate change might lead to significant feedbacks affecting global warming. This response can be studied by coupled climate-carbon cycle models but so far the description of soil organic carbon cycle in these models has been quite simple. In this work we used...... the coupled climate-carbon cycle model ECHAM5/JSBACH (European Center/Hamburg Model 5/Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg) with two different soil carbon modules, namely (1) the original soil carbon model of JSBACH called CBALANCE and (2) a new soil carbon model Yasso07, to study...... the interaction between climate variability and soil organic carbon. Equivalent ECHAM5/JSBACH simulations were conducted using both soil carbon models, with freely varying atmospheric CO2 for the last 30 years (1977-2006). In this study, anthropogenic CO2 emissions and ocean carbon cycle were excluded. The new...

Acidic deposition and global climate change

International Nuclear Information System (INIS)

Nikolaidis, N.P.; Ecsedy, C.; Olem, H.; Nikolaidis, V.S.

1990-01-01

A literature is presented which examines the research published on understanding ecosystem acidification and the effects of acidic deposition on freshwaters. Topics of discussion include the following: acidic deposition; regional assessments; atmospheric deposition and transport; aquatic effects; mathematical modeling; liming acidic waters; global climate change; atmospheric changes; climate feedbacks; and aquatic effects

Impact of global warming on the geobotanic zones: an experiment with a statistical-dynamical climate model

Energy Technology Data Exchange (ETDEWEB)

Franchito, Sergio H.; Brahmananda Rao, V. [Instituto Nacional de Pesquisas Espaciais, Centro de Ciencia do Sistema Terrestre, CCST, Sau Paulo, SP (Brazil); Moraes, E.C. [Instituto Nacional de Pesquisas Espaciais, Divisao de Sensoriamento Remoto, DSR, Sau Paulo, SP (Brazil)

2011-11-15

In this study, a zonally-averaged statistical climate model (SDM) is used to investigate the impact of global warming on the distribution of the geobotanic zones over the globe. The model includes a parameterization of the biogeophysical feedback mechanism that links the state of surface to the atmosphere (a bidirectional interaction between vegetation and climate). In the control experiment (simulation of the present-day climate) the geobotanic state is well simulated by the model, so that the distribution of the geobotanic zones over the globe shows a very good agreement with the observed ones. The impact of global warming on the distribution of the geobotanic zones is investigated considering the increase of CO{sub 2} concentration for the B1, A2 and A1FI scenarios. The results showed that the geobotanic zones over the entire earth can be modified in future due to global warming. Expansion of subtropical desert and semi-desert zones in the Northern and Southern Hemispheres, retreat of glaciers and sea-ice, with the Arctic region being particularly affected and a reduction of the tropical rainforest and boreal forest can occur due to the increase of the greenhouse gases concentration. The effects were more pronounced in the A1FI and A2 scenarios compared with the B1 scenario. The SDM results confirm IPCC AR4 projections of future climate and are consistent with simulations of more complex GCMs, reinforcing the necessity of the mitigation of climate change associated to global warming. (orig.)

An evaluation of temperature and precipitation from global and regional climate models over Scandinavia

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

Precipitation and temperature from global (GCMs) and regional (RCMs) climate models are compared with reanalysis and observations over Scandinavia. Also projections for the next 50-100 years are considered. The climate development is visualised as moving averages (1920-2100). Box plots are used to illuminate how well GCM runs capture the observed seasonal cycle. Maps show the seasonal difference between results from control runs (RCM) and observations (E-OBS dataset) for the reference period 1981-2000. Plots illustrate the RCM-representation of seasonal temperature and precipitations cycle for five locations in Norway and Sweden: Oslo, Bergen, Trondheim, Tromsoe and Oestersund. The results show rather large differences between control runs and observations, demonstrating the need for bias correction of results from climate models. To get an indicator of which GC M-RCM-combination give the best representation of present climate over Scandinavia, a model ranking is provided. The performance measure used is the root-mean-square deviation of mean monthly and seasonal values. The data is compared both in an area-weighted spatial average of the whole domain as well as for the selected locations. The results indicate that the regional models RACMO2 and RCA show the smallest deviations from observed climate. Among the top ranking GCM-RCM combinations, most were driven by the global model ECHAM5 and some by a version of HadCM3. These two GCMs are also present among the worst performing GCM-RCM combinations indicating that selection of RCMs is crucial. (Author)

Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

NARCIS (Netherlands)

Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

2012-01-01

Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

Directory of Open Access Journals (Sweden)

N. Unger

2013-10-01

Full Text Available We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs, prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64–96% and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr−1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Russia and Global Climate Politics

International Nuclear Information System (INIS)

Tynkkynen, Nina

2014-09-01

Russia, as the fourth largest greenhouse-gas emitter in the world, and a major supplier of fossil fuels causing these emissions, played a decisive role in the enforcement of the Kyoto Protocol, the main instrument of global climate policy so far. Domestically, serious political measures to combat climate change have yet to be taken. Thus, Russia's performance in global climate politics indicates that goals other than genuinely environmental ones, such as political or economic benefits, are the main motivation of Russia's participation. Also, Russia's national pride and its status as a great power are at stake here. This paper scrutinizes Russia's stance in global climate politics, offering an overview of Russia's engagement in international climate politics and its domestic climate policy. In the second part of the paper, Russia's engagement in global environmental politics is discussed in the context of Russia's world status and the great-power concept. Accordingly, the paper aims to shed light on how and why Russia behaves in global climate politics in the way it does. This may be of interest to actors in international environmental politics in general, and relevant to future climate negotiations in particular. (author)

Drought Duration Biases in Current Global Climate Models

Science.gov (United States)

Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia

2016-04-01

Several droughts in the recent past are characterized by their increased duration and intensity. In particular, substantially prolonged droughts have brought major societal and economic losses in certain regions, yet climate change projections of such droughts in terms of duration is subject to large uncertainties. This study analyzes the biases of drought duration in state-of-the-art global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5). Drought durations are defined as negative precipitation anomalies and evaluated with three observation-based datasets in the period of 1901-2010. Large spread in biases of GCMs is commonly found in all regions, with particular strong biases in North East Brazil, Africa, Northern Australia, Central America, Central and Northern Europe, Sahel and Asia. Also in most regions, the interquartile range of bias lies below 0, meaning that the GCMs tend to underestimate drought durations. Meanwhile in some regions such as Western South America, the Amazon, Sahel, West and South Africa, and Asia, considerable inconsistency among the three observation-based datasets were found. These results indicate substantial uncertainties and errors in current GCMs for simulating drought durations as well as a large spread in observation-based datasets, both of which are found to be particularly strong in those regions that are often considered to be hot spots of projected future drying. The underlying sources of these uncertainties need to be identified in further study and will be applied to constrain GCM-based drought projections under climate change.

Global forest sector modeling: application to some impacts of climate change

Science.gov (United States)

Joseph. Buongiorno

2016-01-01

This paper explored the potential long-term effects of a warming climate on the global wood sector, based on Way and Oren's synthesis (Tree Physiology 30,669-688) indicating positive responses of tree growth to higher temperature in boreal and temperative climates, and negative responses in the topics. Changes in forest productivity were introduced in the Global...

Uncertainty and global climate change research

Energy Technology Data Exchange (ETDEWEB)

Tonn, B.E. [Oak Ridge National Lab., TN (United States); Weiher, R. [National Oceanic and Atmospheric Administration, Boulder, CO (United States)

1994-06-01

The Workshop on Uncertainty and Global Climate Change Research March 22--23, 1994, in Knoxville, Tennessee. This report summarizes the results and recommendations of the workshop. The purpose of the workshop was to examine in-depth the concept of uncertainty. From an analytical point of view, uncertainty is a central feature of global climate science, economics and decision making. The magnitude and complexity of uncertainty surrounding global climate change has made it quite difficult to answer even the most simple and important of questions-whether potentially costly action is required now to ameliorate adverse consequences of global climate change or whether delay is warranted to gain better information to reduce uncertainties. A major conclusion of the workshop is that multidisciplinary integrated assessments using decision analytic techniques as a foundation is key to addressing global change policy concerns. First, uncertainty must be dealt with explicitly and rigorously since it is and will continue to be a key feature of analysis and recommendations on policy questions for years to come. Second, key policy questions and variables need to be explicitly identified, prioritized, and their uncertainty characterized to guide the entire scientific, modeling, and policy analysis process. Multidisciplinary integrated assessment techniques and value of information methodologies are best suited for this task. In terms of timeliness and relevance of developing and applying decision analytic techniques, the global change research and policy communities are moving rapidly toward integrated approaches to research design and policy analysis.

A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

Science.gov (United States)

Wehner, M. F.; Oliker, L.; Shalf, J.

2008-12-01

Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

(Un)certainty in climate change impacts on global energy consumption

Science.gov (United States)

van Ruijven, B. J.; De Cian, E.; Sue Wing, I.

2017-12-01

Climate change is expected to have an influence on the energy sector, especially on energy demand. For many locations, this change in energy demand is a balance between increase of demand for space cooling and a decrease of space heating demand. We perform a large-scale uncertainty analysis to characterize climate change risk on energy consumption as driven by climate and socioeconomic uncertainty. We combine a dynamic econometric model1 with multiple realizations of temperature projections from all 21 CMIP5 models (from the NASA Earth Exchange Global Daily Downscaled Projections2) under moderate (RCP4.5) and vigorous (RCP8.5) warming. Global spatial population projections for five SSPs are combined with GDP projections to construct scenarios for future energy demand driven by socioeconomic change. Between the climate models, we find a median global increase in climate-related energy demand of around 24% by 2050 under RCP8.5 with an interquartile range of 18-38%. Most climate models agree on increases in energy demand of more than 25% or 50% in tropical regions, the Southern USA and Southern China (see Figure). With respect to socioeconomic scenarios, we find wide variations between the SSPs for the number of people in low-income countries who are exposed to increases in energy demand. Figure attached: Number of models that agree on total climate-related energy consumption to increase or decrease by more than 0, 10, 25 or 50% by 2050 under RCP8.5 and SSP5 as result of the CMIP5 ensemble of temperature projections. References1. De Cian, E. & Sue Wing, I. Global Energy Demand in a Warming Climate. (FEEM, 2016). 2. Thrasher, B., Maurer, E. P., McKellar, C. & Duffy, P. B. Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol Earth Syst Sci 16, 3309-3314 (2012).

Communicating global climate change using simple indices: an update

Energy Technology Data Exchange (ETDEWEB)

Drost, Frank; Karoly, David [University of Melbourne, School of Earth Sciences, Melbourne, VIC (Australia); Braganza, Karl [National Climate Centre, Bureau of Meteorology, Melbourne, VIC (Australia)

2012-08-15

Previous studies have shown that there are several indices of global-scale temperature variations, in addition to global-mean surface air temperature, that are useful for distinguishing natural internal climate variations from anthropogenic climate change. Appropriately defined, such indices have the ability to capture spatio-temporal information in a similar manner to optimal fingerprints of climate change. These indices include the contrast between the average temperatures over land and over oceans, the Northern Hemisphere meridional temperature gradient, the temperature contrast between the Northern and Southern Hemisphere and the magnitude of the annual cycle of average temperatures over land. They contain information independent of the global-mean temperature for internal climate variations at decadal time scales and represent different aspects of the climate system, yet they show common responses to anthropogenic climate change. In addition, the ratio of average temperature changes over land to those over the oceans should be nearly constant for transient climate change. Hence, supplementing analysis of global-mean surface temperature with analyses of these indices can strengthen results of attribution studies of causes of observed climate variations. In this study, we extend the previous work by including the last 10 years of observational data and the CMIP3 climate model simulations analysed for the IPCC AR4. We show that observed changes in these indices over the last 10 years provide increased evidence of an anthropogenic influence on climate. We also show the usefulness of these indices for evaluating the performance of climate models in simulating large-scale variability of surface temperature. (orig.)

Global Climate Change Pilot Course Project

Science.gov (United States)

Schuenemann, K. C.; Wagner, R.

2011-12-01

In fall 2011 a pilot course on "Global Climate Change" is being offered, which has been proposed to educate urban, diverse, undergraduate students about climate change at the introductory level. The course has been approved to fulfill two general college requirements, a natural sciences requirement that focuses on the scientific method, as well as a global diversity requirement. This course presents the science behind global climate change from an Earth systems and atmospheric science perspective. These concepts then provide the basis to explore the effect of global warming on regions throughout the world. Climate change has been taught as a sub-topic in other courses in the past solely using scientific concepts, with little success in altering the climate change misconceptions of the students. This pilot course will see if new, innovative projects described below can make more of an impact on the students' views of climate change. Results of the successes or failures of these projects will be reported, as well as results of a pre- and post-course questionnaire on climate change given to students taking the course. Students in the class will pair off and choose a global region or country that they will research, write papers on, and then represent in four class discussions spaced throughout the semester. The first report will include details on the current climate of their region and how the climate shapes that region's society and culture. The second report will discuss how that region is contributing to climate change and/or sequestering greenhouse gases. Thirdly, students will discuss observed and predicted changes in that region's climate and what impact it has had, and could have, on their society. Lastly, students will report on what role their region has played in mitigating climate change, any policies their region may have implemented, and how their region can or cannot adapt to future climate changes. They will also try to get a feel for the region

GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics

Science.gov (United States)

Delworth, T.L.; Broccoli, A.J.; Rosati, A.; Stouffer, R.J.; Balaji, V.; Beesley, J.A.; Cooke, W.F.; Dixon, K.W.; Dunne, J.; Dunne, K.A.; Durachta, J.W.; Findell, K.L.; Ginoux, P.; Gnanadesikan, A.; Gordon, C.T.; Griffies, S.M.; Gudgel, R.; Harrison, M.J.; Held, I.M.; Hemler, R.S.; Horowitz, L.W.; Klein, S.A.; Knutson, T.R.; Kushner, P.J.; Langenhorst, A.R.; Lee, H.-C.; Lin, S.-J.; Lu, J.; Malyshev, S.L.; Milly, P.C.D.; Ramaswamy, V.; Russell, J.; Schwarzkopf, M.D.; Shevliakova, E.; Sirutis, J.J.; Spelman, M.J.; Stern, W.F.; Winton, M.; Wittenberg, A.T.; Wyman, B.; Zeng, F.; Zhang, R.

2006-01-01

The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Tw o versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2?? latitude ?? 2.5?? longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1?? in latitude and longitude, with meridional resolution equatorward of 30?? becoming progressively finer, such that the meridional resolution is 1/3?? at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The co ntrol simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and

Inadvertent weather modification urban areas - lessons for global climate change

Energy Technology Data Exchange (ETDEWEB)

Changnon, S A [Illinois State Water Survey, Champaign, IL (USA)

1992-05-01

Large metropolitan areas in North America, home to 65% of the USA's population, have created major changes in their climates over the past 150 years. The rate and amount of the urban climate change approximate those being predicted globally using climate models. Knowledge of urban weather and climate modification holds lessons for the global climate change issue. First, adjustments to urban climate changes can provide guidance for adjusting to global change. A second lesson relates to the difficulty but underscores the necessity of providing scientifically credible proof of change within the noise of natural climatic variability. The evolution of understanding about how urban conditions influence weather reveals several unexpected outcomes, particularly relating to precipitation changes. These suggest that similar future surprises can be expected in a changed global climate, a third lesson. In-depth studies of how urban climate changes affected the hydrologic cycle, the regional economy, and human activities were difficult because of data problems, lack of impact methodology, and necessity for multidisciplinary investigations. Similar impact studies for global climate change will require diverse scientific talents and funding commitments adequate to measure the complexity of impacts and human adjustments. Understanding the processes whereby urban areas and other human activities have altered the atmosphere and changed clouds and precipitation regionally appears highly relevant to the global climate-change issue. Scientific and governmental policy development needs to recognize an old axiom that became evident in the studies of inadvertent urban and regional climate change and their behavioural implications: Think globally but act locally. Global climate change is an international issue, and the atmosphere must be treated globally. But the impacts and the will to act and adjust will occur regionally.

Inadvertent weather modification urban areas - lessons for global climate change

International Nuclear Information System (INIS)

Changnon, S.A.

1992-01-01

Large metropolitan areas in North America, home to 65% of the USA's population, have created major changes in their climates over the past 150 years. The rate and amount of the urban climate change approximate those being predicted globally using climate models. Knowledge of urban weather and climate modification holds lessons for the global climate change issue. First, adjustments to urban climate changes can provide guidance for adjusting to global change. A second lesson relates to the difficulty but underscores the necessity of providing scientifically credible proof of change within the noise of natural climatic variability. The evolution of understanding about how urban conditions influence weather reveals several unexpected outcomes, particularly relating to precipitation changes. These suggest that similar future surprises can be expected in a changed global climate, a third lesson. In-depth studies of how urban climate changes affected the hydrologic cycle, the regional economy, and human activities were difficult because of data problems, lack of impact methodology, and necessity for multidisciplinary investigations. Similar impact studies for global climate change will require diverse scientific talents and funding commitments adequate to measure the complexity of impacts and human adjustments. Understanding the processes whereby urban areas and other human activities have altered the atmosphere and changed clouds and precipitation regionally appears highly relevant to the global climate-change issue. Scientific and governmental policy development needs to recognize an old axiom that became evident in the studies of inadvertent urban and regional climate change and their behavioural implications: Think globally but act locally. Global climate change is an international issue, and the atmosphere must be treated globally. But the impacts and the will to act and adjust will occur regionally

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

Directory of Open Access Journals (Sweden)

Edlund Stefan

2012-09-01

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

Climate change 101 : understanding and responding to global climate change

Science.gov (United States)

2009-01-01

To inform the climate change dialogue, the Pew Center on Global Climate Change and the Pew Center on the States have developed a series of brief reports entitled Climate Change 101: Understanding and Responding to Global Climate Change. These reports...

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

Science.gov (United States)

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

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human

Global soil-climate-biome diagram: linking soil properties to climate and biota

Science.gov (United States)

Zhao, X.; Yang, Y.; Fang, J.

2017-12-01

As a critical component of the Earth system, soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. Despite significant progress in digital soil mapping techniques and the rapidly growing quantity of observed soil information, quantitative linkages between soil properties, climate and biota at the global scale remain unclear. By compiling a large global soil database, we mapped seven major soil properties (bulk density [BD]; sand, silt and clay fractions; soil pH; soil organic carbon [SOC] density [SOCD]; and soil total nitrogen [STN] density [STND]) based on machine learning algorithms (regional random forest [RF] model) and quantitatively assessed the linkage between soil properties, climate and biota at the global scale. Our results demonstrated a global soil-climate-biome diagram, which improves our understanding of the strong correspondence between soils, climate and biomes. Soil pH decreased with greater mean annual precipitation (MAP) and lower mean annual temperature (MAT), and the critical MAP for the transition from alkaline to acidic soil pH decreased with decreasing MAT. Specifically, the critical MAP ranged from 400-500 mm when the MAT exceeded 10 °C but could decrease to 50-100 mm when the MAT was approximately 0 °C. SOCD and STND were tightly linked; both increased in accordance with lower MAT and higher MAP across terrestrial biomes. Global stocks of SOC and STN were estimated to be 788 ± 39.4 Pg (1015 g, or billion tons) and 63 ± 3.3 Pg in the upper 30-cm soil layer, respectively, but these values increased to 1654 ± 94.5 Pg and 133 ± 7.8 Pg in the upper 100-cm soil layer, respectively. These results reveal quantitative linkages between soil properties, climate and biota at the global scale, suggesting co-evolution of the soil, climate and biota under conditions of global environmental change.

Estimated migration rates under scenarios of global climate change.

Science.gov (United States)

Jay R. Malcolm; Adam Markham; Ronald P. Neilson; Michael. Oaraci

2002-01-01

Greefihouse-induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2 doubled climatic forcing.

Consistency of climate change projections from multiple global and regional model intercomparison projects

Science.gov (United States)

Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

2018-03-01

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

Response of the mean global vegetation distribution to interannual climate variability

Energy Technology Data Exchange (ETDEWEB)

Notaro, Michael [University of Wisconsin-Madison, Center for Climatic Research, Madison, WI (United States)

2008-06-15

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States' ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. (orig.)

A vertically resolved, global, gap-free ozone database for assessing or constraining global climate model simulations

Directory of Open Access Journals (Sweden)

G. E. Bodeker

2013-02-01

Full Text Available High vertical resolution ozone measurements from eight different satellite-based instruments have been merged with data from the global ozonesonde network to calculate monthly mean ozone values in 5° latitude zones. These ''Tier 0'' ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km and on 70 pressure levels spaced ~ 1 km apart (878.4 hPa to 0.046 hPa. The Tier 0 data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to the Tier 0 data and then evaluated globally. The regression model fit coefficients are expanded in Legendre polynomials to account for latitudinal structure, and in Fourier series to account for seasonality. Regression model fit coefficient patterns, which are two dimensional fields indexed by latitude and month of the year, from the N-th vertical level serve as an initial guess for the fit at the N + 1-th vertical level. The initial guess field for the first fit level (20 km/58.2 hPa was derived by applying the regression model to total column ozone fields. Perturbations away from the initial guess are captured through the Legendre and Fourier expansions. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. By summing different combinations of contributions from different regression model basis functions, four different ''Tier 1'' databases have been compiled for different intended uses. This database is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not

Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

Science.gov (United States)

Rosenzweig, Cynthia E.; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Mueller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay

2014-01-01

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Climate change - global warming

International Nuclear Information System (INIS)

Ciconkov, Risto

2001-01-01

An explanation about climate, weather, climate changes. What is a greenhouse effect, i.e. global warming and reasons which contribute to this effect. Greenhouse gases (GHG) and GWP (Global Warming Potential) as a factor for estimating their influence on the greenhouse effect. Indicators of the climate changes in the previous period by known international institutions, higher concentrations of global average temperature. Projecting of likely scenarios for the future climate changes and consequences of them on the environment and human activities: industry, energy, agriculture, water resources. The main points of the Kyoto Protocol and problems in its realization. The need of preparing a country strategy concerning the acts of the Kyoto Protocol, suggestions which could contribute in the preparation of the strategy. A special attention is pointed to the energy, its resources, the structure of energy consumption and the energy efficiency. (Author)

Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model

International Nuclear Information System (INIS)

Cox, P.M.; Betts, R.A.; Jones, C.D.; Spall, S.A.; Totterdell, I.J.

2000-01-01

The continued increase in the atmospheric concentration of carbon dioxide due to anthropogenic emissions is predicted to lead to significant changes in climate. About half of the current emissions are being absorbed by the ocean and by land ecosystems, but this absorption is sensitive to climate as well as to atmospheric carbon dioxide concentrations, creating a feedback loop. General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO 2 concentrations from simple carbon-cycle models that do not include climate change. Here we present results from a fully coupled, three-dimensional carbon-climate model, indicating that carbon-cycle feedbacks could significantly accelerate climate change over the twenty-first century. We find that under a 'business as usual' scenario, the terrestrial biosphere acts as an overall carbon sink until about 2050, but turns into a source thereafter. By 2100, the ocean uptake rate of 5 Gt C yr -1 is balanced by the terrestrial carbon source, and atmospheric CO 2 concentrations are 250 p.p.m.v. higher in our fully coupled simulation than in uncoupled carbon models, resulting in a global-mean warming of 5.5 K, as compared to 4 K without the carbon-cycle feedback. (author)

Assessing the Benefits of Global Climate Stabilization Within an Integrated Modeling Framework

Science.gov (United States)

Beach, R. H.

2015-12-01

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been a number of studies of climate change impacts on agriculture or forestry. However, relatively few studies explore climate change impacts on both agriculture and forests simultaneously, including the interactions between alternative land uses and implications for market outcomes. Additionally, there is a lack of detailed analyses of the effects of stabilization scenarios relative to unabated emissions scenarios. Such analyses are important for developing estimates of the benefits of those stabilization scenarios, which can play a vital role in assessing tradeoffs associated with allocating resources across alternative mitigation and adaptation activities. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from 32.7 billion to 54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative

Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

Science.gov (United States)

Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

2017-12-01

Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

Economic implications of climate-driven trends in global hydropower generation

Science.gov (United States)

Turner, S. W. D.; Galelli, S.; Hejazi, M. I.; Clarke, L.; Edmonds, J.; Kim, S. H.

2017-12-01

Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore how these impacts could affect the composition of global electricity supply, and what those changes could mean for power sector emissions and investment needs in the 21st century. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model (1593 major hydropower dams; 54% global installed capacity) with downscaled, bias-corrected climate realizations derived from sixteen General Circulation Models (GCMs). To incorporate possible non-linearity in hydropower response to climate change, dam simulations incorporate plant specifications (e.g., maximum turbine flow), reservoir storage dynamics, reservoir bathymetry, evaporation losses and bespoke, site specific operations. Consequent impacts on regional and global-level electricity generation and associated emissions and investment costs are examined using the Global Change Assessment Model (GCAM). We show that changes in hydropower generation resulting from climate change can shift power demands onto and away from carbon intensive technologies, resulting in significant impacts on CO2 emissions for several regions. Many of these countries are also highly vulnerable to investment impacts (costs of new electricity generating facilities to make up for shortfalls in hydro), which in some cases amount to tens of billions of dollars by 2100. The Balkans region—typified by weak economies in a drying region that relies heavily on hydropower—emerges as the most vulnerable. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity (low emissions requires greater uptake of clean generating technologies, which are more expensive). This means impacts on power sector investment costs are similar for high

Group size effects in two repeated game models of a global climate agreement

International Nuclear Information System (INIS)

Helland, Leif

2002-01-01

What levels of total abatement can one hope for in a global climate agreement. Some potential answers to this question are provided by game theory. This working paper contains a critical discussion of two (prominent) game ,models that answer the question quite pessimistically. Both models take the n-person, infinitely repeated prisoner's dilemma game as their point of departure. The first model is a full information model and utilises the motion of a weakly re negotiation proof equilibrium. This results in the (maybe counterintuitive) prediction that an agreement that can provide high utility to the group will attract less total abatement than an agreement that can only provide low utility to the group. The second model assumes imperfect public information and utilises the notion of a trigger level equilibrium. This results in the (more intuitive) prediction that the level of total abatements will increase with improved verification techniques for a given player set. Still the level of total abatements decrease with an increasing player set for a given verification technique. Empirical implications of the two models are identified and it is argued that one should confront these with experimentally generated data in order to discriminate between the models. One reason for this is that historical data on abatement efforts in a global climate agreement do not exist since no such agreement has entered into force yet. (Author)

Group size effects in two repeated game models of a global climate agreement

Energy Technology Data Exchange (ETDEWEB)

Helland, Leif

2002-07-01

What levels of total abatement can one hope for in a global climate agreement. Some potential answers to this question are provided by game theory. This working paper contains a critical discussion of two (prominent) game ,models that answer the question quite pessimistically. Both models take the n-person, infinitely repeated prisoner's dilemma game as their point of departure. The first model is a full information model and utilises the motion of a weakly re negotiation proof equilibrium. This results in the (maybe counterintuitive) prediction that an agreement that can provide high utility to the group will attract less total abatement than an agreement that can only provide low utility to the group. The second model assumes imperfect public information and utilises the notion of a trigger level equilibrium. This results in the (more intuitive) prediction that the level of total abatements will increase with improved verification techniques for a given player set. Still the level of total abatements decrease with an increasing player set for a given verification technique. Empirical implications of the two models are identified and it is argued that one should confront these with experimentally generated data in order to discriminate between the models. One reason for this is that historical data on abatement efforts in a global climate agreement do not exist since no such agreement has entered into force yet. (Author)

Climate. Meeting the challenge of global warming

International Nuclear Information System (INIS)

Masson-Delmotte, Valerie; Mann, Michael; Greene, Charles; Salas y Melia, David; Dufresne, Jean-Louis; Journe, Venance; Guegan, Jean-Francois; ); Bopp, Laurent; Magnan, Alexandre; Gattuso, Jean-Pierre; Bally, Rene; Duponnois, Robin; Giodda, Alain; MOATTI, JEAN-PAUL; Recio, Carlos; Santana, Luis; Hulot, Nicolas; Criqui, Patrick; Meritet, Sophie; Jacobson, Mark; Delucchi, Mark; Julliard, Romain; Balibar, Sebastien; Prevot, Anne-Caroline; Colleony, Agathe; Mangin, Loic

2015-01-01

The contributions of this publication first discuss and comment the cost of inaction in front of global warming. The authors deny the existence of a climate pause, explain the existence of harsh winters in Europe in the context of global warming, outline that models developed and used in the 1960 already predicted the present trend, discuss the complex relationships between climate change and health, outline the threats on the oceans (acidification, impact on marine species, level rise) and consequently on mankind. A second set of contributions addresses opportunities to be implemented now: to plant trees along the Sahara, the example of an ecologic island (El Hierro, Canaries Islands), the commitment of communities, associations and citizens, the necessary energy transition, innovation at the service of climate, the role of finances and investments. The third set of contributions addresses perspectives: to do without fossil energies, how to reduce the impact of global warming in cities (by planting trees and closing shutters), the emergence of participative science, arguments against climate sceptics, a difficult change of behaviours

A new climate dataset for systematic assessments of climate change impacts as a function of global warming

Directory of Open Access Journals (Sweden)

J. Heinke

2013-10-01

Full Text Available In the ongoing political debate on climate change, global mean temperature change (ΔTglob has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere–Ocean General Circulation Models (AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

Global ice sheet modeling

International Nuclear Information System (INIS)

Hughes, T.J.; Fastook, J.L.

1994-05-01

The University of Maine conducted this study for Pacific Northwest Laboratory (PNL) as part of a global climate modeling task for site characterization of the potential nuclear waste respository site at Yucca Mountain, NV. The purpose of the study was to develop a global ice sheet dynamics model that will forecast the three-dimensional configuration of global ice sheets for specific climate change scenarios. The objective of the third (final) year of the work was to produce ice sheet data for glaciation scenarios covering the next 100,000 years. This was accomplished using both the map-plane and flowband solutions of our time-dependent, finite-element gridpoint model. The theory and equations used to develop the ice sheet models are presented. Three future scenarios were simulated by the model and results are discussed

Global climate change

International Nuclear Information System (INIS)

Levine, J.S.

1991-01-01

Present processes of global climate change are reviewed. The processes determining global temperature are briefly described and the concept of effective temperature is elucidated. The greenhouse effect is examined, including the sources and sinks of greenhouse gases. 18 refs

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.

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

Wintertime urban heat island modified by global climate change over Japan

Science.gov (United States)

Hara, M.

2015-12-01

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

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Science.gov (United States)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Future Global Mortality from Changes in Air Pollution Attributable to Climate Change

Science.gov (United States)

Silva, Raquel A.; West, J. Jason; Lamarque, Jean-Francois; Shindell, Drew T.; Collins, William J.; Faluvegi, Greg; Folberth, Gerd A.; Horowitz, Larry W.; Nagashima, Tatsuya; Naik, Vaishali;

Process-Oriented Diagnostics of Tropical Cyclones in Global Climate Models

Science.gov (United States)

Moon, Y.; Kim, D.; Camargo, S. J.; Wing, A. A.; Sobel, A. H.; Bosilovich, M. G.; Murakami, H.; Reed, K. A.; Vecchi, G. A.; Wehner, M. F.; Zarzycki, C. M.; Zhao, M.

2017-12-01

Simulating tropical cyclone (TC) activity with global climate models (GCMs) remains a challenging problem. While some GCMs are able to simulate TC activity that is in good agreement with the observations, many other models exhibit strong biases. Decreasing horizontal grid spacing of the GCM simulations tends to improve the characteristics of simulated TCs, but this enhancement alone does not necessarily lead to greater skill in simulating TC activity. This study uses process-based diagnostics to identify model characteristics that could explain why some GCM simulations are able to produce more realistic TC activity than others. The diagnostics examine how convection, moisture, clouds and related processes are coupled at individual grid points, which yields useful information into how convective parameterizations interact with resolved model dynamics. These diagnostics share similarities with those originally developed to examine the Madden-Julian Oscillations in climate models. This study will examine TCs in eight different GCM simulations performed at NOAA/GFDL, NCAR and NASA that have different horizontal resolutions and ocean coupling. Preliminary results suggest that stronger TCs are closely associated with greater rainfall - thus greater diabatic heating - in the inner-core regions of the storms, which is consistent with previous theoretical studies. Other storm characteristics that can be used to infer why GCM simulations with comparable horizontal grid spacings produce different TC activity will be examined.

Sixth-Grade Students' Progress in Understanding the Mechanisms of Global Climate Change

Science.gov (United States)

Visintainer, Tammie; Linn, Marcia

2015-04-01

Developing solutions for complex issues such as global climate change requires an understanding of the mechanisms involved. This study reports on the impact of a technology-enhanced unit designed to improve understanding of global climate change, its mechanisms, and their relationship to everyday energy use. Global Climate Change, implemented in the Web-based Inquiry Science Environment (WISE), engages sixth-grade students in conducting virtual investigations using NetLogo models to foster an understanding of core mechanisms including the greenhouse effect. Students then test how the greenhouse effect is enhanced by everyday energy use. This study draws on three data sources: (1) pre- and post-unit interviews, (2) analysis of embedded assessments following virtual investigations, and (3) contrasting cases of two students (normative vs. non-normative understanding of the greenhouse effect). Results show the value of using virtual investigations for teaching the mechanisms associated with global climate change. Interviews document that students hold a wide range of ideas about the mechanisms driving global climate change. Investigations with models help students use evidence-based reasoning to distinguish their ideas. Results show that understanding the greenhouse effect offers a foundation for building connections between everyday energy use and increases in global temperature. An impediment to establishing coherent understanding was the persistence of an alternative conception about ozone as an explanation for climate change. These findings illustrate the need for regular revision of curriculum based on classroom trials. We discuss key design features of models and instructional revisions that can transform the teaching and learning of global climate change.

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

Science.gov (United States)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

BVOC-aerosol-climate interactions in the global aerosol-climate model ECHAM5.5-HAM2

Directory of Open Access Journals (Sweden)

R. Makkonen

2012-11-01

Full Text Available The biosphere emits volatile organic compounds (BVOCs which, after oxidation in the atmosphere, can partition on the existing aerosol population or even form new particles. The large quantities emitted provide means for a large potential impact on both aerosol direct and indirect effects. Biogenic responses to atmospheric temperature change can establish feedbacks even in rather short timescales. However, due to the complexity of organic aerosol partitioning, even the sign of these feedbacks is of large uncertainty. We use the global aerosol-climate model ECHAM5.5-HAM2 to explore the effect of BVOC emissions on new particle formation, clouds and climate. Two BVOC emission models, MEGAN2 and LPJ-GUESS, are used. MEGAN2 shows a 25% increase while LPJ-GUESS shows a slight decrease in global BVOC emission between years 2000 and 2100. The change of shortwave cloud forcing from year 1750 to 2000 ranges from −1.4 to −1.8 W m⁻² with 5 different nucleation mechanisms. We show that the change in shortwave cloud forcing from the year 2000 to 2100 ranges from 1.0 to 1.5 W m⁻². Although increasing future BVOC emissions provide 3–5% additional CCN, the effect on the cloud albedo change is modest. Due to simulated decreases in future cloud cover, the increased CCN concentrations from BVOCs can not provide significant additional cooling in the future.

Global Framework for Climate Services (GFCS)

Science.gov (United States)

Lúcio, F.

2012-04-01

a set of international arrangements that will coordinate the activities and build on existing efforts to provide climate services that are truly focused on meeting user needs. It will be implemented through the development of five main components: 1) User Interface Platform — to provide ways for climate service users and providers to interact and improve the effectiveness of the Framework and its climate services 2) Climate Services Information System — to produce and distribute climate data and information according to the needs of users and to agreed standards 3) Observations and Monitoring - to develop agreements and standards for collecting and generating necessary climate data 4) Research, Modeling and Prediction section — to harness science capabilities and results to meet the needs of climate services 5) Capacity Building — to support the systematic development of the institutions, infrastructure and human resources needed for effective production of climate services and their application. Putting the GFCS in place will require unprecedented collaboration among agencies and across political, functional and disciplinary boundaries, and a global mobilization of effort. This communication will provide information on benefits and the process for the development of the GFCS as well as potential entry points for stakeholders to participate. In addition, it will highlight some of the research, modelling and prediction opportunities that will require intra-disciplinary science action.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

Science.gov (United States)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread

Assessing NARCCAP climate model effects using spatial confidence regions

Directory of Open Access Journals (Sweden)

J. P. French

2017-07-01

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

Large-Scale Variation in Forest Carbon Turnover Rate and its Relation to Climate - Remote Sensing vs. Global Vegetation Models

Science.gov (United States)

Carvalhais, N.; Thurner, M.; Beer, C.; Forkel, M.; Rademacher, T. T.; Santoro, M.; Tum, M.; Schmullius, C.

2015-12-01

While vegetation productivity is known to be strongly correlated to climate, there is a need for an improved understanding of the underlying processes of vegetation carbon turnover and their importance at a global scale. This shortcoming has been due to the lack of spatially extensive information on vegetation carbon stocks, which we recently have been able to overcome by a biomass dataset covering northern boreal and temperate forests originating from radar remote sensing. Based on state-of-the-art products on biomass and NPP, we are for the first time able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests. The implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current global vegetation models. In contrast to our observation-based findings, investigated models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well to observation-based NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in global vegetation models and estimating their impact on the land carbon balance.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

Science.gov (United States)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen

Global response to solar radiation absorbed by phytoplankton in a coupled climate model

Energy Technology Data Exchange (ETDEWEB)

Patara, Lavinia [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Helmholtz Centre for Ocean Research Kiel (GEOMAR), Kiel (Germany); Vichi, Marcello; Masina, Simona [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Istituto Nazionale di Geofisica e Vulcanologia (INGV), Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Fogli, Pier Giuseppe [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Manzini, Elisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Bologna (Italy); Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

2012-10-15

The global climate response to solar radiation absorbed by phytoplankton is investigated by performing multi-century simulations with a coupled ocean-atmosphere-biogeochemistry model. The absorption of solar radiation by phytoplankton increases radiative heating in the near-surface ocean and raises sea surface temperature (SST) by overall {approx}0.5 C. The resulting increase in evaporation enhances specific atmospheric humidity by 2-5%, thereby increasing the Earth's greenhouse effect and the atmospheric temperatures. The Hadley Cell exhibits a weakening and poleward expansion, therefore reducing cloudiness at subtropical-middle latitudes and increasing it at tropical latitudes except near the Equator. Higher SST at polar latitudes reduces sea ice cover and albedo, thereby increasing the high-latitude ocean absorption of solar radiation. Changes in the atmospheric baroclinicity cause a poleward intensification of mid-latitude westerly winds in both hemispheres. As a result, the North Atlantic Ocean meridional overturning circulation extends more northward, and the equatorward Ekman transport is enhanced in the Southern Ocean. The combination of local and dynamical processes decreases upper-ocean heat content in the Tropics and in the subpolar Southern Ocean, and increases it at middle latitudes. This study highlights the relevance of coupled ocean-atmosphere processes in the global climate response to phytoplankton solar absorption. Given that simulated impacts of phytoplankton on physical climate are within the range of natural climate variability, this study suggests the importance of phytoplankton as an internal constituent of the Earth's climate and its potential role in participating in its long-term climate adjustments. (orig.)

Global response to solar radiation absorbed by phytoplankton in a coupled climate model

International Nuclear Information System (INIS)

Patara, Lavinia; Vichi, Marcello; Masina, Simona; Fogli, Pier Giuseppe; Manzini, Elisa

2012-01-01

The global climate response to solar radiation absorbed by phytoplankton is investigated by performing multi-century simulations with a coupled ocean-atmosphere-biogeochemistry model. The absorption of solar radiation by phytoplankton increases radiative heating in the near-surface ocean and raises sea surface temperature (SST) by overall ∼0.5 C. The resulting increase in evaporation enhances specific atmospheric humidity by 2-5%, thereby increasing the Earth's greenhouse effect and the atmospheric temperatures. The Hadley Cell exhibits a weakening and poleward expansion, therefore reducing cloudiness at subtropical-middle latitudes and increasing it at tropical latitudes except near the Equator. Higher SST at polar latitudes reduces sea ice cover and albedo, thereby increasing the high-latitude ocean absorption of solar radiation. Changes in the atmospheric baroclinicity cause a poleward intensification of mid-latitude westerly winds in both hemispheres. As a result, the North Atlantic Ocean meridional overturning circulation extends more northward, and the equatorward Ekman transport is enhanced in the Southern Ocean. The combination of local and dynamical processes decreases upper-ocean heat content in the Tropics and in the subpolar Southern Ocean, and increases it at middle latitudes. This study highlights the relevance of coupled ocean-atmosphere processes in the global climate response to phytoplankton solar absorption. Given that simulated impacts of phytoplankton on physical climate are within the range of natural climate variability, this study suggests the importance of phytoplankton as an internal constituent of the Earth's climate and its potential role in participating in its long-term climate adjustments. (orig.)

Overview of IMAGE 2.0. An integrated model of climate change and the global environment

International Nuclear Information System (INIS)

Alcamo, J.; Battjes, C.; Van den Born, G.J.; Bouwman, A.F.; De Haan, B.J.; Klein Goldewijk, K.; Klepper, O.; Kreileman, G.J.J.; Krol, M.; Leemans, R.; Van Minnen, J.G.; Olivier, J.G.J.; De Vries, H.J.M.; Toet, A.M.C.; Van den Wijngaart, R.A.; Van der Woerd, H.J.; Zuidema, G.

1995-01-01

The IMAGE 2.0 model is a multi-disciplinary, integrated model, designed to simulate the dynamics of the global society-biosphere-climate system. In this paper the focus is on the scientific aspects of the model, while another paper in this volume emphasizes its political aspects. The objectives of IMAGE 2.0 are to investigate linkages and feedbacks in the global system, and to evaluate consequences of climate policies. Dynamic calculations are performed to the year 2100, with a spatial scale ranging from grid (0.5x0.5 latitude-longitude) to world political regions, depending on the sub-model. A total of 13 sub-models make up IMAGE 2.0, and they are organized into three fully linked sub-systems: Energy-Industry, Terrestrial Environment, and Atmosphere-Ocean. The fully linked model has been tested against data from 1970 to 1990, and after calibration it can reproduce the following observed trends: regional energy consumption and energy-related emissions, terrestrial flux of carbon dioxide and emissions of greenhouse gases, concentrations of greenhouse gases in the atmosphere, and transformation of land cover. The model can also simulate current zonal average surface and vertical temperatures. 1 fig., 10 refs

Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

Science.gov (United States)

Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

2017-04-01

The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

California Wintertime Precipitation in Regional and Global Climate Models

Energy Technology Data Exchange (ETDEWEB)

Caldwell, P M

2009-04-27

In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

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

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Science.gov (United States)

Gosling, S. N.; Taylor, R. G.; Arnell, N. W.; Todd, M. C.

2011-01-01

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Directory of Open Access Journals (Sweden)

S. N. Gosling

2011-01-01

Full Text Available We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM and catchment-scale hydrological models (CHM. Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada, Mekong (SE Asia, Okavango (SW Africa, Rio Grande (Brazil, Xiangxi (China and Harper's Brook (UK. A single GHM (Mac-PDM.09 is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard, SLURP v. 12.7 (Mekong, Pitman (Okavango, MGB-IPH (Rio Grande, AV-SWAT-X 2005 (Xiangxi and Cat-PDM (Harper's Brook. The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5 and low (Q95 monthly runoff under baseline (1961–1990 and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1 prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM to explore response to different amounts of climate forcing, and (2 a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty.

We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%, and they are generally larger for indicators of high and low monthly runoff

Assessing Climate Change Impacts on Global Hydropower

Directory of Open Access Journals (Sweden)

Aanund Killingtveit

2012-02-01

Full Text Available Currently, hydropower accounts for close to 16% of the world’s total power supply and is the world’s most dominant (86% source of renewable electrical energy. The key resource for hydropower generation is runoff, which is dependent on precipitation. The future global climate is uncertain and thus poses some risk for the hydropower generation sector. The crucial question and challenge then is what will be the impact of climate change on global hydropower generation and what are the resulting regional variations in hydropower generation potential? This paper is a study that aims to evaluate the changes in global hydropower generation resulting from predicted changes in climate. The study uses an ensemble of simulations of regional patterns of changes in runoff, computed from global circulation models (GCM simulations with 12 different models. Based on these runoff changes, hydropower generation is estimated by relating the runoff changes to hydropower generation potential through geographical information system (GIS, based on 2005 hydropower generation. Hydropower data obtained from EIA (energy generation, national sites, FAO (water resources and UNEP were used in the analysis. The countries/states were used as computational units to reduce the complexities of the analysis. The results indicate that there are large variations of changes (increases/decreases in hydropower generation across regions and even within regions. Globally, hydropower generation is predicted to change very little by the year 2050 for the hydropower system in operation today. This change amounts to an increase of less than 1% of the current (2005 generation level although it is necessary to carry out basin level detailed assessment for local impacts which may differ from the country based values. There are many regions where runoff and hydropower generation will increase due to increasing precipitation, but also many regions where there will be a decrease. Based on this

Applying downscaled Global Climate Model data to a groundwater model of the Suwannee River Basin, Florida, USA

Science.gov (United States)

Swain, Eric D.; Davis, J. Hal

2016-01-01

The application of Global Climate Model (GCM) output to a hydrologic model allows for comparisons between simulated recent and future conditions and provides insight into the dynamics of hydrology as it may be affected by climate change. A previously developed numerical model of the Suwannee River Basin, Florida, USA, was modified and calibrated to represent transient conditions. A simulation of recent conditions was developed for the 372-month period 1970-2000 and was compared with a simulation of future conditions for a similar-length period 2039-2069, which uses downscaled GCM data. The MODFLOW groundwater-simulation code was used in both of these simulations, and two different MODFLOW boundary condition “packages” (River and Streamflow-Routing Packages) were used to represent interactions between surface-water and groundwater features.

Global spatiotemporal distribution of soil respiration modeled using a global database

Science.gov (United States)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to

An effective drift correction for dynamical downscaling of decadal global climate predictions

Science.gov (United States)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

Global warming and climate change

International Nuclear Information System (INIS)

1992-10-01

A panel discussion was held to discuss climate change. Six panelists made presentations that summarized ozone depletion and climate change, discussed global responses, argued against the conventional scientific and policy dogmas concerning climate change, examined the effects of ultraviolet radiation on phytoplankton, examined the effects of carbon taxes on Canadian industry and its emissions, and examined the political and strategic aspects of global warming. A question session followed the presentations. Separate abstracts have been prepared for the six presentations

Global climate change policies. An analysis of CDM policies with an adapted GTAP model

International Nuclear Information System (INIS)

Wang, Shunli

2004-01-01

In the context of the relationships between spatial-economic interaction and global warming just discussed, this study aims to analyze the Clean Development Mechanisms (CDM) policies from an economic point of view. The research question of this study is formulated as follows: What will be the impacts of clirnate change policies, in particular CDM policies, on the economic performance of (groups of) countries in our global economic system, taking spatial interaction and general equilibrium effects into account? The purpose of addressing the issue of economic performance for (groups of) countries in the economic system is not just to identify winners and losers from international treaties. Rather, winning or losing may even determine the implementation and willingness of individual countries to participate in international environmental treaties, as illustrated by the recent withdrawal of the US from the Kyoto Protocol. By analyzing the economic impacts of an international environmental treaty for individual (groups of) countries, the framework that will be used to analyze this research question may be useful to determine the attractiveness of some global environmental policies, both for the world as a whole and for individual (groups of) countries. The research question will be answered by dividing it into six subquestions: (1) What is the position of CDM policies in the broad context of climate policy regimes?; (2) How should the relationship between human behavior and the physical environment be ideally modeled from an economic perspective? (3) How should the spatial dimension be incorporated in this framework of interaction between the economic and ecological system?; (4) How can climate change issues be incorporated in general equilibrium models in general, and in GTAP-E (extension of the Global Trade Analysis Project) in particular?; (5) How can CDM policies be implemented in the GTAP-E model?; and (6) What are the impacts of these climate change policies on

Multi-Model Assessment of Global Hydropower and Cooling Water Discharge Potential Under Climate Change

Science.gov (United States)

van Vliet, M. T. H.; van Beek, L. P. H.; Eisener, S.; Wada, Y.; Bierkens, M. F. P.

2016-01-01

Worldwide, 98% of total electricity is currently produced by thermoelectric power and hydropower. Climate change is expected to directly impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power. Improved understanding of how climate change may impact the availability and temperature of water resources is therefore of major importance. Here we use a multi-model ensemble to show the potential impacts of climate change on global hydropower and cooling water discharge potential. For the first time, combined projections of streamflow and water temperature were produced with three global hydrological models (GHMs) to account for uncertainties in the structure and parametrization of these GHMs in both water availability and water temperature. The GHMs were forced with bias-corrected output of five general circulation models (GCMs) for both the lowest and highest representative concentration pathways (RCP2.6 and RCP8.5). The ensemble projections of streamflow and water temperature were then used to quantify impacts on gross hydropower potential and cooling water discharge capacity of rivers worldwide. We show that global gross hydropower potential is expected to increase between +2.4% (GCM-GHM ensemble mean for RCP 2.6) and +6.3% (RCP 8.5) for the 2080s compared to 1971-2000. The strongest increases in hydropower potential are expected for Central Africa, India, central Asia and the northern high-latitudes, with 18-33% of the world population living in these areas by the 2080s. Global mean cooling water discharge capacity is projected to decrease by 4.5-15% (2080s). The largest reductions are found for the United States, Europe, eastern Asia, and southern parts of South America, Africa and Australia, where strong water temperature increases are projected combined with reductions in mean annual streamflow. These regions are expected to affect 11-14% (for RCP2.6 and the shared socioeconomic

Climate Controls AM Fungal Distributions from Global to Local Scales

Science.gov (United States)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model.

Science.gov (United States)

Turner, Sean W D; Ng, Jia Yi; Galelli, Stefano

2017-07-15

An important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction of change in globally aggregated hydropower production (~-5 to +5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~5-20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~5-15%) without investing in new power generation facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

Global change of the climate

International Nuclear Information System (INIS)

Moharam-nejad, Naser.

1995-01-01

Greenhouse effect is defined. greenhouse gases which are capable to produce greenhouse effect is mentioned. The production of greenhouse effects depends on the following factors; The amount of discharge to the atmosphere, Concentration, Life span, stability, Absorption and Emission. The effect of global change of climate on agriculture and living organisms is discussed. Global actions related to climate change and national procedures are described. The aim of climate change convention is given and the important points of convention is also mentioned

Spatial scale separation in regional climate modelling

Energy Technology Data Exchange (ETDEWEB)

Feser, F.

2005-07-01

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

Effects of climate variability on global scale flood risk

Science.gov (United States)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

research. We carried out the research by simulating daily river discharge using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series. From this, we derived peak annual flood volumes for large-scale river basins globally. These were used to force a global inundation model (dynRout) to map inundation extent and depth for return periods between 2 and 1000 years, under El Niño conditions, neutral conditions, and La Niña conditions. Theses flood hazard maps were combined with global datasets on socioeconomic variables such as population and income to represent the socioeconomic exposure to flooding, and depth-damage curves to represent vulnerability.

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.

Simulating vegetation response to climate change in the Blue Mountains with MC2 dynamic global vegetation model

Directory of Open Access Journals (Sweden)

John B. Kim

2018-04-01

Full Text Available Warming temperatures are projected to greatly alter many forests in the Pacific Northwest. MC2 is a dynamic global vegetation model, a climate-aware, process-based, and gridded vegetation model. We calibrated and ran MC2 simulations for the Blue Mountains Ecoregion, Oregon, USA, at 30 arc-second spatial resolution. We calibrated MC2 using the best available spatial datasets from land managers. We ran future simulations using climate projections from four global circulation models (GCM under representative concentration pathway 8.5. Under this scenario, forest productivity is projected to increase as the growing season lengthens, and fire occurrence is projected to increase steeply throughout the century, with burned area peaking early- to mid-century. Subalpine forests are projected to disappear, and the coniferous forests to contract by 32.8%. Large portions of the dry and mesic forests are projected to convert to woodlands, unless precipitation were to increase. Low levels of change are projected for the Umatilla National Forest consistently across the four GCM’s. For the Wallowa-Whitman and the Malheur National Forest, forest conversions are projected to vary more across the four GCM-based simulations, reflecting high levels of uncertainty arising from climate. For simulations based on three of the four GCMs, sharply increased fire activity results in decreases in forest carbon stocks by the mid-century, and the fire activity catalyzes widespread biome shift across the study area. We document the full cycle of a structured approach to calibrating and running MC2 for transparency and to serve as a template for applications of MC2. Keywords: Climate change, Regional change, Simulation, Calibration, Forests, Fire, Dynamic global vegetation model

Climate impacts on hydropower and consequences for global electricity supply investment needs

Energy Technology Data Exchange (ETDEWEB)

Turner, Sean W. D.; Hejazi, Mohamad; Kim, Son H.; Clarke, Leon; Edmonds, Jae

2017-12-01

Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore the possible consequences of these impacts for the electricity supply sector. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model with downscaled, bias-corrected climate realizations derived from sixteen general circulation models. Consequent impacts on power sector composition and associated emissions and investment costs are explored using the Global Change Assessment Model (GCAM). Changes in hydropower generation resulting from climate change can shift power demands onto and away from carbon intensive technologies, resulting in significant impacts on power sector CO2 emissions for certain world regions—primarily those located in Latin America, as well as Canada and parts of Europe. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity—meaning impacts on power sector investment costs are similar for high and low emissions scenarios. Individual countries where impacts on investment costs imply significant risks or opportunities are identified.

The European climate under a 2 °C global warming

International Nuclear Information System (INIS)

Vautard, Robert; Stegehuis, Annemiek; Gobiet, Andreas; Mendlik, Thomas; Sobolowski, Stefan; Kjellström, Erik; Nikulin, Grigory; Watkiss, Paul; Landgren, Oskar; Teichmann, Claas; Jacob, Daniela

2014-01-01

A global warming of 2 °C relative to pre-industrial climate has been considered as a threshold which society should endeavor to remain below, in order to limit the dangerous effects of anthropogenic climate change. The possible changes in regional climate under this target level of global warming have so far not been investigated in detail. Using an ensemble of 15 regional climate simulations downscaling six transient global climate simulations, we identify the respective time periods corresponding to 2 °C global warming, describe the range of projected changes for the European climate for this level of global warming, and investigate the uncertainty across the multi-model ensemble. Robust changes in mean and extreme temperature, precipitation, winds and surface energy budgets are found based on the ensemble of simulations. The results indicate that most of Europe will experience higher warming than the global average. They also reveal strong distributional patterns across Europe, which will be important in subsequent impact assessments and adaptation responses in different countries and regions. For instance, a North–South (West–East) warming gradient is found for summer (winter) along with a general increase in heavy precipitation and summer extreme temperatures. Tying the ensemble analysis to time periods with a prescribed global temperature change rather than fixed time periods allows for the identification of more robust regional patterns of temperature changes due to removal of some of the uncertainty related to the global models’ climate sensitivity. (paper)

Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

Energy Technology Data Exchange (ETDEWEB)

Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

2010-06-15

We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

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

International Nuclear Information System (INIS)

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

2005-01-01

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

The role of natural climatic variation in perturbing the observed global mean temperature trend

Energy Technology Data Exchange (ETDEWEB)

Hunt, B.G. [CSIRO Marine and Atmospheric Research, Aspendale, VIC (Australia)

2011-02-15

Controversy continues to prevail concerning the reality of anthropogenically-induced climatic warming. One of the principal issues is the cause of the hiatus in the current global warming trend. There appears to be a widely held view that climatic change warming should exhibit an inexorable upwards trend, a view that implies there is no longer any input by climatic variability in the existing climatic system. The relative roles of climatic change and climatic variability are examined here using the same coupled global climatic model. For the former, the model is run using a specified CO{sub 2} growth scenario, while the latter consisted of a multi-millennial simulation where any climatic variability was attributable solely to internal processes within the climatic system. It is shown that internal climatic variability can produce global mean surface temperature anomalies of {+-}0.25 K and sustained positive and negative anomalies sufficient to account for the anomalous warming of the 1940s as well as the present hiatus in the observed global warming. The characteristics of the internally-induced negative temperature anomalies are such that if this internal natural variability is the cause of the observed hiatus, then a resumption of the observed global warming trend is to be expected within the next few years. (orig.)

Sources of global climate data and visualization portals

Science.gov (United States)

Douglas, David C.

2014-01-01

Climate is integral to the geophysical foundation upon which ecosystems are structured. Knowledge about mechanistic linkages between the geophysical and biological environments is essential for understanding how global warming may reshape contemporary ecosystems and ecosystem services. Numerous global data sources spanning several decades are available that document key geophysical metrics such as temperature and precipitation, and metrics of primary biological production such as vegetation phenology and ocean phytoplankton. This paper provides an internet directory to portals for visualizing or servers for downloading many of the more commonly used global datasets, as well as a description of how to write simple computer code to efficiently retrieve these data. The data are broadly useful for quantifying relationships between climate, habitat availability, and lower-trophic-level habitat quality - especially in Arctic regions where strong seasonality is accompanied by intrinsically high year-to-year variability. If defensible linkages between the geophysical (climate) and the biological environment can be established, general circulation model (GCM) projections of future climate conditions can be used to infer future biological responses. Robustness of this approach is, however, complicated by the number of direct, indirect, or interacting linkages involved. For example, response of a predator species to climate change will be influenced by the responses of its prey and competitors, and so forth throughout a trophic web. The complexities of ecological systems warrant sensible and parsimonious approaches for assessing and establishing the role of natural climate variability in order to substantiate inferences about the potential effects of global warming.

Global climate change: Social and economic research issues

International Nuclear Information System (INIS)

Rice, M.; Snow, J.; Jacobson, H.

1992-05-01

This workshop was designed to bring together a group of scholars, primarily from the social sciences, to explore research that might help in dealing with global climate change. To illustrate the state of present understanding, it seemed useful to focus this workshop on three broad questions that are involved in coping with climate change. These are: (1) How can the anticipated economic costs and benefits of climate change be identified; (2) How can the impacts of climate change be adjusted to or avoided; (3) What previously studied models are available for institutional management of the global environment? The resulting discussions may (1) identify worthwhile avenues for further social science research, (2) help develop feedback for natural scientists about research information from this domain needed by social scientists, and (3) provide policymakers with the sort of relevant research information from the social science community that is currently available

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.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

OpenAIRE

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynyck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.

2013-01-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. Th...

Northward shift of the agricultural climate zone under 21st-century global climate change.

Science.gov (United States)

King, Myron; Altdorff, Daniel; Li, Pengfei; Galagedara, Lakshman; Holden, Joseph; Unc, Adrian

2018-05-21

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21 st -century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions.

Global Climate Summaries

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Hourly Summaries are simple indicators of observational normals which include climatic data summarizations and frequency distributions. These typically...

Modelling the sequential geographical exploitation and potential collapse of marine fisheries through economic globalization, climate change and management alternatives

Directory of Open Access Journals (Sweden)

Gorka Merino

2011-07-01

Full Text Available Global marine fisheries production has reached a maximum and may even be declining. Underlying this trend is a well-understood sequence of development, overexploitation, depletion and in some instances collapse of individual fish stocks, a pattern that can sequentially link geographically distant populations. Ineffective governance, economic considerations and climate impacts are often responsible for this sequence, although the relative contribution of each factor is contentious. In this paper we use a global bioeconomic model to explore the synergistic effects of climate variability, economic pressures and management measures in causing or avoiding this sequence. The model shows how a combination of climate-induced variability in the underlying fish population production, particular patterns of demand for fish products and inadequate management is capable of driving the world’s fisheries into development, overexploitation, collapse and recovery phases consistent with observations. Furthermore, it demonstrates how a sequential pattern of overexploitation can emerge as an endogenous property of the interaction between regional environmental fluctuations and a globalized trade system. This situation is avoidable through adaptive management measures that ensure the sustainability of regional production systems in the face of increasing global environmental change and markets. It is concluded that global management measures are needed to ensure that global food supply from marine products is optimized while protecting long-term ecosystem services across the world’s oceans.

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.

Sensitivity of regional climate to global temperature and forcing

International Nuclear Information System (INIS)

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

2015-01-01

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

International Business and Global Climate Change

Energy Technology Data Exchange (ETDEWEB)

Kolk, A.; Pinkse, J.

2008-11-15

Climate change has become an important topic on the business agenda with strong pressure being placed on companies to respond and contribute to finding solutions to this urgent problem. This text provides a comprehensive analysis of international business responses to global climate change and climate change policy. Embedded in relevant management literature, this book gives a concise treatment of developments in policy and business activity on global, regional and national levels, using examples and systematic data from a large number of international companies. The first part outlines the international climate policy landscape and voluntary initiatives taken by companies, both alone and together with others. The second part examines companies' strategies, covering innovation for climate change, as well as compensation via emissions trading and carbon offsetting. Written by well-known experts in the field, International Business and Global Climate Change illustrates how an environmental topic becomes strategically important in a mainstream sense, affecting corporate decision-making, business processes, products, reputation, advertising, communication, accounting and finance.

International Business and Global Climate Change

International Nuclear Information System (INIS)

Kolk, A.; Pinkse, J.

2008-11-01

Climate change has become an important topic on the business agenda with strong pressure being placed on companies to respond and contribute to finding solutions to this urgent problem. This text provides a comprehensive analysis of international business responses to global climate change and climate change policy. Embedded in relevant management literature, this book gives a concise treatment of developments in policy and business activity on global, regional and national levels, using examples and systematic data from a large number of international companies. The first part outlines the international climate policy landscape and voluntary initiatives taken by companies, both alone and together with others. The second part examines companies' strategies, covering innovation for climate change, as well as compensation via emissions trading and carbon offsetting. Written by well-known experts in the field, International Business and Global Climate Change illustrates how an environmental topic becomes strategically important in a mainstream sense, affecting corporate decision-making, business processes, products, reputation, advertising, communication, accounting and finance

Emergence of long distance bird migrations: a new model integrating global climate changes

Science.gov (United States)

Louchart, Antoine

2008-12-01

During modern birds history, climatic and environmental conditions have evolved on wide scales. In a continuously changing world, landbirds annual migrations emerged and developed. However, models accounting for the origins of these avian migrations were formulated with static ecogeographic perspectives. Here I reviewed Cenozoic paleoclimatic and paleontological data relative to the palearctic paleotropical long distance (LD) migration system. This led to propose a new model for the origin of LD migrations, the ‘shifting home’ model (SHM). It is based on a dynamic perspective of climate evolution and may apply to the origins of most modern migrations. Non-migrant tropical African bird taxa were present at European latitudes during most of the Cenozoic. Their distribution limits shifted progressively toward modern tropical latitudes during periods of global cooling and increasing seasonality. In parallel, decreasing winter temperatures in the western Palearctic drove shifts of population winter ranges toward the equator. I propose that this induced the emergence of most short distance migrations, and in turn LD migrations. This model reconciliates ecologically tropical ancestry of most LD migrants with predominant winter range shifts, in accordance with requirements for heritable homing. In addition, it is more parsimonious than other non-exclusive models. Greater intrinsic plasticity of winter ranges implied by the SHM is supported by recently observed impacts of the present global warming on migrating birds. This may induce particular threats to some LD migrants. The ancestral, breeding homes of LD migrants were not ‘northern’ or ‘southern’ but shifted across high and middle latitudes while migrations emerged through winter range shifts themselves.

Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology

Science.gov (United States)

Shen, Mingxi; Chen, Jie; Zhuan, Meijia; Chen, Hua; Xu, Chong-Yu; Xiong, Lihua

2018-01-01

Uncertainty estimation of climate change impacts on hydrology has received much attention in the research community. The choice of a global climate model (GCM) is usually considered as the largest contributor to the uncertainty of climate change impacts. The temporal variation of GCM uncertainty needs to be investigated for making long-term decisions to deal with climate change. Accordingly, this study investigated the temporal variation (mainly long-term) of uncertainty related to the choice of a GCM in predicting climate change impacts on hydrology by using multi-GCMs over multiple continuous future periods. Specifically, twenty CMIP5 GCMs under RCP4.5 and RCP8.5 emission scenarios were adapted to adequately represent this uncertainty envelope, fifty-one 30-year future periods moving from 2021 to 2100 with 1-year interval were produced to express the temporal variation. Future climatic and hydrological regimes over all future periods were compared to those in the reference period (1971-2000) using a set of metrics, including mean and extremes. The periodicity of climatic and hydrological changes and their uncertainty were analyzed using wavelet analysis, while the trend was analyzed using Mann-Kendall trend test and regression analysis. The results showed that both future climate change (precipitation and temperature) and hydrological response predicted by the twenty GCMs were highly uncertain, and the uncertainty increased significantly over time. For example, the change of mean annual precipitation increased from 1.4% in 2021-2050 to 6.5% in 2071-2100 for RCP4.5 in terms of the median value of multi-models, but the projected uncertainty reached 21.7% in 2021-2050 and 25.1% in 2071-2100 for RCP4.5. The uncertainty under a high emission scenario (RCP8.5) was much larger than that under a relatively low emission scenario (RCP4.5). Almost all climatic and hydrological regimes and their uncertainty did not show significant periodicity at the P = .05 significance

Climate of Tajikistan in connection with global climate change

International Nuclear Information System (INIS)

Khakimov, F.Kh.; Mirzokhonova, S.O.; Mirzokhonava, N.A.

2006-01-01

The analysis of global climate change for different periods and its consequences on regional climate is given. The chronology of climate change in Tajikistan in various regions and the reasons leading or resulted to these changes are changes are shown as well

Characteristics of Extreme Extratropical Cyclones in a High-Resolution Global Climate Model

Science.gov (United States)

Catalano, A. J.; Broccoli, A. J.; Kapnick, S. B.; Janoski, T. P.

2017-12-01

In the northeastern United States, many of the strongest impacts from extratropical cyclones (ETCs) are associated with storms that exhibit slow movement, unusual tracks, or exceptional intensity. Examples of extreme ETCs include the Appalachian storm of November 1950, the Perfect Storm of October 1991, and the Superstorm of March 1993. Owing to the rare nature of these events, it is difficult to quantify the associated risks (e.g. high winds, storm surge) given the limited duration of high-quality observational datasets. Furthermore, storms with even greater impacts than those observed may be possible, particularly in a warming climate. In the context of tropical cyclones, Lin and Emanuel (2016) have used the metaphor "grey swans" to refer to high-impact events that have not been observed but may be physically possible. One method for analyzing "grey swans" is to generate a larger sample of ETCs using a coupled climate model. Therefore, we use long simulations (over 1,000 years with atmospheric constituents fixed at 1990 levels) from a global climate model (GFDL FLOR) with 50km atmospheric resolution. FLOR has been shown to realistically simulate the spatial distribution and climatology of ETCs during the reanalysis era. We will discuss the climatological features of these extreme ETC events.

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

Global climate change: Social and economic research issues

Energy Technology Data Exchange (ETDEWEB)

Rice, M.; Snow, J.; Jacobson, H. [eds.

1992-05-01

This workshop was designed to bring together a group of scholars, primarily from the social sciences, to explore research that might help in dealing with global climate change. To illustrate the state of present understanding, it seemed useful to focus this workshop on three broad questions that are involved in coping with climate change. These are: (1) How can the anticipated economic costs and benefits of climate change be identified; (2) How can the impacts of climate change be adjusted to or avoided; (3) What previously studied models are available for institutional management of the global environment? The resulting discussions may (1) identify worthwhile avenues for further social science research, (2) help develop feedback for natural scientists about research information from this domain needed by social scientists, and (3) provide policymakers with the sort of relevant research information from the social science community that is currently available. Individual papers are processed separately for the database.

Modeling the potential impacts of global climate change in ...

African Journals Online (AJOL)

One of the hottest issues in the recent environmental research worldwide has become the harmful effects of climate change on the ecosystems and environment due to global warming. Bangladesh is one of the most vulnerable countries not only in the South East Asia but also in the world. It is predicted that a large portion of ...

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."

Experts' workshop on critical issues in the science of global climate change. Proceedings

International Nuclear Information System (INIS)

1994-01-01

A summary is given of the International Petroleum Industry Environmental Conservation Association's Workshop on 'Critical issues in the science of global climate change' held in 1994. The topics of the panel sessions were (1) modelling global climate change: capabilities and limitations; (2)the physics and chemistry of greenhouse gas concentrations; (3) other factors in predicting climate change; and (4) ecosystem response. (UK)

A relationship between regional and global GCM surface air temperature changes and its application to an integrated model of climate change

International Nuclear Information System (INIS)

Jonas, M.; Ganopolski, A.V.; Krabec, J.; Olendrzyski, K.; Petoukhov, V.K.

1994-01-01

This study outlines the advantages of combining the Integrated Model to Assess the Greenhouse affect (IMAGE, an integrated quick turnaround, global model of climate change) with a spatially detailed General Circulation Model (GCM), in this case developed at the Max Planck Institute for Meteorology (MPI) in Hamburg. The outcome is a modified IMAGE model that simulates the MPI GCM projections of annual surface air temperature change globally and regionally. IMAGE thus provides policy analysts with integrated and regional information about global warming for a great range of policy-dependent greenhouse gas emission or concentration scenarios, while preserving its quick turnaround time. With the help of IMAGE various regional temperature response simulations have been produced. None of these simulations has yet been performed by any GCM. The simulations reflect the uncertainty range of a future warming. In this study the authors deal only with a simplified subsystem of such an integrated model of climate change, which begins with policy options, neglects the societal component in the greenhouse gas accounting tool, and ends with temperature change as the only output of the climate model. The model the authors employ is the Integrated Model to Assess the Greenhouse Effect (IMAGE, version 1.0), which was developed by the Netherlands National Institute of Public Health and Environmental Protection (RIVM). IMAGE is a scientifically based, parameterized simulation policy model designed to calculate the historical and future effects of greenhouse gases on global surface and surface air temperatures and sea-level rise

Climate change at the coast: from global to local

International Nuclear Information System (INIS)

Watkinson, A.R.

2009-01-01

The IPCC has recently documented substantial changes in the global heat content of the oceans, salinity, sea level, thermal expansion and biogeochemistry. Over the 21. century anticipated climate related changes include: a rise in sea level of up to 0.6 m or more; increases in sea surface temperatures up to 3 deg. C; an intensification of tropical and extra tropical cyclones; larger extreme waves and storm surges; altered precipitation/ run-off; and ocean acidification. The Tyndall Centre has been exploring how to down-scale the global analysis to the local level within the framework of a coastal simulator. The simulator provides information on possible future states of the coast through the 21. Century under a range of climate and socio-economic futures and shoreline management options. It links models within a nested framework, recognizing three scales: (1) global, (2) regional, and (3) local. The linked models describe a range of processes, including marine climate (waves, surges and mean sea level), sand bank morpho-dynamics, wave transformation, shoreline morpho-dynamics, built environment scenarios, ecosystem change, and erosion and flood risk. Analyses from the simulator reinforce conclusions from IPCC WG2: coasts will be exposed to increasing risks over coming decades due to many compounding climate-change factors; the impact of climate change on coasts will be exacerbated by increasing human induced pressures; the unavoidability of sea-level rise even in the longer-term frequently conflicts with present day human development patterns and trends. (author)

Integrated risk analysis of global climate change

International Nuclear Information System (INIS)

Shlyakhter, Alexander; Wilson, Richard; Valverde A, L.J. Jr.

1995-01-01

This paper discusses several factors that should be considered in integrated risk analyses of global climate change. We begin by describing how the problem of global climate change can be subdivided into largely independent parts that can be linked together in an analytically tractable fashion. Uncertainty plays a central role in integrated risk analyses of global climate change. Accordingly, we consider various aspects of uncertainty as they relate to the climate change problem. We also consider the impacts of these uncertainties on various risk management issues, such as sequential decision strategies, value of information, and problems of interregional and intergenerational equity. (author)

Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

Science.gov (United States)

Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

2017-12-01

At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

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.

Implications of global warming for the climate of African rainforests.

Science.gov (United States)

James, Rachel; Washington, Richard; Rowell, David P

2013-01-01

African rainforests are likely to be vulnerable to changes in temperature and precipitation, yet there has been relatively little research to suggest how the regional climate might respond to global warming. This study presents projections of temperature and precipitation indices of relevance to African rainforests, using global climate model experiments to identify local change as a function of global temperature increase. A multi-model ensemble and two perturbed physics ensembles are used, one with over 100 members. In the east of the Congo Basin, most models (92%) show a wet signal, whereas in west equatorial Africa, the majority (73%) project an increase in dry season water deficits. This drying is amplified as global temperature increases, and in over half of coupled models by greater than 3% per °C of global warming. Analysis of atmospheric dynamics in a subset of models suggests that this could be partly because of a rearrangement of zonal circulation, with enhanced convection in the Indian Ocean and anomalous subsidence over west equatorial Africa, the Atlantic Ocean and, in some seasons, the Amazon Basin. Further research to assess the plausibility of this and other mechanisms is important, given the potential implications of drying in these rainforest regions.

Global climate changes in the past and future

International Nuclear Information System (INIS)

Schoenwiese, C.D.

1993-01-01

Is man changing the climate of the Earth, and if so, is this at a global scale? This question with all its reunifications, usually referred to under the heading ''greenhouse effect'', deservedly stands in the focus of public attention. Besides fears and warnings reaching even to disaster scenarios there have recently also been sceptical voices pointing out the imponderabilities of filtering anthropogenic effects out of the climate data. This uncertainty is not surprising to the expert, as natural changes of climate always have, and will, superimpose anthropogenic influences. Therefore, it is not enough to peer into the future with the help of intricate climate models. Diagnostic analysis of the past climate is at least just as important. (orig.) [de

Simulating the effects of climate and agricultural management practices on global crop yield

Science.gov (United States)

Deryng, D.; Sacks, W. J.; Barford, C. C.; Ramankutty, N.

2011-06-01

Climate change is expected to significantly impact global food production, and it is important to understand the potential geographic distribution of yield losses and the means to alleviate them. This study presents a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) that integrates, in addition to climate, the effect of planting dates and cultivar choices, irrigation, and fertilizer application on crop yield for maize, soybean, and spring wheat. PEGASUS combines carbon dynamics for crops with a surface energy and soil water balance model. It also benefits from the recent development of a suite of global data sets and analyses that serve as model inputs or as calibration data. These include data on crop planting and harvesting dates, crop-specific irrigated areas, a global analysis of yield gaps, and harvested area and yield of major crops. Model results for present-day climate and farm management compare reasonably well with global data. Simulated planting and harvesting dates are within the range of crop calendar observations in more than 75% of the total crop-harvested areas. Correlation of simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop-harvested area, of 0.81 for maize, 0.66 for soybean, and 0.45 for spring wheat. We found that changes in temperature and precipitation as predicted by global climate models for the 2050s lead to a global yield reduction if planting and harvesting dates remain unchanged. However, adapting planting dates and cultivar choices increases yield in temperate regions and avoids 7-18% of global losses.

Global Climate Change as Environmental Megacrisis

OpenAIRE

Endter-Wada, Joanna; Ingram, Helen

2012-01-01

The authors analyze global climate change utilizing insights from the governance and crisis management literatures that seek to understand the prospects, nature, characteristics and the effects of cataclysmic events. They argue that global climate change is a mega-crisis hiding in plain sight yet there has been no proportionate mega-crisis response. People are still grappling with how to make sense of climate change, how to bridge multiple ways of knowing it, and how to negotiate collective c...

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

Science.gov (United States)

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage

Science.gov (United States)

Otto, C.; Schewe, J.; Frieler, K.

2015-12-01

Extreme climate events such as droughts, floods, or heat waves affect agricultural production in major cropping regions and therefore impact the world market prices of staple crops. In the last decade, crop prices exhibited two very prominent price peaks in 2007-2008 and 2010-2011, threatening food security especially for poorer countries that are net importers of grain. There is evidence that these spikes in grain prices were at least partly triggered by actual supply shortages and the expectation of bad harvests. However, the response of the market to supply shocks is nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and trade policies. Quantifying the contributions of such different factors to short-term price variability remains difficult, not least because many existing models ignore the role of storage which becomes important on short timescales. This in turn impedes the assessment of future climate change impacts on food prices. Here, we present a simple model of annual world grain prices that integrates grain stocks into the supply and demand functions. This firstly allows us to model explicitly the effect of storage strategies on world market price, and thus, for the first time, to quantify the potential contribution of trade policies to price variability in a simple global framework. Driven only by reported production and by long--term demand trends of the past ca. 40 years, the model reproduces observed variations in both the global storage volume and price of wheat. We demonstrate how recent price peaks can be reproduced by accounting for documented changes in storage strategies and trade policies, contrasting and complementing previous explanations based on different mechanisms such as speculation. Secondly, we show how the integration of storage allows long-term projections of grain price variability under climate change, based on existing crop yield scenarios.

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.

Modeling lakes and reservoirs in the climate system

Science.gov (United States)

MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

2009-01-01

Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

What about coal? Interactions between climate policies and the global steam coal market until 2030

International Nuclear Information System (INIS)

Haftendorn, C.; Kemfert, C.; Holz, F.

2012-01-01

Because of economic growth and a strong increase in global energy demand the demand for fossil fuels and therefore also greenhouse gas emissions are increasing, although climate policy should lead to the opposite effect. The coal market is of special relevance as coal is available in many countries and often the first choice to meet energy demand. In this paper we assess possible interactions between climate policies and the global steam coal market. Possible market adjustments between demand regions through market effects are investigated with a numerical model of the global steam coal market: the “COALMOD-World” model. This equilibrium model computes future trade flows, infrastructure investments and prices until 2030. We investigate three specific designs of climate policy: a unilateral European climate policy, an Indonesian export-limiting policy and a fast-roll out of carbon capture and storage (CCS) in the broader context of climate policy and market constraints. We find that market adjustment effects in the coal market can have significant positive and negative impacts on the effectiveness of climate policies. - Highlights: ► Interactions between climate policy and the global coal market until 2030 modeled. ► Analysis with the numerical model: “COALMOD-World”. ► Unilateral European climate policy partly compensated by market adjustment effects. ► A fast roll-out of CCS can lead to positive market adjustment effects. ► An export restricting supply-side policy generates virtuous market adjustments.

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

Science.gov (United States)

Mauritsen, T.; Roeckner, E.

2015-12-01

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

State of the Climate - Global Hazards

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The State of the Climate is a collection of periodic summaries recapping climate-related occurrences on both a global and national scale. The State of the Climate...

State of the Climate - Global Analysis

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The State of the Climate is a collection of periodic summaries recapping climate-related occurrences on both a global and national scale. The State of the Climate...

Determining the effect of key climate drivers on global hydropower production

Science.gov (United States)

Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.

2017-12-01

Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.

The response of terrestrial ecosystems to global climate change: Towards an integrated approach

International Nuclear Information System (INIS)

Rustad, Lindsey E.

2008-01-01

Accumulating evidence points to an anthropogenic 'fingerprint' on the global climate change that has occurred in the last century. Climate change has, and will continue to have, profound effects on the structure and function of terrestrial ecosystems. As such, there is a critical need to continue to develop a sound scientific basis for national and international policies regulating carbon sequestration and greenhouse gas emissions. This paper reflects on the nature of current global change experiments, and provides recommendations for a unified multidisciplinary approach to future research in this dynamic field. These recommendations include: (1) better integration between experiments and models, and amongst experimental, monitoring, and space-for-time studies; (2) stable and increased support for long-term studies and multi-factor experiments; (3) explicit inclusion of biodiversity, disturbance, and extreme events in experiments and models; (4) consideration of timing vs intensity of global change factors in experiments and models; (5) evaluation of potential thresholds or ecosystem 'tipping points'; and (6) increased support for model-model and model-experiment comparisons. These recommendations, which reflect discussions within the TERACC international network of global change scientists, will facilitate the unraveling of the complex direct and indirect effects of global climate change on terrestrial ecosystems and their components

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

OpenAIRE

Astitha, M.; Lelieveld, J.; Kader, M. Abdel; Pozzer, A.; de Meij, A.

2012-01-01

Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). One uses a global...

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.

Future aridity under conditions of global climate change

Science.gov (United States)

Asadi Zarch, Mohammad Amin; Sivakumar, Bellie; Malekinezhad, Hossein; Sharma, Ashish

2017-11-01

Global climate change is anticipated to cause some major changes in hydroclimatic conditions around the world. As aridity is a reliable indicator of potential available water, assessment of its changes under future climatic conditions is important for proper management of water. This study employs the UNESCO aridity/humidity index, which is a derivative of precipitation (P) and potential evapotranspiration (PET), for assessment of aridity. Historical (1901-2005) simulations and future (2006-2100) projections of 22 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are studied. The Nested Bias Correction (NBC) approach is used to correct possible biases of precipitation (simulated directly by the GCMs) and PET (estimated by applying FAO56-Penman-Monteith model on simulated parameters of the GCMs). To detect future aridity changes, the areal extents of the aridity zones in the past and future periods as well as through four sub-periods (2006-2025, 2026-2050, 2051-2075, and 2076-2100) of the future are compared. The results indicate that changes in climate will alter the areal extents of aridity zones in the future. In general, from the first sub-period towards the last one, the area covered by hyper-arid, arid, semi-arid, and sub-humid zones will increase (by 7.46%, 7.01%, 5.80%, and 2.78%, respectively), while the area of the humid regions will decrease (by 4.76%), suggesting that there will be less water over the global land area in the future. To understand the cause of these changes, precipitation and PET are also separately assumed to be stationary throughout the four future sub-periods and the resulting aridity changes are then analyzed. The results reveal that the aridity changes are mostly caused by the positive PET trends, even though the slight precipitation increase lessens the magnitude of the changes.

Life on a warmer earth: possible climatic consequences of man made global warming

Energy Technology Data Exchange (ETDEWEB)

Flohn, H

1981-01-01

The interaction between energy and climate is explored, including the impact on global climate of three main energy sources: solar, nuclear and fossil fuels. The global warming problem is introduced. Comprehensive analogies with warmer times are made. From the best models available, the future global average surface temperature is found and modified, describing the global warming effects caused by greenhouse effect caused by gases other than carbon dioxide, released into the atmosphere by man, i.e. nitrous oxide, methane, ammonia, and the chlorofluoromethanes. Paleoclimatic scenarios are reviewed, showing possible effects of global warming. An 800 to 1100 ppm CO/sub 2/ concentration causes irreversible Arctic melting, leading to displacement of present climatic zones by 400 to 800 km.

[The global climate: a sick patient

DEFF Research Database (Denmark)

Lidegaard, O.; Lidegaard, M.

2008-01-01

, and major climatic disasters, including health threats to millions of people, are probable if the CO2 emission increases further. Therefore, serious global initiatives should be taken now in order to prevent global over heating. Denmark should be at the forefront of these initiatives Udgivelsesdato: 2008/8/25......Over the last 100 years the human use of fossil fuel has increased the atmospheric CO2 content from 280 parts per million (ppm) to 380 ppm. This increase is expected to increase the global average temperature by a few degrees. The global climate is very sensitive to an increase in temperature...

Enhancing climate literacy through the use of an interdisciplinary global change framework and conceptual models

Science.gov (United States)

Bean, J. R.; Zoehfeld, K.; Mitchell, K.; Levine, J.; White, L. D.

2016-12-01

Understanding climate change and how to mitigate the causes and consequences of anthropogenic activities are essential components of the Next Generations Science Standards. To comprehend climate change today and why current rates and magnitudes of change are of concern, students must understand the various factors that drive Earth system processes and also how they interrelate. The Understanding Global Change web resource in development from the UC Museum of Paleontology will provide science educators with a conceptual framework, graphical models, lessons, and assessment templates for teaching NGSS aligned, interdisciplinary, climate change curricula. To facilitate students learning about the Earth as a dynamic, interacting system of ongoing processes, the Understanding Global Change site will provide explicit conceptual links for the causes of climate change (e.g., burning of fossil fuels, deforestation), Earth system processes (e.g., Earth's energy budget, water cycle), and the changes scientists measure in the Earth system (e.g., temperature, precipitation). The conceptual links among topics will be presented in a series of storyboards that visually represent relationships and feedbacks among components of the Earth system and will provide teachers with guides for implementing NGSS-aligned climate change instruction that addresses physical science, life sciences, Earth and space science, and engineering performance expectations. These visualization and instructional methods are used by teachers during professional development programs at UC Berkeley and the Smithsonian National Museum of Natural History and are being tested in San Francisco Bay Area classrooms.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

Science.gov (United States)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

2017-12-01

Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

Uncertainty and learning in a strategic environment. Global climate change

International Nuclear Information System (INIS)

Baker, Erin

2005-01-01

Global climate change is rife with uncertainties. Yet, we can expect to resolve much of this uncertainty in the next 100 years or so. Therefore, current actions should reflect the value of flexibility. Nevertheless, most models of climate change, particularly game-theoretic models, abstract from uncertainty. A model of the impacts of uncertainty and learning in a non-cooperative game shows that the level of correlation of damages across countries is crucial for determining optimal policy

The role of aerosols in cloud drop parameterizations and its applications in global climate models

Energy Technology Data Exchange (ETDEWEB)

Chuang, C.C.; Penner, J.E. [Lawrence Livermore National Lab., CA (United States)

1996-04-01

The characteristics of the cloud drop size distribution near cloud base are initially determined by aerosols that serve as cloud condensation nuclei and the updraft velocity. We have developed parameterizations relating cloud drop number concentration to aerosol number and sulfate mass concentrations and used them in a coupled global aerosol/general circulation model (GCM) to estimate the indirect aerosol forcing. The global aerosol model made use of our detailed emissions inventories for the amount of particulate matter from biomass burning sources and from fossil fuel sources as well as emissions inventories of the gas-phase anthropogenic SO{sub 2}. This work is aimed at validating the coupled model with the Atmospheric Radiation Measurement (ARM) Program measurements and assessing the possible magnitude of the aerosol-induced cloud effects on climate.

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.

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

Science.gov (United States)

John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

2016-01-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

Evaluation of skill at simulating heatwave and heat-humidity indices in Global and Regional Climate Models

Science.gov (United States)

Goldie, J. K.; Alexander, L. V.; Lewis, S. C.; Sherwood, S. C.

2017-12-01

A wide body of literature now establishes the harm of extreme heat on human health, and work is now emerging on the projection of future health impacts. However, heat-health relationships vary across different populations (Gasparrini et al. 2015), so accurate simulation of regional climate is an important component of joint health impact projection. Here, we evaluate the ability of nine Global Climate Models (GCMs) from CMIP5 and the NARCliM Regional Climate Model to reproduce a selection of 15 health-relevant heatwave and heat-humidity indices over the historical period (1990-2005) using the Perkins skill score (Perkins et al. 2007) in five Australian cities. We explore the reasons for poor model skill, comparing these modelled distributions to both weather station observations and gridded reanalysis data. Finally, we show changes in the modelled distributions from the highest-performing models under RCP4.5 and RCP8.5 greenhouse gas scenarios and discuss the implications of simulated heat stress for future climate change adaptation. ReferencesGasparrini, Antonio, Yuming Guo, Masahiro Hashizume, Eric Lavigne, Antonella Zanobetti, Joel Schwartz, Aurelio Tobias, et al. "Mortality Risk Attributable to High and Low Ambient Temperature: A Multicountry Observational Study." The Lancet 386, no. 9991 (July 31, 2015): 369-75. doi:10.1016/S0140-6736(14)62114-0. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney. "Evaluation of the AR4 Climate Models' Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions." Journal of Climate 20, no. 17 (September 1, 2007): 4356-76. doi:10.1175/JCLI4253.1.

Resolving the Aerosol Piece of the Global Climate Picture

Science.gov (United States)

Kahn, R. A.

2017-12-01

Factors affecting our ability to calculate climate forcing and estimate model predictive skill include direct radiative effects of aerosols and their indirect effects on clouds. Several decades of Earth-observing satellite observations have produced a global aerosol column-amount (AOD) record, but an aerosol microphysical property record required for climate and many air quality applications is lacking. Surface-based photometers offer qualitative aerosol-type classification, and several space-based instruments map aerosol air-mass types under favorable conditions. However, aerosol hygroscopicity, mass extinction efficiency (MEE), and quantitative light absorption, must be obtained from in situ measurements. Completing the aerosol piece of the climate picture requires three elements: (1) continuing global AOD and qualitative type mapping from space-based, multi-angle imagers and aerosol vertical distribution from near-source stereo imaging and downwind lidar, (2) systematic, quantitative in situ observations of particle properties unobtainable from space, and (3) continuing transport modeling to connect observations to sources, and extrapolate limited sampling in space and time. At present, the biggest challenges to producing the needed aerosol data record are: filling gaps in particle property observations, maintaining global observing capabilities, and putting the pieces together. Obtaining the PDFs of key particle properties, adequately sampled, is now the leading observational deficiency. One simplifying factor is that, for a given aerosol source and season, aerosol amounts often vary, but particle properties tend to be repeatable. SAM-CAAM (Systematic Aircraft Measurements to Characterize Aerosol Air Masses), a modest aircraft payload deployed frequently could fill this gap, adding value to the entire satellite data record, improving aerosol property assumptions in retrieval algorithms, and providing MEEs to translate between remote-sensing optical constraints

ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yuying [North Carolina State Univ., Raleigh, NC (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-05-01

It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model output and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP

Peak globalization. Climate change, oil depletion and global trade

Energy Technology Data Exchange (ETDEWEB)

Curtis, Fred [Department of Economics, Drew University, Madison, NJ 07940 (United States)

2009-12-15

The global trade in goods depends upon reliable, inexpensive transportation of freight along complex and long-distance supply chains. Global warming and peak oil undermine globalization by their effects on both transportation costs and the reliable movement of freight. Countering the current geographic pattern of comparative advantage with higher transportation costs, climate change and peak oil will thus result in peak globalization, after which the volume of exports will decline as measured by ton-miles of freight. Policies designed to mitigate climate change and peak oil are very unlikely to change this result due to their late implementation, contradictory effects and insufficient magnitude. The implication is that supply chains will become shorter for most products and that production of goods will be located closer to where they are consumed. (author)

Peak globalization. Climate change, oil depletion and global trade

International Nuclear Information System (INIS)

Curtis, Fred

2009-01-01

The global trade in goods depends upon reliable, inexpensive transportation of freight along complex and long-distance supply chains. Global warming and peak oil undermine globalization by their effects on both transportation costs and the reliable movement of freight. Countering the current geographic pattern of comparative advantage with higher transportation costs, climate change and peak oil will thus result in peak globalization, after which the volume of exports will decline as measured by ton-miles of freight. Policies designed to mitigate climate change and peak oil are very unlikely to change this result due to their late implementation, contradictory effects and insufficient magnitude. The implication is that supply chains will become shorter for most products and that production of goods will be located closer to where they are consumed. (author)

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.

Global and regional health effects of future food production under climate change: a modelling study.

Science.gov (United States)

Springmann, Marco; Mason-D'Croz, Daniel; Robinson, Sherman; Garnett, Tara; Godfray, H Charles J; Gollin, Douglas; Rayner, Mike; Ballon, Paola; Scarborough, Peter

2016-05-07

One of the most important consequences of climate change could be its effects on agriculture. Although much research has focused on questions of food security, less has been devoted to assessing the wider health impacts of future changes in agricultural production. In this modelling study, we estimate excess mortality attributable to agriculturally mediated changes in dietary and weight-related risk factors by cause of death for 155 world regions in the year 2050. For this modelling study, we linked a detailed agricultural modelling framework, the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT), to a comparative risk assessment of changes in fruit and vegetable consumption, red meat consumption, and bodyweight for deaths from coronary heart disease, stroke, cancer, and an aggregate of other causes. We calculated the change in the number of deaths attributable to climate-related changes in weight and diets for the combination of four emissions pathways (a high emissions pathway, two medium emissions pathways, and a low emissions pathway) and three socioeconomic pathways (sustainable development, middle of the road, and more fragmented development), which each included six scenarios with variable climatic inputs. The model projects that by 2050, climate change will lead to per-person reductions of 3·2% (SD 0·4%) in global food availability, 4·0% (0·7%) in fruit and vegetable consumption, and 0·7% (0·1%) in red meat consumption. These changes will be associated with 529,000 climate-related deaths worldwide (95% CI 314,000-736,000), representing a 28% (95% CI 26-33) reduction in the number of deaths that would be avoided because of changes in dietary and weight-related risk factors between 2010 and 2050. Twice as many climate-related deaths were associated with reductions in fruit and vegetable consumption than with climate-related increases in the prevalence of underweight, and most climate-related deaths were projected to

How Will Climate Change Affect Globalization?

DEFF Research Database (Denmark)

Dilyard, John Raymond; Bals, Lydia; Zhuplev, Anatoly

2011-01-01

, it will effect globalization. Businesses, if they want to be sustained, will have to adjust to climate change. This panel will examine two topics within which the relationship between climate change and globalization can be assessed - the sourcing of resources and services when the location of those resources...... is subject to change and the nature of competition in agriculture-based business, focusing on wine....

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

Science.gov (United States)

Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-01-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model.

Science.gov (United States)

Betts, Richard A; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J; Tsanis, Ioannis; Wyser, Klaus

2018-05-13

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

Science.gov (United States)

Betts, Richard A.; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-05-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme

Climate change impacts on soil carbon storage in global croplands: 1901-2010

Science.gov (United States)

Ren, W.; Tian, H.

2015-12-01

New global data finds 12% of earth's surface in cropland at present. Croplands will take on the responsibility to support approximate 60% increase in food production by 2050 as FAO estimates. In addition to nutrient supply to plants, cropland soils also play a major source and sink of greenhouse gases regulating global climate system. It is a big challenge to understand how soils function under global changes, but it is also a great opportunity for agricultural sector to manage soils to assure sustainability of agroecosystems and mitigate climate change. Previous studies have attempted to investigate the impacts of different land uses and climates on cropland soil carbon storage. However, large uncertainty still exists in magnitude and spatiotemporal patterns of global cropland soil organic carbon, due to the lack of reliable environmental databases and relatively poorly understanding of multiple controlling factors involved climate change and land use etc. Here, we use a process-based agroecosystem model (DLEM-Ag) in combination with diverse data sources to quantify magnitude and tempo-spatial patterns of soil carbon storage in global croplands during 1901-2010. We also analyze the relative contributions of major environmental variables (climate change, land use and management etc.). Our results indicate that intensive land use management may hidden the vulnerability of cropland soils to climate change in some regions, which may greatly weaken soil carbon sequestration under future climate change.

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

Science.gov (United States)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

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

Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

Science.gov (United States)

Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

2014-05-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) lacked the sufficient representation of permafrost physics in their land surface schemes. In order to assess the response of permafrost to projected climate change for the 21st century, the land surface scheme of the Max-Planck-Institute for Meteorology, JSBACH, has recently been equipped with the important physical processes for permafrost studies, and was driven globally with bias corrected climate data, thereby spanning a period from 1850 until 2100. The applied land surface scheme JSBACH now considers the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. To address the uncertainty range arising through different greenhouse gas concentrations as well as through different climate realisations when using various climate models, combinations of two Representative Concentration Pathways (RCPs) and two GCMs were used as driving data. In order to focus only on the climatic impact on permafrost, effects due to feedbacks between climate and permafrost (namely via carbon fluxes between land and atmosphere) are excluded in the experiments

European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

Science.gov (United States)

Haylock, M. R.

2011-10-01

Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961-2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed. The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

Directory of Open Access Journals (Sweden)

M. R. Haylock

2011-10-01

Full Text Available Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961–2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed.

The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

Science.gov (United States)

Beach, Robert H.; Cai, Yongxia; Thomson, Allison; Zhang, Xuesong; Jones, Russell; McCarl, Bruce A.; Crimmins, Allison; Martinich, Jeremy; Cole, Jefferson; Ohrel, Sara; DeAngelo, Benjamin; McFarland, James; Strzepek, Kenneth; Boehlert, Brent

2015-09-01

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from 32.7 billion to 54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

Energy Technology Data Exchange (ETDEWEB)

Beach, Robert H.; Cai, Yongxia; Thomson, Allison; Zhang, Xuesong; Jones, Russell; McCarl, Bruce A.; Crimmins, Allison; Martinich, Jeremy; Cole, Jefferson; Ohrel, Sara; DeAngelo, Benjamin; McFarland, James; Strzepek, Kenneth; Boehlert, Brent

2015-09-01

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from $32.7 billion to $54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.

Emergent constraint on equilibrium climate sensitivity from global temperature variability

Science.gov (United States)

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

2018-01-01

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

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

Science.gov (United States)

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

2018-01-17

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

A globally integrated climate policy for Canada

International Nuclear Information System (INIS)

Bernstein, S.; Brunnee, J.; Duff, D.G.; Green, A.J.

2008-01-01

This book explored policy ideas and options from various perspectives, including science, law, political science, economics and sociology. The costs, opportunities and imperatives to participate in international diplomatic initiatives were considered along with the opportunities of regional global carbon markets. Canada's current policy on climate change negotiations have been focused on domestic regulation and incentives for technological responses and the setting of a domestic carbon price. The sense of urgency about global warming was discussed and the need for action to respond to the threat of global climate change was emphasized. The book also reviewed Canada's role in international climate policies and presented parameters and imperatives for global regime building in Canada. Domestic policy tools were also reviewed along with policy obstacles and opportunities. refs., tabs., figs.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

Science.gov (United States)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

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.

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.

The tundra - a threat to global climate?

International Nuclear Information System (INIS)

Roejle Christensen, T.

1997-01-01

The tundra biome has an important direct influence on the global climate through its exchange of radiatively active 'greenhouse gases', carbon dioxide and methane. A number of suggestions have been raised as to how a changing climate may alter the natural state of this exchange causing significant feedback effects in a changing climate. This paper provides a brief discussion of three different issues relating to the interaction between tundra and climate. It is concluded that release of methane hydrates, permafrost degradation and major biome changes are processes which in the long term may have important effects on further development of the global climate. (au) 32 refs

Global Climate Exchange: Peer collaboration in a “Global classroom”

OpenAIRE

Korsager, Majken; Jorde, Doris; Slotta, Jim

2014-01-01

This paper reports on student peer collaboration in an online environment in an international shared curriculum, the Global Climate Exchange. Four cohorts of students (age 16 -19) from Canada, China, Norway and Sweden (n=157) were engaged in four wiki-based activities where they collaborated with peers locally and internationally. Previously, impact from Global Climate Exchange on students’ conceptual understanding was analysed, indicating a positive impact which might be explained by the amo...

Climate Change and Global Wine Quality

Energy Technology Data Exchange (ETDEWEB)

Jones, G.V. [Department of Geography, Southern Oregon University, 1250 Siskiyou Blvd, Ashland, Oregon, 97520 (United States); White, M.A. [Department of Aquatic, Watershed, and Earth Resources, Utah State University, Logan, Utah, 84322 (United States); Cooper, O.R. [Cooperative Institute for Research in Environmental Sciences CIRES, University of Colorado/NOAA Aeronomy Laboratory, Boulder, Colorado, 80305 (United States); Storchmann, K. [Department of Economics, Yale University, New Haven, Connecticut, 06520 (United States)

2005-12-01

From 1950 to 1999 the majority of the world's highest quality wine-producing regions experienced growing season warming trends. Vintage quality ratings during this same time period increased significantly while year-to-year variation declined. While improved winemaking knowledge and husbandry practices contributed to the better vintages it was shown that climate had, and will likely always have, a significant role in quality variations. This study revealed that the impacts of climate change are not likely to be uniform across all varieties and regions. Currently, many European regions appear to be at or near their optimum growing season temperatures, while the relationships are less defined in the New World viticulture regions. For future climates, model output for global wine producing regions predicts an average warming of 2C in the next 50 yr. For regions producing high-quality grapes at the margins of their climatic limits, these results suggest that future climate change will exceed a climatic threshold such that the ripening of balanced fruit required for existing varieties and wine styles will become progressively more difficult. In other regions, historical and predicted climate changes could push some regions into more optimal climatic regimes for the production of current varietals. In addition, the warmer conditions could lead to more poleward locations potentially becoming more conducive to grape growing and wine production.

Benchmark Comparison of Dual- and Quad-Core Processor Linux Clusters with Two Global Climate Modeling Workloads

Science.gov (United States)

McGalliard, James

2008-01-01

This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.

Scientist's Perceptions of Uncertainty During Discussions of Global Climate

Science.gov (United States)

Romanello, S.; Fortner, R.; Dervin, B.

2003-04-01

This research examines the nature of disagreements between natural and social scientists during discussions of global climate change. In particular, it explores whether the disagreements between natural and social scientists are related to the ontological, epistemological, or methodological nature of the uncertainty of global climate change during these discussions. A purposeful sample of 30 natural and social scientists recognized as experts in global climate change by the United States Global Change Research Program (USGCRP) and National Academies Committee on Global Change were interviewed to elicit their perceptions of disagreements during their three most troublesome discussions on global climate change. A mixed-method (qualitative plus quantitative research) approach with three independent variables was used to explore nature of uncertainty as a mediating variable in the relationships between academic training, level of sureness, level of knowledge, and position on global climate change, and the nature of disagreements and bridging strategies of natural and social scientists (Patton, 1997; Frechtling et al., 1997). This dissertation posits that it is the differences in the nature of uncertainty communicated by natural and social scientists and not sureness, knowledge, and position on global climate change that causes disagreements between the groups. By describing the nature of disagreements between natural and social scientists and illuminating bridging techniques scientists use during these disagreements, it is hoped that information collected from this research will create a better dialogue between the scientists studying global climate change by providing communication strategies which will allow those versed in one particular area to speak to non-experts whether they be other scientists, media officials, or the public. These tangible strategies can then be used by government agencies to create better communications and education plans, which can

Global Air Quality and Climate

Science.gov (United States)

Fiore, Arlene M.; Naik, Vaishali; Steiner, Allison; Unger, Nadine; Bergmann, Dan; Prather, Michael; Righi, Mattia; Rumbold, Steven T.; Shindell, Drew T.; Skeie, Ragnhild B.;

Strategic Global Climate Command?

Science.gov (United States)

Long, J. C. S.

2016-12-01

Researchers have been exploring geoengineering because Anthropogenic GHG emissions could drive the globe towards unihabitability for people, wildlife and vegetation. Potential global deployment of these technologies is inherently strategic. For example, solar radiation management to reflect more sunlight might be strategically useful during a period of time where the population completes an effort to cease emissions and carbon removal technologies might then be strategically deployed to move the atmospheric concentrations back to a safer level. Consequently, deployment of these global technologies requires the ability to think and act strategically on the part of the planet's governments. Such capacity most definitely does not exist today but it behooves scientists and engineers to be involved in thinking through how global command might develop because the way they do the research could support the development of a capacity to deploy intervention rationally -- or irrationally. Internationalizing research would get countries used to working together. Organizing the research in a step-wise manner where at each step scientists become skilled at explaining what they have learned, the quality of the information they have, what they don't know and what more they can do to reduce or handle uncertainty, etc. Such a process can increase societal confidence in being able to make wise decisions about deployment. Global capacity will also be enhanced if the sceintific establishment reinvents misssion driven research so that the programs will identify the systemic issues invovled in any proposed technology and systematically address them with research while still encouraging individual creativity. Geoengineering will diverge from climate science in that geoengineering research needs to design interventions for some publically desirable goal and investigates whether a proposed intervention will acheive desired outcomes. The effort must be a systems-engineering design problem

NASA/JPL CLIMATE DAY: Middle and High School Students Get the Facts about Global Climate Change

Science.gov (United States)

Richardson, Annie; Callery, Susan; Srinivasan, Margaret

2013-04-01

In 2007, NASA Headquarters requested that Earth Science outreach teams brainstorm new education and public outreach activities that would focus on the topic of global climate change. At the Jet Propulsion Laboratory (JPL), Annie Richardson, outreach lead for the Ocean Surface Topography missions came up with the idea of a "Climate Day", capitalizing on the popular Earth Day name and events held annually throughout the world. JPL Climate Day would be an education and public outreach event whose objectives are to provide the latest scientific facts about global climate change - including the role the ocean plays in it, the contributions that NASA/JPL satellites and scientists make to the body of knowledge on the topic, and what we as individuals can do to promote global sustainability. The primary goal is that participants get this information in a fun and exciting environment, and walk away feeling empowered and capable of confidently engaging in the global climate debate. In March 2008, JPL and its partners held the first Climate Day event. 950 students from seven school districts heard from five scientists; visited exhibits, and participated in hands-on-activities. Pleased with the outcome, we organized JPL Climate Day 2010 at the Pasadena Convention Center in Pasadena, California, reaching more than 1700 students, teachers, and members of the general public over two days. Taking note of this successful model, NASA funded a multi-center, NASA Climate Day proposal in 2010 to expand Climate Day nation-wide. The NASA Climate Day proposal is a three-pronged project consisting of a cadre of Earth Ambassadors selected from among NASA-affiliated informal educators; a "Climate Day Kit" consisting of climate-related electronic resources available to the Earth Ambassadors; and NASA Climate Day events to be held in Earth Ambassador communities across the United States. NASA/JPL continues to host the original Climate Day event and in 2012 held its 4th event, at the Pasadena

Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

Science.gov (United States)

Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

2001-12-01

A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations

Reconciling uncertainties in integrated science and policy models: Applications to global climate change

Energy Technology Data Exchange (ETDEWEB)

Kandlikar, Milind [Carnegie Mellon Univ., Pittsburgh, PA (United States)

1994-12-01

In this thesis tools of data reconciliation are used to integrate available information into scientific and policy models of greenhouse gases. The role of uncertainties in scientific and policy models of global climate change is examined, and implications for global change policy are drawn. Methane is the second most important greenhouse gas. Global sources and sinks of methane have significant uncertainties. A chance constrained methodology was developed and used to perform inversions on the global methane cycle. Budgets of methane that are consistent with source fluxes, isotopic and ice core measurements were determined. While it is not possible to come up with a single budget for CH{sub 4}, performing the calculation with a number of sets of assumed priors suggests a convergence in the allowed range for sources. In some cases -- wetlands (70-130 Tg/yr), rice paddies (60-125 Tg/yr) a significant reduction in the uncertainty of the source estimate is achieved. Our results compare favorably with the most recent measurements of flux estimates. For comparison, a similar analysis using bayes monte carlo simulation was performed. The question of the missing sink for carbon remains unresolved. Two analyses that attempt to quantify the missing sink were performed. First, a steady state analysis of the carbon cycle was used to determine the pre-industrial inter-hemispheric carbon concentration gradient. Second, a full blown dynamic inversion of the carbon cycle was performed. An advection diffusion ocean model with surface chemistry, coupled to box models of the atmosphere and the biosphere was inverted to fit available measurements of {sup 12}C and {sup 14}C carbon isotopes using Differential-Algebraic Optimization. The model effectively suggests that the {open_quotes}missing{close_quotes} sink for carbon is hiding in the biosphere. Scenario dependent trace gas indices were calculated for CH{sub 4}, N{sub 2}O, HCFC-22.

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

Science.gov (United States)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

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)

Global climate change: Implications, challenges, and mitigation measures

International Nuclear Information System (INIS)

Majumdar, S.K.

1992-01-01

This book presents a perspective of the potential problem of global climate change induced by human activity. The editors have presented viewpoints of experts (advocates and skeptics) representing the issues of climate change. Possible results from long-term global change discussed in this book include mass migrations of plants and animals; changes in crop yields; flood and drought; and economic, political, and cultural changes. The text contains 20 chapters on the impact of global climate change and 10 chapters on the mitigation of effects and policy development

Snowball Earth: Asynchronous coupling of sea-glacier flow with a global climate model

Science.gov (United States)

Pollard, D.; Kasting, J. F.; Zugger, M. E.

2017-05-01

During Snowball Earth episodes of the Neoproterozoic and Paleoproterozoic, limited amounts of tropical open ocean (Jormungand), or tropical ocean with thin ice cover, would help to explain (1) vigorous glacial activity in low latitudes, (2) survival of photosynthetic life, and (3) deglacial recovery without excessive buildup of atmospheric CO2. Some previous models have suggested that tropical open ocean or thin-ice cover is possible; however, its viability in the presence of kilometer-thick sea glaciers flowing from higher latitudes has not been demonstrated conclusively. Here we describe a new method of asynchronously coupling a zonal sea-glacier model with a 3-D global climate model and apply it to Snowball Earth. Equilibrium curves of ice line versus CO2 are mapped out, as well as their dependence on ocean heat transport efficiency, sea-glacier flow, and other model parameters. No climate states with limited tropical open ocean or thin ice are found in any of our model runs, including those with sea glaciers. If this result is correct, then other refugia such as cryoconite pans would have been required for life to survive. However, the reasons for the differences between our results and others should first be resolved. It is suggested that small-scale convective dynamics, affecting fractional snow cover in low latitudes, may be a critical factor accounting for these differences.

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

Energy Technology Data Exchange (ETDEWEB)

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

1995-04-01

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

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

Science.gov (United States)

Wang, Guiling

2005-12-01

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

Global climate change and California's water resources

International Nuclear Information System (INIS)

Vaux, H.J. Jr.

1991-01-01

This chapter records the deliberations of a group of California water experts about answers to these and other questions related to the impact of global warming on California's water resources. For the most part, those participating in the deliberations believe that the current state of scientific knowledge about global warming and its impacts on water resources is insufficient to permit hard distinctions to be made between short- and long-term changes. consequently, the ideas discussed here are based on a number of assumptions about specific climatic manifestations of global warming in California, as described earlier in this volume. Ultimately, however, effective public responses to forestall the potentially costly impacts of global climate change will probably depend upon the credible validation of the prospects of global climate warming. This chapter contains several sections. First, the likely effects of global warming on California's water resources and water-supply systems are identified and analyzed. Second, possible responses to mitigate these effects are enumerated and discussed. Third, the major policy issues are identified. A final section lists recommendations for action and major needs for information

Global mortality consequences of climate change accounting for adaptation costs and benefits

Science.gov (United States)

Rising, J. A.; Jina, A.; Carleton, T.; Hsiang, S. M.; Greenstone, M.

2017-12-01

Empirically-based and plausibly causal estimates of the damages of climate change are greatly needed to inform rapidly developing global and local climate policies. To accurately reflect the costs of climate change, it is essential to estimate how much populations will adapt to a changing climate, yet adaptation remains one of the least understood aspects of social responses to climate. In this paper, we develop and implement a novel methodology to estimate climate impacts on mortality rates. We assemble comprehensive sub-national panel data in 41 countries that account for 56% of the world's population, and combine them with high resolution daily climate data to flexibly estimate the causal effect of temperature on mortality. We find the impacts of temperature on mortality have a U-shaped response; both hot days and cold days cause excess mortality. However, this average response obscures substantial heterogeneity, as populations are differentially adapted to extreme temperatures. Our empirical model allows us to extrapolate response functions across the entire globe, as well as across time, using a range of economic, population, and climate change scenarios. We also develop a methodology to capture not only the benefits of adaptation, but also its costs. We combine these innovations to produce the first causal, micro-founded, global, empirically-derived climate damage function for human health. We project that by 2100, business-as-usual climate change is likely to incur mortality-only costs that amount to approximately 5% of global GDP for 5°C degrees of warming above pre-industrial levels. On average across model runs, we estimate that the upper bound on adaptation costs amounts to 55% of the total damages.

Climate variability and change scenarios for a marine commodity: Modelling small pelagic fish, fisheries and fishmeal in a globalized market

Science.gov (United States)

Merino, Gorka; Barange, Manuel; Mullon, Christian

2010-04-01

The world's small pelagic fish populations, their fisheries, fishmeal and fish oil production industries and markets are part of a globalised production and consumption system. The potential for climate variability and change to alter the balance in this system is explored by means of bioeconomic models at two different temporal scales, with the objective of investigating the interactive nature of environmental and human-induced changes on this globalised system. Short-term (interannual) environmental impacts on fishmeal production are considered by including an annual variable production rate on individual small pelagic fish stocks over a 10-year simulation period. These impacts on the resources are perceived by the fishmeal markets, where they are confronted by two aquaculture expansion hypotheses. Long-term (2080) environmental impacts on the same stocks are estimated using long-term primary production predictions as proxies for the species' carrying capacities, rather than using variable production rates, and are confronted on the market side by two alternative fishmeal management scenarios consistent with IPCC-type storylines. The two scenarios, World Markets and Global Commons, are parameterized through classic equilibrium solutions for a global surplus production bioeconomic model, namely maximum sustainable yield and open access, respectively. The fisheries explicitly modelled in this paper represent 70% of total fishmeal production, thus encapsulating the expected dynamics of the global production and consumption system. Both short and long-term simulations suggest that the sustainability of the small pelagic resources, in the face of climate variability and change, depends more on how society responds to climate impacts than on the magnitude of climate alterations per se.

Maize production in terms of global climate changes

Directory of Open Access Journals (Sweden)

Bekavac Goran

2010-01-01

Full Text Available Climate changes and expected variability of climatic parameters represent a serious concern of the 21st century agriculture. At the global level, the further rise in temperature, changed quantity and distribution of precipitation, increased variability of climate parameters and the occurrence of extreme climate events are expected. In order to avoid, or at least reduce the negative effects of global climate change, several adaptation strategies are proposed. Adjustment of production technology and breeding for tolerance to changed environment are proposed as two most important adaptation measures.

A hydroclimatic model of global fire patterns

Science.gov (United States)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F

Global warming precipitation accumulation increases above the current-climate cutoff scale.

Science.gov (United States)

Neelin, J David; Sahany, Sandeep; Stechmann, Samuel N; Bernstein, Diana N

2017-02-07

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

Global warming precipitation accumulation increases above the current-climate cutoff scale

Science.gov (United States)

Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

2017-01-01

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff. PMID:28115693

Governing Global Climate Change: Past Achievements, Future Prospects

Directory of Open Access Journals (Sweden)

Ella Kokotsis

2014-11-01

Full Text Available The cumulative effects of a significantly changing climate are projected to have disastrous implications on the world’s natural habitats, and along with that, are projected to drastically increase the rate and likelihood of violent conflict globally, particularly in high-density, urban, poverty hotspots. Limiting the effects of a changing climate is thus critical in influencing multiple societal goals including equitable sustainable development, human health, biodiversity, food security and access to reliable energy sources. This paper argues that the G7/8 has led global climate governance in ways other international environmental institu­tions have largely failed to do. It has done so largely by placing climate protection at the forefront of its policy objectives, alongside economic, health, energy and security goals, and reaching consensus repeatedly amongst its leaders on the impor­tance of stabilizing emissions through energy efficiency, conservation, investment and technological innovation. Moreover, this chapter argues that the summit’s predominant capability, its constricted participation, democratic convergence and political cohesion – as well as the combined effects of global shocks – have all had positive impacts on the G7/8’s success in mitigating climate change. Following a detailed process-tracing exercise over the summit’s 40-year history in which clear surges and retreats on global climate governance are outlined, this paper concludes by assessing the G7/8’s accountability record on climate mitigation and outlines a set of prescriptive recommendations, allowing for the delivery of a more tangible, coherent, results-driven accountability process for global climate governance.

Geophysical Global Modeling for Extreme Crop Production Using Photosynthesis Models Coupled to Ocean SST Dipoles

Science.gov (United States)

Kaneko, D.

2016-12-01

Climate change appears to have manifested itself along with abnormal meteorological disasters. Instability caused by drought and flood disasters is producing poor harvests because of poor photosynthesis and pollination. Fluctuations of extreme phenomena are increasing rapidly because amplitudes of change are much greater than average trends. A fundamental cause of these phenomena derives from increased stored energy inside ocean waters. Geophysical and biochemical modeling of crop production can elucidate complex mechanisms under seasonal climate anomalies. The models have progressed through their combination with global climate reanalysis, environmental satellite data, and harvest data on the ground. This study examined adaptation of crop production to advancing abnormal phenomena related to global climate change. Global environmental surface conditions, i.e., vegetation, surface air temperature, and sea surface temperature observed by satellites, enable global modeling of crop production and monitoring. Basic streams of the concepts of modeling rely upon continental energy flow and carbon circulation among crop vegetation, land surface atmosphere combining energy advection from ocean surface anomalies. Global environmental surface conditions, e.g., vegetation, surface air temperature, and sea surface temperature observed by satellites, enable global modeling of crop production and monitoring. The method of validating the modeling relies upon carbon partitioning in biomass and grains through carbon flow by photosynthesis using carbon dioxide unit in photosynthesis. Results of computations done for this study show global distributions of actual evaporation, stomata opening, and photosynthesis, presenting mechanisms related to advection effects from SST anomalies in the Pacific, Atlantic, and Indian oceans on global and continental croplands. For North America, climate effects appear clearly in severe atmospheric phenomena, which have caused drought and forest fires

Toward 10-km mesh global climate simulations

Science.gov (United States)

Ohfuchi, W.; Enomoto, T.; Takaya, K.; Yoshioka, M. K.

2002-12-01

An atmospheric general circulation model (AGCM) that runs very efficiently on the Earth Simulator (ES) was developed. The ES is a gigantic vector-parallel computer with the peak performance of 40 Tflops. The AGCM, named AFES (AGCM for ES), was based on the version 5.4.02 of an AGCM developed jointly by the Center for Climate System Research, the University of Tokyo and the Japanese National Institute for Environmental Sciences. The AFES was, however, totally rewritten in FORTRAN90 and MPI while the original AGCM was written in FORTRAN77 and not capable of parallel computing. The AFES achieved 26 Tflops (about 65 % of the peak performance of the ES) at resolution of T1279L96 (10-km horizontal resolution and 500-m vertical resolution in middle troposphere to lower stratosphere). Some results of 10- to 20-day global simulations will be presented. At this moment, only short-term simulations are possible due to data storage limitation. As ten tera flops computing is achieved, peta byte data storage are necessary to conduct climate-type simulations at this super-high resolution global simulations. Some possibilities for future research topics in global super-high resolution climate simulations will be discussed. Some target topics are mesoscale structures and self-organization of the Baiu-Meiyu front over Japan, cyclogenecsis over the North Pacific and typhoons around the Japan area. Also improvement in local precipitation with increasing horizontal resolution will be demonstrated.

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

Global climate evolution during the last deglaciation

OpenAIRE

Clark, Peter U.; Shakun, Jeremy D.; Baker, Paul A.; Bartlein, Patrick J.; Brewer, Simon; Brook, Ed; Carlson, Anders E.; Cheng, Hai; Kaufman, Darrell S.; Liu, Zhengyu; Marchitto, Thomas M.; Mix, Alan C.; Morrill, Carrie; Otto-Bliesner, Bette L.; Pahnke, Katharina

2012-01-01

Deciphering the evolution of global climate from the end of the Last Glacial Maximum approximately 19 ka to the early Holocene 11 ka presents an outstanding opportunity for understanding the transient response of Earth’s climate system to external and internal forcings. During this interval of global warming, the decay of ice sheets caused global mean sea level to rise by approximately 80 m; terrestrial and marine ecosystems experienced large disturbances and range shifts; perturbations to th...

Global Wildfire Forecasts Using Large Scale Climate Indices

Science.gov (United States)

Shen, Huizhong; Tao, Shu

2016-04-01

Using weather readings, fire early warning can provided forecast 4-6 hour in advance to minimize fire loss. The benefit would be dramatically enhanced if relatively accurate long-term projection can be also provided. Here we present a novel method for predicting global fire season severity (FSS) at least three months in advance using multiple large-scale climate indices (CIs). The predictive ability is proven effective for various geographic locations and resolution. Globally, as well as in most continents, the El Niño Southern Oscillation (ENSO) is the dominant driving force controlling interannual FSS variability, whereas other CIs also play indispensable roles. We found that a moderate El Niño event is responsible for 465 (272-658 as interquartile range) Tg carbon release and an annual increase of 29,500 (24,500-34,800) deaths from inhalation exposure to air pollutants. Southeast Asia accounts for half of the deaths. Both intercorrelation and interaction of WPs and CIs are revealed, suggesting possible climate-induced modification of fire responses to weather conditions. Our models can benefit fire management in response to climate change.

The Global Climate Dashboard: a Software Interface to Stream Comprehensive Climate Data

Science.gov (United States)

Gardiner, N.; Phillips, M.; NOAA Climate Portal Dashboard

2011-12-01

The Global Climate Dashboard is an integral component of NOAA's web portal to climate data, services, and value-added content for decision-makers, teachers, and the science-attentive public (www.clmate.gov). The dashboard provides a rapid view of observational data that demonstrate climate change and variability, as well as outputs from the Climate Model Intercomparison Project version 3, which was built to support the Intergovernmental Panel on Climate Change fourth assessment. The data shown in the dashboard therefore span a range of climate science disciplines with applications that serve audiences with diverse needs. The dashboard is designed with reusable software components that allow it to be implemented incrementally on a wide range of platforms including desktops, tablet devices, and mobile phones. The underlying software components support live streaming of data and provide a way of encapsulating graph sytles and other presentation details into a device-independent standard format that results in a common visual look and feel across all platforms. Here we describe the pedagogical objectives, technical implementation, and the deployment of the dashboard through climate.gov and partner web sites and describe plans to develop a mobile application using the same framework.

Clean coal technologies and global climate change

International Nuclear Information System (INIS)

Long, R.S.

1993-01-01

The role for Clean Coal Technologies is discussed in the context of the global climate change debate. Global climate change is, of course as the name implies, a global issue. This clearly distinguishes this issue from acid rain or ozone non-attainment, which are regional in nature. Therefore, the issue requires a global perspective, one that looks at the issue not just from a US policy standpoint but from an international policy view. This includes the positions of other individual nations, trading blocks, common interest groups, and the evolving United Nations bureaucracy. It is assumed that as the global economy continues to grow, energy demand will also grow. With growth in economic activity and energy use, will come growth in worldwide greenhouse gas emissions, including growth in carbon dioxide (CO 2 ) emissions. Much of this growth will occur in developing economies which intend to fuel their growth with coal-fired power, especially China and India. Two basic premises which set out the boundaries of this topic are presented. First, there is the premise that global climate change is occurring, or is about to occur, and that governments must do something to mitigate the causes of climate change. Although this premise is highly rebuttable, and not based on scientific certainty, political science has driven it to the forefront of the debate. Second is the premise that advanced combustion CCTs, with their higher efficiencies, will result in lower CO 2 emissions, and hence lessen any contribution of greater coal use to potential global climate change. This promise is demonstrably true. This discussion focuses on recent and emerging public sector policy actions, which may in large part establish a new framework in which the private sector will find new challenges and new opportunities

Response of the global climate to changes in atmospheric chemical composition due to fossil fuel burning

Science.gov (United States)

Hameed, S.; Cess, R. D.; Hogan, J. S.

1980-01-01

Recent modeling of atmospheric chemical processes (Logan et al, 1978; Hameed et al, 1979) suggests that tropospheric ozone and methane might significantly increase in the future as the result of increasing anthropogenic emissions of CO, NO(x), and CH4 due to fossil fuel burning. Since O3 and CH4 are both greenhouse gases, increases in their concentrations could augment global warming due to larger future amounts of atmospheric CO2. To test the possible climatic impact of changes in tropospheric chemical composition, a zonal energy-balance climate model has been combined with a vertically averaged tropospheric chemical model. The latter model includes all relevant chemical reactions which affect species derived from H2O, O2, CH4, and NO(x). The climate model correspondingly incorporates changes in the infrared heating of the surface-troposphere system resulting from chemically induced changes in tropospheric ozone and methane. This coupled climate-chemical model indicates that global climate is sensitive to changes in emissions of CO, NO(x) and CH4, and that future increases in these emissions could augment global warming due to increasing atmospheric CO2.

Global comparison of three greenhouse climate models

NARCIS (Netherlands)

Bavel, van C.H.M.; Takakura, T.; Bot, G.P.A.

1985-01-01

Three dynamic simulation models for calculating the greenhouse climate and its energy requirements for both heating and cooling were compared by making detailed computations for each of seven sets of data. The data sets ranged from a cold winter day, requiring heating, to a hot summer day, requiring

Global situational awareness and early warning of high-consequence climate change.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Carr, Martin J.; Boslough, Mark Bruce Elrick

2009-08-01

Global monitoring systems that have high spatial and temporal resolution, with long observational baselines, are needed to provide situational awareness of the Earth's climate system. Continuous monitoring is required for early warning of high-consequence climate change and to help anticipate and minimize the threat. Global climate has changed abruptly in the past and will almost certainly do so again, even in the absence of anthropogenic interference. It is possible that the Earth's climate could change dramatically and suddenly within a few years. An unexpected loss of climate stability would be equivalent to the failure of an engineered system on a grand scale, and would affect billions of people by causing agricultural, economic, and environmental collapses that would cascade throughout the world. The probability of such an abrupt change happening in the near future may be small, but it is nonzero. Because the consequences would be catastrophic, we argue that the problem should be treated with science-informed engineering conservatism, which focuses on various ways a system can fail and emphasizes inspection and early detection. Such an approach will require high-fidelity continuous global monitoring, informed by scientific modeling.

Biodiversity Hotspots, Climate Change, and Agricultural Development: Global Limits of Adaptation

Science.gov (United States)

Schneider, U. A.; Rasche, L.; Schmid, E.; Habel, J. C.

2017-12-01

Terrestrial ecosystems are threatened by climate and land management change. These changes result from complex and heterogeneous interactions of human activities and natural processes. Here, we study the potential change in pristine area in 33 global biodiversity hotspots within this century under four climate projections (representative concentration pathways) and associated population and income developments (shared socio-economic pathways). A coupled modelling framework computes the regional net expansion of crop and pasture lands as result of changes in food production and consumption. We use a biophysical crop simulation model to quantify climate change impacts on agricultural productivity, water, and nutrient emissions for alternative crop management systems in more than 100 thousand agricultural land polygons (homogeneous response units) and for each climate projection. The crop simulation model depicts detailed soil, weather, and management information and operates with a daily time step. We use time series of livestock statistics to link livestock production to feed and pasture requirements. On the food consumption side, we estimate national demand shifts in all countries by processing population and income growth projections through econometrically estimated Engel curves. Finally, we use a global agricultural sector optimization model to quantify the net change in pristine area in all biodiversity hotspots under different adaptation options. These options include full-scale global implementation of i) crop yield maximizing management without additional irrigation, ii) crop yield maximizing management with additional irrigation, iii) food yield maximizing crop mix adjustments, iv) food supply maximizing trade flow adjustments, v) healthy diets, and vi) combinations of the individual options above. Results quantify the regional potentials and limits of major agricultural producer and consumer adaptation options for the preservation of pristine areas in

The global climate Policy Evaluation Framework

International Nuclear Information System (INIS)

Cohan, D.; Stafford, R.K.; Scheraga, J.D.; Herrod, S.

1994-01-01

The Policy Evaluation Framework (PEF) is a decision analysis tool that enables decision makers to continuously formulate policies that take into account the existing uncertainties, and to refine policies as new scientific information is developed. PEF integrates deterministic parametric models of physical, biological, and economic systems with a flexible decision tree system. The deterministic models represent greenhouse gas emissions, atmospheric accumulation of these gases, global and regional climate changes, ecosystem impacts, economic impacts, and mitigation and adaptation options, The decision tree system captures the key scientific and economic uncertainties, and reflects the wide range of possible outcomes of alternative policy actions. The framework contains considerable flexibility to allow a wide range of scientific and economic assumptions or scenarios to be represented and explored. A key feature of PEF is its capability to address both mitigation policies and investments in anticipatory adaptation to protect ecological and economic systems, as well as interactions among such options. PEF's time structure allows issues related to the timing and flexibility of alternatives to be evaluated, while the decision tree structure facilitates examining questions involving the value of information, contingent actions, and probabilistic representations. This paper is intended to introduce PEF to the global climate policy community. The paper provides an overview of the structure, modules, and capabilities of PEF, and discusses selected results from an initial set of illustrative applications

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

The contribution of China's emissions to global climate forcing.

Science.gov (United States)

Li, Bengang; Gasser, Thomas; Ciais, Philippe; Piao, Shilong; Tao, Shu; Balkanski, Yves; Hauglustaine, Didier; Boisier, Juan-Pablo; Chen, Zhuo; Huang, Mengtian; Li, Laurent Zhaoxin; Li, Yue; Liu, Hongyan; Liu, Junfeng; Peng, Shushi; Shen, Zehao; Sun, Zhenzhong; Wang, Rong; Wang, Tao; Yin, Guodong; Yin, Yi; Zeng, Hui; Zeng, Zhenzhong; Zhou, Feng

2016-03-17

Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on "common but differentiated responsibilities" reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development, accompanied by increased emission of greenhouse gases, ozone precursors and aerosols, but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model and a chemistry and transport model to quantify China's present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% ± 4% of the current global radiative forcing. China's relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% ± 2%. Its relative contribution to the negative (cooling) component is 15% ± 6%, dominated by the effect of sulfate and nitrate aerosols. China's strongest contributions are 0.16 ± 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 ± 0.05 watts per square metre for CH4, -0.11 ± 0.05 watts per square metre for sulfate aerosols, and 0.09 ± 0.06 watts per square metre for black carbon aerosols. China's eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.

Global climate change and the equity-efficiency puzzle

International Nuclear Information System (INIS)

Manne, Alan S.; Stephan, Gunter

2005-01-01

There is a broad consensus that the costs of abatement of global climate change can be reduced efficiently through the assignment of quota rights and through international trade in these rights. There is, however, no consensus on whether the initial assignment of emissions permits can affect the Pareto-optimal global level of abatement. This paper provides some insight into the equity-efficiency puzzle. Qualitative results are obtained from a small-scale model; then quantitative evidence of separability is obtained from MERGE, a multiregion integrated assessment model. It is shown that if all the costs of climate change can be expressed in terms of GDP losses, Pareto-efficient abatement strategies are independent of the initial allocation of emissions rights. This is the case sometimes described as 'market damages'. If, however, different regions assign different values to nonmarket damages such as species losses, different sharing rules may affect the Pareto-optimal level of greenhouse gas abatement. Separability may then be demonstrated only in specific cases (e.g. identical welfare functions or quasi-linearity of preferences or small shares of wealth devoted to abatement)

Global terrestrial water storage connectivity revealed using complex climate network analyses

Science.gov (United States)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Global vs climate change

International Nuclear Information System (INIS)

Watson, H.L.; Bach, M.C.; Goklany, I.M.

1991-01-01

The various agents of global change that will affect the state of natural resources 50-100 years from now are discussed. These include economic and population growth, technological progress, and climatic change. The importance of climatic change lies in its effects on natural resources and on human activities that depend on those resources. Other factors affecting those resources include the demand on those resources from an increasing population and from a growing economy, and a more efficient use of those resources that comes from technological changes and from the consequences of economic growth itself. It is shown that there is a considerable ability to adapt to climatic change, since humans already have an intrinsic ability to adapt to the wide variations in climates that already exist and since technological developments can make it easier to cope with climatic variability. It appears that agents other than climatic change are more significant to the future state of natural resources than climatic change. Criteria for selecting options for addressing climatic change are outlined. Technological change and economic growth are seen to be key response options, since the vulnerability to climatic change depends on economic resources and technological progress. Specific options to stimulate sustainable economic growth and technological progress are listed. 16 refs., 1 fig., 2 tabs

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

Recursive inter-generational utility in global climate risk modeling

Energy Technology Data Exchange (ETDEWEB)

Minh, Ha-Duong [Centre International de Recherche sur l' Environnement et le Developpement (CIRED-CNRS), 75 - Paris (France); Treich, N. [Institut National de Recherches Agronomiques (INRA-LEERNA), 31 - Toulouse (France)

2003-07-01

This paper distinguishes relative risk aversion and resistance to inter-temporal substitution in climate risk modeling. Stochastic recursive preferences are introduced in a stylized numeric climate-economy model using preliminary IPCC 1998 scenarios. It shows that higher risk aversion increases the optimal carbon tax. Higher resistance to inter-temporal substitution alone has the same effect as increasing the discount rate, provided that the risk is not too large. We discuss implications of these findings for the debate upon discounting and sustainability under uncertainty. (author)

Global but fair. Controvert the climatic change, allow development; Global aber gerecht. Klimawandel bekaempfen, Entwicklung ermoeglichen

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

The book includes the following chapters: global but fair: climate compatible development for everybody; climatic change consequences und vulnerabilities; ethic dimension: fairness in the context of climatic change and poverty; options and challenges for emissions abatement; options for the adaptation to the climatic change; global deal for climate and development policy; convert the climatic change, allow development: ten political messages.

Technical Report Series on Global Modeling and Data Assimilation, Volume 43. MERRA-2; Initial Evaluation of the Climate

Science.gov (United States)

Koster, Randal D. (Editor); Bosilovich, Michael G.; Akella, Santha; Lawrence, Coy; Cullather, Richard; Draper, Clara; Gelaro, Ronald; Kovach, Robin; Liu, Qing; Molod, Andrea;

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

Science.gov (United States)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Remote sensing for global change, climate change and atmosphere and ocean forecasting. Volume 1

International Nuclear Information System (INIS)

1992-01-01

This volume is separated in three sessions. First part is on remote sensing for global change (with global modelling, land cover change on global scale, ocean colour studies of marine biosphere, biological and hydrological interactions and large scale experiments). Second part is on remote sensing for climate change (with earth radiation and clouds, sea ice, global climate research programme). Third part is on remote sensing for atmosphere and ocean forecasting (with temperatures and humidity, winds, data assimilation, cloud imagery, sea surface temperature, ocean waves and topography). (A.B.). refs., figs., tabs

Integrated regional changes in arctic climate feedbacks: Implications for the global climate system

Science.gov (United States)

McGuire, A.D.; Chapin, F. S.; Walsh, J.E.; Wirth, C.; ,

2006-01-01

The Arctic is a key part of the global climate system because the net positive energy input to the tropics must ultimately be resolved through substantial energy losses in high-latitude regions. The Arctic influences the global climate system through both positive and negative feedbacks that involve physical, ecological, and human systems of the Arctic. The balance of evidence suggests that positive feedbacks to global warming will likely dominate in the Arctic during the next 50 to 100 years. However, the negative feedbacks associated with changing the freshwater balance of the Arctic Ocean might abruptly launch the planet into another glacial period on longer timescales. In light of uncertainties and the vulnerabilities of the climate system to responses in the Arctic, it is important that we improve our understanding of how integrated regional changes in the Arctic will likely influence the evolution of the global climate system. Copyright ?? 2006 by Annual Reviews. All rights reserved.

A probabilistic model of ecosystem response to climate change

International Nuclear Information System (INIS)

Shevliakova, E.; Dowlatabadi, H.

1994-01-01

Anthropogenic activities are leading to rapid changes in land cover and emissions of greenhouse gases into the atmosphere. These changes can bring about climate change typified by average global temperatures rising by 1--5 C over the next century. Climate change of this magnitude is likely to alter the distribution of terrestrial ecosystems on a large scale. Options available for dealing with such change are abatement of emissions, adaptation, and geoengineering. The integrated assessment of climate change demands that frameworks be developed where all the elements of the climate problem are present (from economic activity to climate change and its impacts on market and non-market goods and services). Integrated climate assessment requires multiple impact metrics and multi-attribute utility functions to simulate the response of different key actors/decision-makers to the actual physical impacts (rather than a dollar value) of the climate-damage vs. policy-cost debate. This necessitates direct modeling of ecosystem impacts of climate change. The authors have developed a probabilistic model of ecosystem response to global change. This model differs from previous efforts in that it is statistically estimated using actual ecosystem and climate data yielding a joint multivariate probability of prevalence for each ecosystem, given climatic conditions. The authors expect this approach to permit simulation of inertia and competition which have, so far, been absent in transfer models of continental-scale ecosystem response to global change. Thus, although the probability of one ecotype will dominate others at a given point, others would have the possibility of establishing an early foothold

The Role of Volcanic Activity in Climate and Global Change

KAUST Repository

Stenchikov, Georgiy L.

2015-09-23

Explosive volcanic eruptions are magnificent events that in many ways affect the Earth\\'s natural processes and climate. They cause sporadic perturbations of the planet\\'s energy balance, activating complex climate feedbacks and providing unique opportunities to better quantify those processes. We know that explosive eruptions cause cooling in the atmosphere for a few years, but we have just recently realized that volcanic signals can be seen in the subsurface ocean for decades. The volcanic forcing of the previous two centuries offsets the ocean heat uptake and diminishes global warming by about 30%. The explosive volcanism of the twenty-first century is unlikely to either cause any significant climate signal or to delay the pace of global warming. The recent interest in dynamic, microphysical, chemical, and climate impacts of volcanic eruptions is also excited by the fact that these impacts provide a natural analogue for climate geoengineering schemes involving deliberate development of an artificial aerosol layer in the lower stratosphere to counteract global warming. In this chapter we aim to discuss these recently discovered volcanic effects and specifically pay attention to how we can learn about the hidden Earth-system mechanisms activated by explosive volcanic eruptions. To demonstrate these effects we use our own model results when possible along with available observations, as well as review closely related recent publications.

Climate Model Diagnostic Analyzer Web Service System

Science.gov (United States)

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

2015-12-01

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

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

Science.gov (United States)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

International business and global climate change

NARCIS (Netherlands)

Pinkse, J.; Kolk, A.

2008-01-01

Climate change has become an important topic on the business agenda with strong pressure being placed on companies to respond and contribute to finding solutions to this urgent problem. This text provides a comprehensive analysis of international business responses to global climate change and

Modeling of the Global Water Cycle - Analytical Models

Science.gov (United States)

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

ASM Lecture Series: Global Warming and Climate Change

International Nuclear Information System (INIS)

Rowland, F. S.

2010-01-01

The melting of ice and permafrost in the north polar region and the shrinking of the tropical glaciers are signals that global warming is no longer solely a warning about the future, but changes which have already arrived. The initial effects of this warming are noticeably present, and the concerns are now of substantial climate change in the near future. Modeling of the consequences on the future atmosphere from increased release of greenhouse gases and some of the possible consequences of climate change, such as rising sea levels and melting of the north polar ice, are discussed. (author)

Impacts of climate extremes on gross primary production under global warming

International Nuclear Information System (INIS)

Williams, I N; Torn, M S; Riley, W J; Wehner, M F

2014-01-01

The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at the warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections

A global conservation system for climate-change adaptation.

Science.gov (United States)

Hannah, Lee

2010-02-01

Climate change has created the need for a new strategic framework for conservation. This framework needs to include new protected areas that account for species range shifts and management that addresses large-scale change across international borders. Actions within the framework must be effective in international waters and across political frontiers and have the ability to accommodate large income and ability-to-pay discrepancies between countries. A global protected-area system responds to these needs. A fully implemented global system of protected areas will help in the transition to a new conservation paradigm robust to climate change and will ensure the integrity of the climate services provided by carbon sequestration from the world's natural habitats. The internationally coordinated response to climate change afforded by such a system could have significant cost savings relative to a system of climate adaptation that unfolds solely at a country level. Implementation of a global system is needed very soon because the effects of climate change on species and ecosystems are already well underway.

Global Climate Change: Threat Multiplier for AFRICOM?

National Research Council Canada - National Science Library

Yackle, Terri A

2007-01-01

.... Whatever the catalyst for this abrupt climate change, stability for Africa hinges upon mitigating the effects of global climate change to prevent future conflicts such as Darfur, and the instability...

Climate Change, Globalization and Geopolitics in the New Maritime Arctic

Science.gov (United States)

Brigham, L. W.

2011-12-01

Early in the 21st century a confluence of climate change, globalization and geopolitics is shaping the future of the maritime Arctic. This nexus is also fostering greater linkage of the Arctic to the rest of the planet. Arctic sea ice is undergoing a historic transformation of thinning, extent reduction in all seasons, and reduction in the area of multiyear ice in the central Arctic Ocean. Global Climate Model simulations of Arctic sea ice indicate multiyear ice could disappear by 2030 for a short period of time each summer. These physical changes invite greater marine access, longer seasons of navigation, and potential, summer trans-Arctic voyages. As a result, enhanced marine safety, environmental protection, and maritime security measures are under development. Coupled with climate change as a key driver of regional change is the current and future integration of the Arctic's natural wealth with global markets (oil, gas and hard minerals). Abundant freshwater in the Arctic could also be a future commodity of value. Recent events such as drilling for hydrocarbons off Greenland's west coast and the summer marine transport of natural resources from the Russian Arctic to China across the top of Eurasia are indicators of greater global economic ties to the Arctic. Plausible Arctic futures indicate continued integration with global issues and increased complexity of a range of regional economic, security and environmental challenges.

Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe

Directory of Open Access Journals (Sweden)

A. P. van Ulden

2006-01-01

Full Text Available The quality of global sea level pressure patterns has been assessed for simulations by 23 coupled climate models. Most models showed high pattern correlations. With respect to the explained spatial variance, many models showed serious large-scale deficiencies, especially at mid-latitudes. Five models performed well at all latitudes and for each month of the year. Three models had a reasonable skill. We selected the five models with the best pressure patterns for a more detailed assessment of their simulations of the climate in Central Europe. We analysed observations and simulations of monthly mean geostrophic flow indices and of monthly mean temperature and precipitation. We used three geostrophic flow indices: the west component and south component of the geostrophic wind at the surface and the geostrophic vorticity. We found that circulation biases were important, and affected precipitation in particular. Apart from these circulation biases, the models showed other biases in temperature and precipitation, which were for some models larger than the circulation induced biases. For the 21st century the five models simulated quite different changes in circulation, precipitation and temperature. Precipitation changes appear to be primarily caused by circulation changes. Since the models show widely different circulation changes, especially in late summer, precipitation changes vary widely between the models as well. Some models simulate severe drying in late summer, while one model simulates significant precipitation increases in late summer. With respect to the mean temperature the circulation changes were important, but not dominant. However, changes in the distribution of monthly mean temperatures, do show large indirect influences of circulation changes. Especially in late summer, two models simulate very strong warming of warm months, which can be attributed to severe summer drying in the simulations by these models. The models differ also

Global Responses to Potential Climate Change: A Simulation.

Science.gov (United States)

Williams, Mary Louise; Mowry, George

This interdisciplinary five-day unit provides students with an understanding of the issues in the debate on global climate change. Introductory lessons enhance understanding of the "greenhouse gases" and their sources with possible global effects of climate change. Students then roleplay negotiators from 10 nations in a simulation of the…

Climate Cases: Learning about Student Conceptualizations of Global Climate Change

Science.gov (United States)

Tierney, Benjamin P.

2013-01-01

The complex topic of global climate change continues to be a challenging yet important topic among science educators and researchers. This mixed methods study adds to the growing research by investigating student conceptions of climate change from a system theory perspective (Von Bertalanffy, 1968) by asking the question, "How do differences…

Integrated assessment of global climate change with learning-by-doing and energy-related research and development

International Nuclear Information System (INIS)

Mueller-Fuerstenberger, Georg; Stephan, Gunter

2007-01-01

This paper presents a small-scale version of an Integrated Assessment Model (IAM) of global climate change, which is based on a global, regionally differentiated computable general equilibrium (CGE) model with endogenous technological change. This model can be viewed as a basic framework for analyzing a broad range of economic issues related to climate change, in particular since technological change is represented in two ways: on the one hand, there is learning-by-doing (LbD) in non-fossil energy supply technologies, and on the other hand there is research and development (R and D)-driven energy-saving technical progress in production. Computational experiments are added for illustrating the role of technological innovation in a world both with and without cooperation in the solution of the global climate problem

Statistical models of global Langmuir mixing

Science.gov (United States)

Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean

2017-05-01

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

Global temperature definition affects achievement of long-term climate goals

Science.gov (United States)

Richardson, Mark; Cowtan, Kevin; Millar, Richard J.

2018-05-01

The Paris Agreement on climate change aims to limit ‘global average temperature’ rise to ‘well below 2 °C’ but reported temperature depends on choices about how to blend air and water temperature data, handle changes in sea ice and account for regions with missing data. Here we use CMIP5 climate model simulations to estimate how these choices affect reported warming and carbon budgets consistent with the Paris Agreement. By the 2090s, under a low-emissions scenario, modelled global near-surface air temperature rise is 15% higher (5%–95% range 6%–21%) than that estimated by an approach similar to the HadCRUT4 observational record. The difference reduces to 8% with global data coverage, or 4% with additional removal of a bias associated with changing sea-ice cover. Comparison of observational datasets with different data sources or infilling techniques supports our model results regarding incomplete coverage. From high-emission simulations, we find that a HadCRUT4 like definition means higher carbon budgets and later exceedance of temperature thresholds, relative to global near-surface air temperature. 2 °C warming is delayed by seven years on average, to 2048 (2035–2060), and CO2 emissions budget for a >50% chance of <2 °C warming increases by 67 GtC (246 GtCO2).

Evidence of Climate Change (Global Warming) and Temperature Increases in Arctic Areas

OpenAIRE

Eric Kojo Wu Aikins

2012-01-01

This paper contributes to the debate on the proximate causes of climate change. Also, it discusses the impact of the global temperature increases since the beginning of the twentieth century and the effectiveness of climate change models in isolating the primary cause (anthropogenic influences or natural variability in temperature) of the observed temperature increases that occurred within this period. The paper argues that if climate scientist and policymakers ignore the...

Assessing global vegetation activity using spatio-temporal Bayesian modelling

Science.gov (United States)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

Climate effects of anthropogenic sulfate: Simulations from a coupled chemistry/climate model

International Nuclear Information System (INIS)

Chuang, C.C.; Penner, J.E.; Taylor, K.E.; Walton, J.J.

1993-09-01

In this paper, we use a more comprehensive approach by coupling a climate model with a 3-D global chemistry model to investigate the forcing by anthropogenic aerosol sulfate. The chemistry model treats the global-scale transport, transformation, and removal of SO 2 , DMS and H 2 SO 4 species in the atmosphere. The mass concentration of anthropogenic sulfate from fossil fuel combustion and biomass burning is calculated in the chemistry model and provided to the climate model where it affects the shortwave radiation. We also investigate the effect, with cloud nucleation parameterized in terms of local aerosol number, sulfate mass concentration and updraft velocity. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. Uncertainties in these results will be discussed

The impact of global warming on the range distribution of different climatic groups of Aspidoscelis costata costata.

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Güizado-Rodríguez, Martha Anahí; Ballesteros-Barrera, Claudia; Casas-Andreu, Gustavo; Barradas-Miranda, Victor Luis; Téllez-Valdés, Oswaldo; Salgado-Ugarte, Isaías Hazarmabeth

2012-12-01

The ectothermic nature of reptiles makes them especially sensitive to global warming. Although climate change and its implications are a frequent topic of detailed studies, most of these studies are carried out without making a distinction between populations. Here we present the first study of an Aspidoscelis species that evaluates the effects of global warming on its distribution using ecological niche modeling. The aims of our study were (1) to understand whether predicted warmer climatic conditions affect the geographic potential distribution of different climatic groups of Aspidoscelis costata costata and (2) to identify potential altitudinal changes of these groups under global warming. We used the maximum entropy species distribution model (MaxEnt) to project the potential distributions expected for the years 2020, 2050, and 2080 under a single simulated climatic scenario. Our analysis suggests that some climatic groups of Aspidoscelis costata costata will exhibit reductions and in others expansions in their distribution, with potential upward shifts toward higher elevation in response to climate warming. Different climatic groups were revealed in our analysis that subsequently showed heterogeneous responses to climatic change illustrating the complex nature of species geographic responses to environmental change and the importance of modeling climatic or geographic groups and/or populations instead of the entire species' range treated as a homogeneous entity.

Global warming and climate change in Amazonia: Climate-vegetation feedback and impacts on water resources

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Marengo, José; Nobre, Carlos A.; Betts, Richard A.; Cox, Peter M.; Sampaio, Gilvan; Salazar, Luis

This chapter constitutes an updated review of long-term climate variability and change in the Amazon region, based on observational data spanning more than 50 years of records and on climate-change modeling studies. We start with the early experiments on Amazon deforestation in the late 1970s, and the evolution of these experiments to the latest studies on greenhouse gases emission scenarios and land use changes until the end of the twenty-first century. The "Amazon dieback" simulated by the HadCM3 model occurs after a "tipping point" of CO2 concentration and warming. Experiments on Amazon deforestation and change of climate suggest that once a critical deforestation threshold (or tipping point) of 40-50% forest loss is reached in eastern Amazonia, climate would change in a way which is dangerous for the remaining forest. This may favor a collapse of the tropical forest, with a substitution of the forest by savanna-type vegetation. The concept of "dangerous climate change," as a climate change, which induces positive feedback, which accelerate the change, is strongly linked to the occurrence of tipping points, and it can be explained as the presence of feedback between climate change and the carbon cycle, particularly involving a weakening of the current terrestrial carbon sink and a possible reversal from a sink (as in present climate) to a source by the year 2050. We must, therefore, currently consider the drying simulated by the Hadley Centre model(s) as having a finite probability under global warming, with a potentially enormous impact, but with some degree of uncertainty.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

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Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Land-use change and global climate policies

International Nuclear Information System (INIS)

Gitz, V.

2004-03-01

This PhD thesis assess the role of land-use dynamics and carbon sequestration within climate policies. First, it describes the emergence, from the Rio-1992 to the Marrakech Accords (2001), of diplomatic controversies upon carbon sinks, in the context of the progressive constitution of a scientific basis on terrestrial carbon sinks. It questions the ability of the actual form of international climate regime to generate the appropriate incentives to sequester within the forestry sector in developed countries, or to control tropical deforestation. Second, the contribution of land-use change to atmospheric CO 2 rise is quantified using a newly designed model of the global carbon cycle and regional land-use (OSCAR). We show that carbon emitted via land-use is not equivalent to fossil carbon emission in respect to atmospheric CO 2 rise. This effect, all the more than land-use emissions are increasing, requires a greater mitigation effort to stabilize atmospheric CO 2 . Finally, optimal timing of mixed climate policies involving fossil emissions mitigation and biological sequestration is assessed within an inter temporal cost-benefit framework. We show that the social value of sequestered carbon depends on anticipating future climate damages. Within optimal control models, this links the timing of sequestration to fossil effort and to the evolution of climate damages; if the latter are uncertain, but might be revealed at a later date, then it might be optimal to reserve part of the limited sequestration potential to cut off an eventual future abatement cost peak, were a climate surprise to finally imply stringent concentration ceilings. (author)

Global vegetation-fire pattern under different land use and climate conditions

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Thonicke, K.; Poulter, B.; Heyder, U.; Gumpenberger, M.; Cramer, W.

2008-12-01

Fire is a process of global significance in the Earth System influencing vegetation dynamics, biogeochemical cycling and biophysical feedbacks. Naturally ignited wildfires have long history in the Earth System. Humans have been using fire to shape the landscape for their purposes for many millenia, sometimes influencing the status of the vegetation remarkably as for example in Mediterranean-type ecosystems. Processes and drivers describing fire danger, ignitions, fire spread and effects are relatively well-known for many fire-prone ecosystems. Modeling these has a long tradition in fire-affected regions to predict fire risk and behavior for fire-fighting purposes. On the other hand, the global vegetation community realized the importance of disturbances to be recognized in their global vegetation models with fire being globally most important and so-far best studied. First attempts to simulate fire globally considered a minimal set of drivers, whereas recent developments attempt to consider each fire process separately. The process-based fire model SPITFIRE (SPread and InTensity of FIRE) simulates these processes embedded in the LPJ DGVM. Uncertainties still arise from missing measurements for some parameters in less-studied fire regimes, or from broad PFT classifications which subsume different fire-ecological adaptations and tolerances. Some earth observation data sets as well as fire emission models help to evaluate seasonality and spatial distribution of simulated fire ignitions, area burnt and fire emissions within SPITFIRE. Deforestation fires are a major source of carbon released to the atmosphere in the tropics; in the Amazon basin it is the second-largest contributor to Brazils GHG emissions. How ongoing deforestation affects fire regimes, forest stability and biogeochemical cycling in the Amazon basin under present climate conditions will be presented. Relative importance of fire vs. climate and land use change is analyzed. Emissions resulting from

Regional Climate Impacts of Stabilizing Global Warming at 1.5 K Using Solar Geoengineering

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Jones, Anthony C.; Hawcroft, Matthew K.; Haywood, James M.; Jones, Andy; Guo, Xiaoran; Moore, John C.

2018-02-01

The 2015 Paris Agreement aims to limit global warming to well below 2 K above preindustrial levels, and to pursue efforts to limit global warming to 1.5 K, in order to avert dangerous climate change. However, current greenhouse gas emissions targets are more compatible with scenarios exhibiting end-of-century global warming of 2.6-3.1 K, in clear contradiction to the 1.5 K target. In this study, we use a global climate model to investigate the climatic impacts of using solar geoengineering by stratospheric aerosol injection to stabilize global-mean temperature at 1.5 K for the duration of the 21st century against three scenarios spanning the range of plausible greenhouse gas mitigation pathways (RCP2.6, RCP4.5, and RCP8.5). In addition to stabilizing global mean temperature and offsetting both Arctic sea-ice loss and thermosteric sea-level rise, we find that solar geoengineering could effectively counteract enhancements to the frequency of extreme storms in the North Atlantic and heatwaves in Europe, but would be less effective at counteracting hydrological changes in the Amazon basin and North Atlantic storm track displacement. In summary, solar geoengineering may reduce global mean impacts but is an imperfect solution at the regional level, where the effects of climate change are experienced. Our results should galvanize research into the regionality of climate responses to solar geoengineering.

Global climate change: an unequivocal reality; Cambio climatico global: una realidad inequivoca

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Raynal-Villasenor, J.A. [Universidad de las Americas, Puebla, Puebla (Mexico)]. E-mail: josea.raynal@udlap.mx

2011-10-15

During several years, a long discussion has taken place over the reality of global climate change phenomenon and, if there is one, what could be its cause. Once the 4th Assessment Report of the Intergovernmental Panel on Climatic Change (IPCC, 2007) - IPCC is part the United Nations Organization (UN) - was published, it was stated that there is a developing global climatic change and that the cause is unequivocally related with the human activity in the planet Earth. In this paper, relevant information is given about the development of global climatic change issues and some actions are mentioned that each human being of this planet can implement to mitigate it, since it has been accepted that it's impossible to stop it. [Spanish] Durante varios anos se ha discutido si existe un cambio climatico global y, si lo hay, cual es su causa. Una vez publicado el 4o. Reporte de Valoracion del Panel Intergubernamental sobre Cambio Climatico (IPCC, 2007) - el IPCC es parte de la Organizacion de las Naciones Unidas (ONU) - se preciso que hay un cambio climatico global en desarrollo y la causa inequivoca que lo esta produciendo es la actividad humana en el planeta Tierra, tambien se hablo en el IPCC de las causas naturales por las cuales el planeta se esta calentando. En el presente articulo, se da informacion relevante al cambio climatico global en desarrollo y se mencionan algunas acciones que cada ser humano de este planeta puede implementar para mitigarlo, ya que es imposible detenerlo.

The status and challenge of global fire modelling

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Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

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Storelvmo, T.

2015-12-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

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Gisselle Yang Xie

Full Text Available Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd, a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary, including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific and also separately per region (region-specific. One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas

Global land-use and market interactions between climate and bioenergy policies

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Golub, A.; Hertel, T. W.; Rose, S. K.

2011-12-01

Over the past few years, interest in bioenergy has boomed with higher oil prices and concerns about energy security, farm incomes, and mitigation of climate change. Large-scale commercial bioenergy production could have far reaching implications for regional and global land use and output markets associated with food, forestry, chemical, and energy sectors, as well as household welfare. Similarly, there is significant interest in international agricultural and forestry based carbon sequestration and greenhouse gas (GHG) mitigation policies, which could also provide revenue to developing countries and farmers in exchange for modifying land management practices. However, bioenergy and climate policies are being formulated largely independent of one another. Understanding the interaction between these potentially competing policy objectives is important for identifying possible constraints that one policy might place on the other, potential complementarities that could be exploited in policy design, and net land-use change and management implications over time. This study develops a new dynamic global computable general equilibrium (CGE) model GDyn-E-AEZ to assess the interaction between biofuels production and climate mitigation policies. The model is built on several existing CGE platforms, including 1) GTAP-AEZ-GHG model (Golub et al., 2009), 2) GTAP-BIO (Birur et al., 2008; Taheripour and Tyner, 2011), and 3) GDyn framework (Ianchovichina and McDougall, 2001) extended to investigate the role of population and per capita income growth, changing consumption patterns, and global economic integration in determining long-run patterns of land-use change. The new model is used to assess the effects of domestic and global bioenergy expansion on future land use, as well as sectoral, regional and global GHG emissions mitigation potential. Do bioenergy programs facilitate or constrain GHG mitigation opportunities? For instance, Golub et al. (2009) estimate substantial GHG

Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies