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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

DOE PAGES

Kim, John B.; Monier, Erwan; Sohngen, Brent; ...

2017-03-28

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 business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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 business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO2 fertilization effects may considerably reduce the range of projections.

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

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

Kim, John B.; Monier, Erwan; Sohngen, Brent

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 business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

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

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

NASA Astrophysics Data System (ADS)

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

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

Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.

2017-12-01

Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate

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

Gao, Yang; Leung, Lai-Yung R.; Lu, Jian

2014-03-16

This study compares climate simulations over the United States produced by a regional climate model with the driving global climate simulations as well as a large multi-model ensemble of global climate simulations to investigate robust changes in water availability (precipitation (P) – evapotranspiration (E)). A robust spring dry signal across multiple models is identified in the Southwest that results from a decrease in P and an increase in E in the future. In the boreal winter and summer, the prominent changes in P – E are associated with a north – south dipole pattern, while in spring, the prominent changesmore » in P – E appear as an east – west dipole pattern. The progression of the north – south and east – west dipole patterns through the seasons manifests clearly as a seasonal “clockwise” migration of wet/dry patterns, which is shown to be a robust feature of water availability changes in the US consistent across regional and global climate simulations.« less

El Niño/Southern Oscillation response to global warming

PubMed Central

Latif, M.; Keenlyside, N. S.

2009-01-01

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO2, accelerating global warming. PMID:19060210

The global distribution of ecosystems in a world without fire.

PubMed

Bond, W J; Woodward, F I; Midgley, G F

2005-02-01

This paper is the first global study of the extent to which fire determines global vegetation patterns by preventing ecosystems from achieving the potential height, biomass and dominant functional types expected under the ambient climate (climate potential). To determine climate potential, we simulated vegetation without fire using a dynamic global-vegetation model. Model results were tested against fire exclusion studies from different parts of the world. Simulated dominant growth forms and tree cover were compared with satellite-derived land- and tree-cover maps. Simulations were generally consistent with results of fire exclusion studies in southern Africa and elsewhere. Comparison of global 'fire off' simulations with landcover and treecover maps show that vast areas of humid C(4) grasslands and savannas, especially in South America and Africa, have the climate potential to form forests. These are the most frequently burnt ecosystems in the world. Without fire, closed forests would double from 27% to 56% of vegetated grid cells, mostly at the expense of C(4) plants but also of C(3) shrubs and grasses in cooler climates. C(4) grasses began spreading 6-8 Ma, long before human influence on fire regimes. Our results suggest that fire was a major factor in their spread into forested regions, splitting biotas into fire tolerant and intolerant taxa.

El Nino/Southern Oscillation response to global warming.

PubMed

Latif, M; Keenlyside, N S

2009-12-08

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO(2), accelerating global warming.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

Effects of global climate change on the US forest sector: response functions derived from a dynamic resource and market simulator.

Treesearch

Bruce A. McCarl; Darius M. Adams; Ralph J. Alig; Diana Burton; Chi-Chung. Chen

2000-01-01

A multiperiod, regional, mathematical programming economic model is used to evaluate the potential economic impacts of global climatic change on the US forest sector. A wide range of scenarios for the biological response of forests to climate change are developed, ranging from small to large changes in forest growth rates. These scenarios are simulated in the economic...

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

PubMed

Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

2015-04-21

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

PubMed Central

Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

2015-01-01

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

Ground-water/surface-water responses to global climate simulations, Santa Clara-Calleguas basin, Ventura County, California, 1950-93

USGS Publications Warehouse

Hanson, Randall T.; Dettinger, Michael D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.

Ground water/surface water responses to global climate simulations, Santa Clara-Calleguas Basin, Ventura, California

USGS Publications Warehouse

Hanson, R.T.; Dettinger, M.D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa ClaraCalleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Nin??o Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/??C, compared to 0.9 m/??C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and - when the GCM forecast skills are adequate - for near term predictions.

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

DOE PAGES

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.; ...

2017-08-11

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

Towards a unified Global Weather-Climate Prediction System

NASA Astrophysics Data System (ADS)

Lin, S. J.

2016-12-01

The Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

CONSTABLE: A Global Climate Model for Classroom Use.

ERIC Educational Resources Information Center

Cerveny, Randall S.; And Others

1985-01-01

Described is the global climate model CONSTABLE (Climatic One-Dimensional Numerical Simulation of the Annual Balance of Latitudinal Energy), which can be used in undergraduate and graduate level climatology courses. Classroom exercises that can be used with the model are also included. (RM)

Inability of CMIP5 Climate Models to Simulate Recent Multi-decadal Climate Change in the Tropical Pacific.

NASA Astrophysics Data System (ADS)

Power, S.; Delage, F.; Kociuba, G.; Wang, G.; Smith, I.

2017-12-01

Observed 15-year surface temperature trends beginning 1998 or later have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short trends, whether they indicate a possible bias in models and the implications for global warming generally. Here we analyse historical and projected changes in 38 CMIP5 climate models. All of the models simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This stark difference cannot be fully explained by observed, internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. We also show that CMIP5 models are not able to simulate the magnitude of the strengthening of the Walker Circulation over the past thirty years. Some of the reasons for these major shortcomings in the ability of models to simulate multi-decadal variability in the Pacific, and the impact these findings have on our confidence in global 21st century projections, will be discussed.

Global Trends and Variability in Integrated Water Vapor from Ground-Based GPS Data and Climate Models

NASA Astrophysics Data System (ADS)

Bock, O.; Parracho, A. C.; Bastin, S.; Hourdin, F.

2016-12-01

A high-quality, consistent, global, long-term dataset of integrated water vapor (IWV) was produced from Global Positioning System (GPS) measurements at more than 400 sites over the globe among which 120 sites have more than 15 years of data. The GPS delay data were converted to IWV using surface pressure and weighted mean temperature estimates from ERA-Interim reanalysis. A two-step screening method was developed to detect and remove outliers in the IWV data. It is based on: 1) GPS data processing information and delay formal errors, and 2) inter-comparison with ERA-Interim reanalysis data. The GPS IWV data are also homogenized to correct for offsets due to instrumental changes and other unknown factors. The differential homogenization method uses ERA-Interim IWV as a reference. The resulting GPS data are used to document the mean distribution, the global trends and the variability of IWV over the period 1995-2010, and to assess global climate model simulations extracted from the IPCC AR5 archive. Large coherent spatial patterns of moistening and drying are evidenced but significant discrepancies are also seen between GPS measurements, reanalysis and climate models in various regions. In terms of variability, the monthly mean anomalies are inter-compared. The temporal correlation between GPS and the climate model simulations is overall quite small but the spatial variation of the magnitude of the anomalies is globally well simulated. GPS IWV data prove to be useful to validate global climate model simulations and highlight deficiencies in their representation of the water cycle.

Analysing regional climate change in Africa in a 1.5 °C global warming world

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-04-01

At the 21st session of the UNFCCC Conference of the Parties (COP21) in Paris, a reaffirmation to strengthen the effort to limit the global temperature increase to 1.5 °C was decided. However, even if global warming is limited, some regions might still be substantially affected by climate change, especially for continents like Africa where the socio-economic conditions are strongly linked to the climatic conditions. Hence, providing a detailed analysis of the projected climate changes in a 1.5 °C global warming scenario will allow the African society to undertake measures for adaptation in order to mitigate potential negative consequences. In order to provide such climate change information, the existing CORDEX Africa ensemble for RCP2.6 scenario simulations has systematically been increased by conducting additional REMO simulations using data from various global circulation models (GCMs) as lateral boundary conditions. Based on this ensemble, which now consists of eleven CORDEX Africa RCP2.6 regional climate model simulations from three RCMs (forced with different GCMs), various temperature and precipitation indices such as number of cold/hot days and nights, duration of the rainy season, the amount of rainfall in the rainy seasons and the number of dry spells have been calculated for a 1.5 °C global warming scenario. The applied method to define the 1.5 °C global warming period has been already applied in the IMPACT2C project. In our presentation, we will discuss the analysis of the climate indices in a 1.5 °C global warming world for the CORDEX-Africa region. Amongst presenting the magnitude of projected changes, we will also address the question for selected indices if the changes projected in a 1.5 °C global warming scenario are already larger than the climate variability and we will also draw links to the changes projected under a more extreme scenario.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Toward 10-km mesh global climate simulations

NASA Astrophysics Data System (ADS)

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.

Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

NASA Astrophysics Data System (ADS)

Fuhrer, Oliver; Chadha, Tarun; Hoefler, Torsten; Kwasniewski, Grzegorz; Lapillonne, Xavier; Leutwyler, David; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph; Schulthess, Thomas C.; Vogt, Hannes

2018-05-01

The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth - the dominant bottleneck of climate codes - is being used.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

NASA Astrophysics Data System (ADS)

Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

2016-09-01

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Multi-millennia simulation of Greenland deglaciation from the Max-Plank-Institute Model (MPI-ISM) 2xCO2 simulation

NASA Astrophysics Data System (ADS)

Cabot, Vincent; Vizcaino, Miren; Mikolajewicz, Uwe

2016-04-01

Long-term ice sheet and climate coupled simulations are of great interest since they assess how the Greenland Ice Sheet (GrIS) will respond to global warming and how GrIS changes will impact on the climate system. We have run the Max-Plank-Institute Earth System Model coupled with an Ice Sheet Model (SICOPOLIS) over a time period of 10500 years under two times CO2 forcing. This is a coupled atmosphere (ECHAM5T31), ocean (MPI-OM), dynamic vegetation (LPJ), and ice sheet (SICOPOLIS, 10 km horizontal resolution) model. Given the multi-millennia simulation, the horizontal spatial resolution of the atmospheric component is relatively coarse (3.75°). A time-saving technique (asynchronous coupling) is used once the global climate reaches quasi-equilibrium. In our doubling-CO2 simulation, the GrIS is expected to break up into two pieces (one ice cap in the far north on one ice sheet in the south and east) after 3000 years. During the first 500 simulation years, the GrIS climate and surface mass balance (SMB) are mainly affected by the greenhouse effect-forced climate change. After the simulated year 500, the global climate reaches quasi-equilibrium. Henceforth Greenland climate change is mainly due to ice sheet decay. GrIS albedo reduction enhances melt and acts as a powerful feedback for deglaciation. Due to increased cloudiness in the Arctic region as a result of global climate change, summer incoming shortwave radiation is substantially reduced over Greenland, reducing deglaciation rates. At the end of the simulation, Greenland becomes green with forest growing over the newly deglaciated regions. References: Helsen, M. M., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., and Oerlemans, J. (2013), Coupled regional climate-ice-sheet simulation shows limited Greenland ice loss during the Eemian, Climate of the Past, 9, 1773-1788, doi: 10.5194/cp-9-1773-2013 Helsen, M. M., van de Wal, R. S. W., van den Broeke, M. R., van de Berg, W. J., and Oerlemans, J. (2015), Coupling of climate models and ice sheet models by the surface mass balance gradients: application to the Greenland Ice Sheet, The Cryosphere, 6, 255-272, doi: 10.5194/tc-6-255-2012 Robinson, A., Calov, R., and Ganopolski, A. (2011), Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial, Climate of the Past, 7, 381-396, doi: 10.5194/cp-7-381-2011 Vizcaino, M., Mikolajewicz, U., Ziemen, F., Rodehacke, C. B., Greve, R., and van den Broeke, M. R. (2015), Coupled simulations of Greenland Ice Sheet and climate change up to A.D. 2300, Geophysical Research Letters, 42, doi: 10.1002/2014GL061142

On the limitations of General Circulation Climate Models

NASA Technical Reports Server (NTRS)

Stone, Peter H.; Risbey, James S.

1990-01-01

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality

EPA Science Inventory

We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

PubMed Central

Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

2012-01-01

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

Global and Arctic climate engineering: numerical model studies.

PubMed

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.

Biomes computed from simulated climatologies

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

Claussen, M.; Esch, M.

1994-01-01

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

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

NASA Technical Reports Server (NTRS)

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

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

NASA Astrophysics Data System (ADS)

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.

High Resolution Modeling of Hurricanes in a Climate Context

NASA Astrophysics Data System (ADS)

Knutson, T. R.

2007-12-01

Modeling of tropical cyclone activity in a climate context initially focused on simulation of relatively weak tropical storm-like disturbances as resolved by coarse grid (200 km) global models. As computing power has increased, multi-year simulations with global models of grid spacing 20-30 km have become feasible. Increased resolution also allowed for simulation storms of increasing intensity, and some global models generate storms of hurricane strength, depending on their resolution and other factors, although detailed hurricane structure is not simulated realistically. Results from some recent high resolution global model studies are reviewed. An alternative for hurricane simulation is regional downscaling. An early approach was to embed an operational (GFDL) hurricane prediction model within a global model solution, either for 5-day case studies of particular model storm cases, or for "idealized experiments" where an initial vortex is inserted into an idealized environments derived from global model statistics. Using this approach, hurricanes up to category five intensity can be simulated, owing to the model's relatively high resolution (9 km grid) and refined physics. Variants on this approach have been used to provide modeling support for theoretical predictions that greenhouse warming will increase the maximum intensities of hurricanes. These modeling studies also simulate increased hurricane rainfall rates in a warmer climate. The studies do not address hurricane frequency issues, and vertical shear is neglected in the idealized studies. A recent development is the use of regional model dynamical downscaling for extended (e.g., season-length) integrations of hurricane activity. In a study for the Atlantic basin, a non-hydrostatic model with grid spacing of 18km is run without convective parameterization, but with internal spectral nudging toward observed large-scale (basin wavenumbers 0-2) atmospheric conditions from reanalyses. Using this approach, our model reproduces the observed increase in Atlantic hurricane activity (numbers, Accumulated Cyclone Energy (ACE), Power Dissipation Index (PDI), etc.) over the period 1980-2006 fairly realistically, and also simulates ENSO-related interannual variations in hurricane counts. Annual simulated hurricane counts from a two-member ensemble correlate with observed counts at r=0.86. However, the model does not simulate hurricanes as intense as those observed, with minimum central pressures of 937 hPa (category 4) and maximum surface winds of 47 m/s (category 2) being the most intense simulated so far in these experiments. To explore possible impacts of future climate warming on Atlantic hurricane activity, we are re-running the 1980- 2006 seasons, keeping the interannual to multidecadal variations unchanged, but altering the August-October mean climate according to changes simulated by an 18-member ensemble of AR4 climate models (years 2080- 2099, A1B emission scenario). The warmer climate state features higher Atlantic SSTs, and also increased vertical wind shear across the Caribbean (Vecchi and Soden, GRL 2007). A key assumption of this approach is that the 18-model ensemble-mean climate change is the best available projection of future climate change in the Atlantic. Some of the 18 global models show little increase in wind shear, or even a decrease, and thus there will be considerable uncertainty associated with the hurricane frequency results, which will require further exploration. Results from our simulations will be presented at the meeting.

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

2001-01-01

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Impact of global warming on tropical cyclone genesis in coupled and forced simulations: role of SST spatial anomalies

NASA Astrophysics Data System (ADS)

Royer, Jean-François; Chauvin, Fabrice; Daloz, Anne-Sophie

2010-05-01

The response of tropical cyclones (TC) activity to global warming has not yet reached a clear consensus in the Fourth Assessment Report (AR4) published by the Intergovernmental Panel on Climate Change (IPCC, 2007) or in the recent scientific literature. Observed series are neither long nor reliable enough for a statistically significant detection and attribution of past TC trends, and coupled climate models give widely divergent results for the future evolution of TC activity in the different ocean basins. The potential importance of the spatial structure of the future SST warming has been pointed out by Chauvin et al. (2006) in simulations performed at CNRM with the ARPEGE-Climat GCM. The current presentation describes a new set of simulations that have been performed with the ARPEGE-Climat model to try to understand the possible role of SST patterns in the TC cyclogenesis response in 15 CMIP3 coupled simulations analysed by Royer et al (2009). The new simulations have been performed with the atmospheric component of the ARPEGE-Climat GCM forced in 10 year simulations by the SST patterns from each of 15 CMIP3 simulations with different climate model at the end of the 21st century according to scenario A2. The TC analysis is based on the computation of a Convective Yearly Genesis Parameter (CYGP) and the Genesis Potential Index (GPI). The computed genesis indices for each of the ARPEGE-Climat forced simulations is compared with the indices computed directly from the initial coupled simulation. The influence of SST patterns can then be more easily assessed since all the ARPEGE-Climat simulations are performed with the same atmospheric model, whereas the original simulations used models with different parameterization and resolutions. The analysis shows that CYGP or GPI anomalies obtained with ARPEGE are as variable between each other as those obtained originally by the different IPCC models. The variety of SST patterns used to force ARPEGE explains a large part of the dispersion, though for a given SST pattern, ARPEGE does not necessarily reproduce the anomaly produced originally by the IPCC model which produced the SST anomaly. Many factors can contribute to this discrepancy, but the most prominent seems to be the absence of coupling between the forced atmospheric ARPEGE simulation and the underlying ocean. When the atmospheric model is forced by prescribed SST anomalies some retroactions between cyclogenesis and ocean are missing. There are however areas over the globe were models agree about the CYGP or GPI anomalies induced by global warming, such as the Indian Ocean that shows a better coherency in the coupled and forced responses. This could be an indication that interaction between ocean and atmosphere is not as strong there as in the other basins. Details of the results for all the other ocean basins will be presented. References: Chauvin F. and J.-F. Royer and M. Déqué , 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dynamics 27(4), 377-399. IPCC [Intergovernmental Panel for Climate Change], Climate change 2007: The physical science basis, in: S. Solomon et al. (eds.), Cambridge University Press. Royer JF, F Chauvin, 2009: Response of tropical cyclogenesis to global warming in an IPCC AR-4 scenario assessed by a modified yearly genesis parameter. "Hurricanes and Climate Change", J. B. Elsner and T. H. Jagger (Eds.), Springer, ISBN: 978-0-387-09409-0, pp 213-234.

Future change in seasonal march of snow water equivalent due to global climate change

NASA Astrophysics Data System (ADS)

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

2012-04-01

Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

Climate in the absence of ocean heat transport

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2017-12-01

The energy transported by the oceans to mid- and high latitudes is small compared to the atmosphere, yet exerts an outsized influence on climate. A key reason is the strong interaction between ocean heat transport (OHT) and sea ice extent. I quantify the absolute climatic impact of OHT using the state-of-the-art CESM simulations by comparing a realistic control climate against a slab ocean simulation in which OHT is disabled. The absence of OHT leads to a massive expansion of sea ice into the subtropics in both hemispheres, and a 24 K global cooling. Analysis of the transient simulation after setting the OHT to zero reveals a global cooling process fueled by a runaway sea ice albedo feedback. This process is eventually self-limiting in the cold climate due to a combination of subtropical cloud feedbacks and surface wind effects that are both connected to a massive spin-up of the atmospheric Hadley circulation. A parameter sensitivity study shows that the simulated climate is far more sensitive to small changes in ice surface albedo in the absence of OHT. I conclude that the oceans are responsible for an enormous global warming by mitigating an otherwise very potent sea ice albedo feedback, but that the magnitude of this effect is rather uncertain. These simulations provide a graphic illustration of how the intimate coupling between sea ice and ocean circulation governs the present-day climate, and by extension, highlight the importance of modeling ocean - sea ice interaction with high fidelity.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Impacts of Stratospheric Black Carbon on Agriculture

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.; Elliott, J. W.

2017-12-01

A regional nuclear war between India and Pakistan could inject 5 Tg of soot into the stratosphere, which would absorb sunlight, decrease global surface temperature by about 1°C for 5-10 years and have major impacts on precipitation and the amount of solar radiation reaching Earth's surface. Using two global gridded crop models forced by one global climate model simulation, we investigate the impacts on agricultural productivity in various nations. The crop model in the Community Land Model 4.5 (CLM-crop4.5) and the parallel Decision Support System for Agricultural Technology (pDSSAT) in the parallel System for Integrating Impact Models and Sectors are participating in the Global Gridded Crop Model Intercomparison. We force these two crop models with output from the Whole Atmospheric Community Climate Model to characterize the global agricultural impact from climate changes due to a regional nuclear war. Crops in CLM-crop4.5 include maize, rice, soybean, cotton and sugarcane, and crops in pDSSAT include maize, rice, soybean and wheat. Although the two crop models require a different time frequency of weather input, we downscale the climate model output to provide consistent temperature, precipitation and solar radiation inputs. In general, CLM-crop4.5 simulates a larger global average reduction of maize and soybean production relative to pDSSAT. Global rice production shows negligible change with climate anomalies from a regional nuclear war. Cotton and sugarcane benefit from a regional nuclear war from CLM-crop4.5 simulation, and global wheat production would decrease significantly in the pDSSAT simulation. The regional crop yield responses to a regional nuclear conflict are different for each crop, and we present the changes in production on a national basis. These models do not include the crop responses to changes in ozone, ultraviolet radiation, or diffuse radiation, and we would like to encourage more modelers to improve crop models to account for those impacts. We present these results as a demonstration of using different crop models to study this problem, and we invite more global crop modeling groups to use the same climate forcing, which we would be happy to provide, to gain a better understanding of global agricultural responses under different future climate scenarios with stratospheric aerosols.

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

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”

EPA Science Inventory

Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

PubMed Central

Porada, P.; Lenton, T. M.; Pohl, A.; Weber, B.; Mander, L.; Donnadieu, Y.; Beer, C.; Pöschl, U.; Kleidon, A.

2016-01-01

It has been hypothesized that predecessors of today's bryophytes significantly increased global chemical weathering in the Late Ordovician, thus reducing atmospheric CO2 concentration and contributing to climate cooling and an interval of glaciations. Studies that try to quantify the enhancement of weathering by non-vascular vegetation, however, are usually limited to small areas and low numbers of species, which hampers extrapolating to the global scale and to past climatic conditions. Here we present a spatially explicit modelling approach to simulate global weathering by non-vascular vegetation in the Late Ordovician. We estimate a potential global weathering flux of 2.8 (km3 rock) yr−1, defined here as volume of primary minerals affected by chemical transformation. This is around three times larger than today's global chemical weathering flux. Moreover, we find that simulated weathering is highly sensitive to atmospheric CO2 concentration. This implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate. PMID:27385026

Scaling a Convection-Resolving RCM to Near-Global Scales

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Chadha, T.; Kwasniewski, G.; Hoefler, T.; Lapillonne, X.; Lüthi, D.; Osuna, C.; Schar, C.; Schulthess, T. C.; Vogt, H.

2017-12-01

In the recent years, first decade-long kilometer-scale resolution RCM simulations have been performed on continental-scale computational domains. However, the size of the planet Earth is still an order of magnitude larger and thus the computational implications of performing global climate simulations at this resolution are challenging. We explore the gap between the currently established RCM simulations and global simulations by scaling the GPU accelerated version of the COSMO model to a near-global computational domain. To this end, the evolution of an idealized moist baroclinic wave has been simulated over the course of 10 days with a grid spacing of up to 930 m. The computational mesh employs 36'000 x 16'001 x 60 grid points and covers 98.4% of the planet's surface. The code shows perfect weak scaling up to 4'888 Nodes of the Piz Daint supercomputer and yields 0.043 simulated years per day (SYPD) which is approximately one seventh of the 0.2-0.3 SYPD required to conduct AMIP-type simulations. However, at half the resolution (1.9 km) we've observed 0.23 SYPD. Besides formation of frontal precipitating systems containing embedded explicitly-resolved convective motions, the simulations reveal a secondary instability that leads to cut-off warm-core cyclonic vortices in the cyclone's core, once the grid spacing is refined to the kilometer scale. The explicit representation of embedded moist convection and the representation of the previously unresolved instabilities exhibit a physically different behavior in comparison to coarser-resolution simulations. The study demonstrates that global climate simulations using kilometer-scale resolution are imminent and serves as a baseline benchmark for global climate model applications and future exascale supercomputing systems.

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

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

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 climatemore » 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.« less

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

NASA Astrophysics Data System (ADS)

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

2012-09-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon cycle range. These high end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real world climate sensitivity constraints which, if achieved, would lead to reductions on the uppper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present day observables and future changes while the large spread of future projected changes, highlights the ongoing need for such work.

The Prodiguer Messaging Platform

NASA Astrophysics Data System (ADS)

Denvil, S.; Greenslade, M. A.; Carenton, N.; Levavasseur, G.; Raciazek, J.

2015-12-01

CONVERGENCE is a French multi-partner national project designed to gather HPC and informatics expertise to innovate in the context of running French global climate models with differing grids and at differing resolutions. Efficient and reliable execution of these models and the management and dissemination of model output are some of the complexities that CONVERGENCE aims to resolve.At any one moment in time, researchers affiliated with the Institut Pierre Simon Laplace (IPSL) climate modeling group, are running hundreds of global climate simulations. These simulations execute upon a heterogeneous set of French High Performance Computing (HPC) environments. The IPSL's simulation execution runtime libIGCM (library for IPSL Global Climate Modeling group) has recently been enhanced so as to support hitherto impossible realtime use cases such as simulation monitoring, data publication, metrics collection, simulation control, visualizations … etc. At the core of this enhancement is Prodiguer: an AMQP (Advanced Message Queue Protocol) based event driven asynchronous distributed messaging platform. libIGCM now dispatches copious amounts of information, in the form of messages, to the platform for remote processing by Prodiguer software agents at IPSL servers in Paris. Such processing takes several forms: Persisting message content to database(s); Launching rollback jobs upon simulation failure; Notifying downstream applications; Automation of visualization pipelines; We will describe and/or demonstrate the platform's: Technical implementation; Inherent ease of scalability; Inherent adaptiveness in respect to supervising simulations; Web portal receiving simulation notifications in realtime.

Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change

NASA Astrophysics Data System (ADS)

He, F.; Vavrus, S. J.; Kutzbach, J. E.; Ruddiman, W. F.; Kaplan, J. O.; Krumhardt, K. M.

2015-12-01

Surface albedo changes from anthropogenic land cover change (ALCC) represent the second-largest negative radiative forcing behind aerosol during the industrial era. Using a new reconstruction of ALCC during the Holocene era by Kaplan et al. [2011], we quantify the local and global temperature response induced by Holocene ALCC in the Community Climate System Model, version 4 (CCSM4). With 1-degree resolution of the CCSM4 slab-ocean model,we find that Holocene ALCC cause a global cooling of 0.17 °C due to the biogeophysical effects of land-atmosphere exchange of momentum, moisture, radiative and heat fluxes. On the global scale, the biogeochemical effects of Holocene ALCC from carbon emissions dominate the biogeophysical effects by causing 0.9 °C global warming. The net effects of Holocene ALCC amount to a global warming of 0.73 °C during the pre-industrial era, which is comparable to the ~0.8 °C warming during industrial times. On local to regional scales, such as parts of Europe, North America and Asia, the biogeophysical effects of Holocene ALCC are significant and comparable to the biogeochemical effect. The lack of ocean dynamics in the 1° CCSM4 slab-ocean simulations could underestimate the climate sensitivity because of the lack of feedbacks from ocean heat transport [Kutzbach et al., 2013; Manabe and Bryan, 1985]. In 1° CCSM4 fully coupled simulations, the climate sensitivity is ~65% larger than the 1° CCSM4 slab-ocean simulations during the Holocene (5.3 °C versus 3.2 °C) [Kutzbach et al., 2013]. With this greater climate sensitivity, the biogeochemical effects of Holocene ALCC could have caused a global warming of ~1.5 °C, and the net biogeophysical and biogeochemical effects of Holocene ALCC could cause a global warming of 1.2 °C during the preindustrial era in our simulations, which is 50% higher than the global warming of ~0.8 °C during industrial times.

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans

NASA Astrophysics Data System (ADS)

Brown, Patrick T.; Li, Wenhong; Jiang, Jonathan H.; Su, Hui

2016-12-01

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.

Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey

2017-06-01

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.