Clouds enhance Greenland ice sheet meltwater runoff.

PubMed

Van Tricht, K; Lhermitte, S; Lenaerts, J T M; Gorodetskaya, I V; L'Ecuyer, T S; Noël, B; van den Broeke, M R; Turner, D D; van Lipzig, N P M

2016-01-12

The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m(-2). Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

Clouds enhance Greenland ice sheet meltwater runoff

PubMed Central

Van Tricht, K.; Lhermitte, S.; Lenaerts, J. T. M.; Gorodetskaya, I. V.; L'Ecuyer, T. S.; Noël, B.; van den Broeke, M. R.; Turner, D. D.; van Lipzig, N. P. M.

2016-01-01

The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m−2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise. PMID:26756470

Cloud feedback mechanisms and their representation in global climate models

DOE PAGES

Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.; ...

2017-05-11

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less

Cloud feedback mechanisms and their representation in global climate models

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

Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less

Is U.S. climatic diversity well represented within the existing federal protection network?

PubMed

Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.

Arctic indigenous peoples as representations and representatives of climate change.

PubMed

Martello, Marybeth Long

2008-06-01

Recent scientific findings, as presented in the Arctic Climate Impact Assessment (ACIA), indicate that climate change in the Arctic is happening now, at a faster rate than elsewhere in the world, and with major implications for peoples of the Arctic (especially indigenous peoples) and the rest of the planet. This paper examines scientific and political representations of Arctic indigenous peoples that have been central to the production and articulation of these claims. ACIA employs novel forms and strategies of representation that reflect changing conceptual models and practices of global change science and depict indigenous peoples as expert, exotic, and at-risk. These portrayals emerge alongside the growing political activism of Arctic indigenous peoples who present themselves as representatives or embodiments of climate change itself as they advocate for climate change mitigation policies. These mutually constitutive forms of representation suggest that scientific ways of seeing the global environment shape and are shaped by the public image and voice of global citizens. Likewise, the authority, credibility, and visibility of Arctic indigenous activists derive, in part, from their status as at-risk experts, a status buttressed by new scientific frameworks and methods that recognize and rely on the local experiences and knowledges of indigenous peoples. Analyses of these relationships linking scientific and political representations of Arctic climate change build upon science and technology studies (STS) scholarship on visualization, challenge conventional notions of globalization, and raise questions about power and accountability in global climate change research.

Multiple External Representations: Bridges or Barriers to Climate Literacy?

NASA Astrophysics Data System (ADS)

Holzer, M. A.

2012-12-01

The continuous barrage of science related headlines and other media sources warn us of the need to heed the imperative for a science literate society. Climate change, genetics, evolution are a few of the charged and complex scientific topics requiring public understanding of the science to fully grasp the enormous reach of these topics in our daily lives. For instance, our global climate is changing as evidenced by the analysis of Earth observing satellite data, in-situ data, and proxy data records. How we as a global society decide to address the needs associated with a changing climate are contingent upon having a population that understands how the climate system functions, and can therefore make informed decisions on how to mitigate the effects of climate change. Communication in science relies heavily on the use of multiple representations to support the claims presented. However, these multiple representations require spatial and temporal skills to interpret information portrayed in them, and how a person engages with complex text and the multiple representations varies with the level of expertise one has with the content area. For example, a climatologist will likely identify anomalous data more quickly than a novice when presented with a graph of temperature change over time. These representations are used throughout textbooks as well as popular reading materials such as newspapers and magazines without much consideration for how a reader engages with complex text, diagrams, images, and graphs. If the ability to read and interact with scientific text found in popular literature is perceived as a worthy goal of scientific literacy, then it is imperative that readers understand the relationship between multiple representations and the text while interacting with the science literature they are reading. For example, in climate related articles multiple representations not only support the content, but they are part of the content not to be overlooked by a reader. Climatologists recognize the wealth of data and content found in these representations and therefore find themselves in a position where they can effectively interact with the author and their claims. This expert ability to seamlessly integrate text with the associated representations is at one end of the continuum of scientific text comprehension, but what abilities define a novice and those in between expert and novice in this continuum of scientific text comprehension? This talk will describe an ongoing research project with the overarching goal to establish the balance of this continuum in order to identify scaffolds that will assist non expert readers negotiate meaning from complex scientific text inclusive of multiple representations found in popular literature in climatology. It will inform those creating data representations on how best to create the representations so that claims and causal relationships may be derived from the literature or media source.

Reserve Design under Climate Change: From Land Facets Back to Ecosystem Representation

PubMed Central

Schneider, Richard R.; Bayne, Erin M.

2015-01-01

Ecosystem distributions are expected to shift as a result of global warming, raising concerns about the long-term utility of reserve systems based on coarse-filter ecosystem representation. We tested the extent to which proportional ecosystem representation targets would be maintained under a changing climate by projecting the distribution of the major ecosystems of Alberta, Canada, into the future using bioclimatic envelope models and then calculating the composition of reserves in successive periods. We used the Marxan conservation planning software to generate the suite of reserve systems for our test, varying the representation target and degree of reserve clumping. Our climate envelope projections for the 2080s indicate that virtually all reserves will, in time, be comprised of different ecosystem types than today. Nevertheless, our proportional targets for ecosystem representation were maintained across all time periods, with only minor exceptions. We hypothesize that this stability in representation arises because ecosystems may be serving as proxies for land facets, the stable abiotic landscape features that delineate major arenas of biological activity. The implication is that accommodating climate change may not require abandoning the conventional ecosystem-based approach to reserve design in favour of a strictly abiotic approach, since the two approaches may be largely synonymous. PMID:25978759

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Modification of land-atmosphere interactions by CO2 effects

NASA Astrophysics Data System (ADS)

Lemordant, Leo; Gentine, Pierre

2017-04-01

Plant stomata couple the energy, water and carbon cycles. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the impact of potential heat waves. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels, and of the coupling between the carbon and water cycles are therefore critical to forecasting seasonal climate, water cycle dynamics and to enhance the accuracy of extreme event prediction under future climate.

Improving the Representation of Land in Climate Models by Application of EOS Observations

NASA Technical Reports Server (NTRS)

2004-01-01

The PI's IDS current and previous investigation has focused on the applications of the land data toward the improvement of climate models. The previous IDS research identified the key factors limiting the accuracy of climate models to be the representation of albedos, land cover, fraction of landscape covered by vegetation, roughness lengths, surface skin temperature and canopy properties such as leaf area index (LAI) and average stomatal conductance. Therefore, we assembled a team uniquely situated to focus on these key variables and incorporate the remotely sensed measures of these variables into the next generation of climate models.

Representing agriculture in Earth System Models: Approaches and priorities for development

NASA Astrophysics Data System (ADS)

McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

2017-09-01

Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

NASA Technical Reports Server (NTRS)

Potter, Christopher; Malhi, Yadvinder

2004-01-01

Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

Improving Climate and Gender Equity in Physics Departments

NASA Astrophysics Data System (ADS)

Yennello, Sherry

2010-02-01

We need to open the door of science to women and minorities. We need to invite them in and encourage them to succeed. We need to teach them the secret handshake and transfer all the writing on the men's room walls and all-white country clubs into accessible places. We need to promote them to positions of national prominence. We need to do this out of respect to our mothers and the pioneering scientists who have come before us. We need to do this for our daughters and sons, so that our grandchildren may only know this discrimination as a piece of history. We need to do this now -- for the sake of our country, our science, our technical workforce, our economy and because it is the right thing to do. The Committee on the Status of Women in Physics (CSWP) has been helping physics departments improve their climate as a means to enhance gender equity. The CSWP site visit program has been giving departments valuable feedback on their climate for many years. In May 2007, a workshop on ``Gender Equity: Enhancing the Physics Enterprise in Universities and National Laboratories'' was held to address the issue of underrepresentation of women in physics by engaging the stake holders. This fall a new ``Conversation on Gender Equity'' has begun. Successful strategies for improving the climate and increasing the representation of women in physics will be presented. )

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

NASA Astrophysics Data System (ADS)

Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

2016-02-01

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

Presentation of uncertainties on web platforms for climate change information

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Wrobel, Markus; Reusser, Dominik

2014-05-01

Climate research has a long tradition, however there is still uncertainty about the specific effects of climate change. One of the key tasks is - beyond discussing climate change and its impacts in specialist groups - to present these to a wider audience. In that respect, decision-makers in the public sector as well as directly affected professional groups require to obtain easy-to-understand information. These groups are not made up of specialist scientists. This gives rise to the challenge that the scientific information must be presented such that it is commonly understood, however, the complexity of the science behind needs to be incorporated. In particular, this requires the explicit representation of spatial and temporal uncertainty information to lay people. Within this talk/poster we survey how climate change and climate impact uncertainty information is presented on various climate service web-based platforms. We outline how the specifics of this medium make it challenging to find adequate and readable representations of uncertainties. First, we introduce a multi-step approach in communicating the uncertainty basing on a typology of uncertainty distinguishing between epistemic, natural stochastic, and human reflexive uncertainty. Then, we compare existing concepts and representations for uncertainty communication with current practices on web-based platforms, including own solutions within our web platforms ClimateImpactsOnline and ci:grasp. Finally, we review surveys on how spatial uncertainty visualization techniques are conceived by untrainded users.

Modification of land-atmosphere interactions by CO2 effects: Implications for summer dryness and heat wave amplitude

NASA Astrophysics Data System (ADS)

Lemordant, Léo.; Gentine, Pierre; Stéfanon, Marc; Drobinski, Philippe; Fatichi, Simone

2016-10-01

Plant stomata couple the energy, water, and carbon cycles. We use the framework of Regional Climate Modeling to simulate the 2003 European heat wave and assess how higher levels of surface CO2 may affect such an extreme event through land-atmosphere interactions. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the heat wave impact. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels and of the coupling between the carbon and water cycles is therefore critical to forecasting seasonal climate, water cycle dynamics, and to enhance the accuracy of extreme event prediction under future climate.

Ocean Dynamics in the Key Regions of North Atlantic-Arctic Exchanges: Evaluation of Global Multi-Resolution FESOM and CMIP-type INMCM Models with Long-Term Observations

NASA Astrophysics Data System (ADS)

Beszczynska-Moeller, A.; Gürses, Ö.; Sidorenko, D.; Goessling, H.; Volodin, E. M.; Gritsun, A.; Iakovlev, N. G.; Andrzejewski, J.

2017-12-01

Enhancing the fidelity of climate models in the Arctic and North Atlantic in order to improve Arctic predictions requires better understanding of the underlying causes of common biases. The main focus of the ERA.Net project NAtMAP (Amending North Atlantic Model Biases to Improve Arctic Predictions) is on the dynamics of the key regions connecting the Arctic and the North Atlantic climate. The study aims not only at increased model realism, but also at a deeper understanding of North Atlantic-Arctic links and their contribution to Arctic predictability. Two complementary approaches employing different global coupled climate models, ECHAM6-FESOM and INMCM4/5, were adopted. The first approach is based on a recent development of climate models with ocean components based on unstructured meshes, allowing to resolve eddies and narrow boundary currents in the most crucial regions while keeping a moderate resolution elsewhere. The multi-resolution sea ice-ocean component of ECHAM6-FESOM allows studying the benefits of very high resolution in key areas of the North Atlantic. An alternative approach to address the North Atlantic and Arctic biases is also tried by tuning the performance of the relevant sub-grid-scale parameterizations in eddy resolving version the CMIP5 climate model INMCM4. Using long-term in situ and satellite observations and available climatologies we attempt to evaluate to what extent a higher resolution, allowing the explicit representation of eddies and narrow boundary currents in the North Atlantic and Nordic Seas, can alleviate the common model errors. The effects of better resolving the Labrador Sea area on reducing the model bias in surface hydrography and improved representation of ocean currents are addressed. Resolving eddy field in the Greenland Sea is assessed in terms of reducing the deep thermocline bias. The impact of increased resolution on the modeled characteristics of Atlantic water transport into the Arctic is examined with a special focus on separation of Atlantic inflow between Fram Strait and the Barents Sea, lateral exchanges in the Nordic Seas, and a role of eddies in modulating the poleward flow of Atlantic water. We also explore the effects of resolving boundary currents in the Arctic basin on the representation of the adjacent sea ice.

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert

2017-08-01

Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.

Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

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

Zhang, Yang; Leung, L. Ruby; Fan, Jiwen

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and globalmore » climate models.« less

The atmospheric ocean: eddies and jets in the Antarctic Circumpolar Current.

PubMed

Thompson, Andrew F

2008-12-28

Although the Antarctic Circumpolar Current (ACC) is the longest and the strongest oceanic current on the Earth and is the primary means of inter-basin exchange, it remains one of the most poorly represented components of global climate models. Accurately describing the circulation of the ACC is made difficult owing to the prominent role that mesoscale eddies and jets, oceanic equivalents of atmospheric storms and storm tracks, have in setting the density structure and transport properties of the current. The successes and limitations of different representations of eddy processes in models of the ACC are considered, with particular attention given to how the circulation responds to changes in wind forcing. The dynamics of energetic eddies and topographically steered jets may both temper and enhance the sensitivity of different aspects of the ACC's circulation to changes in climate.

Alleviating tropical Atlantic sector biases in the Kiel climate model by enhancing horizontal and vertical atmosphere model resolution: climatology and interannual variability

NASA Astrophysics Data System (ADS)

Harlaß, Jan; Latif, Mojib; Park, Wonsun

2018-04-01

We investigate the quality of simulating tropical Atlantic (TA) sector climatology and interannual variability in integrations of the Kiel climate model (KCM) with varying atmosphere model resolution. The ocean model resolution is kept fixed. A reasonable simulation of TA sector annual-mean climate, seasonal cycle and interannual variability can only be achieved at sufficiently high horizontal and vertical atmospheric resolution. Two major reasons for the improvements are identified. First, the western equatorial Atlantic westerly surface wind bias in spring can be largely eliminated, which is explained by a better representation of meridional and especially vertical zonal momentum transport. The enhanced atmospheric circulation along the equator in turn greatly improves the thermal structure of the upper equatorial Atlantic with much reduced warm sea surface temperature (SST) biases. Second, the coastline in the southeastern TA and steep orography are better resolved at high resolution, which improves wind structure and in turn reduces warm SST biases in the Benguela upwelling region. The strongly diminished wind and SST biases at high atmosphere model resolution allow for a more realistic latitudinal position of the intertropical convergence zone. Resulting stronger cross-equatorial winds, in conjunction with a shallower thermocline, enable a rapid cold tongue development in the eastern TA in boreal spring. This enables simulation of realistic interannual SST variability and its seasonal phase locking in the KCM, which primarily is the result of a stronger thermocline feedback. Our findings suggest that enhanced atmospheric resolution, both vertical and horizontal, could be a key to achieving more realistic simulation of TA climatology and interannual variability in climate models.

Basic state lower-tropospheric humidity distribution: key to successful simulation and prediction of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Kim, D.; Ahn, M. S.; DeMott, C. A.; Jiang, X.; Klingaman, N. P.; Kim, H. M.; Lee, J. H.; Lim, Y.; Xavier, P. K.

2017-12-01

The Madden-Julian Oscillation (MJO) influences the global weather-climate system, thereby providing the source of predictability on the intraseasonal timescales worldwide. An accurate representation of the MJO, however, is still one of the most challenging tasks for many contemporary global climate models (GCMs). Identifying aspects of the GCMs that are tightly linked to GCMs' MJO simulation capability is a step toward improving the GCM representation of the MJO. This study surveys recent modeling work that collectively evidence that the horizontal distribution of the basic state low-tropospheric humidity is crucial to a successful simulation and prediction of the MJO. Specifically, the simulated horizontal and meridional gradients of the mean low-tropospheric humidity determine the magnitude of the moistening (drying) to the east (west) of the enhance MJO, thereby enabling or disabling the eastward propagation of the MJO. Supporting this argument, many MJO-incompetent GCMs also exhibit biases in the mean humidity that weaken the horizontal moisture gradient. Also, MJO prediction skill of the S2S models is tightly related to the biases in the mean moisture gradient. Implications of the robust relationship between the MJO and the mean state on MJO modeling and prediction will be discussed.

Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

ERIC Educational Resources Information Center

Rau, Martina A.

2017-01-01

Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students' learning of content knowledge, compared to text-only. But should students learn with a single type of visual…

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Enhancing Young Infants' Representations of Physical Events through Improved Retrieval (Not Encoding) of Information

ERIC Educational Resources Information Center

Wang, Su-hua; Onishi, Kristine H.

2017-01-01

Infants' representations of physical events are surprisingly flexible. Brief exposure to one event can immediately enhance infants' representations of another event. The present experiments tested two potential mechanisms underlying this priming: enhanced encoding or improved retrieval. Five-month-olds saw a target block become hidden inside a…

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

The regional climate model REMO (v2015) coupled with the 1-D freshwater lake model FLake (v1): Fenno-Scandinavian climate and lakes

NASA Astrophysics Data System (ADS)

Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi

2018-04-01

The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.

Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

NASA Astrophysics Data System (ADS)

Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.

2013-08-01

This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

Increased future ice discharge from Antarctica owing to higher snowfall

NASA Astrophysics Data System (ADS)

Winkelmann, Ricarda; Levermann, Anders; Martin, Maria A.; Frieler, Katja

2013-04-01

Anthropogenic climate change is likely to cause continuing global sea-level rise, but some processes within the Earth system may mitigate the magnitude of the projected effect. Regional and global climate models simulate enhanced snowfall over Antarctica, which would provide a direct offset of the future contribution to global sea level rise from cryospheric mass loss and ocean expansion. Uncertainties exist in modelled snowfall, but even larger uncertainties exist in the potential changes of dynamic ice discharge from Antarctica. Here we show that snowfall and discharge are not independent, but that future ice discharge will increase by up to three times as a result of additional snowfall under global warming. Our results, based on an ice-sheet model forced by climate simulations through to the end of 2500, show that the enhanced discharge effect exceeds the effect of surface warming as well as that of basal ice-shelf melting, and is due to the difference in surface elevation change caused by snowfall on grounded versus floating ice. Although different underlying forcings drive ice loss from basal melting versus increased snowfall, similar ice dynamical processes are nonetheless at work in both; therefore results are relatively independent of the specific representation of the transition zone. In an ensemble of simulations designed to capture ice-physics uncertainty, the additional dynamic ice loss along the coastline compensates between 30 and 65 per cent of the ice gain due to enhanced snowfall over the entire continent. This results in a dynamic ice loss of up to 1.25 metres in the year 2500 for the strongest warming scenario.

Arctic atmospheric preconditioning: do not rule out shortwave radiation just yet

NASA Astrophysics Data System (ADS)

Sedlar, J.

2017-12-01

Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus in recent years. A general consensus points to enhanced poleward atmospheric transport of moisture and heat during spring, effectively increasing the emission of longwave radiation to the surface. Studies have essentially ruled out the role of shortwave radiation as an effective preconditioning mechanism because of the relatively weak incident solar radiation and high surface albedo from sea ice and snow during spring. These conclusions, however, are derived primarily from atmospheric reanalysis data, which may not always represent an accurate depiction of the Arctic climate system. Here, observations of top of atmosphere radiation from state of the art satellite sensors are examined and compared with reanalysis and climate model data to examine the differences in the spring radiative budget over the Arctic Ocean for years with extreme low/high ice extent at the end of the ice melt season (September). Distinct biases are observed between satellite-based measurements and reanalysis/models, particularly for the amount of shortwave radiation trapped (warming effect) within the Arctic climate system during spring months. A connection between the differences in reanalysis/model surface albedo representation and the albedo observed by satellite is discussed. These results suggest that shortwave radiation should not be overlooked as a significant contributing mechanism to springtime Arctic atmospheric preconditioning.

Quantifying Risks in the Global Water-Food-Climate Nexus in the Coming Decades: An Integrated Modeling Approach

NASA Astrophysics Data System (ADS)

Schlosser, C. A.; Strzepek, K.; Arndt, C.; Gueneau, A.; Cai, Y.; Gao, X.; Robinson, S.; Sokolov, A. P.; Thurlow, J.

2011-12-01

The growing need for risk-based assessments of impacts and adaptation to regional climate change calls for the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Moreover, our global water resources include energy, agricultural and environmental systems, which are linked together as well as to climate. With the prospect of potential climate change and associated shifts in hydrologic variation and extremes, the MIT Integrated Global Systems Model (IGSM) framework, in collaboration with UNU-WIDER, has enhanced its capabilities to model impacts (or effects) on the managed water-resource systems. We first present a hybrid approach that extends the MIT Integrated Global System Model (IGSM) framework to provide probabilistic projections of regional climate changes. This procedure constructs meta-ensembles of the regional hydro-climate, combining projections from the MIT IGSM that represent global-scale uncertainties with regionally resolved patterns from archived climate-model projections. From these, a river routing and water-resource management module allocates water among irrigation, hydropower, urban/industrial, and in-stream uses and investigate how society might adapt water resources due to shifts in hydro-climate variations and extremes. These results are then incorporated into economic models allowing us to consider the implications of climate for growth, land use, and development prospects. In this model-based investigation, we consider how changes in the regional hydro-climate over major river basins in southern Africa, Vietnam, as well as the United States impact agricultural productivity and water-management systems, and whether adaptive strategies can cope with the more severe climate-related threats to growth and development. All this is cast under a probabilistic description of regional climate changes encompassed by the IGSM framework.

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

Nitschke, Kim

The ARM Climate Research Facility, a DOE scientific user facility, provides the climate research community with strategically located in situ and remote sensing observatories designed to improve the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their interactions and coupling with the Earth’s surface.

Continuous versus discontinuous albedo representations in a simple diffusive climate model

NASA Astrophysics Data System (ADS)

Simmons, P. A.; Griffel, D. H.

1988-07-01

A one-dimensional annually and zonally averaged energy-balance model, with diffusive meridional heat transport and including icealbedo feedback, is considered. This type of model is found to be very sensitive to the form of albedo used. The solutions for a discontinuous step-function albedo are compared to those for a more realistic smoothly varying albedo. The smooth albedo gives a closer fit to present conditions, but the discontinuous form gives a better representation of climates in earlier epochs.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed

Ma, Xiaohui; Chang, Ping; Saravanan, R; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-12-04

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy-atmosphere interaction in forecast and climate models.

Changes in future air quality, deposition, and aerosol-cloud interactions under future climate and emission scenarios

NASA Astrophysics Data System (ADS)

Glotfelty, Timothy; Zhang, Yang; Karamchandani, Prakash; Streets, David G.

2016-08-01

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality is projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O3 level and of 0.3 μg m-3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO2, H2O2, and the nitrate radical and increasing the atmosphere's near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O3, and increases in CH4 and VOCs. Increasing NOx and O3 levels enhances the nitrogen and O3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth's surface with a global average reduction in shortwave radiation of 1.2 W m-2. This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR's CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.

Satellite-enhanced dynamical downscaling for the analysis of extreme events

NASA Astrophysics Data System (ADS)

Nunes, Ana M. B.

2016-09-01

The use of regional models in the downscaling of general circulation models provides a strategy to generate more detailed climate information. In that case, boundary-forcing techniques can be useful to maintain the large-scale features from the coarse-resolution global models in agreement with the inner modes of the higher-resolution regional models. Although those procedures might improve dynamics, downscaling via regional modeling still aims for better representation of physical processes. With the purpose of improving dynamics and physical processes in regional downscaling of global reanalysis, the Regional Spectral Model—originally developed at the National Centers for Environmental Prediction—employs a newly reformulated scale-selective bias correction, together with the 3-hourly assimilation of the satellite-based precipitation estimates constructed from the Climate Prediction Center morphing technique. The two-scheme technique for the dynamical downscaling of global reanalysis can be applied in analyses of environmental disasters and risk assessment, with hourly outputs, and resolution of about 25 km. Here the satellite-enhanced dynamical downscaling added value is demonstrated in simulations of the first reported hurricane in the western South Atlantic Ocean basin through comparisons with global reanalyses and satellite products available in ocean areas.

Application of an Integrated Assessment Model with state-level resolution for examining strategies for addressing air, climate and energy goals

EPA Science Inventory

The Global Climate Assessment Model (GCAM) is a global integrated assessment model used for exploring future scenarios and examining strategies that address air pollution, climate change, and energy goals. GCAM includes technology-rich representations of the energy, transportati...

Multi-representation based on scientific investigation for enhancing students’ representation skills

NASA Astrophysics Data System (ADS)

Siswanto, J.; Susantini, E.; Jatmiko, B.

2018-03-01

This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.

Hexagonal wavelet processing of digital mammography

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Schuler, Sergio; Huda, Walter; Honeyman-Buck, Janice C.; Steinbach, Barbara G.

1993-09-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: the hexagonal wavelet transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by local and global non-linear operators. Multiscale edges identified within distinct levels of transform space provide local support for enhancement. We demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

NASA Technical Reports Server (NTRS)

Zhang, Zhen; Babst, Flurin; Bellassen, Valentin; Frank, David; Launois, Thomas; Tan, Kun; Ciais, Philippe; Poulter, Benjamin

2017-01-01

The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feed backs of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of above ground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to year variation in plant growth.

Climate Penalty on Air Quality and Human Health in China and India

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2017-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Adaptation of global land use and management intensity to changes in climate and atmospheric carbon dioxide.

PubMed

Alexander, Peter; Rabin, Sam; Anthoni, Peter; Henry, Roslyn; Pugh, Thomas A M; Rounsevell, Mark D A; Arneth, Almut

2018-02-27

Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide (CO 2 ) levels' changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model (LPJ-GUESS) with a new land use and food system model (PLUMv2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO 2 concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Enhancing Undergraduate Chemistry Learning by Helping Students Make Connections among Multiple Graphical Representations

ERIC Educational Resources Information Center

Rau, Martina A.

2015-01-01

Multiple representations are ubiquitous in chemistry education. To benefit from multiple representations, students have to make connections between them. However, connection making is a difficult task for students. Prior research shows that supporting connection making enhances students' learning in math and science domains. Most prior research…

Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations

NASA Astrophysics Data System (ADS)

Liu, Lu; Hejazi, Mohamad; Li, Hongyi; Forman, Barton; Zhang, Xiao

2017-08-01

Previous modelling studies suggest that thermoelectric power generation is vulnerable to climate change, whereas studies based on historical data suggest the impact will be less severe. Here we explore the vulnerability of thermoelectric power generation in the United States to climate change by coupling an Earth system model with a thermoelectric power generation model, including state-level representation of environmental regulations on thermal effluents. We find that the impact of climate change is lower than in previous modelling estimates due to an inclusion of a spatially disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. More specifically, our results indicate that climate change alone may reduce average generating capacity by 2-3% by the 2060s, while reductions of up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. Our work highlights the significance of accounting for legal constructs and underscores the effects of provisional variances in addition to environmental requirements.

Engaging 5th/6th Graders in Representations of Change Over Time in the Context of Adaptations to Climate Change in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Peake, L.; Young Morse, R.

2017-12-01

Since 2005, the Gulf of Maine Research Institute has brought 70% of Maine's 5th/6th grade cohort annually to our marine research lab for a 2.5-hour exploration of ecosystem complexity. Using a digital platform, tools of science, and live marine species, students consider the interconnections among key Gulf of Maine species while experiencing the process of authentic marine research. With funding from NASA, we are renovating the program's learning content, underlying technology, and physical interfaces to leverage NASA data sets. The new experience will emphasize development of students' data skills as they investigate the impacts of climate change in the Gulf of Maine. To do this, students will explore representations of rising ocean temperatures and connect that to representations of changes in the populations of key species like lobster and black sea bass. Past experience suggests the abstraction and synthesis required to make meaning from data visualizations is extremely challenging for this age student. We will report on an early round of informal testing with 250+ students to understand their ability to extract meaning from geospatial and graphical representations of change over time. We will also report on experiments that will be conducted in Fall 2017 to understand the kinds of informal learning experiences, and the sequences of data representations, that best support growth in students' ability to interpret a range of representations. Finally, we will discuss the project's work to extend the learning experiences 1) back into the classroom, including through citizen science; and 2) out to regional science centers for adaptation to investigations of local climate impacts.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Readings from Visibility Meters: Do They Really Mean the Maximum Distance of Observing A Black Object?

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2016-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Examining the Complexity of the Campus Racial Climate at a Hispanic Serving Community College

ERIC Educational Resources Information Center

Cuellar, Marcela; Johnson-Ahorlu, Robin Nicole

2016-01-01

Objective: Despite the growing representation of Hispanic Serving Institutions (HSIs) among community colleges, relatively little is known about student perceptions of the campus climate at these institutions. Although perceptions of campus climate may differ by race and adversely affect students of color, most research has been conducted at…

Increased future ice discharge from Antarctica owing to higher snowfall.

PubMed

Winkelmann, R; Levermann, A; Martin, M A; Frieler, K

2012-12-13

Anthropogenic climate change is likely to cause continuing global sea level rise, but some processes within the Earth system may mitigate the magnitude of the projected effect. Regional and global climate models simulate enhanced snowfall over Antarctica, which would provide a direct offset of the future contribution to global sea level rise from cryospheric mass loss and ocean expansion. Uncertainties exist in modelled snowfall, but even larger uncertainties exist in the potential changes of dynamic ice discharge from Antarctica and thus in the ultimate fate of the precipitation-deposited ice mass. Here we show that snowfall and discharge are not independent, but that future ice discharge will increase by up to three times as a result of additional snowfall under global warming. Our results, based on an ice-sheet model forced by climate simulations through to the end of 2500 (ref. 8), show that the enhanced discharge effect exceeds the effect of surface warming as well as that of basal ice-shelf melting, and is due to the difference in surface elevation change caused by snowfall on grounded versus floating ice. Although different underlying forcings drive ice loss from basal melting versus increased snowfall, similar ice dynamical processes are nonetheless at work in both; therefore results are relatively independent of the specific representation of the transition zone. In an ensemble of simulations designed to capture ice-physics uncertainty, the additional dynamic ice loss along the coastline compensates between 30 and 65 per cent of the ice gain due to enhanced snowfall over the entire continent. This results in a dynamic ice loss of up to 1.25 metres in the year 2500 for the strongest warming scenario. The reported effect thus strongly counters a potential negative contribution to global sea level by the Antarctic Ice Sheet.

Terrestrial ecosystem model performance for net primary productivity and its vulnerability to climate change in permafrost regions

NASA Astrophysics Data System (ADS)

Xia, J.; McGuire, A. D.; Lawrence, D. M.; Burke, E.; Chen, X.; Delire, C. L.; Koven, C. D.; MacDougall, A. H.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D. P.; Miller, P. A.; Moore, J. C.; Smith, B.; Sueyoshi, T.; Shi, Z.; Yan, L.; Liang, J.; Jiang, L.; Luo, Y.

2014-12-01

A more accurate prediction of future climate-carbon (C) cycle feedbacks requires better understanding and improved representation of the carbon cycle in permafrost regions within current earth system models. Here, we evaluated 10 terrestrial ecosystem models for their estimated net primary productivity (NPP) and its vulnerability to climate change in permafrost regions in the Northern Hemisphere. Those models were run retrospectively between 1960 and 2009. In comparison with MODIS satellite estimates, most models produce higher NPP (310 ± 12 g C m-2 yr-1) than MODIS (240 ± 20 g C m-2 yr-1) over the permafrost regions during 2000‒2009. The modeled NPP was then decomposed into gross primary productivity (GPP) and the NPP/GPP ratio (i.e., C use efficiency; CUE). By comparing the simulated GPP with a flux-tower-based database [Jung et al. Journal of Geophysical Research 116 (2011) G00J07] (JU11), we found although models only produce 10.6% higher mean GPP than JU11 over 1982‒2009, there was a two-fold disparity among models (397 to 830 g C m-2 yr-1). The model-to-model variation in GPP mainly resulted from the seasonal peak GPP and in low-latitudinal permafrost regions such as the Tibetan Plateau. Most models overestimate the CUE in permafrost regions in comparison to calculated CUE from the MODIS NPP and JU11 GPP products and observation-based estimates at 8 forest sites. The models vary in their sensitivities of NPP, GPP and CUE to historical changes in air temperature, atmospheric CO2 concentration and precipitation. For example, climate warming enhanced NPP in four models via increasing GPP but reduced NPP in two other models by decreasing both GPP and CUE. The results indicate that the model predictability of C cycle in permafrost regions can be improved by better representation of those processes controlling the seasonal maximum GPP and the CUE as well as their sensitivity to climate change.

Measuring the Dynamics of Climate Change Communication in Mass Media and Social Networks with Computer-Assisted Content Analysis

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Stepchenkova, S.

2012-12-01

To date, multiple authors have examined media representations of and public attitudes towards climate change, as well as how these representations and attitudes differ from scientific knowledge on the issue of climate change. Content analysis of newspaper publications, TV news, and, recently, Internet blogs has allowed for identification of major discussion themes within the climate change domain (e.g., newspaper trends, comparison of climate change discourse in different countries, contrasting liberal vs. conservative press). The majority of these studies, however, have processed texts manually, limiting textual population size, restricting the analysis to a relatively small number of themes, and using time-expensive coding procedures. The use of computer-assisted text analysis (CATA) software is important because the difficulties with manual processing become more severe with an increased volume of data. We developed a CATA approach that allows a large body of text materials to be surveyed in a quantifiable, objective, transparent, and time-efficient manner. While staying within the quantitative tradition of content analysis, the approach allows for an interpretation of the public discourse closer to one of more qualitatively oriented methods. The methodology used in this study contains several steps: (1) sample selection; (2) data preparation for computer processing and obtaining a matrix of keyword frequencies; (3) identification of themes in the texts using Exploratory Factor Analysis (EFA); (4) combining identified themes into higher order themes using Confirmatory Factor Analysis (CFA); (5) interpretation of obtained public discourse themes using factor scores; and (6) tracking the development of the main themes of the climate change discourse through time. In the report, we concentrate on two examples of CATA applied to study public perception of climate change. First example is an analysis of temporal change in public discourse on climate change. Applying CATA to a conservatively selected sample of 4043 articles published on climate change in The New York Times from 1995, we found a considerable change in major topics of discussion. One of the most significant tendencies is a gradual decline in the volume of material within the "Science" topic and an expansion of themes classified under the "Politics" topic. The second example is the analysis of public ability to detect climate change, in which we used a database of over 1 million Twitter messages on climate change that we have collected. We compared the intensity of tweeting on climate change with the "common-sense climate index" by Hansen et al (1999) and found that the weather extremes experienced at a certain location is immediately reflected in the number of tweets discussing climate change originating from that location. Although the CATA approach certainly has its limitations, we are convinced that it has a number of advantages over manual processing: it is able to analyze large textual bodies, is more time efficient, has a higher level of detail, enhances the richness of interpretation, and is able to reliably track discourse development through time.

Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory.

PubMed

Mather, Mara; Clewett, David; Sakaki, Michiko; Harley, Carolyn W

2016-01-01

Emotional arousal enhances perception and memory of high-priority information but impairs processing of other information. Here, we propose that, under arousal, local glutamate levels signal the current strength of a representation and interact with norepinephrine (NE) to enhance high priority representations and out-compete or suppress lower priority representations. In our "glutamate amplifies noradrenergic effects" (GANE) model, high glutamate at the site of prioritized representations increases local NE release from the locus coeruleus (LC) to generate "NE hotspots." At these NE hotspots, local glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. In contrast, arousal-induced LC activity inhibits less active representations via two mechanisms: 1) Where there are hotspots, lateral inhibition is amplified; 2) Where no hotspots emerge, NE levels are only high enough to activate low-threshold inhibitory adrenoreceptors. Thus, LC activation promotes a few hotspots of excitation in the context of widespread suppression, enhancing high priority representations while suppressing the rest. Hotspots also help synchronize oscillations across neural ensembles transmitting high-priority information. Furthermore, brain structures that detect stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during, or after encoding enhances synaptic plasticity at NE hotspots, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms promote selective attention and memory under arousal. GANE not only reconciles apparently contradictory findings in the emotion-cognition literature but also extends previous influential theories of LC neuromodulation by proposing specific mechanisms for how LC-NE activity increases neural gain.

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

Glotfelty, Timothy; Zhang, Yang; Karamchandani, Prakash

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality ismore » projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O 3 level and of 0.3 mg m 3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO 2, H 2O 2, and the nitrate radical and increasing the atmosphere’s near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O 3, and increases in CH 4 and VOCs. Increasing NO x and O 3 levels enhances the nitrogen and O 3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth’s surface with a global average reduction in shortwave radiation of 1.2 W m 2 . This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR’s CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.« less

An enhanced forest classification scheme for modeling vegetation-climate interactions based on national forest inventory data

NASA Astrophysics Data System (ADS)

Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.

2018-01-01

Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed Central

Ma, Xiaohui; Chang, Ping; Saravanan, R.; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-01-01

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy–atmosphere interaction in forecast and climate models. PMID:26635077

A prognostic pollen emissions model for climate models (PECM1.0)

NASA Astrophysics Data System (ADS)

Wozniak, Matthew C.; Steiner, Allison L.

2017-11-01

We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

Representation of Precipitation in a Decade-long Continental-Scale Convection-Resolving Climate Simulation

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2017-12-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Regional climate simulations using horizontal resolutions of O(1km) allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. A new version of the Consortium for Small-Scale Modeling weather and climate model (COSMO) is capable of exploiting new supercomputer architectures employing GPU accelerators, and allows convection-resolving climate simulations on computational domains spanning continents and time periods up to one decade. We present results from a decade-long, convection-resolving climate simulation on a European-scale computational domain. The simulation has a grid spacing of 2.2 km, 1536x1536x60 grid points, covers the period 1999-2008, and is driven by the ERA-Interim reanalysis. Specifically we present an evaluation of hourly rainfall using a wide range of data sets, including several rain-gauge networks and a remotely-sensed lightning data set. Substantial improvements are found in terms of the diurnal cycles of precipitation amount, wet-hour frequency and all-hour 99th percentile. However the results also reveal substantial differences between regions with and without strong orographic forcing. Furthermore we present an index for deep-convective activity based on the statistics of vertical motion. Comparison of the index with lightning data shows that the convection-resolving climate simulations are able to reproduce important features of the annual cycle of deep convection in Europe. Leutwyler D., D. Lüthi, N. Ban, O. Fuhrer, and C. Schär (2017): Evaluation of the Convection-Resolving Climate Modeling Approach on Continental Scales , J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD026013.

Hydrologic impacts of thawing permafrost—A review

USGS Publications Warehouse

Walvoord, Michelle Ann; Kurylyk, Barret L.

2016-01-01

Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process-based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.

Building partnerships to produce actionable science to support climate-informed management decisions: North Central Climate Science Center example

NASA Astrophysics Data System (ADS)

Lackett, J.; Ojima, D. S.; McNeeley, S.

2017-12-01

As climate change impacts become more apparent in our environment, action is needed to enhance the social-ecological system resilience. Incorporating principles which lead to actionable research and project co-development, when appropriate, will facilitate building linkages between the research and the natural resource management communities. In order to develop strategies to manage for climatic and ecosystem changes, collaborative actions are needed between researchers and resource managers to apply appropriate knowledge of the ecosystem and management environments to enable feasible solutions and management actions to respond to climate change. Our team has been involved in developing and establishing a research and engagement center, the North Central Climate Science Center (NC CSC), for the US Department of Interior, to support the development and translation of pertinent climate science information to natural resource managers in the north central portion of the United States. The NC CSC has implemented a platform to support the Resource for Vulnerability Assessment, Adaptation, and Mitigation Projects (ReVAMP) with research, engagement, and training activities to support resource managers and researchers. These activities are aimed at the co-production of appropriate response strategies to climate change in the region, in particular to drought-related responses. Through this platform we, with other partners in the region, including the Department of Interior and the Department of Agriculture, are bringing various training tools, climate information, and management planning tools to resource managers. The implementation of ReVAMP has led to development of planning efforts which include a more explicit representation of climate change as a driver of drought events in our region. Scenario planning provides a process which integrates management goals with possible outcomes derived from observations and simulations of ecological impacts of climate change. Co-development of management options under these various scenarios have allowed for guidance about further research needed, observations needed to better monitor ecological conditions under climate changes, and adaptive management practices to increase resilience.

Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

Evaluation of additional biogeochemical impacts on mitigation pathways in an energy sytem integrated assessment model.

NASA Astrophysics Data System (ADS)

Dessens, O.

2017-12-01

Within the last IPCC AR5 a large and systematic sensitivity study around available technologies and timing of policies applied in IAMs to achieve the 2°C target has been conducted. However the simple climate representations included in IAMs are generally tuned to the results of ensemble means. This may result in hiding within the ensemble mean results possible challenging mitigation pathways for the economy or the technology future scenarios. This work provides new insights on the sensitivity of the socio-economic response to different climate factors under a 2°C climate change target in order to help guide future efforts to reduce uncertainty in the climate mitigation decisions. The main objective is to understand and bring new insights on how future global warming will affect the natural biochemical feedbacks on the climate system and what could be the consequences of these feedbacks on the anthropogenic emission pathways with a specific focus on the energy-economy system. It specifically focuses on three issues of the climate representation affecting the energy system transformation and GHG emissions pathways: 1- Impacts of the climate sensitivity (or TCR); 2- Impacts of warming on the radiative forcing (cloudiness,...); 3- Impacts of warming on the carbon cycle (carbon cycle feedback). We use the integrated assessment model TIAM-UCL to examine the mitigation pathways compatible with the 2C target depending on assumptions regarding the 3 issues of the climate representation introduced above. The following key conclusions drawn from this study are that mitigation to 2°C is still possible under strong climate sensitivity (TCR), strong carbon cycle amplification or positive radiative forcing feedback. However, this level of climate mitigation will require a significant transformation in the way we produce and consume energy. Carbon capture and sequestration on electricity generation, industry and biomass is part of the technology pool needed to achieve this level of decarbonisation. In extreme condition (positive correlation between the 3 issues discussed) the integrated assessment model TIAM-UCL creates pathways requiring additional negative emission technologies at the end of this century to keep temperature change well below 2°C.

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

NASA Astrophysics Data System (ADS)

Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.

2013-05-01

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

Could geoengineering research help answer one of the biggest questions in climate science?

NASA Astrophysics Data System (ADS)

Wood, Robert; Ackerman, Thomas; Rasch, Philip; Wanser, Kelly

2017-07-01

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol-cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experiments whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. The control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol-cloud interactions needed to better constrain aerosol forcing in global climate models.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Modeling the effects of vegetation heterogeneity on wildland fire behavior

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Sieg, C.; Middleton, R. S.

2017-12-01

Vegetation structure and densities are known to drive fire-spread rate and burn severity. Many fire-spread models incorporate an average, homogenous fuel density in the model domain to drive fire behavior. However, vegetation communities are rarely homogenous and instead present significant heterogeneous structure and fuel densities in the fires path. This results in observed patches of varied burn severities and mosaics of disturbed conditions that affect ecological recovery and hydrologic response. Consequently, to understand the interactions of fire and ecosystem functions, representations of spatially heterogeneous conditions need to be incorporated into fire models. Mechanistic models of fire disturbance offer insight into how fuel load characterization and distribution result in varied fire behavior. Here we use a physically-based 3D combustion model—FIRETEC—that solves conservation of mass, momentum, energy, and chemical species to compare fire behavior on homogenous representations to a heterogeneous vegetation distribution. Results demonstrate the impact vegetation heterogeneity has on the spread rate, intensity, and extent of simulated wildfires thus providing valuable insight in predicted wildland fire evolution and enhanced ability to estimate wildland fire inputs into regional and global climate models.

Air-climate-energy investigations with a state-level Integrated Assessment Model: GCAM-USA

EPA Science Inventory

The Global Change Assessment Model (GCAM) is a global integrated assessment model used for exploring future scenarios and examining strategies that address air pollution, climate change, and energy goals.  GCAM includes technology-rich representations of the energy, transportatio...

Imagining a Future for the Planet through Literature, Writing, Images, and Drama

ERIC Educational Resources Information Center

Beach, Richard

2015-01-01

This Commentary posits the need to analyze how the energy/transportation, agricultural/food, and economic/political systems influence climate change through responding to literary "cli-fi" texts, place-based writing, visual representation of the effects of climate change, and drama activities.

Impacts of Marine Ecodynamics on the Dimethyl Sulfide(DMS) Production

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

Wang, Shanlin; Maltrud, Mathew Einar; Elliott, Scott M.

2017-11-05

Given the new explicit Phaeocystis representation, the DMS distribution shows significant improvements, especially regarding the amplitude and location of high latitude peaks. The production of DMS varies with climate. It is therefore necessary to couple the dynamics DMS module in climate projections.

A National Program for Analysis of the Climate System

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Arkin, Phil; Kalnay, Eugenia; Laver, James; Trenberth, Kevin

2002-01-01

Perhaps the single greatest roadblock to fundamental advances in our understanding of climate variability and climate change is the lack of robust and unbiased long-term global observations of the climate system. Such observations are critical for the identification and diagnosis of climate variations, and provide the constraints necessary for developing and validating climate models. The first generation of reanalysis efforts, by using fixed analysis systems, eliminated the artificial climate signals that occurred in analyses generated at the operational numerical weather prediction centers. These datasets are now widely used by the scientific community in a variety of applications including atmosphere-ocean interactions, seasonal prediction, climate monitoring, the hydrological cycle, and a host of regional and other diagnostic studies. These reanalyses, however, had problems that made them sub-optimal or even unusable for some applications. Perhaps the most serious problem for climate applications was that, while the assimilation system remained fixed, changes in the observing systems did produce spurious changes in the perceived climate. The first generation reanalysis products also exposed problems with physical consistency of the products and the accurate representation of physical processes in the climate system. Examples are bias in the estimates of ocean surface fluxes, and inadequate representation of polar hydrology. In this talk, I will describe some initial plans for a national program on reananlysis. The program is envisioned to be part of an on-going activity to maintain, improve, and reprocess our record of climate observations. I will discuss various issues affecting the quality of reanalyses, with a special focus on those relevant to the ocean.

Impact of Land Cover Characterization and Properties on Snow Albedo in Climate Models

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Chan, E.; Montesano, P.

2017-12-01

The simulation of winter albedo in boreal and northern environments has been a particular challenge for land surface modellers. Assessments of output from CMIP3 and CMIP5 climate models have revealed that many simulations are characterized by overestimation of albedo in the boreal forest. Recent studies suggest that inaccurate representation of vegetation distribution, improper simulation of leaf area index, and poor treatment of canopy-snow processes are the primary causes of albedo errors. While several land cover datasets are commonly used to derive plant functional types (PFT) for use in climate models, new land cover and vegetation datasets with higher spatial resolution have become available in recent years. In this study, we compare the spatial distribution of the dominant PFTs and canopy cover fractions based on different land cover datasets, and present results from offline simulations of the latest version Canadian Land Surface Scheme (CLASS) over the northern Hemisphere land. We discuss the impact of land cover representation and surface properties on winter albedo simulations in climate models.

Sensitivities of the hydrologic cycle to model physics, grid resolution, and ocean type in the aquaplanet Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Benedict, James J.; Medeiros, Brian; Clement, Amy C.; Pendergrass, Angeline G.

2017-06-01

Precipitation distributions and extremes play a fundamental role in shaping Earth's climate and yet are poorly represented in many global climate models. Here, a suite of idealized Community Atmosphere Model (CAM) aquaplanet simulations is examined to assess the aquaplanet's ability to reproduce hydroclimate statistics of real-Earth configurations and to investigate sensitivities of precipitation distributions and extremes to model physics, horizontal grid resolution, and ocean type. Little difference in precipitation statistics is found between aquaplanets using time-constant sea-surface temperatures and those implementing a slab ocean model with a 50 m mixed-layer depth. In contrast, CAM version 5.3 (CAM5.3) produces more time mean, zonally averaged precipitation than CAM version 4 (CAM4), while CAM4 generates significantly larger precipitation variance and frequencies of extremely intense precipitation events. The largest model configuration-based precipitation sensitivities relate to choice of horizontal grid resolution in the selected range 1-2°. Refining grid resolution has significant physics-dependent effects on tropical precipitation: for CAM4, time mean zonal mean precipitation increases along the Equator and the intertropical convergence zone (ITCZ) narrows, while for CAM5.3 precipitation decreases along the Equator and the twin branches of the ITCZ shift poleward. Increased grid resolution also reduces light precipitation frequencies and enhances extreme precipitation for both CAM4 and CAM5.3 resulting in better alignment with observational estimates. A discussion of the potential implications these hydrologic cycle sensitivities have on the interpretation of precipitation statistics in future climate projections is also presented.