Introducing Subgrid-scale convective cloud and aerosol interactions to the WRF-CMAQ integrated modeling system

EPA Science Inventory

Many regional and global climate models include aerosol indirect effects (AIE) on grid-scale/resolved clouds. However, the interaction between aerosols and convective clouds remains highly uncertain, as noted in the IPCC AR4 report. The objective of this work is to help fill in ...

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Uncertainty quantification of US Southwest climate from IPCC projections.

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

Boslough, Mark Bruce Elrick

2011-01-01

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statisticalmore » analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.« less

Use of circulation types classifications to evaluate AR4 climate models over the Euro-Atlantic region

NASA Astrophysics Data System (ADS)

Pastor, M. A.; Casado, M. J.

2012-10-01

This paper presents an evaluation of the multi-model simulations for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in terms of their ability to simulate the ERA40 circulation types over the Euro-Atlantic region in winter season. Two classification schemes, k-means and SANDRA, have been considered to test the sensitivity of the evaluation results to the classification procedure. The assessment allows establishing different rankings attending spatial and temporal features of the circulation types. Regarding temporal characteristics, in general, all AR4 models tend to underestimate the frequency of occurrence. The best model simulating spatial characteristics is the UKMO-HadGEM1 whereas CCSM3, UKMO-HadGEM1 and CGCM3.1(T63) are the best simulating the temporal features, for both classification schemes. This result agrees with the AR4 models ranking obtained when having analysed the ability of the same AR4 models to simulate Euro-Atlantic variability modes. This study has proved the utility of applying such a synoptic climatology approach as a diagnostic tool for models' assessment. The ability of the models to properly reproduce the position of ridges and troughs and the frequency of synoptic patterns, will therefore improve our confidence in the response of models to future climate changes.

Influences of Regional Climate Change on Air Quality across the Continental U.S. Projected from Downscaling IPCC ARS Simulations

EPA Science Inventory

Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate ...

Earths Climate Sensitivity: Apparent Inconsistencies in Recent Assessments

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

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph

Earth's equilibrium climate sensitivity (ECS) and forcing of Earth's climate system over the industrial era have been re-examined in two new assessments: the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and a study by Otto et al. (2013). The ranges of these quantities given in these assessments and also in the Fourth (2007) IPCC Assessment are analyzed here within the framework of a planetary energy balance model, taking into account the observed increase in global mean surface temperature over the instrumental record together with best estimates of the rate of increase of planetary heat content.more » This analysis shows systematic differences among the several assessments and apparent inconsistencies within individual assessments. Importantly, the likely range of ECS to doubled CO₂ given in AR5, 1.5–4.5 K/(3.7 W m⁻²) exceeds the range inferred from the assessed likely range of forcing, 1.2–2.9 K/(3.7 W m⁻²), where 3.7 W ⁻² denotes the forcing for doubled CO₂. Such differences underscore the need to identify their causes and reduce the underlying uncertainties. Explanations might involve underestimated negative aerosol forcing, overestimated total forcing, overestimated climate sensitivity, poorly constrained ocean heating, limitations of the energy balance model, or a combination of effects.« less

Earths Climate Sensitivity: Apparent Inconsistencies in Recent Assessments

DOE PAGES

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph; ...

2014-12-08

Earth's equilibrium climate sensitivity (ECS) and forcing of Earth's climate system over the industrial era have been re-examined in two new assessments: the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and a study by Otto et al. (2013). The ranges of these quantities given in these assessments and also in the Fourth (2007) IPCC Assessment are analyzed here within the framework of a planetary energy balance model, taking into account the observed increase in global mean surface temperature over the instrumental record together with best estimates of the rate of increase of planetary heat content.more » This analysis shows systematic differences among the several assessments and apparent inconsistencies within individual assessments. Importantly, the likely range of ECS to doubled CO₂ given in AR5, 1.5–4.5 K/(3.7 W m⁻²) exceeds the range inferred from the assessed likely range of forcing, 1.2–2.9 K/(3.7 W m⁻²), where 3.7 W ⁻² denotes the forcing for doubled CO₂. Such differences underscore the need to identify their causes and reduce the underlying uncertainties. Explanations might involve underestimated negative aerosol forcing, overestimated total forcing, overestimated climate sensitivity, poorly constrained ocean heating, limitations of the energy balance model, or a combination of effects.« less

Assessment of the impact of climate change on spatiotemporal variability of blue and green water resources under CMIP3 and CMIP5 models in a highly mountainous watershed

NASA Astrophysics Data System (ADS)

Fazeli Farsani, Iman; Farzaneh, M. R.; Besalatpour, A. A.; Salehi, M. H.; Faramarzi, M.

2018-04-01

The variability and uncertainty of water resources associated with climate change are critical issues in arid and semi-arid regions. In this study, we used the soil and water assessment tool (SWAT) to evaluate the impact of climate change on the spatial and temporal variability of water resources in the Bazoft watershed, Iran. The analysis was based on changes of blue water flow, green water flow, and green water storage for a future period (2010-2099) compared to a historical period (1992-2008). The r-factor, p-factor, R 2, and Nash-Sutcliff coefficients for discharge were 1.02, 0.89, 0.80, and 0.80 for the calibration period and 1.03, 0.76, 0.57, and 0.59 for the validation period, respectively. General circulation models (GCMs) under 18 emission scenarios from the IPCC's Fourth (AR4) and Fifth (AR5) Assessment Reports were fed into the SWAT model. At the sub-basin level, blue water tended to decrease, while green water flow tended to increase in the future scenario, and green water storage was predicted to continue its historical trend into the future. At the monthly time scale, the 95% prediction uncertainty bands (95PPUs) of blue and green water flows varied widely in the watershed. A large number (18) of climate change scenarios fell within the estimated uncertainty band of the historical period. The large differences among scenarios indicated high levels of uncertainty in the watershed. Our results reveal that the spatial patterns of water resource components and their uncertainties in the context of climate change are notably different between IPCC AR4 and AR5 in the Bazoft watershed. This study provides a strong basis for water supply-demand analyses, and the general analytical framework can be applied to other study areas with similar challenges.

Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

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

Liu, Zhengyu; Kutzbach, J.; Jacob, R.

2011-12-05

In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadalmore » climate prediction.« less

Coupled Long-Term Evolution of Climate and the Greenland Ice Sheet During the Last Interglacial and Implications for the Future

NASA Astrophysics Data System (ADS)

Otto-Bliesner, B. L.; Lofverstrom, M.; Lipscomb, W.; Fyke, J. G.; Marshall, S.; Sacks, B.

2017-12-01

The Greenland Ice Sheet (GrIS) is expected to contribute increasingly to global sea level rise by the end of this century, and potentially several meters in this millennium, but still with considerable uncertainty. The rate of Greenland melt will impact on regional sea levels. The Last Interglacial (LIG, 129 ka to 116 ka) is recognized as an important period for testing our knowledge of climate-ice sheet interactions in warm climate states. Although the LIG was discussed in the First Assessment Report of the IPCC, it gained more prominence in the IPCC Fourth and Fifth Assessment (AR4 and AR5) with reconstructions highlighting that global mean sea level was at least 5 m higher (but probably no more than 10 m higher) than present for several thousand years during the LIG. Model results assessed for the AR5 suggest a sea level contribution of 1.4 to 4.3 m from the GrIS. These model simulations, though, did not include all the feedbacks of the climate system and the GrIS. Here, we examine the response of the Arctic climate system and the GrIS in simulations with the Community Earth System Model (CESM) fully coupled to the Community Ice Sheet Model (CISM), using a surface energy balance scheme and without bias corrections. The analysis focuses on how the GrIS responds to the imposed high boreal summer insolation of the LIG and in addition, to the long-term feedbacks of high-latitude vegetation changes. Results will highlight the evolution of the ice sheet and the surface mass balance (patterns of ablation and accumulation) as compared to data-based reconstructions for the LIG. We conclude with a discussion on how the LIG may be informative as a potential process analogue for the GrIS response for future centuries to come.

Problems with the North American Monsoon in CMIP/IPCC GCM Precipitation

NASA Astrophysics Data System (ADS)

Schiffer, N. J.; Nesbitt, S. W.

2011-12-01

Successful water management in the Desert Southwest and surrounding areas hinges on anticipating the timing and distribution of precipitation. IPCC AR4 models predict a more arid climate, more extreme precipitation events, and an earlier peak in springtime streamflow in the North American Monsoon region as the area warms. This study aims to assess the summertime skill with which general circulation models (GCMs) simulate precipitation and related dynamics over this region, a necessary precursor to reliable hydroclimate projections. Thirty-year climatologies of several GCMs in the third and fifth Climate Model Intercomparison Projects (CMIP) are statistically evaluated against each other and observed climatology for their skill in representing the location, timing, variability, character, and large-scale forcing of precipitation over the southwestern United States and northwestern Mexico. The results of this study will lend greater credence to more detailed, higher resolution studies, based on the CMIP and IPCC models, of the region's future hydrology. Our ultimate goal is to provide guidance such that decision-makers can plan future water management with more confidence.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Towards the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)

NASA Astrophysics Data System (ADS)

Fuglestvedt, J. S.; Masson-Delmotte, V.; Zhai, P.; Pirani, A.

2016-12-01

The IPCC, set up in 1988 by WMO and UNEP, is the international body for assessing the science related to climate change. The reports of the IPCC include Assessments, Synthesis and Special Reports (and their Summaries for Policymakers), as well as Methodological Reports, providing policymakers with regular assessments of the scientific basis of climate change, its impacts and future risks, and options for adaptation and mitigation. These assessments are policy-relevant, but not policy-prescriptive, and based on the assessment of the published literature. The assessments of the IPCC follow precise procedures to ensure that they provide a rigorous and balanced scientific information. Particularly critical is the volunteer involvment of tens of scientists involved in the scoping of each report, as well as the work of hundreds of Coordinating Lead Authors and Lead Authors of reports, with the complementary expertise of hundreds of sollicited Contributing Authors. The review process plays a key role in the open and transparent process underlying the IPCC reports. It is organized in multiple rounds and mobilizes thousands of other experts, a process monitored by Review Editors. The author teams develop rigorous methodologies to report the degree of confidence associated with each finding and report information with uncertainty. As a result, successive IPCC reports provide regular steps to determine matured climate science, through robust findings, but also emerging research pathways, and facilitate science maturation through analyses of multiple perspectives provided by the scientific literature in a comprehensive approach. While the IPCC does not conduct its own scientific research, the timeline of the IPCC reports acts as a stimulation for the research community, especially for internationally coordinated research programmes associated with global climate projections. These aspects will be developed in this presentation, with a focus on Working Group I (the physical science basis), and the 6th Assessment Report (AR6). For more information, see : www.ipcc.ch For new special reports planned in 2018-2019 : http://www.ipcc.ch/activities/activities.shtml For the strategic planning schedule for the AR6 : http://www.ipcc.ch/activities/pdf/ar6_WSPSchedule_07072016.pdf

Regional Climate Change across North America in 2030 Projected from RCP6.0

NASA Astrophysics Data System (ADS)

Otte, T.; Nolte, C. G.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. In this research, downscaling techniques that we developed with historical data are now applied to GCM fields. Results from downscaling NASA/GISS ModelE2 simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model has been used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 over North America and illustrate potential changes in regional climate that are projected by ModelE2 and WRF under RCP6.0. The analysis focuses on regional climate fields that most strongly influence the interactions between climate change and air quality. In particular, an analysis of extreme temperature and precipitation events will be presented.

An interactive web application for visualizing climate data

USGS Publications Warehouse

Alder, J.; Hostetler, S.; Williams, D.

2013-01-01

Massive volumes of data are being created as modeling centers from around the world finalize their submission of climate simulations for the Coupled Model Intercomparison Project, phase 5 (CMIP5), in preparation for the forthcoming Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Scientists, resource managers, and other potential users of climate data are faced with the daunting task of analyzing, distilling, and summarizing this unprecedented wealth of climate information.

An Interactive Web Application for Visualizing Climate Data

NASA Astrophysics Data System (ADS)

Alder, J.; Hostetler, S.; Williams, D.

2013-05-01

Massive volumes of data are being created as modeling centers from around the world finalize their submission of climate simulations for the Coupled Model Intercomparison Project, phase 5 (CMIP5), in preparation for the forthcoming Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Scientists, resource managers, and other potential users of climate data are faced with the daunting task of analyzing, distilling, and summarizing this unprecedented wealth of climate information.

Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) "reasons for concern".

PubMed

Smith, Joel B; Schneider, Stephen H; Oppenheimer, Michael; Yohe, Gary W; Hare, William; Mastrandrea, Michael D; Patwardhan, Anand; Burton, Ian; Corfee-Morlot, Jan; Magadza, Chris H D; Füssel, Hans-Martin; Pittock, A Barrie; Rahman, Atiq; Suarez, Avelino; van Ypersele, Jean-Pascal

2009-03-17

Article 2 of the United Nations Framework Convention on Climate Change [United Nations (1992) http://unfccc.int/resource/docs/convkp/conveng.pdf. Accessed February 9, 2009] commits signatory nations to stabilizing greenhouse gas concentrations in the atmosphere at a level that "would prevent dangerous anthropogenic interference (DAI) with the climate system." In an effort to provide some insight into impacts of climate change that might be considered DAI, authors of the Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC) identified 5 "reasons for concern" (RFCs). Relationships between various impacts reflected in each RFC and increases in global mean temperature (GMT) were portrayed in what has come to be called the "burning embers diagram." In presenting the "embers" in the TAR, IPCC authors did not assess whether any single RFC was more important than any other; nor did they conclude what level of impacts or what atmospheric concentrations of greenhouse gases would constitute DAI, a value judgment that would be policy prescriptive. Here, we describe revisions of the sensitivities of the RFCs to increases in GMT and a more thorough understanding of the concept of vulnerability that has evolved over the past 8 years. This is based on our expert judgment about new findings in the growing literature since the publication of the TAR in 2001, including literature that was assessed in the IPCC Fourth Assessment Report (AR4), as well as additional research published since AR4. Compared with results reported in the TAR, smaller increases in GMT are now estimated to lead to significant or substantial consequences in the framework of the 5 "reasons for concern."

Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) “reasons for concern”

PubMed Central

Smith, Joel B.; Schneider, Stephen H.; Oppenheimer, Michael; Yohe, Gary W.; Hare, William; Mastrandrea, Michael D.; Patwardhan, Anand; Burton, Ian; Corfee-Morlot, Jan; Magadza, Chris H. D.; Füssel, Hans-Martin; Pittock, A. Barrie; Rahman, Atiq; Suarez, Avelino; van Ypersele, Jean-Pascal

2009-01-01

Article 2 of the United Nations Framework Convention on Climate Change [United Nations (1992) http://unfccc.int/resource/docs/convkp/conveng.pdf. Accessed February 9, 2009] commits signatory nations to stabilizing greenhouse gas concentrations in the atmosphere at a level that “would prevent dangerous anthropogenic interference (DAI) with the climate system.” In an effort to provide some insight into impacts of climate change that might be considered DAI, authors of the Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC) identified 5 “reasons for concern” (RFCs). Relationships between various impacts reflected in each RFC and increases in global mean temperature (GMT) were portrayed in what has come to be called the “burning embers diagram.” In presenting the “embers” in the TAR, IPCC authors did not assess whether any single RFC was more important than any other; nor did they conclude what level of impacts or what atmospheric concentrations of greenhouse gases would constitute DAI, a value judgment that would be policy prescriptive. Here, we describe revisions of the sensitivities of the RFCs to increases in GMT and a more thorough understanding of the concept of vulnerability that has evolved over the past 8 years. This is based on our expert judgment about new findings in the growing literature since the publication of the TAR in 2001, including literature that was assessed in the IPCC Fourth Assessment Report (AR4), as well as additional research published since AR4. Compared with results reported in the TAR, smaller increases in GMT are now estimated to lead to significant or substantial consequences in the framework of the 5 “reasons for concern.” PMID:19251662

Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

NASA Astrophysics Data System (ADS)

Li, Wenhong; Fu, Rong; Dickinson, Robert E.

2006-01-01

The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

A Defence of the AR4’s Bayesian Approach to Quantifying Uncertainty

NASA Astrophysics Data System (ADS)

Vezer, M. A.

2009-12-01

The field of climate change research is a kimberlite pipe filled with philosophic diamonds waiting to be mined and analyzed by philosophers. Within the scientific literature on climate change, there is much philosophical dialogue regarding the methods and implications of climate studies. To this date, however, discourse regarding the philosophy of climate science has been confined predominately to scientific - rather than philosophical - investigations. In this paper, I hope to bring one such issue to the surface for explicit philosophical analysis: The purpose of this paper is to address a philosophical debate pertaining to the expressions of uncertainty in the International Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), which, as will be noted, has received significant attention in scientific journals and books, as well as sporadic glances from the popular press. My thesis is that the AR4’s Bayesian method of uncertainty analysis and uncertainty expression is justifiable on pragmatic grounds: it overcomes problems associated with vagueness, thereby facilitating communication between scientists and policy makers such that the latter can formulate decision analyses in response to the views of the former. Further, I argue that the most pronounced criticisms against the AR4’s Bayesian approach, which are outlined below, are misguided. §1 Introduction Central to AR4 is a list of terms related to uncertainty that in colloquial conversations would be considered vague. The IPCC attempts to reduce the vagueness of its expressions of uncertainty by calibrating uncertainty terms with numerical probability values derived from a subjective Bayesian methodology. This style of analysis and expression has stimulated some controversy, as critics reject as inappropriate and even misleading the association of uncertainty terms with Bayesian probabilities. [...] The format of the paper is as follows. The investigation begins (§2) with an explanation of background considerations relevant to the IPCC and its use of uncertainty expressions. It then (§3) outlines some general philosophical worries regarding vague expressions and (§4) relates those worries to the AR4 and its method of dealing with them, which is a subjective Bayesian probability analysis. The next phase of the paper (§5) examines the notions of ‘objective’ and ‘subjective’ probability interpretations and compares the IPCC’s subjective Bayesian strategy with a frequentist approach. It then (§6) addresses objections to that methodology, and concludes (§7) that those objections are wrongheaded.

Evaluation of simulated ocean carbon in the CMIP5 earth system models

NASA Astrophysics Data System (ADS)

Orr, James; Brockmann, Patrick; Seferian, Roland; Servonnat, Jérôme; Bopp, Laurent

2013-04-01

We maintain a centralized model output archive containing output from the previous generation of Earth System Models (ESMs), 7 models used in the IPCC AR4 assessment. Output is in a common format located on a centralized server and is publicly available through a web interface. Through the same interface, LSCE/IPSL has also made available output from the Coupled Model Intercomparison Project (CMIP5), the foundation for the ongoing IPCC AR5 assessment. The latter includes ocean biogeochemical fields from more than 13 ESMs. Modeling partners across 3 EU projects refer to the combined AR4-AR5 archive and comparison as OCMIP5, building on previous phases of OCMIP (Ocean Carbon Cycle Intercomparison Project) and making a clear link to IPCC AR5 (CMIP5). While now focusing on assessing the latest generation of results (AR5, CMIP5), this effort is also able to put them in context (AR4). For model comparison and evaluation, we have also stored computed derived variables (e.g., those needed to assess ocean acidification) and key fields regridded to a common 1°x1° grid, thus complementing the standard CMIP5 archive. The combined AR4-AR5 output (OCMIP5) has been used to compute standard quantitative metrics, both global and regional, and those have been synthesized with summary diagrams. In addition, for key biogeochemical fields we have deconvolved spatiotemporal components of the mean square error in order to constrain which models go wrong where. Here we will detail results from these evaluations which have exploited gridded climatological data. The archive, interface, and centralized evaluation provide a solid technical foundation, upon which collaboration and communication is being broadened in the ocean biogeochemical modeling community. Ultimately we aim to encourage wider use of the OCMIP5 archive.

Climate of the past 2000 years in IPCC AR5 (Invited)

NASA Astrophysics Data System (ADS)

Masson-Delmotte, V.

2013-12-01

Different aspects of the climate of the past 2000 years are covered in several chapters of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, including information from paleoclimate archives, changes in the carbon and biogeochemical cycles, changes in sea level, climate model evaluation and detection and attribution. This presentation will summarize the main findings regarding pre-industrial changes in radiative forcings, reconstructed and simulated temperature variations at the hemispheric and regional scales, as well as global sea level for the past 2000 years, in the perspective of the current and earlier interglacial periods.

;Agreement; in the IPCC Confidence measure

NASA Astrophysics Data System (ADS)

Rehg, William; Staley, Kent

2017-02-01

The Intergovernmental Panel on Climate Change (IPCC) has, in its most recent Assessment Report (AR5), articulated guidelines for evaluating and communicating uncertainty that include a qualitative scale of confidence. We examine one factor included in that scale: the "degree of agreement." Some discussions of the degree of agreement in AR5 suggest that the IPCC is employing a consensus-oriented social epistemology. We consider the application of the degree of agreement factor in practice in AR5. Our findings, though based on a limited examination, suggest that agreement attributions do not so much track the overall consensus among investigators as the degree to which relevant research findings substantively converge in offering support for IPCC claims. We articulate a principle guiding confidence attributions in AR5 that centers not on consensus but on the notion of support. In concluding, we tentatively suggest a pluralist approach to the notion of support.

A review of uncertainty visualization within the IPCC reports

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Reusser, Dominik; Wrobel, Markus

2015-04-01

Results derived from climate model simulations confront non-expert users with a variety of uncertainties. This gives rise to the challenge that the scientific information must be communicated such that it can be easily understood, however, the complexity of the science behind is still incorporated. With respect to the assessment reports of the IPCC, the situation is even more complicated, because heterogeneous sources and multiple types of uncertainties need to be compiled together. Within this work, we systematically (1) analyzed the visual representation of uncertainties in the IPCC AR4 and AR5 reports, and (2) executed a questionnaire to evaluate how different user groups such as decision-makers and teachers understand these uncertainty visualizations. Within the first step, we classified visual uncertainty metaphors for spatial, temporal and abstract representations. As a result, we clearly identified a high complexity of the IPCC visualizations compared to standard presentation graphics, sometimes even integrating two or more uncertainty classes / measures together with the "certain" (mean) information. Further we identified complex written uncertainty explanations within image captions even within the "summary reports for policy makers". In the second step, based on these observations, we designed a questionnaire to investigate how non-climate experts understand these visual representations of uncertainties, how visual uncertainty coding might hinder the perception of the "non-uncertain" data, and if alternatives for certain IPCC visualizations exist. Within the talk/poster, we will present first results from this questionnaire. Summarizing, we identified a clear trend towards complex images within the latest IPCC reports, with a tendency to incorporate as much as possible information into the visual representations, resulting in proprietary, non-standard graphic representations that are not necessarily easy to comprehend on one glimpse. We conclude that further translation is required to (visually) present the IPCC results to non-experts, providing tailored static and interactive visualization solutions for different user groups.

Advanced Large Scale Cross Domain Temporal Topic Modeling Algorithms to Infer the Influence of Recent Research on IPCC Assessment Reports

NASA Astrophysics Data System (ADS)

Sleeman, J.; Halem, M.; Finin, T.; Cane, M. A.

2016-12-01

Approximately every five years dating back to 1989, thousands of climate scientists, research centers and government labs volunteer to prepare comprehensive Assessment Reports for the Intergovernmental Panel on Climate Change. These are highly curated reports distributed to 200 nation policy makers. There have been five IPCC Assessment Reports to date, the latest leading to a Paris Agreement in Dec. 2016 signed thus far by 172 nations to limit the amount of global Greenhouse gases emitted to producing no more than a 20 C warming of the atmosphere. These reports are a living evolving big data collection tracing 30 years of climate science research, observations, and model scenario intercomparisons. They contain more than 200,000 citations over a 30 year period that trace the evolution of the physical basis of climate science, the observed and predicted impact, risk and adaptation to increased greenhouse gases and mitigation approaches, pathways, policies for climate change. Document-topic and topic-term probability distributions are built from the vocabularies of the respective assessment report chapters and citations. Using Microsoft Bing, we retrieve 150,000 citations referenced across chapters and convert those citations to text. Using a word n-gram model based on a heterogeneous set of climate change terminology, lemmatization, noise filtering and stopword elimination, we calculate word frequencies for chapters and citations. Temporal document sets are built based on the assessment period. In addition to topic modeling, we employ cross domain correlation measures. Using the Jensen-Shannon divergence and Pearson correlation we build correlation matrices for chapter and citations topics. The shared vocabulary acts as the bridge between domains resulting in chapter-citation point pairs in space. Pairs are established based on a document-topic probability distribution. Each chapter and citation is associated with a vector of topics and based on the n most probable topics, we establish which chapter-citation pairs are most similar. We will perform posterior inferences based on Hastings -Metropolis simulated annealing MCMC algorithm to infer, from the evolution of topics starting from AR1 to AR4, assertions of topics for AR5 and potentially AR6.

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

DTIC Science & Technology

2012-09-30

of the present-day Arctic atmosphere in CCSM4. J. Climate, 2676-2695. Overeem, I ., R . S. Anderson, C. W. Wobus, G. D. Clow, F. E. Urban, and N...intensity of extreme Arctic cyclones? APPROACH I am targeting these objectives through a retrospective analysis of the transient 20th century...simulations (spanning years 1850-2005) among the GCMs participating in the latest Coupled Model Intercomparison Project (CMIP5). I am including 14

Summary for Policymakers IPCC Fourth Assessment Report, WorkingGroup III

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

Barker, Terry; Bashmakov, Igor; Bernstein, Lenny

2007-04-30

A. Introduction 1. The Working Group III contribution to theIPCC Fourth Assessment Report (AR4) focuses on new literature on thescientific, technological, environmental, economic and social aspects ofmitigation of climate change, published since the IPCC Third AssessmentReport (TAR) and the Special Reports on COB2B Capture and Storage (SRCCS)and on Safeguarding the Ozone Layer and the Global Climate System (SROC).The following summary is organised into six sections after thisintroduction: - Greenhouse gas (GHG) emission trends, - Mitigation in theshort and medium term, across different economic sectors (until 2030), -Mitigation in the long-term (beyond 2030), - Policies, measures andinstruments to mitigate climate change,more » - Sustainable development andclimate change mitigation, - Gaps in knowledge. References to thecorresponding chapter sections are indicated at each paragraph in squarebrackets. An explanation of terms, acronyms and chemical symbols used inthis SPM can be found in the glossary to the main report.« less

Harmonisation of Global Land-Use Scenarios for the Period 1500-2100 for IPCC-AR5

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

Hurtt, George; Chini, Louise Parsons; Frolking, Steve

2009-06-01

In preparation for the fifth Intergovernmental Panel on Climate Change climate change assessment (IPCC-AR5), the international community is developing new advanced computer models (CMs) to address the combined effects of human activities (e.g. land-use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being developed by four Integrated Assessment Modeling teams (IAMs) to be used as input to the CMs for future climate projections. The diversity of requirements and approaches among CMs and IAMs for tracking land-use changes (past, present, and future), presents major challenges for treating land-usemore » comprehensively and consistently between these communities. As part of an international working group, we have been working to meet these challenges by developing a "harmonized" set of land-use change scenarios that smoothly connects gridded historical reconstructions of land-use with future projections, in a format required by CMs. This approach to harmonizing the treatment of land-use between two key modeling communities, CMs and IAMs, represents a major advance that will facilitate more consistent and fuller treatments of land-use/land-use change effects including both CO2 emissions and corresponding land-surface changes.« less

Projecting Range Limits with Coupled Thermal Tolerance - Climate Change Models: An Example Based on Gray Snapper (Lutjanus griseus) along the U.S. East Coast

PubMed Central

Hare, Jonathan A.; Wuenschel, Mark J.; Kimball, Matthew E.

2012-01-01

We couple a species range limit hypothesis with the output of an ensemble of general circulation models to project the poleward range limit of gray snapper. Using laboratory-derived thermal limits and statistical downscaling from IPCC AR4 general circulation models, we project that gray snapper will shift northwards; the magnitude of this shift is dependent on the magnitude of climate change. We also evaluate the uncertainty in our projection and find that statistical uncertainty associated with the experimentally-derived thermal limits is the largest contributor (∼ 65%) to overall quantified uncertainty. This finding argues for more experimental work aimed at understanding and parameterizing the effects of climate change and variability on marine species. PMID:23284974

Authorship in IPCC AR5 and its implications for content: climate change and Indigenous populations in WGII.

PubMed

Ford, James D; Vanderbilt, Will; Berrang-Ford, Lea

This essay examines the extent to which we can expect Indigenous Knowledge, understanding, and voices on climate change ('Indigenous content') to be captured in WGII of the IPCC Fifth Assessment Report (AR5), based on an analysis of chapter authorship. Reviewing the publishing history of 309 chapter authors (CAs) to WGII, we document 9 (2.9%) to have published on climate change and Indigenous populations and involved as authors in 6/30 chapters. Drawing upon recent scholarship highlighting how authorship affect structure and content of assessment reports, we argue that, unaddressed, this will affect the extent to which Indigenous content is examined and assessed. While it is too late to alter the structure of AR5, there are opportunities to prioritize the recruitment of contributing authors and reviewers with expertise on Indigenous issues, raise awareness among CAs on the characteristics of impacts, adaptation, and vulnerability faced by Indigenous peoples, and highlight how Indigenous perspectives can help broaden our understanding of climate change and policy interventions.

Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC

NASA Astrophysics Data System (ADS)

Drouet, L.; Bosetti, V.; Tavoni, M.

2015-10-01

Strategies for dealing with climate change must incorporate and quantify all the relevant uncertainties, and be designed to manage the resulting risks. Here we employ the best available knowledge so far, summarized by the three working groups of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5; refs , , ), to quantify the uncertainty of mitigation costs, climate change dynamics, and economic damage for alternative carbon budgets. We rank climate policies according to different decision-making criteria concerning uncertainty, risk aversion and intertemporal preferences. Our findings show that preferences over uncertainties are as important as the choice of the widely discussed time discount factor. Climate policies consistent with limiting warming to 2 °C above preindustrial levels are compatible with a subset of decision-making criteria and some model parametrizations, but not with the commonly adopted expected utility framework.

From up to date climate and ocean evidence with updated UN emissions projections, the time is now to recommend an immediate massive effort on CO2.

NASA Astrophysics Data System (ADS)

Carter, Peter

2017-04-01

This paper provides further compelling evidence for 'an immediate, massive effort to control CO2 emissions, stopped by mid-century' (Cai, Lenton & Lontzek, 2016). Atmospheric CO2 which is above 405 ppm (actual and trend) still accelerating, despite flat emissions since 2014, with a 2015 >3ppm unprecedented spike in Earth history (A. Glikson),is on the worst case IPCC scenario. Atmospheric methane is increasing faster than its past 20-year rate, almost on the worst-case IPCC AR5 scenario (Global Carbon Project, 2016). Observed effects of atmospheric greenhouse gas (GHG) pollution are increasing faster. This includes long-lived atmospheric GHG concentrations, radiative forcing, surface average warming, Greenland ice sheet melting, Arctic daily sea ice anomaly, ocean heat (and rate of going deeper), ocean acidification, and ocean de-oxygenation. The atmospheric GHG concentration of 485 ppm CO2 eq (WMO, 2015) commits us to 'about 2°C' equilibrium (AR5). 2°C by 2100 would require 'substantial emissions reductions over the next few decades' (AR5). Instead, the May 2016 UN update on 'intended' national emissions targets under the Paris Agreement projects global emissions will be 16% higher by 2030 and the November 2016 International Energy Agency update projects energy-related CO2 eq emissions will be 30% higher by 2030, leading to 'around 2.7°C by 2100 and above 3°C thereafter'. Climate change feedback will be positive this century and multiple large vulnerable sources of amplifying feedback exist (AR5). 'Extensive tree mortality and widespread forest die-back linked to drought and temperature stress have been documented on all vegetated continents' (AR5). 'Recent studies suggest a weakening of the land sink, further amplifying atmospheric growth of CO2' (WMO, 2016). Under all but the best-case IPCC AR5 scenario, surface temperature is projected to increase above 2°C by 2100, which is above 3°C (equilibrium) after 2100, with ocean acidification still increasing at 2100. Ocean heat is increasing under all scenarios at 2100. For all producing regions 'With or without adaptation, negative impacts on average crop yields become likely from the 2030s' (AR5). Crop models do not capture all adverse effects. The climate change of 2030 is practically locked in. NASA NEX downscaled daily maximum temperature projections at 1.5°C are incompatible with today's crop yields in major agricultural regions. Climate-change-related impacts from extreme events are high at 1.5°C (AR5) and add to modeled crop declines. 'Some unique and threatened systems are already at risk from climate change (high confidence)' with 'risk of severe consequences' higher with warming of around 1.5°C (AR5). At today's surface temperature increase, 'risks associated with tipping points become moderate' and 'increase disproportionately' as temperature increases above 1.5°C (AR5). According to mitigation projections, global emissions would decline forthwith for a better than 66% chance of a 2°C limit by 2100 (over 3°C after 2100). Failure to do so would risk the future sustainability of civilization and the human population. The IPCC does not make recommendations so this falls on scientists. By recommending immediate (emergency) massive action on CO2, the science community would make a momentous contribution to the future of humanity.

Assessing Climate Change Risks Using a Multi-Model Approach

NASA Astrophysics Data System (ADS)

Knorr, W.; Scholze, M.; Prentice, C.

2007-12-01

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from the IPCC AR4 data archive using 16 climate models and mapping the proportions of model runs showing exceedance of natural variability in wildfire frequency and freshwater supply or shifts in vegetation cover. Our analysis does not assign probabilities to scenarios. Instead, we consider the distribution of outcomes within three sets of model runs grouped according to the amount of global warming they simulate: < 2 degree C (including committed climate change simulations), 2-3 degree C, and >3 degree C. Here, we are contrasting two different methods for calculating the risks: first we use an equal weighting approach giving every model within one of the three sets the same weight, and second, we weight the models according to their ability to model ENSO. The differences are underpinning the need for the development of more robust performance metrics for global climate models.

Emulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 2: Applications

NASA Astrophysics Data System (ADS)

Meinshausen, M.; Wigley, T. M. L.; Raper, S. C. B.

2011-02-01

Intercomparisons of coupled atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models are important for galvanizing our current scientific knowledge to project future climate. Interpreting such intercomparisons faces major challenges, not least because different models have been forced with different sets of forcing agents. Here, we show how an emulation approach with MAGICC6 can address such problems. In a companion paper (Meinshausen et al., 2011a), we show how the lower complexity carbon cycle-climate model MAGICC6 can be calibrated to emulate, with considerable accuracy, globally aggregated characteristics of these more complex models. Building on that, we examine here the Coupled Model Intercomparison Project's Phase 3 results (CMIP3). If forcing agents missed by individual AOGCMs in CMIP3 are considered, this reduces ensemble average temperature change from pre-industrial times to 2100 under SRES A1B by 0.4 °C. Differences in the results from the 1980 to 1999 base period (as reported in IPCC AR4) to 2100 are negligible, however, although there are some differences in the trajectories over the 21st century. In a second part of this study, we consider the new RCP scenarios that are to be investigated under the forthcoming CMIP5 intercomparison for the IPCC Fifth Assessment Report. For the highest scenario, RCP8.5, relative to pre-industrial levels, we project a median warming of around 4.6 °C by 2100 and more than 7 °C by 2300. For the lowest RCP scenario, RCP3-PD, the corresponding warming is around 1.5 °C by 2100, decreasing to around 1.1 °C by 2300 based on our AOGCM and carbon cycle model emulations. Implied cumulative CO2 emissions over the 21st century for RCP8.5 and RCP3-PD are 1881 GtC (1697 to 2034 GtC, 80% uncertainty range) and 381 GtC (334 to 488 GtC), when prescribing CO2 concentrations and accounting for uncertainty in the carbon cycle. Lastly, we assess the reasons why a previous MAGICC version (4.2) used in IPCC AR4 gave roughly 10% larger warmings over the 21st century compared to the CMIP3 average. We find that forcing differences and the use of slightly too high climate sensitivities inferred from idealized high-forcing runs were the major reasons for this difference.

Causes and implications of the growing divergence between climate model simulations and observations

NASA Astrophysics Data System (ADS)

Curry, Judith

2014-03-01

For the past 15+ years, there has been no increase in global average surface temperature, which has been referred to as a 'hiatus' in global warming. By contrast, estimates of expected warming in the first several decades of 21st century made by the IPCC AR4 were 0.2C/decade. This talk summarizes the recent CMIP5 climate model simulation results and comparisons with observational data. The most recent climate model simulations used in the AR5 indicate that the warming stagnation since 1998 is no longer consistent with model projections even at the 2% confidence level. Potential causes for the model-observation discrepancies are discussed. A particular focus of the talk is the role of multi-decadal natural internal variability on the climate variability of the 20th and early 21st centuries. The ``stadium wave'' climate signal is described, which propagates across the Northern Hemisphere through a network of ocean, ice, and atmospheric circulation regimes that self-organize into a collective tempo. The stadium wave hypothesis provides a plausible explanation for the hiatus in warming and helps explain why climate models did not predict this hiatus. Further, the new hypothesis suggests how long the hiatus might last. Implications of the hiatus are discussed in context of climate model sensitivity to CO2 forcing and attribution of the warming that was observed in the last quarter of the 20th century.

Assessing modelled spatial distributions of ice water path using satellite data

NASA Astrophysics Data System (ADS)

Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

2010-05-01

The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile).

PubMed

Orrego, R; Abarca-Del-Río, R; Ávila, A; Morales, L

2016-01-01

Climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962-1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070-2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°-40°S and 71°-74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns such as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

DOE PAGES

Orrego, R.; Abarca-del-Rio, R.; Avila, A.; ...

2016-09-28

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

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

Orrego, R.; Abarca-del-Rio, R.; Avila, A.

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

Estimating the potential for methane clathrate instability in the 1%-CO2 IPCC AR-4 simulations

NASA Astrophysics Data System (ADS)

Lamarque, Jean-François

2008-10-01

The recent work of Reagan and Moridis (2007) has shown that even a limited warming of 1 K over 100 years can lead to clathrate destabilization, leading to a significant flux of methane into the ocean water, at least for shallow deposits. Here we study the potential for methane clathrate destabilization by identifying the 100-year temperature increase in the available IPCC (Intergovernmental Panel on Climate Change) AR-4 1%-CO2 increase per year (up to doubling over pre-industrial conditions, which occurs after 70 years) simulations. Depending on assumptions made on the possible locations (in this case, only depth) of methane clathrates and on temperature dependence, our calculation leads to an estimated model-mean release of methane at the bottom of the ocean of approximately 560-2140 Tg(CH4)/year; as no actual geographical distribution of methane clathrates is considered here, these flux estimates must be viewed as upper bound estimates. Using an observed 1% ratio to estimate the amount of methane reaching the atmosphere, our analysis leads to a relatively small methane flux of approximately 5-21 Tg(CH4)/year, with an estimated inter-model standard deviation of approximately 30%. The role of sea-level rise by 2100 will be to further stabilize methane clathrates, albeit to a small amount as the sea-level rise is expected to be less than a few meters.

Northern African and Indian Precipitation at the end of the 21st Century: An Integrated Application of Regional and Global Climate Models

NASA Astrophysics Data System (ADS)

Patricola, C. M.; Cook, K. H.

2008-12-01

As greenhouse warming continues there is growing concern about the future climate of both Africa, which is highlighted by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) as exceptionally vulnerable to climate change, and India. Precipitation projections from the AOGCMs of the IPCC AR4 are relatively consistent over India, but not over northern Africa. Inconsistencies can be related to the model's inability to capture climate process correctly, deficiencies in physical parameterizations, different SST projections, or horizontal atmospheric resolution that is too coarse to realistically represent the tight gradients over West Africa and complex topography of East Africa and India. Treatment of the land surface in a model may also be an issue over West Africa and India where land-surface/atmosphere interactions are very important. Here a method for simulating future climate is developed and applied using a high-resolution regional model in conjunction with output from a suite of AOGCMs, drawing on the advantages of both the regional and global modeling approaches. Integration by the regional model allows for finer horizontal resolution and regionally appropriate selection of parameterizations and land-surface model. AOGCM output is used to provide SST projections and lateral boundary conditions to constrain the regional model. The control simulation corresponds to 1981-2000, and eight future simulations representing 2081-2100 are conducted, each constrained by a different AOGCM and forced by CO2 concentrations from the SRES A2 emissions scenario. After model spin-up, May through October remain for investigation. Analysis is focused on climate change parameters important for impacts on agriculture and water resource management, and is presented in a format compatible with the IPCC reports. Precipitation projections simulated by the regional model are quite consistent, with 75% or more ensemble members agreeing on the sign of the anomaly over vast regions of Africa and India. Over West Africa, where the regional model provides the greatest improvement over the AOGCMs in consistency of ensemble members, precipitation at the end of the century is generally projected to increase during May and decrease in June and July. Wetter conditions are simulated during August though October, with the exception of drying close to the Guinean Coast in August. In late summer, high rainfall rates are simulated more frequently in the future, indicating the possibility for increases in flooding events. The regional model's projections over India are in stark contrast to the AOGCM's, producing intense and generally widespread drying in August and September. The very promising method developed here is young and further potential developments are recognized, including the addition of ocean, vegetation, and dust models. Ensembles which employ other regional models, sets of parameterizations, and emissions scenarios should also be explored.

Evaluation of surface water budget and assessment the global water cycle for the IPCC AR4 A1B scenario simulations

NASA Astrophysics Data System (ADS)

Baek, H.; Park, E.; Kwon, W.

2009-12-01

Water balance calculations are becoming increasingly important for earth-system studies, because humans require water for their survival. Especially, the relationship between climate change and freshwater resources is of primary concern to human society and also has implications for all living species. The goal of this study is to assess the closure and annual variations of the water cycles based on the multi-model ensemble approach. In this study, the projection results of the previous works focusing on global and six sub-regions are updated using sixteen atmosphere-ocean general circulation model (AOGCM) simulations based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. Before projecting future climate, model performances are evaluated on the simulation of the present-day climate. From the result, we construct and use mainly multi-model ensembles (MMEs), which is referred to as MME9, defined from nine selected AOGCMs of higher performance. Analyzed variables include annual and seasonal precipitation, evaporation, and runoff. The overall projection results from MME9 show that most regions will experience warmer and wetter climate at the end of 21st century. The evaporation shows a very similar trend to precipitation, but not in the runoff projection. The internal and inter-model variabilities are larger in the runoff than both precipitation and evaporation. Moreover, the runoff is notably reduced in Europe at the end of 21st century.

Land-Use and Climate : first results from the LUCID experiments ; implications for experimental design in IPCC-AR5

NASA Astrophysics Data System (ADS)

de Noblet, N.; Pitman, A.; Participants, Lucid

2009-04-01

The project "Land-Use and Climate, IDentification of robust impacts" (LUCID) was conceived under the auspices of IGBP-iLEAPS and GEWEX-GLASS, to address the robustness of 'local' and possible remote impacts of land-use induced land-cover changes (LCC). LUCID explores, using methodologies that major climate modelling groups recognise, those impacts of LCC that are robust - that is, above the noise generated by model variability and consistent across a suite of climate models. To start with, seven climate models were run, in ensemble mode (5 realisations per 31-years long experiment), with prescribed observed sea-surface temperatures (SSTs) and sea ice extent (SIc). Pre-industrial and present-day simulations were used to explore the impacts of biogeophysical impacts of human-induced land cover change. The imposed LCC perturbation led to statistically significant changes in latent heat flux and near-surface temperature over the regions of land cover change, but few significant changes in precipitation. Our results show no common remote impacts of land cover change. They also highlight a dilemma for both historical hind-casts and future projections; land cover change is regionally important, but it is not feasible within the time frame of the next IPCC (AR5) assessment to implement this change commonly across multiple models. Further analysis are in progress and will be presented to identify the continental regions where changes in LCC may have been more important than the combined changes in SSTs, SIc and CO2 between the pre-industrial times and nowadays.

The Earth System Grid Center for Enabling Technologies (ESG-CET): Scaling the Earth System Grid to Petascale Data

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

Williams, Dean N.

2007-09-27

This report, which summarizes work carried out by the ESG-CET during the period April 1, 2007 through September 30, 2007, includes discussion of overall progress, period goals, highlights, collaborations and presentations. To learn more about our project, please visit the Earth System Grid website. In addition, this report will be forwarded to the DOE SciDAC project management, the Office of Biological and Environmental Research (OBER) project management, national and international stakeholders (e.g., the Community Climate System Model (CCSM), the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the Climate Science Computational End Station (CCES), etc.), and collaborators. Themore » ESG-CET executive committee consists of David Bernholdt, ORNL; Ian Foster, ANL; Don Middleton, NCAR; and Dean Williams, LLNL. The ESG-CET team is a collective of researchers and scientists with diverse domain knowledge, whose home institutions include seven laboratories (ANL, LANL, LBNL, LLNL, NCAR, ORNL, PMEL) and one university (ISI/USC); all work in close collaboration with the project's stakeholders and domain researchers and scientists. During this semi-annual reporting period, the ESG-CET increased its efforts on completing requirement documents, framework design, and component prototyping. As we strove to complete and expand the overall ESG-CET architectural plans and use-case scenarios to fit our constituency's scope of use, we continued to provide production-level services to the community. These services continued for IPCC AR4, CCES, and CCSM, and were extended to include Cloud Feedback Model Intercomparison Project (CFMIP) data.« less

Investigation of the climate change within Moscow metropolitan area

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Trusilova, Kristina; Konstantinov, Pavel; Samsonov, Timofey

2014-05-01

As the urbanization continues worldwide more than half of the Earth's population live in the cities (U.N., 2010). Therefore the vulnerability of the urban environment - the living space for millions of people - to the climate change has to be investigated. It is well known that urban features strongly influence the atmospheric boundary layer and determine the microclimatic features of the local environment, such as urban heat island (UHI). Available temperature observations in cities are, however, influenced by the natural climate variations, human-induced climate warming (IPCC, 2007) and in the same time by the growth and structural modification of the urban areas. The relationship between these three factors and their roles in climate changes in the cities are very important for the climatic forecast and requires better understanding. In this study, we made analysis of the air temperature change and urban heat island evolution within Moscow urban area during decades 1970-2010, while this urban area had undergone intensive growth and building modification allowing the population of Moscow to increase from 7 to 12 million people. Analysis was based on the data from several meteorological stations in Moscow region and Moscow city, including meteorological observatory of Lomonosov Moscow State University. Differences in climate change between urban and rural stations, changes of the power and shape of urban heat island and their relationships with changes of building height and density were investigated. Collected data and obtained results are currently to be used for the validation of the regional climate model COSMO-CLM with the purpose to use this model for further more detailed climate research and forecasts for Moscow metropolitan area. References: 1. U.N. (2010), World Urbanization Prospects. The 2009 Revision.Rep., 1-47 pp, United Nations. Department of Economic and Social Affairs. Population Division., New York. 2. IPCC (2007), IPCC Fourth Assessment Report: Climate Change 2007 (AR4) Rep.,Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Atmospheric Aerosol Properties and Climate Impacts

NASA Technical Reports Server (NTRS)

Chin, Mian; Kahn, Ralph A.; Remer, Lorraine A.; Yu, Hongbin; Rind, David; Feingold, Graham; Quinn, Patricia K.; Schwartz, Stephen E.; Streets, David G.; DeCola, Phillip;

Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea.

PubMed

Kim, Jinsoo; Choi, Jisun; Choi, Chuluong; Park, Soyoung

2013-05-01

This study examined the separate and combined impacts of future changes in climate and land use/land cover (LULC) on streamflow in the Hoeya River Basin, South Korea, using the representative concentration pathway (RCP) 4.5 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). First, a LULC change model was developed using RCP 4.5 and RCP 8.5 storylines and logistic regression. Three scenarios (climate change only, LULC change only, and climate and LULC change combined) were established, and the streamflow in future periods under these scenarios was simulated by the Soil and Water Assessment Tool (SWAT) model. Each scenario showed distinct seasonal variations in streamflow. Under climate change only, streamflow increased in spring and winter but decreased in summer and autumn, whereas LULC change increased high flow during wet periods but decreased low flow in dry periods. Although the LULC change had less effect than climate change on the changes in streamflow, the effect of LULC change on streamflow was significant. The result for the combined scenario was similar to that of the climate change only scenario, but with larger seasonal changes in streamflow. Although the effects of LULC change were smaller than those caused by climate change, LULC changes may heighten the problems of increased seasonal variability in streamflow caused by climate change. The results obtained in this study provide further insight into the availability of future streamflow and can aid in water resource management planning in the study area. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of Drought Occurrence and Climate Change in the Pearl River Basin in South China

NASA Astrophysics Data System (ADS)

DU, Y.; Chen, J.; Wang, K.; Shi, H.

2015-12-01

This study uses the Variable Infiltration Capacity (VIC) Model to simulate the hydrological processes over the Pearl River basin in South China. The observed streamflow data in the Pearl River Basin for the period 1951-2000 are used to evaluate the model simulation results. Further, in this study, the 55 datasets of climate projection from 18 General Circulation Models (GCMs) for the IPCC AR4 (SRES A2/A1B/B1) and AR5 (RCP 2.6/4.5/6.0/8.5) are used to drive the VIC model at 0.5°× 0.5°spatial resolution and daily temporal resolution. Then, the monthly Standard Precipitation Index (SPI) and standardized runoff index (SRI) are generated to detect the drought occurrence. This study validates the GCMs projection through comparing the observed precipitation for the period of 2000-2013. Then, spatial variation of the frequency change of moderate drought, severe drought and extreme drought are analyzed for the 21st century. The study reveals that the frequencies of severe drought and extreme drought occurrences over the Pearl River Basin increase along with time. Specifically, for the scenario of AR5 RCP 8.5, the east and west parts of the Pearl River Basin most likely suffer from severe drought and extreme drought with an increased frequency throughout the 21st century.

The Contribution of Agriculture, Forestry and other Land Use activities to Global Warming, 1990-2012.

PubMed

Tubiello, Francesco N; Salvatore, Mirella; Ferrara, Alessandro F; House, Jo; Federici, Sandro; Rossi, Simone; Biancalani, Riccardo; Condor Golec, Rocio D; Jacobs, Heather; Flammini, Alessandro; Prosperi, Paolo; Cardenas-Galindo, Paola; Schmidhuber, Josef; Sanz Sanchez, Maria J; Srivastava, Nalin; Smith, Pete

2015-01-10

We refine the information available through the IPCC AR5 with regard to recent trends in global GHG emissions from agriculture, forestry and other land uses (AFOLU), including global emission updates to 2012. Using all three available AFOLU datasets employed for analysis in the IPCC AR5, rather than just one as done in the IPCC AR5 WGIII Summary for Policy Makers, our analyses point to a down-revision of global AFOLU shares of total anthropogenic emissions, while providing important additional information on subsectoral trends. Our findings confirm that the share of AFOLU emissions to the anthropogenic total declined over time. They indicate a decadal average of 28.7 ± 1.5% in the 1990s and 23.6 ± 2.1% in the 2000s and an annual value of 21.2 ± 1.5% in 2010. The IPCC AR5 had indicated a 24% share in 2010. In contrast to previous decades, when emissions from land use (land use, land use change and forestry, including deforestation) were significantly larger than those from agriculture (crop and livestock production), in 2010 agriculture was the larger component, contributing 11.2 ± 0.4% of total GHG emissions, compared to 10.0 ± 1.2% of the land use sector. Deforestation was responsible for only 8% of total anthropogenic emissions in 2010, compared to 12% in the 1990s. Since 2010, the last year assessed by the IPCC AR5, new FAO estimates indicate that land use emissions have remained stable, at about 4.8 Gt CO 2 eq yr -1 in 2012. Emissions minus removals have also remained stable, at 3.2 Gt CO 2 eq yr -1 in 2012. By contrast, agriculture emissions have continued to grow, at roughly 1% annually, and remained larger than the land use sector, reaching 5.4 Gt CO 2 eq yr -1 in 2012. These results are useful to further inform the current climate policy debate on land use, suggesting that more efforts and resources should be directed to further explore options for mitigation in agriculture, much in line with the large efforts devoted to REDD+ in the past decade. © 2015 John Wiley & Sons Ltd.

The use of Meteonorm weather generator for climate change studies

NASA Astrophysics Data System (ADS)

Remund, J.; Müller, S. C.; Schilter, C.; Rihm, B.

2010-09-01

The global climatological database Meteonorm (www.meteonorm.com) is widely used as meteorological input for simulation of solar applications and buildings. It's a combination of a climate database, a spatial interpolation tool and a stochastic weather generator. Like this typical years with hourly or minute time resolution can be calculated for any site. The input of Meteonorm for global radiation is the Global Energy Balance Archive (GEBA, http://proto-geba.ethz.ch). All other meteorological parameters are taken from databases of WMO and NCDC (periods 1961-90 and 1996-2005). The stochastic generation of global radiation is based on a Markov chain model for daily values and an autoregressive model for hourly and minute values (Aguiar and Collares-Pereira, 1988 and 1992). The generation of temperature is based on global radiation and measured distribution of daily temperature values of approx. 5000 sites. Meteonorm generates also additional parameters like precipitation, wind speed or radiation parameters like diffuse and direct normal irradiance. Meteonorm can also be used for climate change studies. Instead of climate values, the results of IPCC AR4 results are used as input. From all 18 public models an average has been made at a resolution of 1°. The anomalies of the parameters temperature, precipitation and global radiation and the three scenarios B1, A1B and A2 have been included. With the combination of Meteonorm's current database 1961-90, the interpolation algorithms and the stochastic generation typical years can be calculated for any site, for different scenarios and for any period between 2010 and 2200. From the analysis of variations of year to year and month to month variations of temperature, precipitation and global radiation of the past ten years as well of climate model forecasts (from project prudence, http://prudence.dmi.dk) a simple autoregressive model has been formed which is used to generate realistic monthly time series of future periods. Meteonorm can therefore be used as a relatively simple method to enhance the spatial and temporal resolution instead of using complicated and time consuming downscaling methods based on regional climate models. The combination of Meteonorm, gridded historical (based on work of Luterbach et al.) and IPCC results has been used for studies of vegetation simulation between 1660 and 2600 (publication of first version based on IS92a scenario and limited time period 1950 - 2100: http://www.pbl.nl/images/H5_Part2_van%20CCE_opmaak%28def%29_tcm61-46625.pdf). It's also applicable for other adaptation studies for e.g. road surfaces or building simulation. In Meteonorm 6.1 one scenario (IS92a) and one climate model has been included (Hadley CM3). In the new Meteonorm 7 (coming spring 2011) the model averages of the three above mentioned scenarios of the IPCC AR4 will be included.

Dominant frames in legacy and social media coverage of the IPCC Fifth Assessment Report

NASA Astrophysics Data System (ADS)

O'Neill, Saffron; Williams, Hywel T. P.; Kurz, Tim; Wiersma, Bouke; Boykoff, Maxwell

2015-04-01

The media are powerful agents that translate information across the science-policy interface, framing it for audiences. Yet frames are never neutral: they define an issue, identify causes, make moral judgements and shape proposed solutions. Here, we show how the IPCC Fifth Assessment Report (AR5) was framed in UK and US broadcast and print coverage, and on Twitter. Coverage of IPCC Working Group I (WGI) was contested and politicized, employing the `Settled Science, Uncertain Science, Political or Ideological Struggle and Role of Science’ frames. WGII coverage commonly used Disaster or Security. More diverse frames were employed for WGII and WGIII, including Economics and Morality and Ethics. Framing also varied by media institution: for example, the BBC used Uncertain Science, whereas Channel 4 did not. Coverage varied by working group, with WGIII gaining far less coverage than WGI or WGII. We suggest that media coverage and framing of AR5 was influenced by its sequential three-part structure and by the availability of accessible narratives and visuals. We recommend that these communication lessons be applied to future climate science reports.

The climate crisis: An introductory guide to climate change

NASA Astrophysics Data System (ADS)

Trenberth, Kevin E.

2011-06-01

Human-induced climate change, sometimes called “global warming,” has, unfortunately, become a “hot” topic, embroiled in controversy, misinformation, and claims and counterclaims. It should not be this way, because there are many scientific facts that provide solid information on which to base policy. There is a very strong observational, theoretical, and modeling base in physical science that underpins current understanding of what has happened to Earth's climate and why and what the prospects are for the future under certain assumptions. Moreover, these changes have impacts, which are apt to grow, on the environment and human society. To avoid or reduce these impacts and the economic and human effects of undesirable future climate change requires actions that are strongly opposed by those with vested interests in the status quo, some of whom have funded misinformation campaigns that have successfully confused the public and some politicians, leading to paralysis in political action. Without mitigation of climate change, one would suppose that at least society would plan sensibly for the changes already happening and projected, but such future adaptation plans are also largely in limbo. The implication is that we will suffer the consequences. All of these aspects are addressed in this informative and attractive book, which is written for a fairly general but technically informed audience. The book is strongly based upon the 2007 Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) and therefore has a solid scientific basis. Many figures, graphs, and maps come from the three IPCC working group reports, although the captions often do not explain the detail shown. Given that the IPCC reports totaled nearly 3000 pages, to distill the complex material down to 249 pages is no mean task, and the authors have succeeded quite well.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Progress toward Consensus Estimates of Regional Glacier Mass Balances for IPCC AR5

NASA Astrophysics Data System (ADS)

Arendt, A. A.; Gardner, A. S.; Cogley, J. G.

2011-12-01

Glaciers are potentially large contributors to rising sea level. Since the last IPCC report in 2007 (AR4), there has been a widespread increase in the use of geodetic observations from satellite and airborne platforms to complement field observations of glacier mass balance, as well as significant improvements in the global glacier inventory. Here we summarize our ongoing efforts to integrate data from multiple sources to arrive at a consensus estimate for each region, and to quantify uncertainties in those estimates. We will use examples from Alaska to illustrate methods for combining Gravity Recovery and Climate Experiment (GRACE), elevation differencing and field observations into a single time series with related uncertainty estimates. We will pay particular attention to reconciling discrepancies between GRACE estimates from multiple processing centers. We will also investigate the extent to which improvements in the glacier inventory affect the accuracy of our regional mass balances.

Climate change unlikely to increase malaria burden in West Africa

NASA Astrophysics Data System (ADS)

Yamana, Teresa K.; Bomblies, Arne; Eltahir, Elfatih A. B.

2016-11-01

The impact of climate change on malaria transmission has been hotly debated. Recent conclusions have been drawn using relatively simple biological models and statistical approaches, with inconsistent predictions. Consequently, the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) echoes this uncertainty, with no clear guidance for the impacts of climate change on malaria transmission, yet recognizing a strong association between local climate and malaria. Here, we present results from a decade-long study involving field observations and a sophisticated model simulating village-scale transmission. We drive the malaria model using select climate models that correctly reproduce historical West African climate, and project reduced malaria burden in a western sub-region and insignificant impact in an eastern sub-region. Projected impacts of climate change on malaria transmission in this region are not of serious concern.

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

PubMed

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

Interactive Photochemistry in Earth System Models to Assess Uncertainty in Ozone and Greenhouse Gases. Final report

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

Prather, Michael J.; Hsu, Juno; Nicolau, Alex

Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N 2O, CH 4, HFCs, CFCs, and O 3. Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfullymore » implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O 3, N 2O, NO y and CH 4) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.« less

Making sense of past climate changes

NASA Astrophysics Data System (ADS)

Masson-Delmotte, Valérie; Schulz, Michael

2014-05-01

This presentation will summarize the paleoclimate perspective in IPCC AR5, which combines information from natural archives, paleoclimate simulations using both the CMIP5 framework and other simulations, model-data comparisons for model evaluation at hemispheric to regional scales, detection - attribution, and process studies throughout timescales such as polar amplification, carbon cycle or sea level change. It will highlight new findings and coordinated efforts which, within the scientific community, have allowed new information to emerge on time for AR5. It will also stress the aspects which could not be covered or assessed as well as suggestions for further inclusion of paleoclimate information to inform projections.

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Climate Products and Services to Meet the Challenges of Extreme Events

NASA Astrophysics Data System (ADS)

McCalla, M. R.

2008-12-01

The 2002 Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM1)-sponsored report, Weather Information for Surface Transportation: National Needs Assessment Report, addressed meteorological needs for six core modes of surface transportation: roadway, railway, transit, marine transportation/operations, pipeline, and airport ground operations. The report's goal was to articulate the weather information needs and attendant surface transportation weather products and services for those entities that use, operate, and manage America's surface transportation infrastructure. The report documented weather thresholds and associated impacts which are critical for decision-making in surface transportation. More recently, the 2008 Climate Change Science Program's (CCSP) Synthesis and Assessment Product (SAP) 4.7 entitled, Impacts of Climate Change and Variability on Transportation Systems and Infrastructure: Gulf Coast Study, Phase I, included many of the impacts from the OFCM- sponsored report in Table 1.1 of this SAP.2 The Intergovernmental Panel on Climate Change (IPCC) reported that since 1950, there has been an increase in the number of heat waves, heavy precipitation events, and areas of drought. Moreover, the IPCC indicated that greater wind speeds could accompany more severe tropical cyclones.3 Taken together, the OFCM, CCSP, and IPCC reports indicate not only the significance of extreme events, but also the potential increasing significance of many of the weather thresholds and associated impacts which are critical for decision-making in surface transportation. Accordingly, there is a real and urgent need to understand what climate products and services are available now to address the weather thresholds within the surface transportation arena. It is equally urgent to understand what new climate products and services are needed to address these weather thresholds, and articulate what can be done to fill the gap between the existing federal climate products and services and the needed federal climate products and services which will address these weather thresholds. Just as important, as we work to meet the needs, a robust education and outreach program is essential to take full advantage of new products, services and capabilities. To ascertain what climate products and services currently exist to address weather thresholds relative to surface transportation, what climate products and services are needed to address these weather thresholds, and how to bridge the gap between what is available and what is needed, the OFCM surveyed the federal meteorological community. Consistent with the extreme events highlighted in the IPCC report, the OFCM survey categorized the weather thresholds associated with surface transportation into the following extreme event areas: (a) excessive heat, (b) winter precipitation, (c) summer precipitation, (d) high winds, and (e) flooding and coastal inundation. The survey results, the gap analysis, as well as OFCM's planned, follow-on activities with additional categories (i.e., in addition to surface transportation) and weather thresholds will be shared with meeting participants. 1 The OFCM is an interdepartmental office established in response to Public Law 87-843 with the mission to ensure the effective use of federal meteorological resources by leading the systematic coordination of operational weather and climate requirements, products, services, and supporting research among the federal agencies. 2 http://www.climatescience.gov/Library/sap/sap4-7/final-report/sap4-7-final-ch1.pdf 3 http://www.gcrio.org/ipcc/ar4/wg1/faq/ar4wg1faq-3-3.pdf

Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

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

Qian, Yun; Long, Charles N.; Wang, Hailong

2012-02-17

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulations in the IPCC AR4 GCMs against ARM ground measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity, for both inter-model deviation and model-measurement discrepancy. Our intercomparisons of three CF or sky-cover related dataset reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The results also show that the model-observation and the inter-model deviations have a similar magnitude for themore » total CF (TCF) and the normalized cloud effect, and they are twice as large as the surface downward solar radiation and cloud transmissivity. This implies that the other cloud properties, such as cloud optical depth and height, have a similar magnitude of disparity to TCF among the GCMs, and suggests that a better agreement among the GCMs in solar radiative fluxes could be the result of compensating errors in either cloud vertical structure, cloud optical depth or cloud fraction. Similar deviation pattern between inter-model and model-measurement suggests that the climate models tend to generate larger bias against observations for those variables with larger inter-model deviation. The simulated TCF from IPCC AR4 GCMs are very scattered through all seasons over three ARM sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). The GCMs perform better at SGP than at Manus and NSA in simulating the seasonal variation and probability distribution of TCF; however, the TCF in these models is remarkably underpredicted and cloud transmissivity is less susceptible to the change of TCF than the observed at SGP. Much larger inter-model deviation and model bias are found over NSA than the other sites in estimating the TCF, cloud transmissivity and cloud-radiation interaction, suggesting that the Arctic region continues to challenge cloud simulations in climate models. Most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels in the tropics. The high altitude CF is much larger in the GCMs than the observation and the inter-model variability of CF also reaches maximum at high levels in the tropics. Most of the GCMs tend to underpredict CF by 50-150% relative to the measurement average at low and middle levels over SGP. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near surface over the Arctic. The internal variability of CF simulated in ensemble runs with the same model is very minimal.« less

Defining climate change scenario characteristics with a phase space of cumulative primary energy and carbon intensity

NASA Astrophysics Data System (ADS)

Ritchie, Justin; Dowlatabadi, Hadi

2018-02-01

Climate change modeling relies on projections of future greenhouse gas emissions and other phenomena leading to changes in planetary radiative forcing. Scenarios of socio-technical development consistent with end-of-century forcing levels are commonly produced by integrated assessment models. However, outlooks for forcing from fossil energy combustion can also be presented and defined in terms of two essential components: total energy use this century and the carbon intensity of that energy. This formulation allows a phase space diagram to succinctly describe a broad range of possible outcomes for carbon emissions from the future energy system. In the following paper, we demonstrate this phase space method with the Representative Concentration Pathways (RCPs) as used in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The resulting RCP phase space is applied to map IPCC Working Group III (WGIII) reference case ‘no policy’ scenarios. Once these scenarios are described as coordinates in the phase space, data mining techniques can readily distill their core features. Accordingly, we conduct a k-means cluster analysis to distinguish the shared outlooks of these scenarios for oil, gas and coal resource use. As a whole, the AR5 database depicts a transition toward re-carbonization, where a world without climate policy inevitably leads to an energy supply with increasing carbon intensity. This orientation runs counter to the experienced ‘dynamics as usual’ of gradual decarbonization, suggesting climate change targets outlined in the Paris Accord are more readily achievable than projected to date.

Test of High-resolution Global and Regional Climate Model Projections

NASA Astrophysics Data System (ADS)

Stenchikov, Georgiy; Nikulin, Grigory; Hansson, Ulf; Kjellström, Erik; Raj, Jerry; Bangalath, Hamza; Osipov, Sergey

2014-05-01

In scope of CORDEX project we have simulated the past (1975-2005) and future (2006-2050) climates using the GFDL global high-resolution atmospheric model (HIRAM) and the Rossby Center nested regional model RCA4 for the Middle East and North Africa (MENA) region. Both global and nested runs were performed with roughly the same spatial resolution of 25 km in latitude and longitude, and were driven by the 2°x2.5°-resolution fields from GFDL ESM2M IPCC AR5 runs. The global HIRAM simulations could naturally account for interaction of regional processes with the larger-scale circulation features like Indian Summer Monsoon, which is lacking from regional model setup. Therefore in this study we specifically address the consistency of "global" and "regional" downscalings. The performance of RCA4, HIRAM, and ESM2M is tested based on mean, extreme, trends, seasonal and inter-annual variability of surface temperature, precipitation, and winds. The impact of climate change on dust storm activity, extreme precipitation and water resources is specifically addressed. We found that the global and regional climate projections appear to be quite consistent for the modeled period and differ more significantly from ESM2M than between each other.

Coastal sea level projections with improved accounting for vertical land motion

PubMed Central

Han, Guoqi; Ma, Zhimin; Chen, Nan; Yang, Jingsong; Chen, Nancy

2015-01-01

Regional and coastal mean sea level projections in the Intergovernmental Panel for Climate Change (IPCC) Fifth Assessment Report (AR5) account only for vertical land motion (VLM) associated with glacial isostatic adjustment (GIA), which may significantly under- or over-estimate sea level rise. Here we adjust AR5-like regional projections with the VLM from Global Positioning Satellite (GPS) measurements and/or from a combination of altimetry and tide-gauge data, which include both GIA and non-GIA VLM. Our results at selected tide-gauge locations on the North American and East Asian coasts show drastically different projections with and without non-GIA VLM being accounted for. The present study points to the importance of correcting IPCC AR5 coastal projections for the non-GIA VLM in making adaptation decisions. PMID:26526287

Coastal sea level projections with improved accounting for vertical land motion.

PubMed

Han, Guoqi; Ma, Zhimin; Chen, Nan; Yang, Jingsong; Chen, Nancy

2015-11-03

Regional and coastal mean sea level projections in the Intergovernmental Panel for Climate Change (IPCC) Fifth Assessment Report (AR5) account only for vertical land motion (VLM) associated with glacial isostatic adjustment (GIA), which may significantly under- or over-estimate sea level rise. Here we adjust AR5-like regional projections with the VLM from Global Positioning Satellite (GPS) measurements and/or from a combination of altimetry and tide-gauge data, which include both GIA and non-GIA VLM. Our results at selected tide-gauge locations on the North American and East Asian coasts show drastically different projections with and without non-GIA VLM being accounted for. The present study points to the importance of correcting IPCC AR5 coastal projections for the non-GIA VLM in making adaptation decisions.

Population exposure to heat-related extremes: Demographic change vs climate change

NASA Astrophysics Data System (ADS)

Jones, B.; O'Neill, B. C.; Tebaldi, C.; Oleson, K. W.

2014-12-01

Extreme heat events are projected to increase in frequency and intensity in the coming decades [1]. The physical effects of extreme heat on human populations are well-documented, and anticipating changes in future exposure to extreme heat is a key component of adequate planning/mitigation [2, 3]. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we focus on systematically quantifying exposure to extreme heat as a function of both climate and population change. We compare exposure outcomes across multiple global climate and spatial population scenarios, and characterize the relative contributions of each to population exposure to extreme heat. We consider a 2 x 2 matrix of climate and population output, using projections of heat extremes corresponding to RCP 4.5 and RCP 8.5 from the NCAR community land model, and spatial population projections for SSP 3 and SSP 5 from the NCAR spatial population downscaling model. Our primary comparison is across RCPs - exposure outcomes from RCP 4.5 versus RCP 8.5 - paying particular attention to how variation depends on the choice of SSP in terms of aggregate global and regional exposure, as well as the spatial distribution of exposure. We assess how aggregate exposure changes based on the choice of SSP, and which driver is more important, population or climate change (i.e. does that outcome vary more as a result of RCP or SSP). We further decompose the population component to analyze the contributions of total population change, migration, and changes in local spatial structure. Preliminary results from a similar study of the US suggests a four-to-six fold increase in total exposure by the latter half of the 21st century. Changes in population are as important as changes in climate in driving this outcome, and there is regional variation in the relative importance of each. Aggregate population growth, as well as redistribution of the population across larger US regions, strongly affects outcomes while smaller-scale spatial patterns of population change have smaller effects. [1] Collins, M. et al. (2013) Contribution of WG I to the 5th AR of the IPCC[2] Romero-Lankao, P. et al (2014) Contribution of WG II to the 5th AR of the IPCC[3] Walsh, J. et al. (2014) The 3rd National Climate Assessment

Coupled model simulations of climate changes in the 20th century and beyond

NASA Astrophysics Data System (ADS)

Yu, Yongqiang; Zhi, Hai; Wang, Bin; Wan, Hui; Li, Chao; Liu, Hailong; Li, Wei; Zheng, Weipeng; Zhou, Tianjun

2008-07-01

Several scenario experiments of the IPCC 4th Assessment Report (AR4) are performed by version g1.0 of a Flexible coupled Ocean-Atmosphere-Land System Model (FGOALS) developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), including the “Climate of the 20th century experiment”, “CO2 1% increase per year to doubling experiment” and two separate IPCC greenhouse gases emission scenarios A1B and B1 experiments. To distinguish between the different impacts of natural variations and human activities on the climate change, three-member ensemble runs are performed for each scenario experiment. The coupled model simulations show: (1) from 1900 to 2000, the global mean temperature increases about 0.5°C and the major increase occurs during the later half of the 20th century, which is in consistent with the observations that highlights the coupled model’s ability to reproduce the climate changes since the industrial revolution; (2) the global mean surface air temperature increases about 1.6°C in the CO2 doubling experiment and 1.5°C and 2.4°C in the A1B and B1 scenarios, respectively. The global warming is indicated by not only the changes of the surface temperature and precipitation but also the temperature increase in the deep ocean. The thermal expansion of the sea water would induce the rise of the global mean sea level. Both the control run and the 20th century climate change run are carried out again with version g1.1 of FGOALS, in which the cold biases in the high latitudes were removed. They are then compared with those from version g1.0 of FGOALS in order to distinguish the effect of the model biases on the simulation of global warming.

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

Global warming effects: future feasibility of current cooling equipment for animal houses

NASA Astrophysics Data System (ADS)

Valiño, V.; Perdigones, A.; García, J. L.; de La Plaza, S.

2009-04-01

Interest in global warming effects on the agricultural systems is currently high, especially in areas which are likely to be more affected by this temperature rising, i.e. the Mediterranean area (IPCC, 2008). According to this report, the model projections of surface warming predict a temperature increase between 0.5°C to 1.5°C in the European area by the period 2020-2029. The aim of the present work was to assess the future consequences of the global warming effect on the feasibility of the cooling equipment in animal houses. Several equipment combinations were compared by means of modelling the inside climate in fattening pig houses, including forced ventilation and cooling pad. The modelling was carried out for six different European locations: Spain, Greece, Italy, The Netherlands, Germany and the United Kingdom, for the today conditions; secondly, the global warming effect in the inside climate was considered in a second set of simulations, and a mean temperature rising of 2°C was taken into account. Climate data. The six European locations were: Madrid (Spain); Aliartos (Greece); Bedford (The United Kingdom); Schipol (The Netherlands); Milan (Italy); and Stuttgart (Germany). From every location, the available climate data were monthly mean temperature (To; °C); monthly mean relative humidity (HRo, %) and monthly mean solar irradiation on horizontal surface (So; W m-2). From these monthly values, hourly means were calculated resulting in 24 data for a typical day, each month. Climate model. In this study, cooling strategies resulted from the combination of natural ventilation, mechanical ventilation and cooling pads. The climate model was developed taking into account the following energy fluxes: solar radiation, ventilation (Seginer, 2002), animal heat losses (Blanes and Pedersen, 2005), and loss of energy due to the cooling pads (Seginer, 2002). Results for the present work, show a comparative scene of the inside climate by using different cooling equipment combinations, from natural ventilation to cooling pads. Simulations which include the effects of climate change show the evolution in cooling technologies which will be necessary in this kind of animal houses, in six European locations, if the global temperature rising continues with the current rate. The necessary changes in cooling technologies of animal houses, will be important in Europe when the outside air temperature rising is greater than or equal to two Celsius degrees. Intergovernmental Panel on the Climate Change. 2008. Climate Change 2007: Synthesis Report. http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4syr.pdf I. Seginer. 2002. The Penman-Monteith Evapotranspiration Equation as an Element in Greenhouse Ventilation Design. Biosystems Eng. 82(4): 423-439. doi:10.1006/bioe2002.0086 V. Blanes, S. Pedersen. 2005. Ventilation Flow in Pig Houses measured and calculated by Carbon Dioxide, Moisture and Heat Balance Equations. Biosystems Eng. 92(4): 483-493. doi:10.1006/j.biosystemseng.2005.09.002

Regional Climate and Streamflow Projections in North America Under IPCC CMIP5 Scenarios

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Troch, P. A. A.; Mukherjee, R.

2014-12-01

The Colorado River system is the predominant source of water supply for the Southwest U.S. and is already fully allocated, making the region's environmental and economic health particularly sensitive to annual and multi-year streamflow variability. Observed streamflow declines in the Colorado Basin in recent years are likely due to synergistic combination of anthropogenic global warming and natural climate variability, which are creating an overall warmer and more extreme climate. IPCC assessment reports have projected warmer and drier conditions in arid to semi-arid regions (e.g. Solomon et al. 2007). The NAM-related precipitation contributes to substantial Colorado streamflows. Recent climate change studies for the Southwest U.S. region project a dire future, with chronic drought, and substantially reduced Colorado River flows. These regional effects reflect the general observation that climate is being more extreme globally, with areas climatologically favored to be wet getting wetter and areas favored to be dry getting drier (Wang et al. 2012). Multi-scale downscaling modeling experiments are designed using recent IPCC AR5 global climate projections, which incorporate regional climate and hydrologic modeling components. The Weather Research and Forecasting model (WRF) has been selected as the main regional modeling tool; the Variable Infiltration Capacity model (VIC) will be used to generate streamflow projections for the Colorado River Basin. The WRF domain is set up to follow the CORDEX-North America guideline with 25km grid spacing, and VIC model is individually calibrated for upper and lower Colorado River basins in 1/8° resolution. The multi-scale climate and hydrology study aims to characterize how the combination of climate change and natural climate variability is changing cool and warm season precipitation. Further, to preserve the downscaled RCM sensitivity and maintain a reasonable climatology mean based on observed record, a new bias correction technique is applied when using the RCM climatology to the streamflow model. Of specific interest is how major droughts associated with La Niña-like conditions may worsen in the future, as these are the times when the Colorado River system is most critically stressed and would define the "worst case" scenario for water resource planning.

Assessing the present and future probability of Hurricane Harvey's rainfall

NASA Astrophysics Data System (ADS)

Emanuel, Kerry

2017-11-01

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981–2000 and will increase to 18% over the period 2081–2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century.

Integration and Exposure of Large Scale Computational Resources Across the Earth System Grid Federation (ESGF)

NASA Astrophysics Data System (ADS)

Duffy, D.; Maxwell, T. P.; Doutriaux, C.; Williams, D. N.; Chaudhary, A.; Ames, S.

2015-12-01

As the size of remote sensing observations and model output data grows, the volume of the data has become overwhelming, even to many scientific experts. As societies are forced to better understand, mitigate, and adapt to climate changes, the combination of Earth observation data and global climate model projects is crucial to not only scientists but to policy makers, downstream applications, and even the public. Scientific progress on understanding climate is critically dependent on the availability of a reliable infrastructure that promotes data access, management, and provenance. The Earth System Grid Federation (ESGF) has created such an environment for the Intergovernmental Panel on Climate Change (IPCC). ESGF provides a federated global cyber infrastructure for data access and management of model outputs generated for the IPCC Assessment Reports (AR). The current generation of the ESGF federated grid allows consumers of the data to find and download data with limited capabilities for server-side processing. Since the amount of data for future AR is expected to grow dramatically, ESGF is working on integrating server-side analytics throughout the federation. The ESGF Compute Working Team (CWT) has created a Web Processing Service (WPS) Application Programming Interface (API) to enable access scalable computational resources. The API is the exposure point to high performance computing resources across the federation. Specifically, the API allows users to execute simple operations, such as maximum, minimum, average, and anomalies, on ESGF data without having to download the data. These operations are executed at the ESGF data node site with access to large amounts of parallel computing capabilities. This presentation will highlight the WPS API, its capabilities, provide implementation details, and discuss future developments.

Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

PubMed Central

Hao, Zhenchun; Ju, Qin; Jiang, Weijuan; Zhu, Changjun

2013-01-01

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least. PMID:23970827

The importance of hydrological uncertainty assessment methods in climate change impact studies

NASA Astrophysics Data System (ADS)

Honti, M.; Scheidegger, A.; Stamm, C.

2014-08-01

Climate change impact assessments have become more and more popular in hydrology since the middle 1980s with a recent boost after the publication of the IPCC AR4 report. From hundreds of impact studies a quasi-standard methodology has emerged, to a large extent shaped by the growing public demand for predicting how water resources management or flood protection should change in the coming decades. The "standard" workflow relies on a model cascade from global circulation model (GCM) predictions for selected IPCC scenarios to future catchment hydrology. Uncertainty is present at each level and propagates through the model cascade. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. Our hypothesis was that the relative importance of climatic and hydrologic uncertainty is (among other factors) heavily influenced by the uncertainty assessment method. To test this we carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on two small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment with two different likelihood functions. One was a time series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was an approximate likelihood function for the flow quantiles. The results showed that the expected climatic impact on flow quantiles was small compared to prediction uncertainty. The choice of uncertainty assessment method actually determined what sources of uncertainty could be identified at all. This demonstrated that one could arrive at rather different conclusions about the causes behind predictive uncertainty for the same hydrological model and calibration data when considering different objective functions for calibration.

The Risks of Missing the 2°C Target and the Risks of Framing the Target As 2°C

NASA Astrophysics Data System (ADS)

Nichols, L. H.

2014-12-01

The publication of IPCC AR5 has made it very clear that we are at risk of missing the 2°C target. It has also made it clear that the risks of missing this target would be very dire. But when read through a precautionary lens, it also illustrates potential risks of framing an appropriate climate target as 2°C. We ought to be doing all we can to limit the extent of climate change as much as possible, and framing our target as limiting warming to 2°C may mask the demandingness and urgency of addressing climate change aggressively and holistically. In this session I will summarize my work on what precaution demands in the face of climate change and discuss how it applies to AR5. I argue for a Catastrophic Precautionary Principle that gives us strong moral reasons to take precautionary measures against threats of catastrophe, such as those posed by climate change. I will explain how the IPCC's discussion of the five reasons for concern about climate change support a strong moral argument that we ought to be taking a much more precautionary approach to climate policy than is currently evidenced by UNFCCC agreements and domestic policies around the world. While AR5 supports the conclusion that we should not risk missing the 2°C target, it also supports reevaluating what our target - and more generally what our comprehensive approach to climate policy - should be. In this way, I will discuss the complex science-ethics-policy nexus and the role of climate science in guiding precautionary global climate policies.

Global precipitation measurements for validating climate models

NASA Astrophysics Data System (ADS)

Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

2017-11-01

The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

Contributions of the Atmospheric Radiation Measurement (ARM) Program and the ARM Climate Research Facility to the U.S. Climate Change Science Program

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

SA Edgerton; LR Roeder

The Earth’s surface temperature is determined by the balance between incoming solar radiation and thermal (or infrared) radiation emitted by the Earth back to space. Changes in atmospheric composition, including greenhouse gases, clouds, and aerosols can alter this balance and produce significant climate change. Global climate models (GCMs) are the primary tool for quantifying future climate change; however, there remain significant uncertainties in the GCM treatment of clouds, aerosol, and their effects on the Earth’s energy balance. The 2007 assessment (AR4) by the Intergovernmental Panel on Climate Change (IPCC) reports a substantial range among GCMs in climate sensitivity to greenhousemore » gas emissions. The largest contributor to this range lies in how different models handle changes in the way clouds absorb or reflect radiative energy in a changing climate (Solomon et al. 2007). In 1989, the U.S. Department of Energy (DOE) Office of Science created the Atmospheric Radiation Measurement (ARM) Program within the Office of Biological and Environmental Research (BER) to address scientific uncertainties related to global climate change, with a specific focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. To address this problem, BER has adopted a unique two-pronged approach: * The ARM Climate Research Facility (ACRF), a scientific user facility for obtaining long-term measurements of radiative fluxes, cloud and aerosol properties, and related atmospheric characteristics in diverse climate regimes. * The ARM Science Program, focused on the analysis of ACRF data to address climate science issues associated with clouds, aerosols, and radiation, and to improve GCMs. This report describes accomplishments of the BER ARM Program toward addressing the primary uncertainties related to climate change prediction as identified by the IPCC.« less

Measuring Engagement with the Potential Consequences of Climate Change

NASA Astrophysics Data System (ADS)

Young, N.; Danielson, R. W.; Lombardi, D.

2015-12-01

Across three studies, we investigated engagement with the consequences of climate change. We drew from the conceptual change and risk analysis literatures to find the factors that determine how much people will care about future risks. Questions derived from these factors were then asked about many hypothesized consequences of climate change. These consequences were drawn from an Intergovernmental Panel on Climate Change special report (IPCC, 2012) and, in the third study, additionally from the IPCC AR5 (IPCC, 2014). The first two studies, using undergraduate students, demonstrated that some consequences were indeed considerably more engaging than others. The third study used a more representative sample of American adults, drawn from Amazon Mechanical Turk and used the Global Warming's Six Americas Screening Tool (Maibach, Leiserowitz, Roser-Renouf, Mertz, & Akerlof, 2011) in a large screening survey to find 20 participants in each of the six audiences defined by this tool. These participants were then asked about the potential consequences of climate change. Results again showed that some consequences are considered more engaging than others, and also showed the ways in which members of these six audiences perceive the consequences of climate change differently.

Permafrost carbon-climate feedbacks accelerate global warming.

PubMed

Koven, Charles D; Ringeval, Bruno; Friedlingstein, Pierre; Ciais, Philippe; Cadule, Patricia; Khvorostyanov, Dmitry; Krinner, Gerhard; Tarnocai, Charles

2011-09-06

Permafrost soils contain enormous amounts of organic carbon, which could act as a positive feedback to global climate change due to enhanced respiration rates with warming. We have used a terrestrial ecosystem model that includes permafrost carbon dynamics, inhibition of respiration in frozen soil layers, vertical mixing of soil carbon from surface to permafrost layers, and CH(4) emissions from flooded areas, and which better matches new circumpolar inventories of soil carbon stocks, to explore the potential for carbon-climate feedbacks at high latitudes. Contrary to model results for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), when permafrost processes are included, terrestrial ecosystems north of 60°N could shift from being a sink to a source of CO(2) by the end of the 21st century when forced by a Special Report on Emissions Scenarios (SRES) A2 climate change scenario. Between 1860 and 2100, the model response to combined CO(2) fertilization and climate change changes from a sink of 68 Pg to a 27 + -7 Pg sink to 4 + -18 Pg source, depending on the processes and parameter values used. The integrated change in carbon due to climate change shifts from near zero, which is within the range of previous model estimates, to a climate-induced loss of carbon by ecosystems in the range of 25 + -3 to 85 + -16 Pg C, depending on processes included in the model, with a best estimate of a 62 + -7 Pg C loss. Methane emissions from high-latitude regions are calculated to increase from 34 Tg CH(4)/y to 41-70 Tg CH(4)/y, with increases due to CO(2) fertilization, permafrost thaw, and warming-induced increased CH(4) flux densities partially offset by a reduction in wetland extent.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

Assessing the present and future probability of Hurricane Harvey's rainfall.

PubMed

Emanuel, Kerry

2017-11-28

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981-2000 and will increase to 18% over the period 2081-2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century. Copyright © 2017 the Author(s). Published by PNAS.

Climate-change-driven accelerated sea-level rise detected in the altimeter era.

PubMed

Nerem, R S; Beckley, B D; Fasullo, J T; Hamlington, B D; Masters, D; Mitchum, G T

2018-02-27

Using a 25-y time series of precision satellite altimeter data from TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3, we estimate the climate-change-driven acceleration of global mean sea level over the last 25 y to be 0.084 ± 0.025 mm/y 2 Coupled with the average climate-change-driven rate of sea level rise over these same 25 y of 2.9 mm/y, simple extrapolation of the quadratic implies global mean sea level could rise 65 ± 12 cm by 2100 compared with 2005, roughly in agreement with the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5) model projections. Copyright © 2018 the Author(s). Published by PNAS.

The Equatorial Pacific Cold Tongue Simulated by IPCC AR4 Coupled GCMs: Upper Ocean Heat Budget and Feedback Analysis

DTIC Science & Technology

2012-05-15

ET AL .: THE PACIFIC COLD TONGUE BIAS ANALYSIS C05024 circulation, which intensifies the surface easterly winds over the Pacific Basin, further...productivity, and in carbon cycling since it is the major oceanic source of C02 for the atmosphere [Field et al , 1998; Calvo et al , 2011]. Large SST anomalies...used for climate predictions and projec- tions [Neelin et al , 1992; Mechoso et al , 1995; Delecluse et al , 1998; Laufet al , 2001; Davey

Simulating Soil C Stock with the Process-based Model CQESTR

NASA Astrophysics Data System (ADS)

Gollany, H.; Liang, Y.; Rickman, R.; Albrecht, S.; Follett, R.; Wilhelm, W.; Novak, J.; Douglas, C.

2009-04-01

The prospect of storing carbon (C) in soil, as soil organic matter (SOM), provides an opportunity for agriculture to contribute to the reduction of carbon dioxide in the atmosphere while enhancing soil properties. Soil C models are useful for examining the complex interactions between crop, soil management practices and climate and their effects on long-term carbon storage or loss. The process-based carbon model CQESTR, pronounced ‘sequester,' was developed by USDA-ARS scientists at the Columbia Plateau Conservation Research Center, Pendleton, Oregon, USA. It computes the rate of biological decomposition of crop residues or organic amendments as they convert to SOM. CQESTR uses readily available field-scale data to assess long-term effects of cropping systems or crop residue removal on SOM accretion/loss in agricultural soil. Data inputs include weather, above- ground and below-ground biomass additions, N content of residues and amendments, soil properties, and management factors such as tillage and crop rotation. The model was calibrated using information from six long-term experiments across North America (Florence, SC, 19 yrs; Lincoln, NE, 26 yrs; Hoytville, OH, 31 yrs; Breton, AB, 60 yrs; Pendleton, OR, 76 yrs; and Columbia, MO, >100 yrs) having a range of soil properties and climate. CQESTR was validated using data from several additional long-term experiments (8 - 106 yrs) across North America having a range of SOM (7.3 - 57.9 g SOM/kg). Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites resulted in a linear relationship with an r2 of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM/kg. Estimated SOC values from CQESTR and IPCC (the Intergovernmental Panel on Climate Change) were compared to observed values in three relatively long-term experiments (20 - 24 years). At one site, CQESTR and IPCC estimates of SOC stocks were within 5% of each other for three rotations. At a second site, decreasing tillage intensity increased SOC stocks for winter wheat-fallow rotation for both observed and estimated values by CQESTR and IPCC. At the third site, CQESTR simulated an increase in SOC stocks with increased fertility levels, while IPCC estimates of SOC stocks did not reflect an increase. The CQESTR model successfully predicts SOM dynamics from various management practices and offers the potential for C sequestration planning for C credits or to guide crop residue removal for bio-energy production without degrading the soil resource, environmental quality, or productivity.

Reassessing Storm Surge Risk for New York City (Invited)

NASA Astrophysics Data System (ADS)

Lin, N.; Emanuel, K.

2013-12-01

New York City (NYC) is highly vulnerable to tropical cyclone (TC) storm surge flooding. In a previous study, we coupled a (reanalysis- or GCM-driven) hurricane model with hydrodynamic models to simulate large numbers of synthetic surge events under observed and projected climates and assess surge threat for NYC. The storm surge return levels under the current and future climates (IPCC AR4 A1B scenario) were obtained. The results showed that the distribution of surge levels may shift to higher values in the future by a magnitude comparable to the projected sea-level rise. The study focused on typical TCs that have a storm size of the climatological mean for the Atlantic Basin and pass within a 200-km radius of the Battery, NYC. In October 2012, Hurricane Sandy, a barely Category-1 storm that made landfall about 200-km southwest from the Battery, caused the highest surge flooding of the instrumental record (~3.5 m above the mean sea level or ~2.8 m surge over the high tide) at the Battery. The extreme surge was due to the fact that the storm was a 'hybrid' event, undergoing extensive extratropical transition when making landfall almost perpendicularly to the NJ coast with an unusually large size. Sandy's case calls for a reassessment of storm surge risk for NYC that account for the special features of the storms in this region. In this reassessment, we account for the effect of extratropical transition on the wind fields through improving the surface background wind estimation, which was assumed to be uniform for typical TCs, by developing a representation of the interaction between the highly localized potential vorticity anomaly of the TC and its environmental baroclinic fields. We account for the storm size variation through incorporating the full probability distribution of the size for the region. Our preliminary results show that estimated wind and surge return levels are much higher with the effect of extratropical transition. The effect of the storm size variation is relatively large in the upper tail of the surge distribution. Also, we will update the prediction for future climates using the IPCC AR5 RCP 8.5 and RCP 4.5 scenarios, and extend our focus area further south to capture storms that can induce high surges at the Battery, although making landfall relatively further away on the NJ coast. The results will be compared with those using the AR4 scenario in our previous study. The combined effects of storm climatology change and sea level rise on the risk of NYC surge flooding will be discussed.

Dissemination of Climate Model Output to the Public and Commercial Sector

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

Robert Stockwell, PhD

2010-09-23

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature andmore » precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).« less

Simple Climate Model Evaluation Using Impulse Response Tests

NASA Astrophysics Data System (ADS)

Schwarber, A.; Hartin, C.; Smith, S. J.

2017-12-01

Simple climate models (SCMs) are central tools used to incorporate climate responses into human-Earth system modeling. SCMs are computationally inexpensive, making them an ideal tool for a variety of analyses, including consideration of uncertainty. Despite their wide use, many SCMs lack rigorous testing of their fundamental responses to perturbations. Here, following recommendations of a recent National Academy of Sciences report, we compare several SCMs (Hector-deoclim, MAGICC 5.3, MAGICC 6.0, and the IPCC AR5 impulse response function) to diagnose model behavior and understand the fundamental system responses within each model. We conduct stylized perturbations (emissions and forcing/concentration) of three different chemical species: CO2, CH4, and BC. We find that all 4 models respond similarly in terms of overall shape, however, there are important differences in the timing and magnitude of the responses. For example, the response to a BC pulse differs over the first 20 years after the pulse among the models, a finding that is due to differences in model structure. Such perturbation experiments are difficult to conduct in complex models due to internal model noise, making a direct comparison with simple models challenging. We can, however, compare the simplified model response from a 4xCO2 step experiment to the same stylized experiment carried out by CMIP5 models, thereby testing the ability of SCMs to emulate complex model results. This work allows an assessment of how well current understanding of Earth system responses are incorporated into multi-model frameworks by way of simple climate models.

Hydrodynamic evaluation of long term impacts of climate change and coastal effluents in the Arabian Gulf.

PubMed

Elhakeem, Abubaker; Elshorbagy, Walid

2015-12-30

A comprehensive basin wide hydrodynamic evaluation has been carried out to assess the long term impacts of climate change and coastal effluents on the salinity and seawater temperature of the Arabian Gulf (AG) using Delft3D-Flow model. The long term impacts of climate change scenarios A2 and B1 of the IPCC-AR4 on the AG hydrodynamics were evaluated. Using the current capacity and production rates of coastal desalination, power, and refinery plants, two projection scenarios until the year 2080 with 30 year intervals were developed namely the realistic and the optimistic discharge scenarios. Simulations of the individual climate change scenarios ascertained overall increase of the AG salinity and temperature and decrease of precipitation. The changes varied spatially with different scenarios as per the depth, proximity to exchange with ocean water, flushing, vertical mixing, and flow restriction. The individual tested scenarios of coastal projected discharges showed significant effects but within 10-20 km from the outfalls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Scientists' Views about Attribution of Global Warming

NASA Astrophysics Data System (ADS)

Verheggen, Bart; Strengers, Bart; Cook, John; van Dorland, Rob; Vringer, Kees; Peters, Jeroen; Visser, Hans; Meyer, Leo

2015-04-01

What do scientists think? That is an important question when engaging in science communication, in which an attempt is made to communicate the scientific understanding to a lay audience. To address this question we undertook a large and detailed survey among scientists studying various aspects of climate change , dubbed "perhaps the most thorough survey of climate scientists ever" by well-known climate scientist and science communicator Gavin Schmidt. Among more than 1800 respondents we found widespread agreement that global warming is predominantly caused by human greenhouse gases. This consensus strengthens with increased expertise, as defined by the number of self-reported articles in the peer-reviewed literature. 90% of respondents with more than 10 climate-related peer-reviewed publications (about half of all respondents), agreed that anthropogenic greenhouse gases are the dominant cause of recent global warming, i.e. having contributed more than half of the observed warming. With this survey we specified what the consensus position entails with much greater specificity than previous studies. The relevance of this consensus for science communication will be discussed. Another important result from our survey is that the main attribution statement in IPCC's fourth assessment report (AR4) may lead to an underestimate of the greenhouse gas contribution to warming, because it implicitly includes the lesser known masking effect of cooling aerosols. This shows the importance of the exact wording in high-profile reports such as those from IPCC in how the statement is perceived, even by fellow scientists. The phrasing was improved in the most recent assessment report (AR5). Respondents who characterized the human influence on climate as insignificant, reported having the most frequent media coverage regarding their views on climate change. This shows that contrarian opinions are amplified in the media in relation to their prevalence in the scientific community. This is related to what is sometimes referred to as "false balance" in media reporting and may partly explain the divergence between public and scientific opinion regarding climate change.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Permafrost carbon-climate feedbacks accelerate global warming

PubMed Central

Koven, Charles D.; Ringeval, Bruno; Friedlingstein, Pierre; Ciais, Philippe; Cadule, Patricia; Khvorostyanov, Dmitry; Krinner, Gerhard; Tarnocai, Charles

2011-01-01

Permafrost soils contain enormous amounts of organic carbon, which could act as a positive feedback to global climate change due to enhanced respiration rates with warming. We have used a terrestrial ecosystem model that includes permafrost carbon dynamics, inhibition of respiration in frozen soil layers, vertical mixing of soil carbon from surface to permafrost layers, and CH4 emissions from flooded areas, and which better matches new circumpolar inventories of soil carbon stocks, to explore the potential for carbon-climate feedbacks at high latitudes. Contrary to model results for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), when permafrost processes are included, terrestrial ecosystems north of 60°N could shift from being a sink to a source of CO2 by the end of the 21st century when forced by a Special Report on Emissions Scenarios (SRES) A2 climate change scenario. Between 1860 and 2100, the model response to combined CO2 fertilization and climate change changes from a sink of 68 Pg to a 27 + -7 Pg sink to 4 + -18 Pg source, depending on the processes and parameter values used. The integrated change in carbon due to climate change shifts from near zero, which is within the range of previous model estimates, to a climate-induced loss of carbon by ecosystems in the range of 25 + -3 to 85 + -16 Pg C, depending on processes included in the model, with a best estimate of a 62 + -7 Pg C loss. Methane emissions from high-latitude regions are calculated to increase from 34 Tg CH4/y to 41–70 Tg CH4/y, with increases due to CO2 fertilization, permafrost thaw, and warming-induced increased CH4 flux densities partially offset by a reduction in wetland extent. PMID:21852573

Mid-Twenty-First-Century Changes in Global Wave Energy Flux: Single-Model, Single-Forcing and Single-Scenario Ensemble Projections

NASA Astrophysics Data System (ADS)

Semedo, Alvaro; Lemos, Gil; Dobrynin, Mikhail; Behrens, Arno; Staneva, Joanna; Miranda, Pedro

2017-04-01

The knowledge of ocean surface wave energy fluxes (or wave power) is of outmost relevance since wave power has a direct impact in coastal erosion, but also in sediment transport and beach nourishment, and ship, as well as in coastal and offshore infrastructures design. Changes in the global wave energy flux pattern can alter significantly the impact of waves in continental shelf and coastal areas. Up until recently the impact of climate change in future global wave climate had received very little attention. Some single model single scenario global wave climate projections, based on CMIP3 scenarios, were pursuit under the auspices of the COWCLIP (coordinated ocean wave climate projections) project, and received some attention in the IPCC (Intergovernmental Panel for Climate Change) AR5 (fifth assessment report). In the present study the impact of a warmer climate in the near future global wave energy flux climate is investigated through a 4-member "coherent" ensemble of wave climate projections: single-model, single-forcing, and single-scenario. In this methodology model variability is reduced, leaving only room for the climate change signal. The four ensemble members were produced with the wave model WAM, forced with wind speed and ice coverage from EC-Earth projections, following the representative concentration pathway with a high emissions scenario 8.5 (RCP8.5). The ensemble present climate reference period (the control run) has been set for 1976 to 2005. The projected changes in the global wave energy flux climate are analyzed for the 2031-2060 period.

Scientists' views about attribution of global warming.

PubMed

Verheggen, Bart; Strengers, Bart; Cook, John; van Dorland, Rob; Vringer, Kees; Peters, Jeroen; Visser, Hans; Meyer, Leo

2014-08-19

Results are presented from a survey held among 1868 scientists studying various aspects of climate change, including physical climate, climate impacts, and mitigation. The survey was unique in its size, broadness and level of detail. Consistent with other research, we found that, as the level of expertise in climate science grew, so too did the level of agreement on anthropogenic causation. 90% of respondents with more than 10 climate-related peer-reviewed publications (about half of all respondents), explicitly agreed with anthropogenic greenhouse gases (GHGs) being the dominant driver of recent global warming. The respondents' quantitative estimate of the GHG contribution appeared to strongly depend on their judgment or knowledge of the cooling effect of aerosols. The phrasing of the IPCC attribution statement in its fourth assessment report (AR4)-providing a lower limit for the isolated GHG contribution-may have led to an underestimation of the GHG influence on recent warming. The phrasing was improved in AR5. We also report on the respondents' views on other factors contributing to global warming; of these Land Use and Land Cover Change (LULCC) was considered the most important. Respondents who characterized human influence on climate as insignificant, reported having had the most frequent media coverage regarding their views on climate change.

The Impact of Climate Change in Rainfall Erosivity Index on Humid Mudstone Area

NASA Astrophysics Data System (ADS)

Yang, Ci-Jian; Lin, Jiun-Chuan

2017-04-01

It has been quite often pointed out in many relevant studies that climate change may result in negative impacts on soil erosion. Then, humid mudstone area is highly susceptible to climate change. Taiwan has extreme erosion in badland area, with annual precipitation over 2000 mm/y which is a considerably 3 times higher than other badland areas around the world, and with around 9-13 cm/y in denudation rate. This is the reason why the Erren River, a badland dominated basin has the highest mean sediment yield in the world, over 105 t km2 y. This study aims to know how the climate change would affect soil erosion from the source in the Erren River catchment. Firstly, the data of hourly precipitation from 1992 to 2016 are used to establish the regression between rainfall erosivity index (R, one of component for USLE) and precipitation. Secondly, using the 10 climate change models (provide form IPCC AR5) simulates the changes of monthly precipitation in different scenario from 2017 to 2216, and then over 200 years prediction R values can be use to describe the tendency of soil erosion in the future. The results show that (1) the relationship between rainfall erosion index and precipitation has high correction (>0.85) during 1992-2016. (2) From 2017 to 2216, 7 scenarios show that annual rainfall erosion index will increase over 2-18%. In contrast, the others will decrease over 7-14%. Overall, the variations of annual rainfall erosion index fall in the range of -14 to 18%, but it is important to pay attention to the variation of annual rainfall erosion index in extreme years. These fall in the range of -34 to 239%. This explains the extremity of soil erosion will occur easily in the future. Keywords: Climate Change, Mudstone, Rainfall Erosivity Index, IPCC AR5

A Brazilian Vulnerability Index Towards Natural Disasters and Climatic Change - Flashfloods and Landslides.

NASA Astrophysics Data System (ADS)

Debortoli, N. S.; Camarinha, P. I., Sr.; Marengo, J. A.; Rodrigues, R.

2015-12-01

There are some evidences that hydrological climate extremes events have become more frequent an intense in the last decades due to climatic change. In Brazil, flashfloods and landslides were responsible for 74% of the deaths related to natural disasters in 1991-2010 period. In this sense, climate change could be considered a threat which can further increase these numbers, if actions of adaptation and reducing vulnerability are not taken. To evaluate Brazil's vulnerability hotspots to these disasters, two vulnerability indexes were developed using three sets of variables: (1) climate, with IPCC climate extreme indexes; (2) environmental, including land use, drainage systems, relief map, slope, road density and hydrography variables; (3) socioeconomic, including Gini coefficient, HDI (Human Development Index), housing conditions and poverty-related index. The variables were normalized on a scale between 0 to 1 and related using Map Algebra technique (ArcGIS). As part of the effort to contribute to the elaboration of the Third National Communication to the United Nations Framework Convention on Climate Change (UNFCCC), and to contribute to the assessment of impacts on strategic country's issues, simulations at higher resolution were carried out using Eta-20km RCM (Regional Climate Model) nested with two global climate models: HadGEM ES and MIROC 5 (INPE Brazilian National Institute for Space Research). For the baseline period of 1961-1990, the vulnerability indexes were adjusted by an iterative process, which was validated by comparing it to the Brazilian National Disasters Data. The same indexes found at baseline were used to estimate the vulnerability until the end of the XXI century, using the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. The results indicate a large increase in Brazil's vulnerability to landslides mainly in coastal zone, southern states, high lands of southeast states, and along the Amazon River due to climatic aspects only, not considering other factors such as increase in population size, etc. Flashfloods vulnerability, on the other hand, increases mostly in the south/southeast regions, the northeast coastal zone and parts of the Amazon basin. Funded by: Ministry of Science and Technology of Brazil and the United Nations Development Program in Brazil.

Analysis of Changes in the Lorenz Energy Budget of the Atmosphere

NASA Astrophysics Data System (ADS)

Ellis, T. D.

2009-12-01

Several recent papers have addressed the topic of changes in global precipitation rates related to changes in Earth's global energy balance. Less studied are the processes that may be governing the large-scale regional distribution of precipitation around the globe. This study uses the energy budget partition paradigm first put forth by Lorenz (1955) and follows the methodology of Arpé et al. (1986) and Oriol (1982) to identify latitude bands where the partition of energy amongst zonal and eddy kinetic and potential energy bins may account for the spatial patterns of precipitation change predicted by many IPCC AR4 models. In doing so, this study may help to identify whether or not the climate change predicted by these models is indeed creating enhanced baroclinic storms in the mid-latitudes or if there are other mechanisms at work producing the patterns of precipitation change.

Climate impacts on agricultural biomass production in the CORDEX.be project context

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van Schaeybroeck, Bert; Termonia, Piet; Willems, Patrick; Van Lipzig, Nicole; Marbaix, Philippe; van Ypersele, Jean-Pascal; Fettweis, Xavier; De Ridder, Koen; Stavrakou, Trissevgeni; Luyten, Patrick; Pottiaux, Eric

2016-04-01

The most important coordinated international effort to translate the IPCC-AR5 outcomes to regional climate modelling is the so-called "COordinated Regional climate Downscaling EXperiment" (CORDEX, http://wcrp-cordex.ipsl.jussieu.fr/). CORDEX.be is a national initiative that aims at combining the Belgian climate and impact modelling research into a single network. The climate network structure is naturally imposed by the top-down data flow, from the four participating upper-air Regional Climate Modelling groups towards seven Local Impact Models (LIMs). In addition to the production of regional climate projections following the CORDEX guidelines, very high-resolution results are provided at convection-permitting resolutions of about 4 km across Belgium. These results are coupled to seven local-impact models with severity indices as output. A multi-model approach is taken that allows uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. The down-scaled scenarios at 4 km resolution allow for impact assessment in different Belgian agro-ecological zones. Climate impacts on arable agriculture are quantified using REGCROP which is a regional dynamic agri-meteorological model geared towards modelling climate impact on biomass production of arable crops (Gobin, 2010, 2012). Results from previous work show that heat stress and water shortages lead to reduced crop growth, whereas increased CO2-concentrations and a prolonged growing season have a positive effect on crop yields. The interaction between these effects depend on the crop type and the field conditions. Root crops such as potato will experience increased drought stress particularly when the probability rises that sensitive crop stages coincide with dry spells. This may be aggravated when wet springs cause water logging in the field and delay planting dates. Despite lower summer precipitation projections for future climate in Belgium, winter cereal yield reductions due to drought stress will be smaller due to earlier maturity. Preliminary results will be presented using the new scenario runs for Belgium.

Can we model observed soil carbon changes from a dense inventory? A case study over England and Wales using three versions of the ORCHIDEE ecosystem model (AR5, AR5-PRIM and O-CN)

NASA Astrophysics Data System (ADS)

Guenet, B.; Moyano, F. E.; Vuichard, N.; Kirk, G. J. D.; Bellamy, P. H.; Zaehle, S.; Ciais, P.

2013-12-01

A widespread decrease of the topsoil carbon content was observed over England and Wales during the period 1978-2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr-1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in heterotrophic respiration or net primary productivity were the main causes. So far, all the models used to reproduce the NSI data have not accounted for plant-soil interactions and have only been soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), in order to separate the effect of trends in soil carbon input from soil carbon mineralization induced by climate trends over 1978-2003. The first version of the model (ORCHIDEE-AR5), used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first-order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests either that climate change is not the main driver for observed soil carbon losses or that the ORCHIDEE model even with priming or N effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.

Can we model observed soil carbon changes from a dense inventory? A case study over england and wales using three version of orchidee ecosystem model (AR5, AR5-PRIM and O-CN)

NASA Astrophysics Data System (ADS)

Guenet, B.; Moyano, F. E.; Vuichard, N.; Kirk, G. J. D.; Bellamy, P. H.; Zaehle, S.; Ciais, P.

2013-07-01

A widespread decrease of the top soil carbon content was observed over England and Wales during the period 1978-2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr-1 over 141 550 km2. Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in soil respiration or primary production were the main causes. So far, all the models used to reproduce the NSI data did not account for plant-soil interactions and were only soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE, in order to separate the effect of trends in soil carbon input, and soil carbon mineralisation induced by climate trends over 1978-2003. The first version of the model (ORCHIDEE-AR5) used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests that either climate change is not the main driver for observed soil carbon losses, or that the ORCHIDEE model even with priming or N-effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.

The Earth System Grid Federation: An Open Infrastructure for Access to Distributed Geospatial Data

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

Ananthakrishnan, Rachana; Bell, Gavin; Cinquini, Luca

2013-01-01

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration that aims at developing the software infrastructure needed to facilitate and empower the study of climate change on a global scale. The ESGF s architecture employs a system of geographically distributed peer nodes, which are independently administered yet united by the adoption of common federation protocols and application programming interfaces (APIs). The cornerstones of its interoperability are the peer-to-peer messaging that is continuously exchanged among all nodes in the federation; a shared architecture and API for search and discovery; and a security infrastructure based on industry standards (OpenID, SSL,more » GSI and SAML). The ESGF software is developed collaboratively across institutional boundaries and made available to the community as open source. It has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the entire model output used for the next international assessment report on climate change (IPCC-AR5) and a suite of satellite observations (obs4MIPs) and reanalysis data sets (ANA4MIPs).« less

The Earth System Grid Federation: An Open Infrastructure for Access to Distributed Geo-Spatial Data

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

Cinquini, Luca; Crichton, Daniel; Miller, Neill

2012-01-01

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration that aims at developing the software infrastructure needed to facilitate and empower the study of climate change on a global scale. The ESGF s architecture employs a system of geographically distributed peer nodes, which are independently administered yet united by the adoption of common federation protocols and application programming interfaces (APIs). The cornerstones of its interoperability are the peer-to-peer messaging that is continuously exchanged among all nodes in the federation; a shared architecture and API for search and discovery; and a security infrastructure based on industry standards (OpenID, SSL,more » GSI and SAML). The ESGF software is developed collaboratively across institutional boundaries and made available to the community as open source. It has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the entire model output used for the next international assessment report on climate change (IPCC-AR5) and a suite of satellite observations (obs4MIPs) and reanalysis data sets (ANA4MIPs).« less

The Earth System Grid Federation : an Open Infrastructure for Access to Distributed Geospatial Data

NASA Technical Reports Server (NTRS)

Cinquini, Luca; Crichton, Daniel; Mattmann, Chris; Harney, John; Shipman, Galen; Wang, Feiyi; Ananthakrishnan, Rachana; Miller, Neill; Denvil, Sebastian; Morgan, Mark;

Patterns of authorship in the IPCC Working Group III report

NASA Astrophysics Data System (ADS)

Corbera, Esteve; Calvet-Mir, Laura; Hughes, Hannah; Paterson, Matthew

2016-01-01

The Intergovernmental Panel on Climate Change (IPCC) has completed its Fifth Assessment Report (AR5). Here, we explore the social scientific networks informing Working Group III (WGIII) assessment of mitigation for the AR5. Identifying authors’ institutional pathways, we highlight the persistence and extent of North-South inequalities in the authorship of the report, revealing the dominance of US and UK institutions as training sites for WGIII authors. Examining patterns of co-authorship between WGIII authors, we identify the unevenness in co-authoring relations, with a small number of authors co-writing regularly and indicative of an epistemic community’s influence over the IPCC’s definition of mitigation. These co-authoring networks follow regional patterns, with significant EU-BRICS collaboration and authors from the US relatively insular. From a disciplinary perspective, economists, engineers, physicists and natural scientists remain central to the process, with insignificant participation of scholars from the humanities. The shared training and career paths made apparent through our analysis suggest that the idea that broader geographic participation may lead to a wider range of viewpoints and cultural understandings of climate change mitigation may not be as sound as previously thought.

Projected sea level rise and changes in extreme storm surge and wave events during the 21st century in the region of Singapore

NASA Astrophysics Data System (ADS)

Cannaby, Heather; Palmer, Matthew D.; Howard, Tom; Bricheno, Lucy; Calvert, Daley; Krijnen, Justin; Wood, Richard; Tinker, Jonathan; Bunney, Chris; Harle, James; Saulter, Andrew; O'Neill, Clare; Bellingham, Clare; Lowe, Jason

2016-05-01

Singapore is an island state with considerable population, industries, commerce and transport located in coastal areas at elevations less than 2 m making it vulnerable to sea level rise. Mitigation against future inundation events requires a quantitative assessment of risk. To address this need, regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events have been combined to explore potential changes to coastal flood risk over the 21st century. Local changes in time-mean sea level were evaluated using the process-based climate model data and methods presented in the United Nations Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). Regional surge and wave solutions extending from 1980 to 2100 were generated using ˜ 12 km resolution surge (Nucleus for European Modelling of the Ocean - NEMO) and wave (WaveWatchIII) models. Ocean simulations were forced by output from a selection of four downscaled ( ˜ 12 km resolution) atmospheric models, forced at the lateral boundaries by global climate model simulations generated for the IPCC AR5. Long-term trends in skew surge and significant wave height were then assessed using a generalised extreme value model, fit to the largest modelled events each year. An additional atmospheric solution downscaled from the ERA-Interim global reanalysis was used to force historical ocean model simulations extending from 1980 to 2010, enabling a quantitative assessment of model skill. Simulated historical sea-surface height and significant wave height time series were compared to tide gauge data and satellite altimetry data, respectively. Central estimates of the long-term mean sea level rise at Singapore by 2100 were projected to be 0.52 m (0.74 m) under the Representative Concentration Pathway (RCP)4.5 (8.5) scenarios. Trends in surge and significant wave height 2-year return levels were found to be statistically insignificant and/or physically very small under the more severe RCP8.5 scenario. We conclude that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century. We note that the largest recorded surge residual in the Singapore Strait of ˜ 84 cm lies between the central and upper estimates of sea level rise by 2100, highlighting the vulnerability of the region.

From land use to land cover: Restoring the afforestation signal in a coupled integrated assessment - earth system model and the implications for CMIP5 RCP simulations

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

Di Vittorio, Alan V.; Chini, Louise M.; Bond-Lamberty, Benjamin

2014-11-27

Climate projections depend on scenarios of fossil fuel emissions and land use change, and the IPCC AR5 parallel process assumes consistent climate scenarios across Integrated Assessment and Earth System Models (IAMs and ESMs). To facilitate consistency, CMIP5 used a novel land use harmonization to provide ESMs with seamless, 1500-2100 land use trajectories generated by historical data and four IAMs. However, we have identified and partially addressed a major gap in the CMIP5 land coupling design. The CMIP5 Community ESM (CESM) global afforestation is only 22% of RCP4.5 afforestation from 2005 to 2100. Likewise, only 17% of the Global Change Assessmentmore » Model’s (GCAM’s) 2040 RCP4.5 afforestation signal, and none of the pasture loss, were transmitted to CESM within a newly integrated model. This is a critical problem because afforestation is necessary for achieving the RCP4.5 climate stabilization. We attempted to rectify this problem by modifying only the ESM component of the integrated model, enabling CESM to simulate 66% of GCAM’s afforestation in 2040, and 94% of GCAM’s pasture loss as grassland and shrubland losses. This additional afforestation increases vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, implying different climate scenarios between CMIP5 GCAM and CESM. Similar inconsistencies likely exist in other CMIP5 model results, primarily because land cover information is not shared between models, with possible contributions from afforestation exceeding model-specific, potentially viable forest area. Further work to harmonize land cover among models will be required to adequately rectify this problem.« less

Climate change and Mediterranean storm tracks: present and future climate simulations of a high-resolution Mediterranean model

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Simmonds, I.; Keay, K.; Giannakopoulos, C.; Brikolas, V.; Kouroutzoglou, J.

2010-09-01

A number of studies suggest that cyclone activity over both hemispheres has changed over the second half of the 20th century. General features include a reduction in the number of cyclones but with an increase in the number of more intense cyclones; as well as a poleward shift in the tracks. Moreover, these features are expected to be projected in the future under global warming conditions. The assessment of the future changes of the cyclonic activity as imposed by global warming conditions is very important since these cyclones can be associated with extreme precipitation conditions, severe storms and floods. This is more important for the Mediterranean that has been found to be more vulnerable to climate change. The main objective of the current study is to better understand and assess future changes in the main characteristics of cyclonic tracks in the Mediterranean. The climatology of the cyclonic tracks includes temporal and spatial variations of frequency, and dynamic and kinematic parameters, such as intensity, size, propagation velocity, as well as trend analysis. For this purpose, the ENEA high resolution model is employed, based on PROTHEUS system composed of the RegCM atmospheric regional model and the MITgcm ocean model, coupled through the OASIS3 flux coupler. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. Two experiments are employed; a) the EH5OM_20C3M present climate simulation, where the lateral boundary conditions for the atmosphere (1951-2000) are taken from the ECHAM5-MPIOM 20c3m global simulation (run3) included in the IPCC-AR4, and b) the EH5OM_A1B scenario simulation, where the IPCC-AR4 ECHAM5-MPIOM SRESA1B global simulation (run3) has been used for the period 2001-2050. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. This approach is considered to be crucial, since open lows are also incorporated into the storm life-cycle, preventing possible inappropriate time series breaks, if a temporary weakening to an open-low state occurs. According to the results, a decrease of the storm number and a tendency towards deeper cyclones is expected in the future, in general agreement with the results of previous studies. However, new findings reveal with respect to the dynamic/kinematic characteristics of the cyclonic tracks. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged.

Tropical Andean ecosystems and the need to keep warming limits below a +1.5°C threshold

NASA Astrophysics Data System (ADS)

Ruiz-Carrascal, D.; Herzog, S. K.; Guitierrez Lagoueyte, M. E.; Gonzalez-Duque, D.; Cuevas-Moreno, J.; del Valle, J. I.; Andreu-Hayles, L.; Herrera, D. A.; Martínez, R.

2017-12-01

Long-term climate change and rapid land-use change are synergistically threatening the integrity and functioning of tropical Andean ecosystems. The main goal of our research was to integrate climate change projections, biodiversity data and anthropogenically driven ecosystem disruption assessments to quantify the vulnerability of Andean ecosystems and species to global change at a local scale. We merged discernible trends in local quality-controlled weather station data with reanalysis data, as well as with historical and prospective simulation outputs of five well-known GCMs to assess a long-term context for the analysis of climate change exposure (temperature severity intervals). Individual, medium-term, multi-member GCM simulations included: altitude-corrected 2046-2065 (IPCC-AR4) climate change scenarios for the A1B emission scenario; and spatially-downscaled 2040-2069 (IPCC-AR5) projections for the RCP4.5. Previous studies reported mean annual temperature anomaly intervals that resulted in exceedingly high thresholds: the lowest severity interval (< +2.06°C) and the highest (> +2.71°C). The least severe interval extended up to the threshold widely recognized as `dangerous' climate change, thereby leading to an underestimation of the true vulnerability of Andean species. Our analyses suggest that temperature anomalies for the full extent of the tropical Andes will likely range from low (< +1.60°C) to high (> +2.61°C), exceeding the threshold of 'natural' climate variability (+1.78°C). Our results suggest that most species that were used as proxies of ecosystem vulnerabilities will likely experience overall low-to-medium-to-high temperature increases. Since many of them have potentially high sensitivity to such long-term changes, Andean species will likely experience greatly increases in vulnerability. The already-disrupted Andean ecosystems will suffer a further climatic stress, which will worsen the well-known detrimental synergies between climate and land-use changes. There is an imperative need to prioritize high-risk areas for the implementation of conservation and adaptation actions. Equally important, there is an urgent need to keep warming limits well below 2.0°C, ideally below +1.5°C, if we expect to preserve the integrity of our unique Andean environments.

Projected Sea Level Rise and Changes in Extreme Storm Surge and Wave Events During the 21st Century in the Region of Singapore

NASA Astrophysics Data System (ADS)

Palmer, M. D.; Cannaby, H.; Howard, T.; Bricheno, L.

2016-02-01

Singapore is an island state with considerable population, industries, commerce and transport located in coastal areas at elevations less than 2 m making it vulnerable to sea-level rise. Mitigation against future inundation events requires a quantitative assessment of risk. To address this need, regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events have been combined to explore potential changes to coastal flood risk over the 21st century. Local changes in time mean sea level were evaluated using the process-based climate model data and methods presented in the IPCC AR5. Regional surge and wave solutions extending from 1980 to 2100 were generated using 12 km resolution surge (Nucleus for European Modelling of the Ocean - NEMO) and wave (WaveWatchIII) models. Ocean simulations were forced by output from a selection of four downscaled ( 12 km resolution) atmospheric models, forced at the lateral boundaries by global climate model simulations generated for the IPCC AR5. Long-term trends in skew surge and significant wave height were then assessed using a generalised extreme value model, fit to the largest modelled events each year. An additional atmospheric solution downscaled from the ERA-Interim global reanalysis was used to force historical ocean model simulations extending from 1980-2010, enabling a quantitative assessment of model skill. Simulated historical sea surface height and significant wave height time series were compared to tide gauge data and satellite altimetry data respectively. Central estimates of the long-term mean sea level rise at Singapore by 2100 were projected to be 0.52 m(0.74 m) under the RCP 4.5(8.5) scenarios respectively. Trends in surge and significant wave height 2-year return levels were found to be statistically insignificant and/or physically very small under the more severe RCP8.5 scenario. We conclude that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century. We note that the largest recorded surge residual in the Singapore Strait of 84 cm lies between the central and upper estimates of sea level rise by 2100, highlighting the vulnerability of the region.

Projected sea level rise and changes in extreme storm surge and wave events during the 21st century in the region of Singapore

NASA Astrophysics Data System (ADS)

Cannaby, H.; Palmer, M. D.; Howard, T.; Bricheno, L.; Calvert, D.; Krijnen, J.; Wood, R.; Tinker, J.; Bunney, C.; Harle, J.; Saulter, A.; O'Neill, C.; Bellingham, C.; Lowe, J.

2015-12-01

Singapore is an island state with considerable population, industries, commerce and transport located in coastal areas at elevations less than 2 m making it vulnerable to sea-level rise. Mitigation against future inundation events requires a quantitative assessment of risk. To address this need, regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events have been combined to explore potential changes to coastal flood risk over the 21st century. Local changes in time mean sea level were evaluated using the process-based climate model data and methods presented in the IPCC AR5. Regional surge and wave solutions extending from 1980 to 2100 were generated using ~ 12 km resolution surge (Nucleus for European Modelling of the Ocean - NEMO) and wave (WaveWatchIII) models. Ocean simulations were forced by output from a selection of four downscaled (~ 12 km resolution) atmospheric models, forced at the lateral boundaries by global climate model simulations generated for the IPCC AR5. Long-term trends in skew surge and significant wave height were then assessed using a generalised extreme value model, fit to the largest modelled events each year. An additional atmospheric solution downscaled from the ERA-Interim global reanalysis was used to force historical ocean model simulations extending from 1980-2010, enabling a quantitative assessment of model skill. Simulated historical sea surface height and significant wave height time series were compared to tide gauge data and satellite altimetry data respectively. Central estimates of the long-term mean sea level rise at Singapore by 2100 were projected to be 0.52 m (0.74 m) under the RCP 4.5 (8.5) scenarios respectively. Trends in surge and significant wave height 2 year return levels were found to be statistically insignificant and/or physically very small under the more severe RCP8.5 scenario. We conclude that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century. We note that the largest recorded surge residual in the Singapore Strait of ~ 84 cm lies between the central and upper estimates of sea level rise by 2100, highlighting the vulnerability of the region.

Web based visualization of large climate data sets

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Signal Trees: Communicating Attribution of Climate Change Impacts Through Causal Chain Illustrations

NASA Astrophysics Data System (ADS)

Cutting, H.

2016-12-01

Communicating the attribution of current climate change impacts is a key task for engagment with the general public, news media and policy makers, particularly as climate events unfold in real time. The IPCC WGII in AR5 validated the use of causal chain illustrations to depict attribution of individual climate change impacts. Climate Signals, an online digital platform for mapping and cataloging climate change impacts (launched in May of 2016), explores the use of such illustrations for communicating attribution. The Climate Signals project has developed semi-automated graphing software to produce custom attribution trees for numerous climate change events. This effort offers lessons for engagement of the general public and policy makers in the attribution of climate change impacts.

To What Extent Can Vegetation Mitigate Greenhouse Warming? A Modeling Approach

NASA Technical Reports Server (NTRS)

Bounoua, L.; Hall, F.G.; Collatz, G.J.; Tucker, C.J.; Sellers, P.J.; Kumar, A.

2008-01-01

Climate models participating in the IPCC Fourth Assessment Report indicate that under a 2xCO2 environment, runoff would increase faster than precipitation overland. However, observations over large U.S watersheds indicate otherwise. This inconsistency suggests that there may be important feedbacks between climate and land surface unaccounted for in the present generation of models. We postulate that the increase in precipitation associated with the increase in CO2 is also increasing vegetation density, which may already be feeding back onto climate. Including this feedback in a climate model simulation resulted in precipitation and runoff trends consistent with observations and reduced the warming by 0.6OC overland. This unaccounted for missing water may be linked to about 10% of the missing land carbon sink. A recent compilation of outputs from 19 coupled atmosphere-ocean general circulation models used in the IPCC Fourth Assessment Report (AR4) shows projected increases in air temperature, precipitation and river discharge for 24 major rivers in the world in response to doubling CO2 by the end of the century (1). The ensemble mean from these models also indicates that, compared to their respective baselines overland, the global mean of the runoff change would increase faster (8.9% per year) than that of the precipitation (5% per year). We analyze century-scale observed annual runoff time-series (1901-2002) over 9 hydrological units covering large regions of the Eastern United States (Fig.1) compiled by the United States Geological Survey (USGS)(2). These regions were selected because they are the most forested; the least water-limited and are not under extensive irrigation. We compare these time-series to similar time-series of observed annual precipitation anomalies spanning the period 1900-1995 (3). Both time-series exhibit a positive longterm trend (Fig. 2); however, in contrast to the analysis of (I), these historic data records show that the rate of precipitation increase is 5.5 % per year, roughly double the rate of runoff increase of 3.1 % per year.

Model Estimate of Pan-Arctic Lakes and Wetlands Methane Emissions and Their Future Climate Response

NASA Astrophysics Data System (ADS)

Chen, X.; Bohn, T. J.; Maksyutov, S. S.; Lettenmaier, D. P.

2013-12-01

Lakes and wetlands are important sources of the greenhouse gas CH4, whose emission rate is sensitive to climate. The northern high latitudes, which are especially susceptible to climate change, contain about 50% of the world's lakes and wetlands. Given predicted changes in the climate of this region over the next century (IPCC AR5 scenarios), there is concern about a possible positive feedback resulting from methane emissions from the region's wetlands and lakes. To study the climate response of emissions from northern high latitude lakes and wetlands, we employed a large-scale hydrology and carbon cycling model (Variable Infiltration Capacity model; VIC) over the Pan-Arctic domain, which was linked to an atmospheric model (Japan's National Institute of Environmental Studies transport model; NIES TM). In particular, the VIC model simulates the land surface hydrology and carbon cycling across a dynamic lake-wetland continuum, while NIES TM models the atmospheric mixing and 3-dimension transport of methane emitted. The VIC model includes a distributed wetland water table scheme, which accounts for microtopography around the lakes and simulates variations in inundated area that are calibrated to match a passive microwave based inundation product. Per-unit-area carbon uptake and methane emissions at the land surface have been calibrated using extensive in situ observations at West Siberia. Also, the atmospheric methane concentration from this linked model run was verified for the recent 5 years with satellite observations from Aqua's Atmospheric Infrared Sounder (AIRS) and Envisat's Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instruments. Using RCP4.5 and RCP8.5 future climate scenarios, we examine CH4 emissions from high latitude lakes and wetlands, as well as their net greenhouse warming potential, over the next 3 centuries across the Pan-Arctic domain. We also assess relative uncertainties in emissions from each of the sources.

Quantifying loss and damage from anthropogenic climate change - Bridging the gap between two research communities

NASA Astrophysics Data System (ADS)

Otto, F. E. L.

2015-12-01

The science of attribution of meteorological events to anthropogenic causes has for the first time been included in the latest assessment of the Physical Science Basis of the Climate, (WGI), of the Fifth IPCC Assessment Report AR5 (Stocker et al., 2013). At the same time there is a very rapidly growing body of literature on climate change and its impact on economy, society and environment but apart from very few exemptions no link is made to the causes of these changes. Observed changes in hydrological variables, agriculture, biodiversity and the built environment have been attributed to a changing climate, whether these changes are the result of natural variability or external forcings (Cramer et al., 2014). While the research community represented in WGI assesses whether, and to what extent, recent extreme weather events can be attributed to anthropogenic emissions of greenhouse gases and aerosols, the research community of impact specialists asks how climatic changes lead to different impacts largely independent of the causes of such changes. This distinction becomes potentially very relevant with respect to the 2013 established the Warsaw International Mechanism (WIM) to address loss and damage from the impacts of climate change in developing countries under the UNFCCC climate change negotiations. Currently there is no discussion what consists of loss and damage and the reasons for this inexistence of a definition are not primarily scientific but political however, the absence of a definition could potentially lead to absurd consequences if funds in the context of loss and damage would be redistributed, as e.g. suggested, for all low risk high impact events. Here we present the implications of discussed definitions of loss and damage (Huggel et al. 2015) and how scientific evidence could be included. Cramer et al. (2014) Detection and Attribution of Observed Impacts. In: Climate Change 2014: Impacts, Adaptation and Vulnerability Contribution of WG 2 to AR5 of the IPCC. Huggel, C., Stone, D., Eicken, H., & Hansen, G. (2015). Potential and limitations of the attribution of climate change impacts for informing loss and damage discussions and policies. Clim. Change, doi: 10.1007/s10584-015-1441-z. Stocker et al. (eds.) (2013) The IPCC Fifth Assessment Report: The Physical Science Basis. Cambridge University Press.

High-resolution interpolation of climate scenarios for Canada derived from general circulation model simulations

Treesearch

D. T. Price; D. W. McKenney; L. A. Joyce; R. M. Siltanen; P. Papadopol; K. Lawrence

2011-01-01

Projections of future climate were selected for four well-established general circulation models (GCMs) forced by each of three greenhouse gas (GHG) emissions scenarios recommended by the Intergovernmental Panel on Climate Change (IPCC), namely scenarios A2, A1B, and B1 of the IPCC Special Report on Emissions Scenarios. Monthly data for the period 1961-2100 were...

Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

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

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.

2010-04-01

Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-modelmore » ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.« less

Forecasting Future Sea Ice Conditions: A Lagrangian Approach

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Forecasting Future Sea Ice Conditions: A Lagrangian ...GCMs participating in IPCC AR5 agree with observed source region patterns from the satellite- derived dataset. 4- Compare Lagrangian ice... Lagrangian sea-ice back trajectories to estimate thermodynamic and dynamic (advection) ice loss. APPROACH We use a Lagrangian trajectory model to

Science and Systems in Support of Multi-hazard Early Warnings and Decisions

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2015-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use.

PubMed

Zhang, Ke; de Almeida Castanho, Andrea D; Galbraith, David R; Moghim, Sanaz; Levine, Naomi M; Bras, Rafael L; Coe, Michael T; Costa, Marcos H; Malhi, Yadvinder; Longo, Marcos; Knox, Ryan G; McKnight, Shawna; Wang, Jingfeng; Moorcroft, Paul R

2015-02-20

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century. © 2015 John Wiley & Sons Ltd.

Improvement of downscaled rainfall and temperature across generations over the Western Himalayan region of India

NASA Astrophysics Data System (ADS)

Das, L.; Dutta, M.; Akhter, J.; Meher, J. K.

2016-12-01

It is a challenging task to create station level (local scale) climate change information over the mountainous locations of Western Himalayan Region (WHR) in India because of limited data availability and poor data quality. In the present study, missing values of station data were handled through Multiple Imputation Chained Equation (MICE) technique. Finally 22 numbers of rain gauge and 16 number of temperature station data having continuous record during 1901­2005 and 1969­2009 period respectively were considered as reference stations for developing downscaled rainfall and temperature time series from five commonly available GCMs in the IPCC's different generation assessment reports namely 2nd, 3rd, 4th and 5th hereafter known as SAR, TAR, AR4 and AR5 respectively. Downscaled models were developed using the combined data from the ERA-interim reanalysis and GCMs historical runs (in spite of forcing were not identical in different generation) as predictor and station level rainfall and temperature as predictands. Station level downscaled rainfall and temperature time series were constructed for five GCMs available in each generation. Regional averaged downscaled time series comprising of all stations was prepared for each model and generation and the downscaled results were compared with observed time series. Finally an Overall Model Improvement Index (OMII) was developed using the downscaling results, which was used to investigate the model improvement across generations as well as the improvement of downscaling results obtained from the Empirical Statistical Downscaling (ESD) methods. In case of temperature, models have improved from SAR to AR5 over the study area. In all most all the GCMs TAR is showing worst performance over the WHR by considering the different statistical indices used in this study. In case of precipitation, no model has shown gradual improvement from SAR to AR5 both for interpolated and downscaled values.

Interpolation and Meta-Analysis of IPCC AR4 General Circulation Model Scenarios applied to North America

NASA Astrophysics Data System (ADS)

Price, D. T.; Joyce, L. A.; McKenney, D. W.

2009-12-01

Projections of future climate simulated by four state-of-art general circulation models (GCM), namely the U.S. NCAR CCSM 3.0, Canadian CGCM 3.1, Australian CSIRO Mk. 3.5 and Japanese MIROC 3.2, forced by each of the IPCC AR4 SRA2, SRB1 and SRA1B greenhouse gas (GHG) emissions scenarios, were downscaled for Canada and the continental USA. For each GCM projection, monthly climate values for a rectangle covering North America were interpolated using ANUSPLIN (e.g., Hutchinson 1995), to a common 0.0833° geographic grid. The resulting 12 high resolution scenarios provide projected change factors for monthly solar radiation, windspeed and vapor pressure, air temperature and precipitation, for the 21st century, referenced to the averages of simulated monthly means for 1961-1990. The 12 interpolated scenario data sets were subjected to a meta-analysis. Data for each projected variable of each climate scenario were averaged for three consecutive 30-year periods (starting in 2011), to create scenario maps of changes in annual and seasonal means. The contiguous 48 U.S. States were grouped into seven regions based on the classification of Bailey (1994), with Alaska forming an eighth region, while Canada was divided into twelve regions based on the Canadian Terrestrial Ecozones (Wiken, 1986). In each region, data were spatially averaged (with area-weighting) and used to create graphs and summary tables of annual and seasonal trends, including long-term changes in interannual variability. Overall, the meta-analysis showed remarkable agreement among the four GCMs, in terms both of their sensitivity to increasing GHG forcing (SRB1→SRA1B→SRA2) and in the relative magnitudes of the climate changes projected for each scenario in each region. Temperatures were projected to increase by 2-4 °C in the southern USA (summer) to as much as 4-8 °C in northern Canada and Alaska (winter minima), by the mid-2080s, relative to 2000. Precipitation was projected to increase by 5-10% over the same period, but with distinct seasonal trends that differed among regions; one GCM projected significant decreases in precipitation in the southern USA. Solar radiation inputs were generally projected to decline slightly, showing consistent inverse relationships to projected precipitation changes, while vapor pressure generally increased, particularly in summer and particularly in coastal regions. Projected changes in interannual variability (based on ratios of predicted to observed standard deviations of annual and seasonal means for 2071-2100 and 1961-1990) were generally less consistent but often tended to decrease with increasing GHG forcing. The data sets will support national and regional climate change impacts studies, including the USDA Forest Service National Renewable Resource Assessment for 2010 and Canadian forest vulnerability assessment for the Canadian Council of Forest Ministers in 2011.

Managing the Risks of Extreme Events and Disasters in a Changing Climate: Lessons for Adaptation to Climate Change (Invited)

NASA Astrophysics Data System (ADS)

Mastrandrea, M.; Field, C. B.; Mach, K. J.; Barros, V.

2013-12-01

The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, published in 2012, integrates expertise in climate science, disaster risk reduction, and adaptation to inform discussions on how to reduce and manage the risks of extreme events and disasters in a changing climate. Impacts and the risks of disasters are determined by the interaction of the physical characteristics of weather and climate events with the vulnerability of exposed human society and ecosystems. The Special Report evaluates the factors that make people and infrastructure vulnerable to extreme events, trends in disaster losses, recent and future changes in the relationship between climate change and extremes, and experience with a wide range of options used by institutions, organizations, and communities to reduce exposure and vulnerability, and improve resilience, to climate extremes. Actions ranging from incremental improvements in governance and technology to more transformational changes are assessed. The Special Report provides a knowledge base that is also relevant to the broader context of managing the risks of climate change through mitigation, adaptation, and other responses, assessed in the IPCC's Fifth Assessment Report (AR5), to be completed in 2014. These themes include managing risks through an iterative process involving learning about risks and the effectiveness of responses, employing a portfolio of actions tailored to local circumstances but with links from local to global scales, and considering additional benefits of actions such as improving livelihoods and well-being. The Working Group II contribution to the AR5 also examines the ways that extreme events and their impacts contribute to understanding of vulnerabilities and adaptation deficits in the context of climate change, the extent to which impacts of climate change are experienced through changes in the frequency and severity of extremes as opposed to mean changes, and the emergence of risks that are place-based vs. systemic.

Impacts of climate change on growth period and planting boundaries of winter wheat in China under RCP4.5 scenario

NASA Astrophysics Data System (ADS)

Sun, Z.; Jia, S. F.; Lv, A. F.; Yang, K. J.; Svensson, J.; Gao, Y. C.

2015-10-01

This paper advances understanding of the impacts of climate change on crops in China by moving from ex-post analysis to forecasting, and by demonstrating how the effects of climate change will affect the growth period and the planting boundaries of winter wheat. Using a multiple regression model based on agricultural meteorological observations and the IPCC AR5 GCMs simulations, we find that the sowing date of winter wheat in the base period, 2040s and 2070s, shows a gradually delayed trend from north to south and the growth period of winter wheat in China will be shortened under climate change. The simulation results also show that (i) the north planting boundaries of winter wheat in China will likely move northward and expand westward in the future, while the south planting boundary will rise and spread in south Hainan and Taiwan; and (ii) the Xinjiang Uygur Autonomous Region and the Inner Mongolia Autonomous Region will have the largest increases in planting areas in 2040s and 2070s. Our simulation implies that Xinjiang and Inner Mongolia are more sensitive to climate change than other regions in China and priority should be given to design adaptation strategies for winter wheat planting for these provinces.

Decadal Recruitment and Mortality of Ponderosa pine Predicted for the 21st Century Under five Downscaled Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.

2008-12-01

Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.

A common fallacy in climate model evaluation

NASA Astrophysics Data System (ADS)

Annan, J. D.; Hargreaves, J. C.; Tachiiri, K.

2012-04-01

We discuss the assessment of model ensembles such as that arising from the CMIP3 coordinated multi-model experiments. An important aspect of this is not merely the closeness of the models to observations in absolute terms but also the reliability of the ensemble spread as an indication of uncertainty. In this context, it has been widely argued that the multi-model ensemble of opportunity is insufficiently broad to adequately represent uncertainties regarding future climate change. For example, the IPCC AR4 summarises the consensus with the sentence: "Those studies also suggest that the current AOGCMs may not cover the full range of uncertainty for climate sensitivity." Similar claims have been made in the literature for other properties of the climate system, including the transient climate response and efficiency of ocean heat uptake. Comparison of model outputs with observations of the climate system forms an essential component of model assessment and is crucial for building our confidence in model predictions. However, methods for undertaking this comparison are not always clearly justified and understood. Here we show that the popular approach which forms the basis for the above claims, of comparing the ensemble spread to a so-called "observationally-constrained pdf", can be highly misleading. Such a comparison will almost certainly result in disagreement, but in reality tells us little about the performance of the ensemble. We present an alternative approach based on an assessment of the predictive performance of the ensemble, and show how it may lead to very different, and rather more encouraging, conclusions. We additionally outline some necessary conditions for an ensemble (or more generally, a probabilistic prediction) to be challenged by an observation.

Global Mean Temperature Timeseries Projections from GCMs: The Implications of Rebasing

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2017-12-01

Global climate models are assessed by comparison with observations through several benchmarks. One highlighted by the InterGovernmental Panel on Climate Change (IPCC) is their ability to reproduce "general features of the global and annual mean surface temperature changes over the historical period" [1,2] and to simulate "a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend" [3]. These aspects of annual mean global mean temperature (GMT) change are presented as one feature demonstrating the relevance of these models for climate projections. Here we consider a formal interpretation of "general features" and discuss the implications of this approach to model assessment and intercomparison, for the interpretation of GCM projections. Following the IPCC, we interpret a major element of "general features" as being the slow timescale response to external forcings. (Shorter timescale behaviour such as the response to volcanic eruptions are also elements of "general features" but are not considered here.) Also following the IPCC, we consider only GMT anomalies. The models have absolute temperatures which range over about 3K so this means their timeseries (and the observations) are rebased. We show that rebasing in combination with general agreement, implies a separation of scales which limits the degree to which sub-global behaviour can feedback on the global response. It also implies a degree of linearity in the GMT slow timescale response. For each individual model these implications only apply over the range of absolute temperatures simulated by the model in historic simulations. Taken together, however, they imply consequences over a wider range of GMTs. [1] IPCC, Fifth Assessment Report, Working Group 1, Technical Summary: Stocker et al. 2013. [2] IPCC, Fifth Assessment Report, Working Group 1, Chapter 9 - "Evaluation of Climate Models": Flato et al. 2013. [3] IPCC, Fifth Assessment Report, Working Group 1, Summary for Policy Makers: IPCC, 2013.

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

Meehl, G A; Covey, C; McAvaney, B

The Coupled Model Intercomparison Project (CMIP) is designed to allow study and intercomparison of multi-model simulations of present-day and future climate. The latter are represented by idealized forcing of compounded 1% per year CO2 increase to the time of CO2 doubling near year 70 in simulations with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice and land surface. Results from CMIP diagnostic subprojects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September, 2003. Significant progress in diagnosing and understanding results from global coupled models hasmore » been made since the First CMIP Workshop in Melbourne, Australia in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multi-century surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models is now usually around 2.5 degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial tropics. Some new-generation coupled models have atmospheric model resolutions of around 1.5 degrees latitude-longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to 20th and 21st century climate simulations with a variety of forcings (e.g. volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases (GHGs), with the anthropogenic forcings for future climate as well). However, persistent systematic errors noted in previous generations of global coupled models still are present in the present generation (e.g. over-extensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and imminent commencement of the IPCC Fourth Assessment Report (AR4) has prompted rapid coupled model development, which will lead to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, 20th, 21st and 22nd century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort, and details are provided below in how to do so.« less

Cumulative carbon emissions budgets consistent with 1.5 °C global warming

NASA Astrophysics Data System (ADS)

Tokarska, Katarzyna B.; Gillett, Nathan P.

2018-04-01

The Paris Agreement1 commits ratifying parties to pursue efforts to limit the global temperature increase to 1.5 °C relative to pre-industrial levels. Carbon budgets2-5 consistent with remaining below 1.5 °C warming, reported in the IPCC Fifth Assessment Report (AR5)2,6,8, are directly based on Earth system model (Coupled Model Intercomparison Project Phase 5)7 responses, which, on average, warm more than observations in response to historical CO2 emissions and other forcings8,9. These models indicate a median remaining budget of 55 PgC (ref. 10, base period: year 1870) left to emit from January 2016, the equivalent to approximately five years of emissions at the 2015 rate11,12. Here we calculate warming and carbon budgets relative to the decade 2006-2015, which eliminates model-observation differences in the climate-carbon response over the historical period9, and increases the median remaining carbon budget to 208 PgC (33-66% range of 130-255 PgC) from January 2016 (with mean warming of 0.89 °C for 2006-2015 relative to 1861-188013-18). There is little sensitivity to the observational data set used to infer warming that has occurred, and no significant dependence on the choice of emissions scenario. Thus, although limiting median projected global warming to below 1.5 °C is undoubtedly challenging19-21, our results indicate it is not impossible, as might be inferred from the IPCC AR5 carbon budgets2,8.

Rainwater harvesting possibility under climate change: A basin-scale case study over western province of Saudi Arabia

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Islam, M. Nazrul; Balkhair, Khaled S.; Şen, Zekâi; Masood, Amjad

2017-06-01

Groundwater reservoirs are important water resources all over the world. Especially, they are of utmost significance for arid and semi-arid regions, and therefore, a sustainable exploitation of these reservoirs needs to be ensured. The natural and most exclusive water supplier to groundwater reservoirs in Saudi Arabia is rainfall, which is characterized by sporadic and random temporal and spatial distributions, particularly under the impacts of climate change; giving rise to uncertainty in groundwater recharge quantification. Although in Saudi Arabia, intense and frequent rainfall events are rare, but they generate significant flash floods with huge amounts of surface water. Under such circumstances, any simple but effective water storage augmentation facility such as rainwater harvesting (RWH) structures gain vital importance for sustainability of water supply and survivals in arid and semi-arid regions. The objective of this study is to explore the possibility of RWH over a basin in the western province of Saudi Arabia called Wadi Al-Lith under climate change. Climatic data is obtained from the IPCC AR5 GCMs, which is further downscaled using a regional climate model RegCM4 for the Arabian Peninsula domain. The RegCM4 is driven to simulate climatic parameters including rainfall at 25 km grid resolution for the present climate (1971-2000), and future climate (2006-2099) with representative concentration pathways, RCP4.5 and RCP8.5. Results indicate that more durable and longer wet durations are expected with increasing surplus rainfall amounts in the far future because of climate change impacts. Consequently, future climate scenarios are expected to enhance floods and flash floods occurrences, which call for progressive measures to harness the RWH opportunity.

An Assessment of IPCC 20th Century Climate Simulations Using the 15-year Sea Level Record from Altimetry

NASA Astrophysics Data System (ADS)

Leuliette, E.; Nerem, S.; Jakub, T.

2006-07-01

Recen tly, multiple ensemble climate simulations h ave been produced for th e forthco ming Fourth A ssessment Report of the Intergovernmental Panel on Climate Change (IPCC). N early two dozen coupled ocean- atmo sphere models have contr ibuted output for a variety of climate scen arios. One scenar io, the climate of the 20th century exper imen t (20C3 M), produces model output that can be comp ared to th e long record of sea level provided by altimetry . Generally , the output from the 20C3M runs is used to initialize simulations of future climate scenar ios. Hence, v alidation of the 20 C3 M experiment resu lts is crucial to the goals of th e IPCC. We present compar isons of global mean sea level (G MSL) , global mean steric sea level change, and regional patterns of sea lev el chang e from these models to r esults from altimetry, tide gauge measurements, and reconstructions.

Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models

PubMed Central

Sugiyama, Masahiro; Shiogama, Hideo; Emori, Seita

2010-01-01

Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models. PMID:20080720

Aerosol direct, indirect, semidirect, and surface albedo effects from sector contributions based on the IPCC AR5 emissions for preindustrial and present-day conditions

NASA Astrophysics Data System (ADS)

Bauer, Susanne E.; Menon, Surabi

2012-01-01

The anthropogenic increase in aerosol concentrations since preindustrial times and its net cooling effect on the atmosphere is thought to mask some of the greenhouse gas-induced warming. Although the overall effect of aerosols on solar radiation and clouds is most certainly negative, some individual forcing agents and feedbacks have positive forcing effects. Recent studies have tried to identify some of those positive forcing agents and their individual emission sectors, with the hope that mitigation policies could be developed to target those emitters. Understanding the net effect of multisource emitting sectors and the involved cloud feedbacks is very challenging, and this paper will clarify forcing and feedback effects by separating direct, indirect, semidirect and surface albedo effects due to aerosols. To this end, we apply the Goddard Institute for Space Studies climate model including detailed aerosol microphysics to examine aerosol impacts on climate by isolating single emission sector contributions as given by the Coupled Model Intercomparison Project Phase 5 (CMIP5) emission data sets developed for Intergovernmental Panel on Climate Change (IPCC) AR5. For the modeled past 150 years, using the climate model and emissions from preindustrial times to present-day, the total global annual mean aerosol radiative forcing is -0.6 W/m2, with the largest contribution from the direct effect (-0.5 W/m2). Aerosol-induced changes on cloud cover often depends on cloud type and geographical region. The indirect (includes only the cloud albedo effect with -0.17 W/m2) and semidirect effects (-0.10 W/m2) can be isolated on a regional scale, and they often have opposing forcing effects, leading to overall small forcing effects on a global scale. Although the surface albedo effects from aerosols are small (0.016 W/m2), triggered feedbacks on top of the atmosphere (TOA) radiative forcing can be 10 times larger. Our results point out that each emission sector has varying impacts by geographical region. For example, the single sector most responsible for a net positive radiative forcing is the transportation sector in the United States, agricultural burning and transportation in Europe, and the domestic emission sector in Asia. These sectors are attractive mitigation targets.

Aerosol Direct, Indirect, Semidirect, and Surface Albedo Effects from Sector Contributions Based on the IPCC AR5 Emissions for Preindustrial and Present-day Conditions

NASA Technical Reports Server (NTRS)

Bauer, Susanne E.; Menon, Surabi

2012-01-01

The anthropogenic increase in aerosol concentrations since preindustrial times and its net cooling effect on the atmosphere is thought to mask some of the greenhouse gas-induced warming. Although the overall effect of aerosols on solar radiation and clouds is most certainly negative, some individual forcing agents and feedbacks have positive forcing effects. Recent studies have tried to identify some of those positive forcing agents and their individual emission sectors, with the hope that mitigation policies could be developed to target those emitters. Understanding the net effect of multisource emitting sectors and the involved cloud feedbacks is very challenging, and this paper will clarify forcing and feedback effects by separating direct, indirect, semidirect and surface albedo effects due to aerosols. To this end, we apply the Goddard Institute for Space Studies climate model including detailed aerosol microphysics to examine aerosol impacts on climate by isolating single emission sector contributions as given by the Coupled Model Intercomparison Project Phase 5 (CMIP5) emission data sets developed for Intergovernmental Panel on Climate Change (IPCC) AR5. For the modeled past 150 years, using the climate model and emissions from preindustrial times to present-day, the total global annual mean aerosol radiative forcing is -0.6 W/m(exp 2), with the largest contribution from the direct effect (-0.5 W/m(exp 2)). Aerosol-induced changes on cloud cover often depends on cloud type and geographical region. The indirect (includes only the cloud albedo effect with -0.17 W/m(exp 2)) and semidirect effects (-0.10 W/m(exp 2)) can be isolated on a regional scale, and they often have opposing forcing effects, leading to overall small forcing effects on a global scale. Although the surface albedo effects from aerosols are small (0.016 W/m(exp 2)), triggered feedbacks on top of the atmosphere (TOA) radiative forcing can be 10 times larger. Our results point out that each emission sector has varying impacts by geographical region. For example, the single sector most responsible for a net positive radiative forcing is the transportation sector in the United States, agricultural burning and transportation in Europe, and the domestic emission sector in Asia. These sectors are attractive mitigation targets.

Multi-Model Simulations of Aerosol and Ozone Radiative Forcing Due to Anthropogenic Emission Changes During the Period 1990-2015

NASA Technical Reports Server (NTRS)

Myhre, Gunnar; Aas, Wenche; Ribu, Cherian; Collins, William; Faluvegi, Gregory S.; Flanner, Mark; Forster, Piers; Hodnebrog, Oivind; Klimont, Zbigniew; Lund, Marianne T.

2017-01-01

Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g. 1 to 3 percent per year in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by 0.17 plus or minus 0.08 watts per square meter, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5 (Intergovernmental Panel on Climate Change Fifth Assessment Report). The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.

Future drying of the southern Amazon and central Brazil

NASA Astrophysics Data System (ADS)

Yoon, J.; Zeng, N.; Cook, B.

2008-12-01

Recent climate modeling suggests that the Amazon rainforest could exhibit considerable dieback under future climate change, a prediction that has raised considerable interest as well as controversy. To determine the likelihood and causes of such changes, we analyzed the output of 15 models from the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC/AR4) and a dynamic vegetation model VEGAS driven by these climate output. Our results suggest that the core of the Amazon rainforest should remain largely stable. However, the periphery, notably the southern edge, is in danger of drying out, driven by two main processes. First, a decline in precipitation of 24% in the southern Amazon lengthens the dry season and reduces soil moisture, despite of an increase in precipitation during the wet season, due to the nonlinear response in hydrology and ecosystem dynamics. Two dynamical mechanisms may explain the lower dry season precipitation: (1) a stronger north-south tropical Atlantic sea surface temperature gradient; (2) a general subtropical drying under global warming when the dry season southern Amazon is under the control of the subtropical high pressure. Secondly, evaporation will increase due to the general warming, thus also reducing soil moisture. As a consequence, the median of the models projects a reduction of vegetation by 20%, and enhanced fire carbon flux by 10-15% in the southern Amazon, central Brazil, and parts of the Andean Mountains. Because the southern Amazon is also under intense human influence, the double pressure of deforestation and climate change may subject the region to dramatic changes in the 21st century.

Methane emissions associated with the conversion of marshland to cropland and climate change on the Sanjiang Plain of Northeast China from 1950 to 2100

NASA Astrophysics Data System (ADS)

Li, T.; Huang, Y.; Zhang, W.; Yu, Y. Q.

2012-05-01

Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in Northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tg yr-1 from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~36 Tg relative to the 1950s, and marshland conversion and the climate contributed 86 % and 14 % of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960-2009 (47 mm yr-1 lower on average than in the 1950s) contributed ~91 % of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 °C per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha-1 yr-1 over the last two decades. For the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 flux is predicted to increase by 36 %, 52 %, 78 % and 95 %, respectively, by the 2080s compared to 1961-1990 in response to climate warming and wetting.

Impacts of climate change in the sugarcane production in the center-south macro-region of Brazil

NASA Astrophysics Data System (ADS)

R Pereira, V.; Zullo, J., Jr.; Koga-Vicente, A.

2016-12-01

This paper describes the most important results of a Project developed over four years by a research network having 19 researchers and 45 students. The main objective of this Project was to generate alcohol production scenarios as support for the formulation of public policy applied to the adaptation of the Brazilian sugar and alcohol industry to the possible climate changes. The study area was the center-south macro-region of Brazil, with the states of São Paulo, Paraná, Minas Gerais, Mato Grosso do Sul and Goiás, that is the main producer area of sugarcane in the world. The scenarios were developed using the HadGEM2-ES and Miroc5 models of CMIP5/IPCC and did not show significant differences between them and were very close to those obtained with the HadCM3 and Miroc3 models of the AR4/IPCC. The results considering the sugarcane varieties grown nowadays indicate that in a scenario with changes in precipitation and temperatures, the main producing region will not have a decrease in municipalities with low climatic risk. Also the expansion region (South of Goiás and North-West of São Paulo) may become of high climatic risk, becoming an area where the artificial irrigation will be demanded. The challenge related to the water use and availability that already exists nowadays will be yet more important in the future. The expansion of Brazilian sugarcane production is being much more based on the territorial extension, i.e. by increasing the production area, than by increasing the productivity. The increased mechanization of cane harvesting improves the air quality and reduces the incidence of respiratory diseases. It is extremely important that incentives to mechanization be extended to other regions of the country since the end of burning benefits the health of people living close to the sugarcane fields. This confirms the need for planning this sector, with the development of new varieties and new production technologies considering the possible future climate conditions.

Exposure age and ice-sheet model constraints on Pliocene East Antarctic ice sheet dynamics.

PubMed

Yamane, Masako; Yokoyama, Yusuke; Abe-Ouchi, Ayako; Obrochta, Stephen; Saito, Fuyuki; Moriwaki, Kiichi; Matsuzaki, Hiroyuki

2015-04-24

The Late Pliocene epoch is a potential analogue for future climate in a warming world. Here we reconstruct Plio-Pleistocene East Antarctic Ice Sheet (EAIS) variability using cosmogenic nuclide exposure ages and model simulations to better understand ice sheet behaviour under such warm conditions. New and previously published exposure ages indicate interior-thickening during the Pliocene. An ice sheet model with mid-Pliocene boundary conditions also results in interior thickening and suggests that both the Wilkes Subglacial and Aurora Basins largely melted, offsetting increased ice volume. Considering contributions from West Antarctica and Greenland, this is consistent with the most recent IPCC AR5 estimate, which indicates that the Pliocene sea level likely did not exceed +20 m on Milankovitch timescales. The inception of colder climate since ∼3 Myr has increased the sea ice cover and inhibited active moisture transport to Antarctica, resulting in reduced ice sheet thickness, at least in coastal areas.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Making climate change projections relevant to water management: opportunities and challenges in the Colorado River basin (Invited)

NASA Astrophysics Data System (ADS)

Vano, J. A.

2013-12-01

By 2007, motivated by the ongoing drought and release of new climate model projections associated with the IPCC AR4 report, multiple independent studies had made estimates of future Colorado River streamflow. Each study had a unique approach, and unique estimate for the magnitude for mid-21st century streamflow change ranging from declines of only 6% to declines of as much as 45%. The differences among studies provided for interesting scientific debates, but to many practitioners this appeared to be just a tangle of conflicting predictions, leading to the question 'why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted?' In response, a group of scientists from academic and federal agencies, brought together through a NOAA cross-RISA project, set forth to identify the major sources of disparities and provide actionable science and guidance for water managers and decision makers. Through this project, four major sources of disparities among modeling studies were identified that arise from both methodological and model differences. These differences, in order of importance, are: (1) the Global Climate Models (GCMs) and emission scenarios used; (2) the ability of land surface hydrology and atmospheric models to simulate properly the high elevation runoff source areas; (3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and (4) the methods used to statistically downscale GCM scenarios. Additionally, reconstructions of pre-instrumental streamflows provided further insights about the greatest risk to Colorado River streamflow of a multi-decadal drought, like those observed in paleo reconstructions, exacerbated by a steady reduction in flows due to climate change. Within this talk I will provide an overview of these findings and insights into the opportunities and challenges encountered in the process of striving to make climate change projections more useful to water managers and decision makers.

Investigating the Greenland ice sheet evolution under changing climate using a three-dimensional full-Stokes model

NASA Astrophysics Data System (ADS)

Seddik, H.; Greve, R.; Zwinger, T.; Gillet-Chaulet, F.; Gagliardini, O.

2010-12-01

A three-dimensional, thermo-mechanically coupled model is applied to the Greenland ice sheet. The model implements the full-Stokes equations for the ice dynamics, and the system is solved with the finite-element method (FEM) using the open source multi-physics package Elmer (http://www.csc.fi/elmer/). The finite-element mesh for the computational domain has been created using the Greenland surface and bedrock DEM data with a spatial resolution of 5 km (SeaRise community effort, based on Bamber and others, 2001). The study is particularly aimed at better understanding the ice dynamics near the major Greenland ice streams. The meshing procedure starts with the bedrock footprint where a mesh with triangle elements and a resolution of 5 km is constructed. Since the resulting mesh is unnecessarily dense in areas with slow ice dynamics, an anisotropic mesh adaptation procedure has been introduced. Using the measured surface velocities to evaluate the Hessian matrix of the velocities, a metric tensor is computed at the mesh vertices in order to define the adaptation scheme. The resulting meshed footprint obtained with the automatic tool YAMS shows a high density of elements in the vicinities of the North-East Greenland Ice Stream (NEGIS), the Jakobshavn ice stream (JIS) and the Kangerdlugssuaq (KL) and Helheim (HH) glaciers. On the other hand, elements with a coarser resolution are generated away from the ice streams and domain margins. The final three-dimensional mesh is obtained by extruding the 2D footprint with 21 vertical layers, so that the resulting mesh contains 400860 wedge elements and 233583 nodes. The numerical solution of the Stokes and the heat transfer equations involves direct and iterative solvers depending on the simulation case, and both methods are coupled with stabilization procedures. The boundary conditions are such that the temperature at the surface uses the present-day mean annual air temperature given by a parameterization or directly from the available data, the geothermal heat flux at the bedrock is prescribed as spatially constant and the lateral sides are open boundaries. A non-linear Weertman law is used for the basal sliding. The project goal is to better assess the effects of dynamical changes of the Greenland ice sheet on sea level rise under global-warming conditions. Hence, the simulations have been conducted in order to investigate the ice sheet evolution using the climate forcing experiments defined in the SeaRISE project. For that purpose, four different experiments have been conducted, (i) constant climate control run beginning at present (epoch 2004-1-1 0:0:0) and running up to 500 years holding the climate constant to its present state, (ii) constant climate forcing with increased basal lubrication, (iii) AR4 climate run forced by anomalies derived from results given in the IPCC 4th Assessment Report (AR4) for the A1B emission scenario, (iv) AR4 climate run with increased basal lubrication.

Data citation in climate sciences: Improvements in CMIP6 compared to CMIP5

NASA Astrophysics Data System (ADS)

Stockhause, M.; Lautenschlager, M.

2017-12-01

Within CMIP5 (Coupled Model Intercomparison Project Phase 5) the citation of the data was not possible prior its long-term archival in the IPCC Data Distribution Centre (DDC). The Reference Data Archive for AR5 (Assessment Report 5) was built up after the submission deadline for part 1 of the AR5. This was too late for many scientific articles. But even the AR5 data in the IPCC DDC is rarely cited in literature in spite of annual download volumes between one and three PBytes. On the other hand, the request for a citation possibility for the evolving CMIP6 data prior to long-term archival came from the CMIP6 data providers. The additional provision of data citations for the project input4MIPs (input data for CMIP6) could raise the scientists' awareness of the discrepancy between the readiness to cite data and the desire to be cited and get credit. The CMIP6 Citation Service is a pragmatic approach built on existing services and services under development, such as ESGF (Earth System Grid Federation) as data infrastructure component, DataCite as DOI registration agency, and Scholix services for tracking data usage information. Other principles followed to overcome barriers of data citation are: Collect data and literature references in the data citation metadata to enable data-data and data-literature interlinking. Visibility of data citation information in the ESGF data portals (low barrier to access data citation information) Provide data usage information in literature for the data providers, data node managers and their funders (requested by some ESGF data node managers) The CMIP6 Citation Service is an implementation only of the credit part of the RDA WGDC recommendation for the citation of dynamic data. The second part, the identification of the data subset underlying an article, is planned for CMIP7 as a data cart approach comprising multiple pre-defined CMIP6 DataCite DOIs. Additional policies on the long-term data availability are required. References: M. Stockhause and M. Lautenschlager (2017). CMIP6 Data Citation of Evolving Data. Data Science Journal. 16, p.30. doi:10.5334/dsj-2017-030. https://doi.org/10.5334/dsj-2017-030 . http://cmip6cite.wdc-climate.de

Record dry summer in 2015 challenges precipitation projections in Central Europe.

PubMed

Orth, René; Zscheischler, Jakob; Seneviratne, Sonia I

2016-06-21

Central Europe was characterized by a humid-temperate climate in the 20(th) century. Climate change projections suggest that climate in this area will shift towards warmer temperatures by the end of the 21(st) century, while projected precipitation changes are highly uncertain. Here we show that the 2015 summer rainfall was the lowest on record since 1901 in Central Europe, and that climate models that perform best in the three driest years of the historical time period 1901-2015 project stronger drying trends in the 21(st) century than models that perform best in the remaining years. Analyses of precipitation and derived soil moisture reveal that the 2015 event was drier than both the recent 2003 or 2010 extreme summers in Central Europe. Additionally there are large anomalies in satellite-derived vegetation greenness. In terms of precipitation and temperature anomalies, the 2015 summer in Central Europe is found to lie between historical climate in the region and that characteristic of the Mediterranean area. Even though the models best capturing past droughts are not necessarily generally more reliable in the future, the 2015 drought event illustrates that potential future drying trends have severe implications and could be stronger than commonly assumed from the entire IPCC AR5 model ensemble.

Earth radiation balance as observed and represented in CMIP5 models

NASA Astrophysics Data System (ADS)

Wild, Martin; Folini, Doris; Schär, Christoph; Loeb, Norman; König-Langlo, Gert

2014-05-01

The genesis and evolution of Earth's climate is largely regulated by the Earth radiation balance. Despite of its key role in the context of climate change, substantial uncertainties still exist in the quantification of the magnitudes of its different components, and its representation in climate models. While the net radiative energy flows in and out of the climate system at the top of atmosphere are now known with considerable accuracy from new satellite programs such as CERES and SORCE, the energy distribution within the climate system and at the Earth's surface is less well determined. Accordingly, the magnitudes of the components of the surface energy balance have recently been controversially disputed, and potential inconsistencies between the estimated magnitudes of the global energy and water cycle have been emphasized. Here we summarize this discussion as presented in Chapter 2.3 of the 5th IPCC assessment report (AR5). In this context we made an attempt to better constrain the magnitudes of the surface radiative components with largest uncertainties. In addition to satellite observations, we thereby made extensive use of the growing number of surface observations to constrain the radiation balance not only from space, but also from the surface. We combined these observations with the latest modeling efforts performed for AR5 (CMIP5) to infer best estimates for the global mean surface radiative components. Our analyses favor global mean values of downward surface solar and thermal radiation near 185 and 342 Wm-2, respectively, which are most compatible with surface observations (Wild et al. 2013). These estimates are on the order of 10 Wm-2 lower and higher, respectively, than in some of the previous global energy balance assessments, including those presented in previous IPCC reports. It is encouraging that these estimates, which make full use of the information contained in the surface networks, coincide within 2 Wm-2 with the latest satellite-derived estimates (Kato et al. 2013), which are completely independently determined. This enhances confidence in these recent surface flux estimates. IPCC AR5 further presents increasing evidence from direct observations that the surface radiative fluxes undergo significant changes on decadal timescales, not only in their thermal components as expected from the increasing greenhouse effect, but also in the amount of solar radiation that reaches the Earth surface. In the thermal range, surface observations suggest an overall increase of downward thermal radiation in line with latest projections from the CMIP5 models and expectations from an increasing greenhouse effect. On the other hand the strong decadal changes in surface solar radiation seen in the observations ("dimming/brightening") are not fully captured by current climate models. These decadal changes in surface solar radiation may largely affect various aspects of climate change. Selected related references: Hartmann, D.L., A.M.G. Klein Tank, M. Rusticucci, L. Alexander, S. Brönnimann, Y. Charabi, F. Dentener, E. Dlugokencky, D. Easterling, A. Kaplan, B. Soden, P. Thorne, M. Wild and P.M. Zhai, 2013: Observations: Atmosphere and Surface. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Kato, S., Loeb, N.G., Rose, F.G., Doelling, D.R., Rutan, D.A., Caldwell, T.E., Yu, L.S, and Weller, R.A., 2013: Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances. Journal of Climate 26 (9):2719-2740. doi:Doi 10.1175/Jcli-D-12-00436.1 Wild, M., 2012: New Directions: A facelift for the picture of the global energy balance. Atmospheric Environment, 55, 366-367. Wild, M. 2012: Enlightening Global Dimming and Brightening. Bull. Amer. Meteor. Soc., 93, 27-37, doi:10.1175/BAMS-D-11-00074.1 Wild, M., Folini, D., Schär, C., Loeb, N., Dutton, E.G., and König-Langlo, G., 2013: The global energy balance from a surface perspective, Clim. Dyn., 40, 3107-3134, Doi:10.1007/s00382-012-1569-8.

Climate Change and Adaptation Planning on the Los Angeles Aqueduct

NASA Astrophysics Data System (ADS)

Roy, S. B.; Bales, R. C.; Costa-Cabral, M. C.; Chen, L.; Maurer, E. P.; Miller, N. L.; Mills, W. B.

2009-12-01

This study provides an assessment of the potential impacts of climate change on the Eastern Sierra Nevada snowpack and snowmelt timing, using a combination of empirical (i.e., data-based) models, and computer simulation models forced by GCM-projected 21st century climatology (IPCC 2007 AR4 projections). Precipitation from the Eastern Sierra Nevada is one of the main water sources for Los Angeles' more than 4 million people - a source whose future availability is critical to the city's growing population and large economy. Precipitation in the region falls mostly in winter and is stored in the large natural reservoir that is the snowpack. Meltwater from the Eastern Sierra is delivered to the city by the 340-mile long Los Angeles Aqueducts. The analysis is focused on the nature of the impact to the LAA water supplies over the 21st century due to potential climate change, including volume of precipitation, the mix of snowfall and rainfall, shifts in the timing of runoff, interannual variability and multi-year droughts. These impacts further affect the adequacy of seasonal and annual carryover water storage, and potentially water treatment. Most of the snow in the 10,000 km^2 Mono-Owens basins that feed the LAA occurs in a relatively narrow, 10-20 km wide, high-elevation band on the steep slopes of 20 smaller basins whose streams drain into the Owens River and thence LAA. Extending over 240 km in the north-south direction, these basins present special challenges for estimating snowpack amounts and downscaling climate-model data. In addition, there are few meteorological stations and snow measurements in the snow-producing parts of the basins to drive physically based hydrologic modeling.

How uncertain are climate model projections of water availability indicators across the Middle East?

PubMed

Hemming, Debbie; Buontempo, Carlo; Burke, Eleanor; Collins, Mat; Kaye, Neil

2010-11-28

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

Future Evolution of Marine Heat Waves in the Mediterranean: Coupled Regional Climate Projections

NASA Astrophysics Data System (ADS)

Darmaraki, Sofia; Somot, Samuel; Sevault, Florence; Nabat, Pierre; Cavicchia, Leone; Djurdjevic, Vladimir; Cabos, William; Sein, Dmitry

2017-04-01

FUTURE EVOLUTION OF MARINE HEAT WAVES IN THE MEDITERRANEAN : COUPLED REGIONAL CLIMATE PROJECTIONS The Mediterranean area is identified as a « Hot Spot » region, vulnerable to future climate change with potentially strong impacts over the sea. By 2100, climate models predict increased warming over the sea surface, with possible implications on the Mediterranean thermohaline and surface circulation,associated also with severe impacts on the ecosystems (e.g. fish habitat loss, species extinction and migration, invasive species). However, a robust assesment of the future evolution of the extreme marine temperatures remains still an open issue of primary importance, under the anthropogenic pressure. In this context, we study here the probability and characteristics of marine heat wave (MHW) occurrence in the Mediterranean Sea in future climate projections. To this end, we use an ensemble of fully coupled regional climate system models (RCSM) from the Med- CORDEX initiative. This multi-model approach includes a high-resolution representation of the atmospheric, land and ocean component, with a free air-sea interface.Specifically, dedicated simulations for the 20th and the 21st century are carried out with respect to the different IPCC-AR5 socioeconomic scenarios (1950-2100, RCP8.5, RCP4.5, RCP2.6). Model evaluation for the historical period is performed using satellite and in situ data. Then, the variety of factors that can cause the MHW (e.g. direct radiative forcing, ocean advection, stratification change) are examined to disentangle the dominant driving force. Finally, the spatial variability and temporal evolution of MHW are analyzed on an annual basis, along with additional integrated indicators, useful for marine ecosystems.

Hydrologic response of Pacific Northwest river to climate change

NASA Astrophysics Data System (ADS)

Su, F.; Cuo, L.; Wu, H.; Mantua, N.; Lettenmaier, D. P.

2009-12-01

The climate of the Pacific Northwest (PNW - which we define as the Columbia River basin and watersheds draining to the Oregon and Washington coasts) is expected to warm by approximately 0.3°C per decade in the next 100 years based on the IPCC the Fourth Assessment Report (AR4) results. PNW hydrology is particularly sensitive to a warming climate because of the dominant role of snowmelt in seasonal streamflow. Timing shifts in seasonality of flows, peak discharge, and base flows will impact water resource management, regional electrical energy production, and freshwater ecosystems. In this work we update previous studies of implications of climate change on PNW hydrology using a macroscale hydrology model driven by simulations of temperature and precipitation downscaled from runs of 20 General Circulation Models (GCMs) under two emissions scenarios (lower B1 and mid-high A1B) in the 21st century. The hydrology model is implemented at 1/16th degree spatial resolution over the entire PNW. A (statistical) bias-correction and spatial disaggregation downscaling approach is used for translating the transient monthly climate model output into continuous daily forcings for the hydrologic analysis. We evaluate projected changes in snow water equivalent, seasonal streamflow, and frequency of peak low flows over a set of case study watersheds in the region. We also compare these hydrologic projections with previous analysis based on delta downscaling method over the PNW. This research is part of a project investigating climate change impacts on the future of wild Pacific salmon, and is a pilot effort to investigate the hydrologic sensitivity of salmon bearing watersheds around the entire North Pacific Rim.

Climate uncertainty and implications for U.S. state-level risk assessment through 2050.

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

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.

2009-10-01

Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to themore » economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.« less

Robust signals of future projections of Indian summer monsoon rainfall by IPCC AR5 climate models: Role of seasonal cycle and interannual variability

NASA Astrophysics Data System (ADS)

Jayasankar, C. B.; Surendran, Sajani; Rajendran, Kavirajan

2015-05-01

Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k-means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d-1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.

The Co-evolution of Climate Models and the Intergovernmental Panel on Climate Change

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2010-12-01

As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already been endorsed by many leading scientific professional societies and academies of science worldwide. These reports are considered as definitive summaries of the state of the science. In 2007, in recognition of its exceptional accomplishments, the IPCC shared the Nobel Peace Prize equally with Al Gore. The present era is characterized not only by the reality and seriousness of human-caused climate change, but also by a young yet powerful science that enables us to understand much about the climate change that has occurred already and that awaits in the future. The development of GCMs is a critical part of the scientific story, and the development of the IPCC is a key factor in connecting the science to the perceptions and priorities of the global public and policymakers. GCMs and the IPCC have co-evolved and strongly influenced one another, as both scientists and the world at large have worked to confront the challenge of climate change.

The impact of SciDAC on US climate change research and the IPCCAR4

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

Wehner, Michael

2005-07-08

SciDAC has invested heavily in climate change research. We offer a candid opinion as to the impact of the DOE laboratories' SciDAC projects on the upcoming Fourth Assessment Report of the Intergovernmental Panel on Climate Change. As a result of the direct importance of climate change to society, climate change research is highly coordinated at the international level. The Intergovernmental Panel on Climate Change (IPCC) is charged with providing regular reports on the state of climate change research to government policymakers. These reports are the product of thousands of scientists efforts. A series of reviews involving both scientists and policymakersmore » make them among the most reviewed documents produced in any scientific field. The high profile of these reports acts a driver to many researchers in the climate sciences. The Fourth Assessment Report (AR4) is scheduled to be released in 2007. SciDAC sponsored research has enabled the United States climate modeling community to make significant contributions to this report. Two large multi-Laboratory SciDAC projects are directly relevant to the activities of the IPCC. The first, entitled ''Collaborative Design and Development of the Community Climate System Model for Terascale Computers'', has made important software contributions to the recently released third version of the Community Climate System Model (CCSM3.0) developed at the National Center for Atmospheric Research. This is a multi-institutional project involving Los Alamos National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The original principal investigators were Robert Malone and John B. Drake. The current principal investigators are Phil Jones and John B. Drake. The second project, entitled ''Earth System Grid II: Turning Climate Datasets into Community Resources'' aims to facilitate the distribution of the copious amounts of data produced by coupled climate model integrations to the general scientific community. This is also a multi-institutional project involving Argonne National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The principal investigators are Ian Foster, Don Middleton and Dean Williams. Perhaps most significant among the activities of the ''Collaborative Design'', project was the development of an efficient multi-processor coupling package. CCSM3.0 is an extraordinarily complicated physics code. The fully coupled model consists of separate submodels of the atmosphere, ocean, sea ice and land. In addition, comprehensive biogeochemistry and atmospheric chemistry submodels are under intensive current development. Each of these submodels is a large and sophisticated program in its own right. Furthermore, in the coupled model, each of the submodels, including the coupler, is a separate multiprocessor executable program. The coupler package must efficiently coordinate the communication as well as interpolate or aggregate information between these programs. This regridding function is necessary because each major subsystem (air, water or surface) is allowed to have its own independent grid.« less

Decarbonizing the Global Economy - An Integrated Assessment of Low Carbon Emission Scenarios proposed in Climate Policy

NASA Astrophysics Data System (ADS)

Hokamp, Sascha; Khabbazan, Mohammad Mohammadi

2017-04-01

In 2015, the Conference of the Parties (COP 21) reaffirmed to targeting the global mean temperature rise below 2 °C in 2100 while finding no consent on decarbonizing the global economy, and instead, the final agreement called for enhanced scientific investigation of low carbon emission scenarios (UNFCC, 2015). In addition, the Climate Action Network International (CAN) proposes Special Reports to address decarbonization and low carbon development including 1.5 °C scenarios (IPCC, 2016). In response to these developments, we investigate whether the carbon emission cuts, in accordance with the recent climate policy proposals, may reach the climate target. To tackle this research question, we employ the coupled climate-energy-economy integrated assessment Model of INvestment and endogenous technological Development (MIND, cf. Edenhofer et al., 2005, Neubersch et al. 2014). Extending MIND's climate module to the two-box version used in the Dynamic Integrated model of Climate and the Economy (DICE, cf. Nordhaus and Sztorc, 2013, Nordhaus 2014), we perform a cost-effectiveness analysis with constraints on anthropogenic carbon emissions. We show that a climate policy scenario with early decarbonization complies with the 2° C climate target, even without Carbon Capturing and Storage (CCS) or negative emissions (see van Vuuren et al., 2013, for negative emissions). However, using emission inertia of 3.7 percent annually, reflecting the inflexibility on transforming the energy sector, we find a climate policy with moderately low emissions from 2100 onwards at a cost in terms of Balanced Growth Equivalents (BGE, cf. Anthoff and Tol, 2009) of 0.764 % that requires an early (2035 vs. 2120) peak of investments in renewable energy production compared to a business-as-usual scenario. Hence, decarbonizing the global economy and achieving the 2 °C target might still be possible before 2100, but the window of opportunity is beginning to close. References: Anthoff, D., and Tol, R. S. J. (2009), "The Impact of Climate Change on the Balanced Growth Equivalent: An Application to FUND", Environmental and Resource Economics, 43 (3), 351-367. Edenhofer, O., Bauer, N., and Kriegler, E. (2005), "The Impact of Technological Change on Climate Protection and Welfare: Insights from the Model MIND", Ecological Economics, 54, 277-292. Neubersch, D., Held, H., and Otto, A., (2014), "Operationalizing Climate Targets under Learning: An Application of Cost-Risk Analysis", Climatic Change, 126, 305-318. Nordhaus, W. D., and Sztorc, P., (2013), DICE2013R: Introduction and User's Manual Nordhaus, W. D. (2014), "Estimates of the Social Cost of Carbon: Concepts and Results from the DICE-2013R Model and Alternative Approaches", Journal of the Association of Environmental and Resource Economists, 1 (1/2, Spring/Summer, 2014), 273-312. IPCC (2016), Sixth Assessment Report (AR6) Products, IPCC-XLIII/INF.7. UNFCCC (2015), Adoption of the Paris Agreement van Vuuren, D. P., Deetman, S., van Vliet, J., van den Berg, M. , van Ruijven, B.J., and Koelbl, B. (2013): "The Role of Negative CO2 Emissions for Reaching 2 °C - Insights from Integrated Assessment Modelling", Climatic Change, 118, 15-27.

From California dreaming to California data: Challenging historic models for landfill CH4 emissions

USDA-ARS?s Scientific Manuscript database

Improved quantification of diverse CH4 sources at the urban scale is needed to guide local greenhouse gas (GHG) mitigation strategies in the Anthropocene. Herein, we focus on landfill CH4 emissions in California, challenging the current IPCC methodology which focuses on a climate dependency for land...

The Uptake of Heat and Carbon by the Southern Ocean in the CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Russell, J. L.; Stouffer, R. J.; Dunne, J. P.; John, J. G.

2011-12-01

The Southern Ocean surrounding the Antarctic continent accounts for a disproportionate share of the heat and carbon dioxide that is removed from contact with the atmosphere into the ocean. The vigorous air-sea exchange driven by the Southern Hemisphere Westerlies, combined with the dearth of observations, makes the Southern Ocean a major source of uncertainty in projecting the rate of warming of our atmosphere, especially considering that the vertical mixing of the ocean and the corollary air-sea fluxes may be vulnerable to climate change. We assess the heat and carbon uptake by the Southern Ocean in future simulations by the IPCC-AR5 Earth System Models (ESMs), focusing on the GFDL simulations. Using the 1860 control simulation as our baseline, we explore the differences in heat and carbon uptake between the major "Representative Concentration Pathways" (RCPs) as simulated by the various ESMs in order to quantify the uncertainties in the climate projections related to the Southern Ocean window into the deep ocean reservoir.

Uncertainty of a hydrological climate change impact assessment - Is it really all about climate uncertainty?

NASA Astrophysics Data System (ADS)

Honti, Mark; Reichert, Peter; Scheidegger, Andreas; Stamm, Christian

2013-04-01

Climate change impact assessments have become more and more popular in hydrology since the middle 1980's with another boost after the publication of the IPCC AR4 report. During hundreds of impact studies a quasi-standard methodology emerged, which is mainly shaped by the growing public demand for predicting how water resources management or flood protection should change in the close future. The ``standard'' workflow considers future climate under a specific IPCC emission scenario simulated by global circulation models (GCMs), possibly downscaled by a regional climate model (RCM) and/or a stochastic weather generator. The output from the climate models is typically corrected for bias before feeding it into a calibrated hydrological model, which is run on the past and future meteorological data to analyse the impacts of climate change on the hydrological indicators of interest. The impact predictions are as uncertain as any forecast that tries to describe the behaviour of an extremely complex system decades into the future. Future climate predictions are uncertain due to the scenario uncertainty and the GCM model uncertainty that is obvious on finer resolution than continental scale. Like in any hierarchical model system, uncertainty propagates through the descendant components. Downscaling increases uncertainty with the deficiencies of RCMs and/or weather generators. Bias correction adds a strong deterministic shift to the input data. Finally the predictive uncertainty of the hydrological model ends the cascade that leads to the total uncertainty of the hydrological impact assessment. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. There are only few studies, which found that the predictive uncertainty of hydrological models can be in the same range or even larger than climatic uncertainty. We carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on 2 small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment method with 2 different likelihood functions. One was a time-series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was a likelihood function for the flow quantiles directly. Due to the better data coverage and smaller hydrological complexity in one of our test catchments we had better performance from the hydrological model and thus could observe that the relative importance of different uncertainty sources varied between sites, boundary conditions and flow indicators. The uncertainty of future climate was important, but not dominant. The deficiencies of the hydrological model were on the same scale, especially for the sites and flow components where model performance for the past observations was further from optimal (Nash-Sutcliffe index = 0.5 - 0.7). The overall uncertainty of predictions was well beyond the expected change signal even for the best performing site and flow indicator.

Relationships of Upper Tropospheric Water Vapor, Clouds and SST: MLS Observations, ECMWF Analyses and GCM Simulations

NASA Technical Reports Server (NTRS)

Su, Hui; Waliser, Duane E.; Jiang, Jonathan H.; Li, Jui-lin; Read, William G.; Waters, Joe W.; Tompkins, Adrian M.

2006-01-01

The relationships of upper tropospheric water vapor (UTWV), cloud ice and sea surface temperature (SST) are examined in the annual cycles of ECMWF analyses and simulations from 15 atmosphere-ocean coupled models which were contributed to the IPCC AR4. The results are compared with the observed relationships based on UTWV and cloud ice measurements from MLS on Aura. It is shown that the ECMWF analyses produce positive correlations between UTWV, cloud ice and SST, similar to the MLS data. The rate of the increase of cloud ice and UTWV with SST is about 30% larger than that for MLS. For the IPCC simulations, the relationships between UTWV, cloud ice and SST are qualitatively captured. However, the magnitudes of the simulated cloud ice show a considerable disagreement between models, by nearly a factor of 10. The amplitudes of the approximate linear relations between UTWV, cloud ice and SST vary by a factor up to 4.

Downscale climate change scenarios over the Western Himalayan region of India using multi-generation CMIP experiments

NASA Astrophysics Data System (ADS)

Das, Lalu; Meher, Jitendra K.; Akhter, Javed

2017-04-01

Assessing climate change information over the Western Himalayan Region (WHR) of India is crucial but challenging task due to its limited numbers of station data containing huge missing values. The issues of missing values of station data were replaced the Multiple Imputation Chained Equation (MICE) technique. Finally 22 numbers of rain gauge stations having continuous data during 1901-2005 and 16 numbers stations having continuous temperature data during 1969-2009 were considered as " reference stations for assessing rainfall and temperature trends in addition to evaluation of the GCMs available in the Coupled Model Intercomparison Project, Phase 3 (CMIP3) and phase 5 (CMIP5) over WRH. Station data indicates that the winter warming is higher and rapid (1.05oC) than other seasons and less warming in the post monsoon season in the last 41 years. Area averaged using 22 station data indicates that monsoon and winter rainfall has decreased by -5 mm and -320 mm during 1901-2000 while pre-monsoon and post monsoon showed an increasing trends of 21 mm and 13 mm respectively. Present study is constructed the downscaled climate change information at station locations (22 and 16 stations for rainfall and temperature respectively) over the WHR from the GCMs commonly available in the IPCC's different generations assessment reports namely 2nd, 3rd, 4th and 5th thereafter known as SAR, TAR, AR4 and AR5 respectively. Once the downscaled results are obtained for each generation model outputs, then a comparison of studies is carried out from the results of each generation. Finally an overall model improvement index (OMII) is developed using the downscaling results which is used to investigate the model improvement across generations as well as the improvement of downscaling results obtained from the empirical statistical downscaling (ESD) methods. In general, the results indicate that there is a gradual improvement of GCMs simulations as well as downscaling results across generation. Key words: MICE Techniques, CMIP3, CMIP5, ESD and OMII

Climate Model Ensemble Methodology: Rationale and Challenges

NASA Astrophysics Data System (ADS)

Vezer, M. A.; Myrvold, W.

2012-12-01

A tractable model of the Earth's atmosphere, or, indeed, any large, complex system, is inevitably unrealistic in a variety of ways. This will have an effect on the model's output. Nonetheless, we want to be able to rely on certain features of the model's output in studies aiming to detect, attribute, and project climate change. For this, we need assurance that these features reflect the target system, and are not artifacts of the unrealistic assumptions that go into the model. One technique for overcoming these limitations is to study ensembles of models which employ different simplifying assumptions and different methods of modelling. One then either takes as reliable certain outputs on which models in the ensemble agree, or takes the average of these outputs as the best estimate. Since the Intergovernmental Panel on Climate Change's Fourth Assessment Report (IPCC AR4) modellers have aimed to improve ensemble analysis by developing techniques to account for dependencies among models, and to ascribe unequal weights to models according to their performance. The goal of this paper is to present as clearly and cogently as possible the rationale for climate model ensemble methodology, the motivation of modellers to account for model dependencies, and their efforts to ascribe unequal weights to models. The method of our analysis is as follows. We will consider a simpler, well-understood case of taking the mean of a number of measurements of some quantity. Contrary to what is sometimes said, it is not a requirement of this practice that the errors of the component measurements be independent; one must, however, compensate for any lack of independence. We will also extend the usual accounts to include cases of unknown systematic error. We draw parallels between this simpler illustration and the more complex example of climate model ensembles, detailing how ensembles can provide more useful information than any of their constituent models. This account emphasizes the epistemic importance of considering degrees of model dependence, and the practice of ascribing unequal weights to models of unequal skill.

Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

NASA Astrophysics Data System (ADS)

Castro, C. L.; Dominguez, F.; Chang, H.

2010-12-01

Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.

The implications of rebasing global mean temperature timeseries for GCM based climate projections

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2017-04-01

Global climate and earth system models are assessed by comparison with observations through a number of metrics. The InterGovernmental Panel on Climate Change (IPCC) highlights in particular their ability to reproduce "general features of the global and annual mean surface temperature changes over the historical period" [1,2] and to simulate "a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend" [3]. This focus on annual mean global mean temperature (hereafter GMT) change is presented as an important element in demonstrating the relevance of these models for climate projections. Any new model or new model version whose historic simulations fail to reproduce the "general features " and 20th century trends is likely therefore to undergo further tuning. Thus this focus could have implications for model development. Here we consider a formal interpretation of "general features" and discuss the implications of this approach to model assessment and intercomparison, for the interpretation of GCM projections. Following the IPCC, we interpret a major element of "general features" as being the slow timescale response to external forcings. (Shorter timescale behaviour such as the response to volcanic eruptions are also elements of "general features" but are not considered here.) Also following the IPCC, we consider only GMT anomalies i.e. changes with respect to some period. Since the models have absolute temperatures which range over about 3K (roughly observed GMT +/- 1.5K) this means their timeseries (and the observations) are rebased. We present timeseries of the slow timescale response of the CMIP5 models rebased to late-20th century temperatures and to mid-19th century temperatures. We provide a mathematical interpretation of this approach to model assessment and discuss two consequences. First is a separation of scales which limits the degree to which sub-global behaviour can feedback on the global response. Second, is an implication of linearity in the GMT response (to the extent that the slow-timescale response of the historic simulations is consistent with observations, and given their uncertainties). For each individual model these consequences only apply over the range of absolute temperatures simulated by the model in historic simulations. Taken together, however, they imply consequences over a much wider range of GMTs. The analysis suggests that this aspect of model evaluation risks providing a model development pressure which acts against a wide exploration of physically plausible responses; in particular against an exploration of potentially globally significant nonlinear responses and feedbacks. [1] IPCC, Fifth Assessment Report, Working Group 1, Technical Summary: Stocker et al. 2013. [2] IPCC, Fifth Assessment Report, Working Group 1, Chapter 9 - "Evaluation of Climate Models": Flato et al. 2013. [3] IPCC, Fifth Assessment Report, Working Group 1, Summary for Policy Makers: IPCC, 2013.

A Harder Rain is Going to Fall: Challenges for Actionable Projections of Extremes

NASA Astrophysics Data System (ADS)

Collins, W.

2014-12-01

Hydrometeorological extremes are projected to increase in both severity and frequency as the Earth's surface continues to warm in response to anthropogenic emissions of greenhouse gases. These extremes will directly affect the availability and reliability of water and other critical resources. The most comprehensive suite of multi-model projections has been assembled under the Coupled Model Intercomparison Project version 5 (CMIP5) and assessed in the Fifth Assessment (AR5) of the Intergovernmental Panel on Climate Change (IPCC). In order for these projections to be actionable, the projections should exhibit consistency and fidelity down to the local length and timescales required for operational resource planning, for example the scales relevant for water allocations from a major watershed. In this presentation, we summarize the length and timescales relevant for resource planning and then use downscaled versions of the IPCC simulations over the contiguous United States to address three questions. First, over what range of scales is there quantitative agreement between the simulated historical extremes and in situ measurements? Second, does this range of scales in the historical and future simulations overlap with the scales relevant for resource management and adaptation? Third, does downscaling enhance the degree of multi-model consistency at scales smaller than the typical global model resolution? We conclude by using these results to highlight requirements for further model development to make the next generation of models more useful for planning purposes.

Emergence of the significant local warming of Korea in CMIP5 projections

NASA Astrophysics Data System (ADS)

Boo, Kyung-On; Shim, Sungbo; Kim, Jee-Eun

2016-04-01

According to IPCC AR5, anthropogenic influence on warming is obvious in local scales, especially in some tropical regions. Detection of significant local warming is important for adaptation to climate change of society and ecosystem. Recently much attention has focused on the time of emergence (ToE) for the signal of anthropogenic climate change against the natural climate variability. Motivated from the previous studies, this study analyzes ToE of regional surface air temperature over Korea. Simulations of CMIP5 15 models are used for RCP 2.6, 4.5 and 8.5. For each year, JJA and DJF temperature anomalies are calculated for the time period 1900-1929. For noise of interannual variability, natural-only historical simulations of CMIP5 12 models are used and the standard deviation of the time series is obtained. For signal of warming, we examine the year when the signal above 2 standard deviations is detected in 80% of the models using 30-year smoothed time series. According to our results, interannual variability is larger in land than ocean. Seasonally, it is larger in winter than in summer. Accordingly, ToE of summertime temperature is earlier than that in winter and is expected to appear in 2030s from three RCPs. The seasonal difference is consistent with previous studies. Wintertime ToE appears in 2040s for RCP85 and 2060s for RCP4.5. The different emergence time between RCP8.5 and RCP4.5 reflects the influence of mitigation. In a similar way, daily maximum and minimum temperatures are analyzed. ToE of Tmin appears earlier than that of Tmax and difference is small. Acknowledgements. This study is supported by the National Institute of Meteorological Sciences, Korea Meteorological Administration (NIMR-2012-B-2).

PM2.5 and tropospheric ozone in China: overview of situation and responses

NASA Astrophysics Data System (ADS)

Zhang, Hua

This work reviewed the observational status of PM2.5 and tropospheric ozone in China. It told us the observational facts on the ratios of typical types of aerosol components to the total PM2.5/PM10, and daily and seasonal change of near surface ozone concentration at different cities of China; the global concentration distribution of tropospheric ozone observed by satellite in 2010-2013 was also given for comparison; the PM2.5 concentration distribution and their seasonal change in China region were simulated by an aerosol chemistry-global climate modeling system. Different contribution from five kinds of aerosols to the simulated PM2.5 was analyzed. Then, it linked the emissions of aerosol and greenhouse gases and their radiative forcing and thus gave their climatic effect by reducing their emissions on the basis of most recently published IPCC AR5. Finally it suggested policies on reducing emissions of short-lived climate pollutants (SLCPs) (such as PM2.5 and tropospheric ozone) in China from protecting both climate and environment.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Climate Change in New York State Updating the 2011 ClimAID Climate Risk Information Supplement to NYSERDA Report 11-18 (Responding to Climate Change in New York State)

NASA Technical Reports Server (NTRS)

Horton, Radley M.; Bader, Daniel A.; Rosenzweig, Cynthia; DeGaetano, Arthur T.; Solecki, William

2014-01-01

In its 2013-2014 Fifth Assessment Report (AR5), the Intergovernmental Panel on Climate Change (IPCC) states that there is a greater than 95 percent chance that rising global average temperatures, observed since the mid-20th century, are primarily due to human activities. As had been predicted in the 1800s, the principal driver of climate change over the past century has been increasing levels of atmospheric greenhouse gases associated with fossil-fuel combustion, changing land-use practices, and other human activities. Atmospheric concentrations of the greenhouse gas carbon dioxide are now approximately 40 percent higher than in preindustrial times. Concentrations of other important greenhouse gases, including methane and nitrous oxide, have increased rapidly as well.

Representative concentration pathways and mitigation scenarios for nitrous oxide

NASA Astrophysics Data System (ADS)

Davidson, Eric A.

2012-06-01

The challenges of mitigating nitrous oxide (N2O) emissions are substantially different from those for carbon dioxide (CO2) and methane (CH4), because nitrogen (N) is essential for food production, and over 80% of anthropogenic N2O emissions are from the agricultural sector. Here I use a model of emission factors of N2O to demonstrate the magnitude of improvements in agriculture and industrial sectors and changes in dietary habits that would be necessary to match the four representative concentration pathways (RCPs) now being considered in the fifth assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). Stabilizing atmospheric N2O by 2050, consistent with the most aggressive of the RCP mitigation scenarios, would require about 50% reductions in emission factors in all sectors and about a 50% reduction in mean per capita meat consumption in the developed world. Technologies exist to achieve such improved efficiencies, but overcoming social, economic, and political impediments for their adoption and for changes in dietary habits will present large challenges.

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

NASA Astrophysics Data System (ADS)

Fan, Tianyi; Liu, Xiaohong; Ma, Po-Lun; Zhang, Qiang; Li, Zhanqing; Jiang, Yiquan; Zhang, Fang; Zhao, Chuanfeng; Yang, Xin; Wu, Fang; Wang, Yuying

2018-02-01

Global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22-28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be -5.02, -18.47, and 13.45 W m-2, respectively, over eastern China, which are enhanced by -0.91, -3.48, and 2.57 W m-2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

Grassland production under global change scenarios for New Zealand pastoral agriculture

NASA Astrophysics Data System (ADS)

Keller, E. D.; Baisden, W. T.; Timar, L.; Mullan, B.; Clark, A.

2014-05-01

We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand (LURNZ) models to simulate pastoral agriculture and to make land-use change, intensification and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1-2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report (AR4) also show national increases of 1-2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3% and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasize that CO2 fertilisation and N cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of Decoupled Land-Use Change Scenarios (DLUCS): the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

Projections of wind-waves in South China Sea for the 21st century

NASA Astrophysics Data System (ADS)

Mohammed, Aboobacker; Dykyi, Pavlo; Zheleznyak, Mark; Tkalich, Pavel

2013-04-01

IPCC-coordinated work has been completed within Fourth Assessment Report (AR4) to project climate and ocean variables for the 21st century using coupled atmospheric-ocean General Circulation Models (GCMs). GCMs are not having a wind-wave variable due to a poor grid resolution; therefore, dynamical downscaling of wind-waves to the regional scale is advisable using well established models, such as Wave Watch III (WWIII) and SWAN. Rectilinear-coordinates WWIII model is adapted for the far field comprising the part of Pacific and Indian Oceans centered at the South China Sea and Sunda Shelf (90 °E-130 °E, 10 °S - 26.83 °N) with a resolution of 10' (about 18 km). Near-field unstructured-mesh SWAN model covers Sunda Shelf and centered on Singapore Strait, while reading lateral boundary values from WWIII model. The unstructured grid has the coarsest resolution in the South China Sea (6 to 10 km), medium resolution in the Malacca Strait (1 to 2 km), and the finest resolution in the Singapore Strait (400 m) and along the Singapore coastline (up to 100 m). Following IPCC methodology, the model chain is validated climatologically for the past period 1961-1990 against Voluntary Observing Ship (VOS) data; additionally, the models are validated using recent high-resolution satellite data. The calibrated model chain is used to project waves to 21st century using WRF-downscaled wind speed output of CCSM GCM run for A1FI climate change scenario. To comply with IPCC methodology the entire modeling period is split into three 30-years periods for which statistical parameters are computed individually. Time series of significant wave height at key points near Singapore and on ship sea routes in the SCS are statistically analysed to get probability distribution functions (PDFs) of extreme values. Climatological maps of mean and maximum significant wave height (SWH) values, and mean wave period are built for Singapore region for each 30-yrs period. Linear trends of mean SWH values for northeast (NE) and southwest (SW) monsoons have been derived. The maximum values of predicted 100 year return period (YRP) SWH are obtained for the 1st 30-yrs period (2011-2040). In the deep eastern part of the Singapore, 100yrp SWH are 2.4 - 2.8 m, whereas those at the shallow nearshore areas are 1.7-2.3 m. On the ship routes at Sunda Shelf the 100 YRP SWHs are 1.1 - 3.2 m, and those at the SCS routes are 3.6 - 10.4 m. The biggest changes in future against hindcasted SWH is in first 30-yrs, where extreme 100 YRP SWH will grow up in the range from 36%-120% at points near Singapore and to 39%-108% at ship sea routes.

Modeling the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

NASA Astrophysics Data System (ADS)

Lowry, T. S.; Backus, G.; Warren, D.

2010-12-01

Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.

New chairman takes helm at Climate Change Panel

NASA Astrophysics Data System (ADS)

Showstack, Randy

An Indian industrial engineer and economist who supports the Kyoto Protocol, and who has sharply criticized the administration of George W. Bush on the climate change issue for not doing enough to curb greenhouse gas emissions, won the first-ever contested election for chairman of the Intergovernmental Panel on Climate Change (IPCC) during a meeting on 19 April.Rajendra Pachauri is the first representative from a developing country to chair the IPCC, a panel of about 2,500 experts on a wide range of areas related to climate change. The IPCC was established in 1988 by the World Meteorological Organization and the United Nations Environment Programme. In total, the IPCC currently includes 192 member states. Although the bulk of the IPCC's work is conducted by three technical working groups, the chairman plays a key role in facilitating the overall process of the IPCC, organizing the scientific debate within the IPCC, and serving as chief spokesman.

Seeing the risks of multiple Arctic amplifying feedbacks.

NASA Astrophysics Data System (ADS)

Carter, P.

2014-12-01

There are several potentially very large sources of Arctic amplifying feedbacks that have been identified. They present a great risk to the future as they could become self and inter-reinforcing with uncontrollable knock-on, or cascading risks. This has been called a domino effect risk by Carlos Duarte. Because of already committed global warming and the millennial duration of global warming, these are highly policy relevant. These Arctic feedback processes are now all operant with emissions of carbon dioxide methane and nitrous oxide detected. The extent of the risks from these feedback sources are not obvious or easy to understand by policy makers and the public. They are recorded in the IPCC AR5 as potential tipping points, as is the irreversibility of permafrost thaw. Some of them are not accounted for in the IPCC AR5 global warming projections because of quantitative uncertainty. UNEP issued a 2012 report (Policy Implications of Thawing Permafrost) advising that by omitting carbon feedback emissions from permafrost, carbon budget calculations by err on the low side. There is the other unassessed issue of a global warming safety limit for preventing uncontrollable increasing Arctic feedback emissions. Along with our paper, we provide illustrations of the Arctic feedback sources and processes from satellite imagery and flow charts that allows for their qualitative consideration. We rely on the IPCC assessments, the 2012 paper Possible role of wetlands permafrost can methane hydrates in the methane cycle under future climate change; a review, by Fiona M. O'Connor et al., and build on the WWF 2009 Arctic Climate Feedbacks: Global Implications. The potential sources of Arctic feedback processes identified include: Arctic and Far North snow albedo decline, Arctic summer sea ice albedo decline, Greenland summer ice surface melting albedo loss, albedo decline by replacement of Arctic tundra with forest, tundra fires, Boreal forest fires, Boreal forest die-back, warming subarctic peat rich wetlands (methane), thawing permafrost (carbon dioxide, methane and nitrous oxide), and Arctic subsea floor methane.

Methane emissions associated with the conversion of marshland to cropland and climate change on the Sanjiang Plain of northeast China from 1950 to 2100

NASA Astrophysics Data System (ADS)

Li, T.; Huang, Y.; Zhang, W.; Yu, Y.-Q.

2012-12-01

Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tg yr-1 (0.7-1.8 Tg yr-1) from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~36 Tg (24-57 Tg) relative to the 1950s, and marshland conversion and the climate contributed 86% and 14% of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960-2009 (47 mm yr-1 lower on average than in the 1950s) contributed ~91% of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 ° per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha-1 yr-1 over the last two decades. In the RCP (Representative Concentration Pathway) 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 fluxes are predicted to increase by 36%, 52%, 78% and 95%, respectively, by the 2080s compared to 1961-1990 in response to climate warming and wetting.

The Current Status and Future of GNSS-Meteorology in Europe

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Dick, G.; Haan, de, S.; Pottiaux, E.; Bock, O.; Pacione, R.

2017-12-01

GNSS is a well established atmospheric observing system which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Water vapour observations are currently under-sampled in operational meteorology and obtaining and exploiting additional high-quality humidity observations is essential to improve severe weather forecasting and climate monitoring. Inconsistencies introduced into long-term time series from improved GNSS processing algorithms make climate trend analysis challenging. Ongoing re-processing efforts using state-of-the-art models are underway which will provide consistent time series' of tropospheric data, using 15+ years of GNSS observations and from over 600 stations worldwide. These datasets will enable validation of systematic biases from a range of instrumentation, improve the knowledge of climatic trends of atmospheric water vapour, and will potentially be of great benefit to global and regional NWP reanalyses and climate model simulations (e.g. IPCC AR5) COST Action ES1206 is a 4-year project, running from 2013 to 2017, which has coordinated new and improved capabilities from concurrent developments in GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations has been used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action has also promoted the use of meteorological data as an input to real-time GNSS positioning, navigation, and timing services and has stimulated knowledge and data transfer throughout Europe and beyond. This presentation will give an overview of COST Action ES1206 plus an overview of ground-based GNSS-meteorology in Europe in general, including current status and future opportunities.

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

Regional Climate Change Index (RCCI), is developed based on regional mean precipitation change, mean surface air temperature change, and change in precipitation and temperature interannual variability. The RCCI is a comparative index designed to identify the most responsive regions to climate change, or Hot- Spots. The RCCI is calculated for Seven land regions over North Africa and Arabian region from the latest set of climate change projections by 14 global climates for the A1B, A2 and B1 IPCC emission scenarios. The concept of climate change can be approaches from the viewpoint of vulnerability or from that of climate response. In the former case a Hot-Spot can be defined as a region for which potential climate change impacts on the environment or different activity sectors can be particularly pronounced. In the other case, a Hot-Spot can be defined as a region whose climate is especially responsive to global change. In particular, the characterization of climate change response-based Hot-Spot can provide key information to identify and investigate climate change Hot-Spots based on results from multi-model ensemble of climate change simulations performed by modeling groups from around the world as contributions to the Assessment Report of Intergovernmental Panel on Climate Change (IPCC). A Regional Climate Change Index (RCCI) is defined based on four variables: change in regional mean surface air temperature relative to the global average temperature change ( or Regional Warming Amplification Factor, RWAF ), change in mean regional precipitation ( , of present day value ), change in regional surface air temperature interannual variability ( ,of present day value), change in regional precipitation interannual variability ( , of present day value ). In the definition of the RCCI it is important to include quantities other than mean change because often mean changes are not the only important factors for specific impacts. We thus also include inter annual variability, which is critical for many activity sectors, such as agriculture and water management. The RCCI is calculated for the above mentioned set of global climate change simulations and is inter compared across regions to identify climate change, Hot- Spots, that is regions with the largest values of RCCI. It is important to stress that, as will be seen, the RCCI is a comparative index, that is a small RCCI value does not imply a small absolute change, but only a small climate response compared to other regions. The models used are: CCMA-3-T47 CNRM-CM3 CSIRO-MK3 GFDL-CM2-0 GISS-ER INMCM3 IPSL-CM4 MIROC3-2M MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2 NCAR-CCSM3 NCAR-PCM1 UKMO-HADCM3 Note that the 3 IPCC emission scenarios, A1B, B1 and A2 almost encompass the entire IPCC scenario range, the A2 being close to the high end of the range, the B1 close to the low end and the A1B lying toward the middle of the range. The model data are obtained from the IPCC site and are interpolated onto a common 1 degree grid to facilitate intercomparison. The RCCI is here defined as in Giorgi (2006), except that the entire yea is devided into two six months periods, D J F M A M and J J A S O N. RCCI=[n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]D...M + [n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]J…N (1)

Complexity and interdisciplinary approaches to environmental research

NASA Astrophysics Data System (ADS)

Kammen, Daniel M.

2013-03-01

The launch of volume 8 of Environmental Research Letters (ERL) comes at a critical time in terms of innovations and exciting areas of science, but particularly in the areas linking environmental research and action. The most recent climate change Conference of the Parties meeting (COP), in Doha in December 2012, has now come and gone. As has been dissected in the press, very little was accomplished. Some will see this as a failure, as I do, and others will reasonably enough note that this meeting, the 18th such COP was1 never intended to be a milestone moment. The current plan, in fact, is for a 'post-Kyoto' international climate agreement to be adopted only at the COP20 summit in December 2015. As we lead up to COP20, and potentially other regional or national approaches to climate protection, innovations in science, innovations in policy tools, and political commitment must come together. The science of climate change only continues to get clearer and clearer, and bleaker [1]. Later this year the IPCC will release its Fifth Assessment Report, AR5. The draft versions are out for review now. ERL has published a number of papers on climate change science, mitigation and adaptation, but one area where the world needs a particular focus is on the nexus of science and action. A summary of the Intergovernmental Panel on Climate Change's findings from the first assessment report (FAR; 1990) to the latest report is presented in figure 1. This graphic is specifically not about the scientific record alone. What is most important about this figure is the juxtaposition of the language of science and the language of ... language. Figure 1. Figure 1. A superposition of the state of climate science in three key data sets, and the dates of the first, second, third and fourth assessment reports (FAR, SAR, TAR, and AR4, respectively) plotted as vertical lines. On the right are the key statements from each of these reports, along with the conclusion of the Special Report on Renewable Energy (SRREN, completed in 2011) which found that up to an 80% decarbonization of the global economy was possible if we can enable and launch a large-scale transition to a clean energy system consistent with what a number of 'leading edge' cities, regions, and nations have already accomplished or started. Note, in particular, that as the physical climate change metrics have progressed, the words—shown on the right—have also progressed. In 1990, at the time of the FAR the strongest scientific consensus statement was that another decade of data would likely be needed to clearly observe climate change. Through the second to fourth (SAR, TAR, and AR4) reports, increasing clarity on the science of climate change translated into a consensus of overwhelming blame on human activities. The key statements from each report are not only about the growing evidence for anthropogenically driven climate change, but they have moved into the ecological and social impacts of this change. AR4 critically concluded that climate change would lead to climate injustice as the poor, globally, bear the brunt of the impacts. Despite this 'Rosetta Stone' translating science to language, we have failed to act collectively. One area where ERL can advance the overall conversation is on this science/action interface. As AR5 emerges, the climate change/climate response interface will need deep, substantive, action that responds rapidly to new ideas and opportunities. The rapid publication and open access features of ERL are particularly critical here as events a such as Hurricane Sandy, economic or political advances in climate response made by cities, regions or nations, all warrant assessment and response. This is one of many areas where ERL has been at the forefront of the conversation, through not only research letters, but also commentary-style Perspective pieces and the conversation that ERL's sister community website environmentalresearchweb can facilitate. This process of translating proposed solutions—innovations—between interest groups, has been in far too short supply recently. One promising example has been the science/action dialog between a leading climate research center and the World Bank [2]. 'The Earth system's responses to climate change appear to be non-linear', points out Potsdam Institute for Climate Impact Research (PIK) Director, John Schellnhuber. 'If we venture far beyond the 2° guardrail, towards the 4° line, the risk of crossing tipping points rises sharply. The only way to avoid this is to break the business-as-usual pattern of production and consumption'. This assessment came in a report on climate science commissioned by the World Bank. Dr Jim Yong Kim, president of the World Bank noted succinctly and critically that: '... most importantly, a 4 °C world is so different from the current one that it comes with high uncertainty and new risks that threaten our ability to anticipate and plan for future adaptation needs.' This statement warrants careful discussion. Not only is World Bank President Kim affirming the results of the PIK study, and by direct extension the IPCC (because the same authors at PIK are also central to the work of the IPCC), but he is clearly noting that while many climate analysts rightly talk about the need to not exceed a 2° temperature increase, the path the world is currently on, namely 4°-6° will be catastrophic. This may come as too soft a statement to many in the scientific community, but it opens the door to an increasingly detailed dialog between climate change science and agencies engaged in action. Where ERL and other outlets for this conversation can play a critical role is in the many dimensions of climate change and response. The story is far from one only at the global level. As http://climatehotmap.org and many other location specific assessments detail, the environmental change story is playing out in millions of critical cases. Each warrants reporting and action, as well as integration with assessments of current data gathering and 'big data' needs, and with wider socioeconomic questions of effective political, and policy response. Through that, dialog papers in ERL will be critically important to advancing not only climate science, but the interactive dialog between knowledge and action. References [1] Hansen J, Sato M and Ruedy R 2012 Perception of climate change Proc. Natl Acad. Sci. USA 109 E2415-23 [2] Potsdam Institute for Climate Impact 2013 Turn Down the Heat: Why a 4 °C Warmer World Must be Avoided (Washington, DC: The World Bank) 1 The Kyoto Protocol was adopted on 11 December 1997 in Kyoto, Japan, and entered into force on 16 February 2005. As of September 2011, 191 states have signed and ratified the protocol. The United States signed but did not ratify the Protocol and Canada withdrew from it in 2011.

Traceable accounts of subjective probability judgments in the IPCC and beyond

NASA Astrophysics Data System (ADS)

Baer, P. G.

2012-12-01

One of the major sources of controversy surrounding the reports of the IPCC has been the characterization of uncertainty. Although arguably the IPCC has paid more attention to the process of uncertainty analysis and communication than any comparable assessment body, its efforts to achieve consistency have produced mixed results. In particular, the extensive use of subjective probability assessment has attracted widespread criticism. Statements such as "Average Northern Hemisphere temperatures during the second half of the 20th century were very likely higher than during any other 50-year period in the last 500 years" are ubiquitous (one online database lists nearly 3000 such claims), and indeed are the primary way in which its key "findings" are reported. Much attention is drawn to the precise quantitative definition of such statements (e.g., "very likely" means >90% probability, vs. "extremely likely" which means >95% certainty). But there is no process by which the decision regarding the choice of such uncertainty level for a given finding is formally made or reported, and thus they are easily by disputed by anyone, expert or otherwise, who disagrees with the assessment. In the "Uncertainty Guidance Paper" for the Third Assessment Report, Richard Moss and Steve Schneider defined the concept of a "traceable account," which gave exhaustive detail regarding how one ought to provide documentation of such an uncertainty assessment. But the guidance, while appearing straightforward and reasonable, in fact was an unworkable recipe, which would have taken near-infinite time if used for more than a few key results, and would have required a different structuring of the text than the conventional scientific assessment. And even then it would have left a gap when it came to the actual provenance of any such specific judgments, because there simply is no formal step at which individuals turn their knowledge of the evidence on some finding into a probability judgment. The Uncertainty Guidance Papers for the TAR and subsequent assessments have left open the possibility of using such an expert elicitation within the IPCC drafting process, but to my knowledge it has never been done. Were it in fact attempted, it would reveal the inconvenient truth that there is no uniquely correct method for aggregating probability statements; indeed the standard practice within climate-related expert elicitations has been to report all individual estimates without aggregation. But if a report requires a single "consensus estimate," once you have even a single divergent opinion, the question of how to aggregate becomes unavoidable. In this paper, I review in greater detail the match or lack of it between the vision of a "traceable account" and IPCC practice, and the public discussion of selected examples of probabilistic judgments in AR4. I propose elements of a structure based on a flexible software architecture that could facilitate the development and documentation of what I call "collective subjective probability." Using a simple prototype and a pair of sample "findings" from AR4, I demonstrate an example of how such a structure could be used by a small expert community to implement a practical model of a "traceable account." I conclude with as discussion of the prospects of using such modular elicitations in support of, or as an alternative to, conventional IPCC assessment processes.

Future Projections of Air Temperature and Precipitation for the CORDEX-MENA Domain by Using RegCM4.3.5

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

2015-04-01

In this study, the projected changes for the periods of 2016 - 2035, 2046 - 2065, and 2081 - 2100 in the seasonal averages of air temperature and precipitation variables with respect to the reference period of 1981 - 2000 were examined for the Middle East and North Africa region. In this context, Regional Climate Model (RegCM4.3.5) of ICTP (International Centre for Theoretical Physics) was run by using two different global climate models. MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology and HadGEM2 of the Met Office Hadley Centre were dynamically downscaled to 50 km for the CORDEX-MENA domain. The projections were realized according to the RCP4.5 and the RCP8.5 emission scenarios of the IPCC (Intergovernmental Panel of Climate Change).

Crop response to climate: ecophysical models

USDA-ARS?s Scientific Manuscript database

Ecophysiological models were the dominant tools used to estimate the potential impact of climate change in agroecosystems in the Third and Fourth Assessment Reports of the IPCC and are widely used elsewhere in climate change research. These models, also known as “crop models” or “simulation models”,...

A carbon cycle science update since IPCC AR-4.

PubMed

Dolman, A J; van der Werf, G R; van der Molen, M K; Ganssen, G; Erisman, J-W; Strengers, B

2010-01-01

We review important advances in our understanding of the global carbon cycle since the publication of the IPCC AR4. We conclude that: the anthropogenic emissions of CO2 due to fossil fuel burning have increased up through 2008 at a rate near to the high end of the IPCC emission scenarios; there are contradictory analyses whether an increase in atmospheric fraction, that might indicate a declining sink strength of ocean and/or land, exists; methane emissions are increasing, possibly through enhanced natural emission from northern wetland, methane emissions from dry plants are negligible; old-growth forest take up more carbon than expected from ecological equilibrium reasoning; tropical forest also take up more carbon than previously thought, however, for the global budget to balance, this would imply a smaller uptake in the northern forest; the exchange fluxes between the atmosphere and ocean are increasingly better understood and bottom up and observation-based top down estimates are getting closer to each other; the North Atlantic and Southern ocean take up less CO2, but it is unclear whether this is part of the 'natural' decadal scale variability; large-scale fires and droughts, for instance in Amazonia, but also at Northern latitudes, have lead to significant decreases in carbon uptake on annual timescales; the extra uptake of CO2 stimulated by increased N-deposition is, from a greenhouse gas forcing perspective, counterbalanced by the related additional N2O emissions; the amount of carbon stored in permafrost areas appears much (two times) larger than previously thought; preservation of existing marine ecosystems could require a CO2 stabilization as low as 450 ppm; Dynamic Vegetation Models show a wide divergence for future carbon trajectories, uncertainty in the process description, lack of understanding of the CO2 fertilization effect and nitrogen-carbon interaction are major uncertainties.

SciDAC's Earth System Grid Center for Enabling Technologies Semiannual Progress Report October 1, 2010 through March 31, 2011

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

Williams, Dean N.

2011-04-02

This report summarizes work carried out by the Earth System Grid Center for Enabling Technologies (ESG-CET) from October 1, 2010 through March 31, 2011. It discusses ESG-CET highlights for the reporting period, overall progress, period goals, and collaborations, and lists papers and presentations. To learn more about our project and to find previous reports, please visit the ESG-CET Web sites: http://esg-pcmdi.llnl.gov/ and/or https://wiki.ucar.edu/display/esgcet/Home. This report will be forwarded to managers in the Department of Energy (DOE) Scientific Discovery through Advanced Computing (SciDAC) program and the Office of Biological and Environmental Research (OBER), as well as national and international collaborators andmore » stakeholders (e.g., those involved in the Coupled Model Intercomparison Project, phase 5 (CMIP5) for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5); the Community Earth System Model (CESM); the Climate Science Computational End Station (CCES); SciDAC II: A Scalable and Extensible Earth System Model for Climate Change Science; the North American Regional Climate Change Assessment Program (NARCCAP); the Atmospheric Radiation Measurement (ARM) program; the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA)), and also to researchers working on a variety of other climate model and observation evaluation activities. The ESG-CET executive committee consists of Dean N. Williams, Lawrence Livermore National Laboratory (LLNL); Ian Foster, Argonne National Laboratory (ANL); and Don Middleton, National Center for Atmospheric Research (NCAR). The ESG-CET team is a group of researchers and scientists with diverse domain knowledge, whose home institutions include eight laboratories and two universities: ANL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), LLNL, NASA/Jet Propulsion Laboratory (JPL), NCAR, Oak Ridge National Laboratory (ORNL), Pacific Marine Environmental Laboratory (PMEL)/NOAA, Rensselaer Polytechnic Institute (RPI), and University of Southern California, Information Sciences Institute (USC/ISI). All ESG-CET work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Through the ESG project, the ESG-CET team has developed and delivered a production environment for climate data from multiple climate model sources (e.g., CMIP (IPCC), CESM, ocean model data (e.g., Parallel Ocean Program), observation data (e.g., Atmospheric Infrared Sounder, Microwave Limb Sounder), and analysis and visualization tools) that serves a worldwide climate research community. Data holdings are distributed across multiple sites including LANL, LBNL, LLNL, NCAR, and ORNL as well as unfunded partners sites such as the Australian National University (ANU) National Computational Infrastructure (NCI), the British Atmospheric Data Center (BADC), the Geophysical Fluid Dynamics Laboratory/NOAA, the Max Planck Institute for Meteorology (MPI-M), the German Climate Computing Centre (DKRZ), and NASA/JPL. As we transition from development activities to production and operations, the ESG-CET team is tasked with making data available to all users who want to understand it, process it, extract value from it, visualize it, and/or communicate it to others. This ongoing effort is extremely large and complex, but it will be incredibly valuable for building 'science gateways' to critical climate resources (such as CESM, CMIP5, ARM, NARCCAP, Atmospheric Infrared Sounder (AIRS), etc.) for processing the next IPCC assessment report. Continued ESG progress will result in a production-scale system that will empower scientists to attempt new and exciting data exchanges, which could ultimately lead to breakthrough climate science discoveries.« less

Application of empirical and dynamical closure methods to simple climate models

NASA Astrophysics Data System (ADS)

Padilla, Lauren Elizabeth

This dissertation applies empirically- and physically-based methods for closure of uncertain parameters and processes to three model systems that lie on the simple end of climate model complexity. Each model isolates one of three sources of closure uncertainty: uncertain observational data, large dimension, and wide ranging length scales. They serve as efficient test systems toward extension of the methods to more realistic climate models. The empirical approach uses the Unscented Kalman Filter (UKF) to estimate the transient climate sensitivity (TCS) parameter in a globally-averaged energy balance model. Uncertainty in climate forcing and historical temperature make TCS difficult to determine. A range of probabilistic estimates of TCS computed for various assumptions about past forcing and natural variability corroborate ranges reported in the IPCC AR4 found by different means. Also computed are estimates of how quickly uncertainty in TCS may be expected to diminish in the future as additional observations become available. For higher system dimensions the UKF approach may become prohibitively expensive. A modified UKF algorithm is developed in which the error covariance is represented by a reduced-rank approximation, substantially reducing the number of model evaluations required to provide probability densities for unknown parameters. The method estimates the state and parameters of an abstract atmospheric model, known as Lorenz 96, with accuracy close to that of a full-order UKF for 30-60% rank reduction. The physical approach to closure uses the Multiscale Modeling Framework (MMF) to demonstrate closure of small-scale, nonlinear processes that would not be resolved directly in climate models. A one-dimensional, abstract test model with a broad spatial spectrum is developed. The test model couples the Kuramoto-Sivashinsky equation to a transport equation that includes cloud formation and precipitation-like processes. In the test model, three main sources of MMF error are evaluated independently. Loss of nonlinear multi-scale interactions and periodic boundary conditions in closure models were dominant sources of error. Using a reduced order modeling approach to maximize energy content allowed reduction of the closure model dimension up to 75% without loss in accuracy. MMF and a comparable alternative model peformed equally well compared to direct numerical simulation.

Observation of Wetland Dynamics with Global Navigation Satellite Signals Reflectometry

NASA Astrophysics Data System (ADS)

Zuffada, C.; Shah, R.; Nghiem, S. V.; Cardellach, E.; Chew, C. C.

2015-12-01

Wetland dynamics is crucial to changes in both atmospheric methane and terrestrial water storage. The Intergovernmental Panel on Climate Change's Fifth Assessment Report (IPCC AR5) highlights the role of wetlands as a key driver of methane (CH4) emission, which is more than one order of magnitude stronger than carbon dioxide as a greenhouse gas in the centennial time scale. Among the multitude of methane emission sources (hydrates, livestock, rice cultivation, freshwaters, landfills and waste, fossil fuels, biomass burning, termites, geological sources, and soil oxidation), wetlands constitute the largest contributor with the widest uncertainty range of 177-284 Tg(CH4) yr-1 according to the IPCC estimate. Wetlands are highly susceptible to climate change that might lead to wetland collapse. Such wetland destruction would decrease the terrestrial water storage capacity and thus contribute to sea level rise, consequently exacerbating coastal flooding problems. For both methane change and water storage change, wetland dynamics is a crucial factor with the largest uncertainty. Nevertheless, a complete and consistent map of global wetlands still needs to be obtained as the Ramsar Convention calls for a wetlands inventory and impact assessment. We develop a new method for observations of wetland change using Global Navigation Satellite Signals Reflectometry (GNSS-R) signatures for global wetland mapping in synergy with the existing capability, not only as a static inventory but also as a temporal dataset, to advance the capability for monitoring the dynamics of wetland extent relevant to addressing the science issues of CH4 emission change and terrestrial water storage change. We will demonstrate the capability of the new GNSS-R method over a rice field in the Ebro Delta wetland in Spain.

Analyses of Projected Changes in Climate for Sub-Saharan Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J.; Engelbrecht, F.; Vezhapparambu, S.

2012-12-01

The conformal-cubic atmospheric model (CCAM) is employed in this study as a flexible downscaling tool at the climate-change time scale. In the downscaling procedure, the sea-ice and bias-corrected SSTs of 6 CGCMs (CSIRO Mk 3.5, GFDL2.1, GFDL2.0, HadCM2, ECHAM5 and Miroc-Medres) from AR4 of the IPCC were first used as lower-boundary forcing in CCAM simulations performed at a quasi-uniform resolution (about 200 km in the horizontal), which were subsequently downscaled to a resolution of about 60 km over southern and tropical Africa. All the simulations were for the A2 scenario of the Special Report on Emission Scenarios (SRES), and for the period 1961-2100. The SST biases were derived by comparing the simulated and observed present-day climatol¬ogy of SSTs for 1979-1999 for each month of the year; the same monthly bias corrections were applied for the duration of the simulations. CCAM ensemble projected change in annual average temperature and Rainfall for 2071-2100 vs 1961-1990 for tropical Africa will be presented and discussed. In summary, a robust signal of drastic increases in surface temperature (more than 3 degrees C for the period 2071-2100 relative to 1961-1990) is projected across the domain. Temperature increases as large as 5 degrees C are projected over the subtropical regions in the north of the domain. Increase in rainfall over tropical Africa (for the period 2071-2100 relative to 1961-1990) is projected across the domain. This is consistent with an increase in moisture in a generally warmer atmosphere. There is a robust signal of drying along the West African coast - however, the CMIP3 CGCM projections indicate a wide range of possible rainfall futures over this region The projections of East Africa becoming wetter is robust across the CCAM ensemble, consistent with the CGCM projections of CMIP3 and AR4.

Detection and Attribution of Anthropogenic Climate Change Impacts

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Neofotis, Peter

2013-01-01

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

Assessment of NASA GISS CMIP5 ModelE simulated clouds and TOA radiation budgets using satellite observations over the southern mid-latitudes

NASA Astrophysics Data System (ADS)

Stanfield, Ryan Evan

Past, current, and future climates have been simulated by the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) ModelE Global Circulation Model (GCM) and summarized by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, AR4). New simulations from the updated CMIP5 version of the NASA GISS ModelE GCM were recently released to the public community during the summer of 2011 and will be included in the upcoming IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, they have not yet been extensively validated against observations. To assess the NASA GISS-E2-R GCM, model simulated clouds and cloud properties are compared to observational cloud properties derived from the Clouds and Earth's Radiant Energy System (CERES) project using MODerate Resolution Imaging Spectroradiometer (MODIS) data for the period of March 2000 through December 2005. Over the 6-year period, the global average modeled cloud fractions are within 1% of observations. However, further study however shows large regional biases between the GCM simulations and CERES-MODIS observations. The southern mid-latitudes (SML) were chosen as a focus region due to model errors across multiple GCMs within the recent phase 5 of the Coupled Model Intercomparison Project (CMIP5). Over the SML, the GISS GCM undersimulates total cloud fraction over 20%, but oversimulates total water path by 2 g m-2. Simulated vertical cloud distributions over the SML when compared to both CERES-MODIS and CloudSat/CALIPSO observations show a drastic undersimulation of low level clouds by the GISS GCM, but higher fractions of thicker clouds. To assess the impact of GISS simulated clouds on the TOA radiation budgets, the modeled TOA radiation budgets are compared to CERES EBAF observations. Because modeled low-level cloud fraction is much lower than observed over the SML, modeled reflected shortwave (SW) flux at the TOA is 13 W m -2 lower and outgoing longwave radiation (OLR) is 3 W m-2 higher than observations. Finally, cloud radiative effects (CRE) are calculated and compared with observations to fully assess the impact of clouds on the TOA radiation budgets. The difference in clear-sky reflected SW flux between model and observation is only +4 W m-2 while the SW CRE difference is up to 17 W m-2, indicating that most of the bias in SW CRE results from the all-sky bias between the model and observation. A sizeable negative bias of 10 W m-2 in simulated clear-sky OLR has been found due to a dry bias in calculating observed clear-sky OLR and lack of upper-level water vapor at the 100-mb level in the model. The dry bias impacts CRE LW, with the model undersimulating by 13 W m-2. The CRE NET difference is only 5 W m-2 due to the cancellation of SW and LW CRE biases.

Global outlook for wood and forests with the bioenergy demand implied by scenarios of the intergovernmental panel on climate change

Treesearch

Ronald Raunikar; Joseph Buongiorno; James A. Turner; Shushuai Zhu

2010-01-01

The Global Forest Products Model (GFPM) was modified to link the forest sector to two scenarios of the Intergovernmental Panel on Climate Change (IPCC), and to represent the utilization of fuelwood and industrial roundwood to produce biofuels. The scenarios examined were a subset of the “story lines” prepared by the IPCC. Each scenario has projections of population and...

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Cheng, Ye

2013-01-01

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

Estimating national landfill methane emissions: an application of the 2006 Intergovernmental Panel on Climate Change Waste Model in Panama.

PubMed

Weitz, Melissa; Coburn, Jeffrey B; Salinas, Edgar

2008-05-01

This paper estimates national methane emissions from solid waste disposal sites in Panama over the time period 1990-2020 using both the 2006 Intergovernmental Panel on Climate Change (IPCC) Waste Model spreadsheet and the default emissions estimate approach presented in the 1996 IPCC Good Practice Guidelines. The IPCC Waste Model has the ability to calculate emissions from a variety of solid waste disposal site types, taking into account country- or region-specific waste composition and climate information, and can be used with a limited amount of data. Countries with detailed data can also run the model with country-specific values. The paper discusses methane emissions from solid waste disposal; explains the differences between the two methodologies in terms of data needs, assumptions, and results; describes solid waste disposal circumstances in Panama; and presents the results of this analysis. It also demonstrates the Waste Model's ability to incorporate landfill gas recovery data and to make projections. The former default method methane emissions estimates are 25 Gg in 1994, and range from 23.1 Gg in 1990 to a projected 37.5 Gg in 2020. The Waste Model estimates are 26.7 Gg in 1994, ranging from 24.6 Gg in 1990 to 41.6 Gg in 2020. Emissions estimates for Panama produced by the new model were, on average, 8% higher than estimates produced by the former default methodology. The increased estimate can be attributed to the inclusion of all solid waste disposal in Panama (as opposed to only disposal in managed landfills), but the increase was offset somewhat by the different default factors and regional waste values between the 1996 and 2006 IPCC guidelines, and the use of the first-order decay model with a time delay for waste degradation in the IPCC Waste Model.

75 FR 3516 - Invitation for Recommendations for U.S. Authors and Reviewers to the Fifth Assessment Report of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-21

... Reviewers to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) ACTION... Intergovernmental Panel on Climate Change (IPCC). SUMMARY: The U.S. Department of State invites recommendations for... Intergovernmental Panel on Climate Change (IPCC), which will be developed and finalized over the coming four years...

Climate sensitivity uncertainty: when is good news bad?

PubMed

Freeman, Mark C; Wagner, Gernot; Zeckhauser, Richard J

2015-11-28

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity--how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the 'likely' range has been 1.5-4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2-4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the 'best estimate'. We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: when might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal well-being? The lowered bottom value also implies higher uncertainty about the temperature increase, definitely bad news. Under reasonable assumptions, both the lowering of the lower bound and the removal of the 'best estimate' may well be bad news. © 2015 The Author(s).

Investigation of polar mesocyclones in Arctic Ocean using COSMO-CLM and WRF numerical models and remote sensing data

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Verezemskaya, Polina; Baranyuk, Anastasia; Zabolotskikh, Elizaveta; Repina, Irina

2015-04-01

Polar lows (PL), high latitude marine mesoscale cyclones, are an enigmatic atmospheric phenomenon, which could result in windstorm damage of shipping and infrastructure in high latitudes. Because of their small spatial scales, short life times and their tendency to develop in remote data sparse regions (Zahn, Strorch, 2008), our knowledge of their behavior and climatology lags behind that of synoptic-scale cyclones. In case of continuing global warming (IPCC, 2013) and prospects of the intensification of economic activity and marine traffic in Arctic region, the problem of relevant simulation of this phenomenon by numerical models of the atmosphere, which could be used for weather and climate prediction, is especially important. The focus of this paper is researching the ability to simulate polar lows by two modern nonhydrostatic mesoscale numerical models, driven by realistic lateral boundary conditions from ERA-Interim reanalysis: regional climate model COSMO-CLM (Böhm et. al., 2009) and weather prediction and research model (WRF). Fields of wind, pressure and cloudiness, simulated by models, were compared with remote sensing data and ground meteorological observations for several cases, when polar lows were observed, in Norwegian, Kara and Laptev seas. Several types of satellite data were used: atmospheric water vapor, cloud liquid water content and surface wind fields were resampled by examining AMSR-E and AMSR-2 microwave radiometer data (MODIS Aqua, GCOM-W1), and wind fields were additionally extracted from QuickSCAT scatterometer. Infrared and visible pictures of cloud cover were obtained from MODIS (Aqua). Completed comparison shown that COSMO-CLM and WRF models could successfully reproduce evolution of polar lows and their most important characteristics such as size and wind speed in short experiments with WRF model and longer (up to half-year) experiments with COSMO-CLM model. Improvement of the quality of polar lows reproduction by these models in relation to source reanalysis fields were investigated. References: 1. Böhm U. et al. CLM - the climate version of LM: Brief description and long-term applications [Journal] // COSMO Newsletter. - 2006. - Vol. 6. 2. IPCC Fifth Assessment Report: Climate Change 2013 (AR5) Rep.,Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 3. Zahn, M., and H. von Storch (2008), A long-term climatology of North Atlantic polar lows, Geophys. Res. Lett., 35, L22702

Modelling Impacts of Climate Change: Case Studies using the New Generation of Erosion Models

USDA-ARS?s Scientific Manuscript database

Climate change is expected to impact upon a number of soil erosion drivers and processes, which should be taken into account when designing a modelling strategy. The fourth assessment report of the Intergovernmental Panel for Climate Change (IPCC) (Parry et al., 2007; Solomon et al., 2007) reviews a...

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

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

Fan, Tianyi; Liu, Xiaohong; Ma, Po -Lun

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results aremore » compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2, respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.« less

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

DOE PAGES

Fan, Tianyi; Liu, Xiaohong; Ma, Po -Lun; ...

2018-02-01

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results aremore » compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2, respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.« less

Effects of Regional Climate Change on the Wave Conditions in the Western Baltic Sea

NASA Astrophysics Data System (ADS)

Dreier, N.; Fröhle, P.

2017-12-01

The local wave climate in the Western Baltic Sea is mainly generated by the local wind field over the area. Long-term changes of the local wind conditions that are induced e.g. by regional climate change, directly affect the local wave climate and other local wind driven coastal processes like e.g. the longshore sediment transport. The changes of the local wave climate play an important role for the safe functional and structural design of new, or the adaption of existing, coastal protection structures as well as for the assessment of long-term morphological changes of the coastline. In this study, the wave model SWAN is used for the calculation of hourly wave conditions in the Western Baltic Sea between 1960 and 2100. Future wind conditions from two regional climate models (Cosmo-CLM and REMO) that have been forced by different future greenhouse gas emission scenarios used within AR4 (A1B, B1) and AR5 (RCP4.5 and RCP8.5) of IPCC are used as input for the wave model. The changes of the average wave conditions are analyzed from comparisons between the 30 years averages for the future (e.g. 2071-2100) and the reference period 1971-2000. Regarding the emission scenarios A1B and B1, a significant change of the 30 years averages of significant wave height at westerly wind exposed locations with predominant higher values up to +10% is found (cf. Fig. 1). In contrast, the change of the 30 years averages of significant wave height is more weak at easterly wind exposed locations, resulting in higher and lower values between -5% to +5%. Moreover, more wave events from W-NW and fewer events from N-NE can be expected, due to changes of the frequency of occurrence of the 30 years averages of mean wave direction. The changes of extreme wave heights are analyzed based on methods of extreme value analysis and the time series of wave parameters at selected locations nearby the German Baltic Sea coast. No robust changes of the significant wave heights with a return period of 200 years are found for the emission scenarios A1B and B1. Both increases and decreases of the extreme wave heights are possible within a range of -18% to +18% (-0.5m to +0.5m). In the presentation, we will show results from the assessment of the changes of the wave conditions for the emission scenarios RCP4.5 and RCP8.5 and discuss possible impacts for the German Baltic Sea coast.

Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.

A CMIP5 Ensemble Assessment of Climate Change Impact on Durum Wheat Production in North Dakota, USA

NASA Astrophysics Data System (ADS)

Dillon, T. D.; Kirilenko, A.

2016-12-01

North Dakota is the main US and one of the world's leading producers of durum wheat (Triticum durum), the hardest wheat variety with high protein content, used in multiple food products. We investigated potential change in durum wheat production in connection with climate change. The study accounted for variations in environmental conditions by running a dynamic wheat yield model in thirteen climatically different regions of the state. North Dakota climate is representative of highly productive agricultural lands of the Northern Great Plains, which encompass five US states and two Canadian provinces. Eastern part of North Dakota has humid continental climate while the western past is semi-desert with distinct west-to east precipitation gradient. Low mean average temperatures (cir. +4C), and high temperature variability lead to relatively short growing season (cir. 130 days). Combined with limited rainfall (cir. 350 mm in the East and 560 mm in the West), it makes agriculture highly dependent on temperature and precipitation. Accordingly, climate change has high potential impact on crop production in the region. We used the ALMANAC crop growth model to simulate the production of durum wheat. Model performance was estimated by comparison of simulated yields with historical observations; and was found satisfactory (RMSE < 1.00 T/ha*yr). To account for uncertainty in projected future climate, we used an ensemble of 17 CMIP5 GCMs run under four IPCC AR5 RCP scenarios, for two time periods characteristic of the 2040s and the 2070s. GCM output data were further downscaled using MarkSim weather generator. We found statistically significant reductions in mean yields in 96% of model runs for both time periods (t-test for independent samples; p<.05). In 2040s climate, yield decrease varied from 17% for RCP 2.6 to 45% for RCP 8.5; in 2070s climate - from 35% for RCP2.6 to 73% for RCP 8.5. Further research will concentrate on crop fail risk analysis and geographical heterogeneity of simulated changes.

Climate Vulnerability of Hydro-power infrastructure in the Eastern African Power Pool

NASA Astrophysics Data System (ADS)

Sridharan, Vignesh

2017-04-01

At present there is around 6000 MW of installed hydropower capacity in the Eastern African power pool (EAPP)[1]. With countries aggressively planning to achieve the Sustainable development goal (SDG) of ensuring access to affordable electricity for all, a three-fold increase in hydropower capacity is expected by 2040 [1]. Most of the existing and planned infrastructure lie inside the Nile River Basin. The latest assessment report (AR 5) from the Intergovernmental Panel on Climate Change (IPCC) indicates a high level of climatic uncertainty in the Nile Basin. The Climate Moisture index (CMI) for the Eastern Nile region and the Nile Equatorial lakes varies significantly across the different General Circulation Models (GCM)[2]. Such high uncertainty casts a shadow on the plans to expand hydropower capacity, doubting whether hydropower expansion can contribute to the goal of improving access to electricity or end up as sunk investments. In this assessment, we analyze adaptation strategies for national energy systems in the Eastern African Power Pool (EAPP), which minimize the regret that could potentially arise from impacts of a changed climate. An energy systems model of the EAPP is developed representing national electricity supply infrastructure. Cross border transmission and hydropower infrastructure is defined at individual project level. The energy systems model is coupled with a water systems management model of the Nile River Basin that calculates the water availability at different hydropower infrastructures under a range of climate scenarios. The results suggest that a robust adaptation strategy consisting of investments in cross border electricity transmission infrastructure and diversifying sources of electricity supply will require additional investments of USD 4.2 billion by 2050. However, this leads to fuel and operational cost savings of up to USD 22.6 billion, depending on the climate scenario. [1] "Platts, 2016. World Electric Power Plants Database," World Electric Power Plants Database. [Online]. Available: http://www.platts.com/Products/worldelectricpowerplantsdatabase. [Accessed: 01-Mar-2016]. [2] Brent Boehlert, Kenneth M. Strzepek, David Groves, and Bruce Hewitson, Chris Jack, "Climate Change Projections in Africa-Chapter 3," in Enhancing the Climate Resilience of Africa's Infrastructure : The Power and Water Sectors, Washington DC: The World Bank, 2016, p. 219.

Long-term climate change commitment and reversibility: An EMIC intercomparison

NASA Astrophysics Data System (ADS)

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

2012-12-01

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to: (i) quantify the climate change "commitment" of a range of radiative forcing trajectories, and (ii) explore the extent to which climate change is reversible if atmospheric CO2 is left to evolve freely or is artificially restored to pre-industrial levels. All commitment simulations follow the four Representative Concentration Pathways (RCPs) and their extensions to 2300. Most EMICs simulate significant surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The additional warming by the year 3000 is 0.0-0.6 °C for RCP4.5 and 0.0-1.2 °C for RCP8.5, and the additional sea level rise is 0.1-1.0 m for RCP4.5 and 0.4-2.6 m for RCP8.5. Elimination of anthropogenic CO2 emissions results in constant or slightly decreasing surface air temperature in all EMICs. Thermosteric sea level rise continues after elimination of anthropogenic CO2 emissions, with additional sea level rise between 2300 and 3000 of 0.0-0.5 m for RCP4.5 and 0.2-2.4 m for RCP8.5. The largest warming and sea level rise commitment are simulated for the case with constant year-2300 CO2 emissions. Restoration of atmospheric CO2 from RCP to pre-industrial levels over 100-1000 years does not result in the simultaneous return to pre-industrial climate conditions, as surface air temperature and sea level rise exhibit a substantial time lag relative to atmospheric CO2, and requires large artificial removal of CO2 from the atmosphere. Results of the climate change commitment and reversibility simulations differ widely among EMICs, both in the physical and biogeochemical response. Particularly large differences are identified in the response of the terrestrial carbon cycle to atmospheric CO2 and climate, highlighting the need for improved understanding and representation of land carbon cycle processes in Earth System models.

Implications of global warming for regional climate and water resources of tropical islands: Case studies over Sri Lanka and Puerto Rico

NASA Astrophysics Data System (ADS)

Mawalagedara, R.; Kumar, D.; Oglesby, R. J.; Ganguly, A. R.

2013-12-01

The IPCC AR4 identifies small islands as particularly vulnerable to climate change. Here we consider the cases of two tropical islands: Sri Lanka in the Indian Ocean and Puerto Rico in the Caribbean. The islands share a predominantly tropical climate with diverse topography and hence significant spatial variability of regional climate. Seasonal variability in temperatures is relatively small, but spatial variations can be large owing to topography. Precipitation mechanisms and patterns over the two islands are different however. Sri Lanka receives a majority of the annual rainfall from the summer and winter monsoons, with convective rainfall dominating in the inter-monsoon period. Rainfall generating mechanisms over Puerto Rico can range from orographic lifting, disturbances embedded in Easterly waves and synoptic frontal systems. Here we compare the projected changes in the regional and seasonal means and extremes of temperature and precipitation over the two islands during the middle of this century with the present conditions. Two 5-year regional climate model runs for each region, representing the present (2006-2010) and future (2056-2060) conditions, are performed using the Weather Research and Forecasting model with the lateral boundary conditions provided using the output from CCSM4 RCP8.5 greenhouse gas emissions pathway simulation from the CMIP5 ensemble. The consequences of global warming for water resources and the overall economy are examined. While both economies have substantial contributions from tourism, there are major differences: The agricultural sector is much more important over Sri Lanka compared to Puerto Rico, while the latter exhibits no recent growth in population or in urbanization trends unlike the former. Policy implications for water sustainability and security are discussed, which highlight how despite the differences, certain lessons learned may generalize across the two relatively small tropical islands, which in turn have diverse economic, infrastructural, and societal constraints.

a Brazilian Vulnerability Index to Natural Disasters of Drought - in the Context of Climate Change

NASA Astrophysics Data System (ADS)

Camarinha, P. I., Sr.; Debortoli, N. S.; Hirota, M.

2015-12-01

Droughts are characterized as one of the main types of natural disasters that occur in Brazil. During the 1991-2012, droughts affected more than 14 million Brazilians, so that the concern for the following decades is about the potential impacts triggered by climate change. To analyze the vulnerability of the Brazilian municipalities to drought disasters, we have assessed the effects of climate change to droughts until the end of 21th century. A composite index was created based on three different dimensions: i) Exposure, represented by climate anomalies related to the drought process, such as changes in accumulated rainfall averages, interannual variability of rainfall, and the frequency and magnitude of severe droughts (measured by the Standardized Precipitation-Evapotranspiration Index); ii) Sensitivity, encompassing socioeconomic, demographic, land use and water management data; iii) Adaptive Capacity, consisting of socioeconomic and institutional data from Brazilian municipalities, such as the Human Development Index (HDI), social inequality (Gini index) and illiteracy rate. The climate variables used in this study are results from simulations of the Regional Climate Model Eta (with a downscaling of 20km spatial resolution) nested with two global climate models (HadGEM ES and MIROC 5) and was provided by National Institute for Space Research. The baseline period was 1961-1990 and future periods was 2011-2040; 2041-2070 and 2071-2099. For the simulations of future climate it was used the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. All variables used in this study was handled, exploited and related in a Geographic Information System (GIS). The methodology allowed the identification of vulnerability hotspots, the targeting of adaptation strategies and the development of public policy to minimize the potential impacts of future droughts. The final results (see attached image) indicate that the most vulnerable regions are located in the Midwest, in the northeastern Brazilian semi-arid and also on western Amazon.

South Asian Summer Monsoon and Its Relationship with ENSO in the IPCC AR4 Simulations

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

Annamalai, H; Hamilton, K; Sperber, K R

In this paper we use the extensive integrations produced for the IPCC Fourth Assessment Report (AR4) to examine the relationship between ENSO and the monsoon at interannual and decadal timescales. We begin with an analysis of the monsoon simulation in the 20th century integrations. Six of the 18 models were found to have a reasonably realistic representation of monsoon precipitation climatology. For each of these six models SST and anomalous precipitation evolution along the equatorial Pacific during El Nino events display considerable differences when compared to observations. Out of these six models only four (GFDL{_}CM{_}2.0, GFDL{_}CM{_}2.1, MRI, and MPI{_}ECHAM5) exhibitmore » a robust ENSO-monsoon contemporaneous teleconnection, including the known inverse relationship between ENSO and rainfall variations over India. Lagged correlations between the all-India rainfall (AIR) index and Nino3.4 SST reveal that three models represent the timing of the teleconnection, including the spring predictability barrier which is manifested as the transition from positive to negative correlations prior to the monsoon onset. Furthermore, only one of these three models (GFDL{_}CM{_}2.1) captures the observed phase lag with the strongest anticorrelation of SST peaking 2-3 months after the summer monsoon, which is partially attributable to the intensity of simulated El Nino itself. We find that the models that best capture the ENSO-monsoon teleconnection are those that correctly simulate the timing and location of SST and diabatic heating anomalies in the equatorial Pacific, and the associated changes to the equatorial Walker Circulation during El Nino events. The strength of the AIR-Nino3.4 SST correlation in the model runs waxes and wanes to some degree on decadal timescales. The overall magnitude and timescale for this decadal modulation in most of the models is similar to that seen in observations. However, there is little consistency in the phase among the realizations, suggesting a lack of predictability of the decadal modulation of the monsoon-ENSO relationship. The analysis was repeated for each of the four models using results from integrations in which the atmospheric CO{sub 2} concentration was raised to twice pre-industrial values. From these ''best'' models in the double CO{sub 2} simulations there are increases in both the mean monsoon rainfall over the Indian sub-continent (by 5-25%) and in its interannual variability (5-10%). We find for each model that the ENSO-monsoon correlation in the global warming runs is very similar to that in the 20th century runs, suggesting that the ENSO-monsoon connection will not weaken as global climate warms. This result, though plausible, needs to be taken with some caution because of the diversity in the simulation of ENSO variability in the coupled models we have analyzed. The implication of the present results for monsoon prediction are discussed.« less

Recent and possible future variations in the North American Monsoon

USGS Publications Warehouse

Hoell, Andrew; Funk, Chris; Barlow, Mathew; Shukla, Shraddhanand

2016-01-01

The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.

Temporal Considerations of Carbon Sequestration in LCA

Treesearch

James Salazar; Richard Bergman

2013-01-01

Accounting for carbon sequestration in LCA illustrates the limitations of a single global warming characterization factor. Typical cradle-to-grave LCA models all emissions from end-of-life processes and then characterizes these flows by IPCC GWP (100-yr) factors. A novel method estimates climate change impact by characterizing annual emissions with the IPCC GHG forcing...

IPCC Report Calls Climate Changes Unprecedented

NASA Astrophysics Data System (ADS)

Showstack, Randy

2013-10-01

Warming of the Earth's climate "is unequivocal and since the 1950s many of the observed changes are unprecedented over decades to millennia," according to a new assessment report by the Intergovernmental Panel on Climate Change (IPCC). The 27 September summary for policy makers of IPCC's report "Climate Change 2013: The Physical Science Basis" also states that "it is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century."

Greenhouse gases inventory and carbon balance of two dairy systems obtained from two methane-estimation methods.

PubMed

Cunha, C S; Lopes, N L; Veloso, C M; Jacovine, L A G; Tomich, T R; Pereira, L G R; Marcondes, M I

2016-11-15

The adoption of carbon inventories for dairy farms in tropical countries based on models developed from animals and diets of temperate climates is questionable. Thus, the objectives of this study were to estimate enteric methane (CH4) emissions through the SF6 tracer gas technique and through equations proposed by the Intergovernmental Panel on Climate Change (IPCC) Tier 2 and to calculate the inventory of greenhouse gas (GHG) emissions from two dairy systems. In addition, the carbon balance of these properties was estimated using enteric CH4 emissions obtained using both methodologies. In trial 1, the CH4 emissions were estimated from seven Holstein dairy cattle categories based on the SF6 tracer gas technique and on IPCC equations. The categories used in the study were prepubertal heifers (n=6); pubertal heifers (n=4); pregnant heifers (n=5); high-producing (n=6); medium-producing (n=5); low-producing (n=4) and dry cows (n=5). Enteric methane emission was higher for the category comprising prepubertal heifers when estimated by the equations proposed by the IPCC Tier 2. However, higher CH4 emissions were estimated by the SF6 technique in the categories including medium- and high-producing cows and dry cows. Pubertal heifers, pregnant heifers, and low-producing cows had equal CH4 emissions as estimated by both methods. In trial 2, two dairy farms were monitored for one year to identify all activities that contributed in any way to GHG emissions. The total emission from Farm 1 was 3.21t CO2e/animal/yr, of which 1.63t corresponded to enteric CH4. Farm 2 emitted 3.18t CO2e/animal/yr, with 1.70t of enteric CH4. IPCC estimations can underestimate CH4 emissions from some categories while overestimate others. However, considering the whole property, these discrepancies are offset and we would submit that the equations suggested by the IPCC properly estimate the total CH4 emission and carbon balance of the properties. Thus, the IPCC equations should be utilized with caution, and the herd composition should be analysed at the property level. When the carbon stock in pasture and other crops was considered, the carbon balance suggested that both farms are sustainable for GHG, by both methods. On the other hand, carbon balance without carbon stock, by both methods, suggests that farms emit more carbon than the system is capable of stock. Copyright © 2016 Elsevier B.V. All rights reserved.

Big Data Challenges in Climate Science: Improving the Next-Generation Cyberinfrastructure

NASA Technical Reports Server (NTRS)

Schnase, John L.; Lee, Tsengdar J.; Mattmann, Chris A.; Lynnes, Christopher S.; Cinquini, Luca; Ramirez, Paul M.; Hart, Andre F.; Williams, Dean N.; Waliser, Duane; Rinsland, Pamela;

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The origin of climate changes.

PubMed

Delecluse, P

2008-08-01

Investigation on climate change is coordinated by the Intergovernmental Panel on Climate Change (IPCC), which has the delicate task of collecting recent knowledge on climate change and the related impacts of the observed changes, and then developing a consensus statement from these findings. The IPCC's last review, published at the end of 2007, summarised major findings on the present climate situation. The observations show a clear increase in the temperature of the Earth's surface and the oceans, a reduction in the land snow cover, and melting of the sea ice and glaciers. Numerical modelling combined with statistical analysis has shown that this warming trend is very likely the signature of increasing emissions of greenhouse gases linked with human activities. Given the continuing social and economic development around the world, the IPCC emission scenarios forecast an increasing greenhouse effect, at least until 2050 according to the most optimistic models. The model ensemble predicts a rising temperature that will reach dangerous levels for the biosphere and ecosystems within this century. Hydrological systems and the potential significant impacts of these systems on the environment are also discussed. Facing this challenging future, societies must take measures to reduce emissions and work on adapting to an inexorably changing environment. Present knowledge is sufficientto start taking action, but a stronger foundation is needed to ensure that pertinent long-term choices are made that will meet the demands of an interactive and rapidly evolving world.

Reconstruction of the boundary between climate science and politics: the IPCC in the Japanese mass media, 1988-2007.

PubMed

Asayama, Shinichiro; Ishii, Atsushi

2014-02-01

The Intergovernmental Panel on Climate Change (IPCC) plays a significant role in bridging the boundary between climate science and politics. Media coverage is crucial for understanding how climate science is communicated and embedded in society. This study analyzes the discursive construction of the IPCC in three Japanese newspapers from 1988 to 2007 in terms of the science-politics boundary. The results show media discourses engaged in boundary-work which rhetorically separated science and politics, and constructed the iconic image of the IPCC as a pure scientific authority. In the linkages between the global and national arenas of climate change, the media "domesticate" the issue, translating the global nature of climate change into a discourse that suits the national context. We argue that the Japanese media's boundary-work is part of the media domestication that reconstructed the boundary between climate science and politics reflecting the Japanese context.

Climatic Droughts and the Impacts on Crop Yields in Northern India during the Past Century

NASA Astrophysics Data System (ADS)

Ge, Y.; Cai, X.; Zhu, T.

2014-12-01

Drought has become an increasingly severe threat to water and food security recently. This study presents a novel method to calculate the return period of drought, considering drought as event characterized by expected drought inter-arrival time, duration, severity and peak intensity. Recently, Copula distribution, a multivariable probability distribution, is used to deal with strongly correlated variables in analyzing complex hydrologic phenomenon. This study assesses drought conditions in Northern India, including 8 sites, in the past century using Palmer Drought Severity Index (PDSI) from two latest datasets, Dai (2011, 2013) and Sheffield et al. (2012), which concluded conflicting results about global average drought trend. Our results include the change of the severity, intensity and duration of drought events during the past century and the impact of the drought condition on crop yields in the region. It is found that drought variables are highly correlated, thus copulas joint distribution enables the estimation of multi-variate return period. Based on Dai's dataset from 1900 to 2012, for a fixed drought return period the severity and duration is lower for the period before1955 in sites close to the Indus basin (site 1) or off the coast of the Indian Ocean (Bay of Bengal) (site 8), while they are higher for the period after 1955 in other inland sites (sites 3-7), (e.g., severity in Fig.1). Projections based on two models (IPCC AR4 and AR5) in Dai (2011, 2013) suggested less severity and shorter duration in longer-year drought (e.g., 100-year drought), but larger in shorter-year drought (e.g., 2-year drought). Drought could bring nonlinear responses and unexpected losses in agriculture system, thus prediction and management are essential. Therefore, in the years with extreme drought conditions, impact assessment of drought on crop yield of corn, barley, wheat and sorghum will be also conducted through correlating crop yields with drought conditions during corresponding growing seasons. A. Dai, J. Geophys. Res., 116, D12115 (2011).A. Dai, Nature Climate Change, 3, 52-58 (2013). J. Sheffield, E.F. Wood, M. L. Roderick, Nature, 491, 435-438 (2012) Fig. 1 Return period for severity from 1900 to 1954 (green), from 1955 to 2012 (red), and from 2013 to 2099 (black for AR4, blue for AR5), respectively for 8 sites.

Estimating the Contrail Impact on Climate Using the UK Met Office Model

NASA Astrophysics Data System (ADS)

Rap, A.; Forster, P. M.

2008-12-01

With air travel predicted to increase over the coming century, the emissions associated with air traffic are expected to have a significant warming effect on climate. According to current best estimates, an important contribution comes from contrails. However, as reported by the IPCC fourth assessment report, these current best estimates still have a high uncertainty. The development and validation of contrail parameterizations in global climate models is therefore very important. This current study develops a contrail parameterization within the UK Met Office Climate Model. Using this new parameterization, we estimate that for the 2002 traffic, the global mean annual contrail coverage is approximately 0.11%, a value which in good agreement with several other estimates. The corresponding contrail radiative forcing (RF) is calculated to be approximately 4 and 6 mWm-2 in all-sky and clear-sky conditions, respectively. These values lie within the lower end of the RF range reported by the latest IPCC assessment. The relatively high cloud masking effect on contrails observed by our parameterization compared with other studies is investigated, and a possible cause for this difference is suggested. The effect of the diurnal variations of air traffic on both contrail coverage and contrail RF is also investigated. The new parameterization is also employed in thirty-year slab-ocean model runs in order to give one of the first insights into contrail effects on daily temperature range and the climate impact of contrails.

Simulations show decreasing carbon stocks and potential for carbon emissions in Rocky Mountain forests over the next century.

PubMed

Boisvenue, Céline; Running, Steven W

2010-07-01

Climate change has altered the environment in which forests grow, and climate change models predict more severe alterations to come. Forests have already responded to these changes, and the future temperature and precipitation scenarios are of foremost concern, especially in the mountainous western United States, where forests occur in the dry environments that interface with grasslands. The objective of this study was to understand the trade-offs between temperature and water controls on these forested sites in the context of available climate projections. Three temperature and precipitation scenarios from IPCC AR4 AOGCMs ranging in precipitation levels were input to the process model Biome-BGC for key forested sites in the northern U.S. Rocky Mountains. Despite the omission of natural and human-caused disturbances in our simulations, our results show consequential effects from these conservative future temperature and precipitation scenarios. According to these projections, if future precipitation and temperatures are similar to or drier than the dry scenario depicted here, high-elevation forests on both the drier and wetter sites, which have in the absence of disturbance accumulated carbon, will reduce their carbon accumulation. Under the marginally drier climate projections, most forests became carbon sources by the end of the simulation horizon (2089). Under all three scenarios, growing season lengthened, the number of days with snow on the ground decreased, peak snow occurred earlier, and water stress increased through the projection horizon (1950-2089) for all sites, which represent the temperature and precipitation spectrum of forests in this region. The quantity, form, and timing of precipitation ultimately drive the carbon accumulation trajectory of forests in this region.

Climate change and future land use in the United States: an economic approach

Treesearch

David Haim; Ralph J. Alig; Andrew J. Plantinga; Brent Sohngen

2011-01-01

An econometric land-use model is used to project regional and national land-use changes in the United States under two IPCC emissions scenarios. The key driver of land-use change in the model is county-level measures of net returns to five major land uses. The net returns are modified for the IPCC scenarios according to assumed trends in population and income and...

[The climate debate: the facts].

PubMed

van den Broeke, Michiel R

2009-01-01

The first report by the Intergovernmental Panel on Climate Change (IPCC) appeared almost 20 years ago. Environmental contamination has a negative effect on the environment in which we live. However, the public at large is confused about the ins and outs of climate change. Managers, politicians, various kinds of advisors, scientists, so-called experts, sceptics and journalists have all taken it upon themselves to lead the debate. Whose task is it to ensure a sound discussion? Surely it is the IPCC's task. However, most politicians and many journalists, and even many scientists, do not take the trouble to read the entire IPCC report or parts of it. As a consequence, much nonsense is published and broadcast. An effective procedure to deal with the climate problem starts with a fair discussion of the scientific evidence. My advice is: just read the free IPCC report: http://www.ipcc.ch/ and click on 'WG I The Physical Science Basis'.

Multi-hazard risk assessment of the Republic of Mauritius

NASA Astrophysics Data System (ADS)

Mysiak, Jaroslav; Galli, Alberto; Amadio, Mattia; Teatini, Chiara

2013-04-01

The Republic of Mauritius (ROM) is a small island developing state (SIDS), part of the Mascarene Islands in West Indian Ocean, comprised by Mauritius, Rodrigues, Agalega and St. Brandon islands and several islets. ROM is exposed to many natural hazards notably cyclones, tsunamis, torrential precipitation, landslides, and droughts; and highly vulnerable sea level rise (SLR) driven by human induced climate change. The multihazard risk assessment presented in this paper is aimed at identifying the areas prone to flood, inundation and landslide hazard, and inform the development of strategy for disaster risk reduction (DRR) and climate change adaptation (CCA). Climate risk analysis - a central component of the analysis - is one of the first comprehensive climate modelling studies conducted for the country. Climate change may lift the temperature by 1-2 degree Celsius by 2060-2070, and increase sizably the intensity and frequency of extreme precipitation events. According to the IPCC Forth Assessment Report (AR4), the expected Sea Level Rise (SLR) ranges between 16 and 49 cm. Individually or in combination, the inland flood, coastal inundation and landslide hazards affect large proportion of the country. Sea level rise and the changes in precipitation regimes will amplified existing vulnerabilities and create new ones. The paper outlines an Action plan for Disaster Risk Reduction that takes into account the likely effects of climate change. The Action Plan calls on the government to establish a National Platform for Disaster Risk Reduction as recommended by the Hyogo Framework for Action (HFA) 2005-2015. It consists of nine recommendations which, if put in practice, will significantly reduce the annual damage to natural hazard and produce additional (ancillary) benefits in economic, social and environmental terms.

Impact of Climate Change on Energy Demand in the Midwestern USA

NASA Astrophysics Data System (ADS)

Yan, M. B.; Zhang, F.; Franklin, M.; Kotamarthi, V. R.

2008-12-01

The impact of climate change on energy demand and use is a significant issue for developing future GHG emission scenarios and developing adaptation and mitigation strategies. A number of studies have evaluated the increase in GHG emissions as a result of changes in energy production from fossil fuels, but the consequences of climate change on energy consumption have not been the focus of many studies. Here we focus on the impacts of climate change on energy use at a regional scale using the Midwestern USA as a test. The paper presents results of analyzing energy use in response to ambient temperature changes in a 17-year period from 1989 to 2006 and projection of energy use under future climate scenarios (2010-2061). This study consisted of a two-step procedure. In the first step, sensitivity of historic energy demand, specifically electricity and natural gas in residential and commercial sectors (42% of end-use energy), with respect to many climatic and non-climatic variables was examined. State-specific regression models were developed to quantify the relationship between energy use and climatic variables using degree days. We found that model parameters and base temperatures for estimating heating and cooling days varied by state and energy sector, mainly depending on climate conditions, infrastructure, economic factors, and seasonal change in energy use. In the second step, we applied these models to predict future energy demand using output data generated by the Community Climate System Model (CCSM) for the SRES A1B scenario used in the IPCC AR-4. The annual demands of electricity and natural gas were predicted for each state from 2010 to 2061. The model results indicate that the average annual electricity demand will increase 3%-5% for the southern states and 1%-3% for the northern states in the region by 2061 and that the demand for natural gas is expected to be reduced in all states. A seasonal analysis of energy distribution in response to climate variables identifies a significant peak in demand in July-August (11%-16% in southern states and 6%-10% in the northern states). These findings suggest that the energy sector is vulnerable to climate change even in the northern Midwest region of the US. Furthermore, we demonstrate that a state-level assessment can help to better identify adaptation strategies for future regional energy sector changes.

A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions

NASA Astrophysics Data System (ADS)

Millar, Richard J.; Nicholls, Zebedee R.; Friedlingstein, Pierre; Allen, Myles R.

2017-06-01

Projections of the response to anthropogenic emission scenarios, evaluation of some greenhouse gas metrics, and estimates of the social cost of carbon often require a simple model that links emissions of carbon dioxide (CO2) to atmospheric concentrations and global temperature changes. An essential requirement of such a model is to reproduce typical global surface temperature and atmospheric CO2 responses displayed by more complex Earth system models (ESMs) under a range of emission scenarios, as well as an ability to sample the range of ESM response in a transparent, accessible and reproducible form. Here we adapt the simple model of the Intergovernmental Panel on Climate Change 5th Assessment Report (IPCC AR5) to explicitly represent the state dependence of the CO2 airborne fraction. Our adapted model (FAIR) reproduces the range of behaviour shown in full and intermediate complexity ESMs under several idealised carbon pulse and exponential concentration increase experiments. We find that the inclusion of a linear increase in 100-year integrated airborne fraction with cumulative carbon uptake and global temperature change substantially improves the representation of the response of the climate system to CO2 on a range of timescales and under a range of experimental designs.

Assessment of surface air temperature over the Arctic Ocean in reanalysis and IPCC AR4 model simulations with IABP/POLES observations

NASA Astrophysics Data System (ADS)

Liu, Jiping; Zhang, Zhanhai; Hu, Yongyun; Chen, Liqi; Dai, Yongjiu; Ren, Xiaobo

2008-05-01

The surface air temperature (SAT) over the Arctic Ocean in reanalyses and global climate model simulations was assessed using the International Arctic Buoy Programme/Polar Exchange at the Sea Surface (IABP/POLES) observations for the period 1979-1999. The reanalyses, including the National Centers for Environmental Prediction Reanalysis II (NCEP2) and European Centre for Medium-Range Weather Forecast 40-year Reanalysis (ERA40), show encouraging agreement with the IABP/POLES observations, although some spatiotemporal discrepancies are noteworthy. The reanalyses have warm annual mean biases and underestimate the observed interannual SAT variability in summer. Additionally, NCEP2 shows an excessive warming trend. Most model simulations (coordinated by the International Panel on Climate Change for its Fourth Assessment Report) reproduce the annual mean, seasonal cycle, and trend of the observed SAT reasonably well, particularly the multi-model ensemble mean. However, large discrepancies are found. Some models have the annual mean SAT biases far exceeding the standard deviation of the observed interannul SAT variability and the across-model standard deviation. Spatially, the largest inter-model variance of the annual mean SAT is found over the North Pole, Greenland Sea, Barents Sea and Baffin Bay. Seasonally, a large spread of the simulated SAT among the models is found in winter. The models show interannual variability and decadal trend of various amplitudes, and can not capture the observed dominant SAT mode variability and cooling trend in winter. Further discussions of the possible attributions to the identified SAT errors for some models suggest that the model's performance in the sea ice simulation is an important factor.

Methodologies for simulating impacts of climate change on crop production

USDA-ARS?s Scientific Manuscript database

Ecophysiological models of crop growth have seen wide use in IPCC and related assessments. However, the diversity of modeling approaches constrains cross-study syntheses and increases potential for bias. We reviewed 139 peer-reviewed papers dealing with climate change and agriculture, considering si...

The effect of future outdoor air pollution on human health and the contribution of climate change

NASA Astrophysics Data System (ADS)

Silva, R.; West, J. J.; Lamarque, J.; Shindell, D.; Collins, W.; Dalsoren, S. B.; Faluvegi, G. S.; Folberth, G.; Horowitz, L. W.; Nagashima, T.; Naik, V.; Rumbold, S.; Skeie, R.; Sudo, K.; Takemura, T.; Bergmann, D. J.; Cameron-Smith, P. J.; Cionni, I.; Doherty, R. M.; Eyring, V.; Josse, B.; MacKenzie, I. A.; Plummer, D.; Righi, M.; Stevenson, D. S.; Strode, S. A.; Szopa, S.; Zeng, G.

2013-12-01

At present, exposure to outdoor air pollution from ozone and fine particulate matter (PM2.5) causes over 2 million deaths per year, due to respiratory and cardiovascular diseases and lung cancer. Future ambient concentrations of ozone and PM2.5 will be affected by both air pollutant emissions and climate change. Here we estimate the potential impact of future outdoor air pollution on premature human mortality, and isolate the contribution of future climate change due to its effect on air quality. We use modeled present-day (2000) and future global ozone and PM2.5 concentrations from simulations with an ensemble of chemistry-climate models from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Future air pollution was modeled for global greenhouse gas and air pollutant emissions in the four IPCC AR5 Representative Concentration Pathway (RCP) scenarios, for 2030, 2050 and 2100. All model outputs are regridded to a common 0.5°x0.5° horizontal resolution. Future premature mortality is estimated for each RCP scenario and year based on changes in concentrations of ozone and PM2.5 relative to 2000. Using a health impact function, changes in concentrations for each RCP scenario are combined with future population and cause-specific baseline mortality rates as projected by a single independent scenario in which the global incidence of cardiopulmonary diseases is expected to increase. The effect of climate change is isolated by considering the difference between air pollutant concentrations from simulations with 2000 emissions and a future year climate and simulations with 2000 emissions and climate. Uncertainties in the results reflect the uncertainty in the concentration-response function and that associated with variability among models. Few previous studies have quantified the effects of future climate change on global human health via changes in air quality, and this is the first such study to use an ensemble of global models.

Impact of Lateral Mixing in the Ocean on El Nino in Fully Coupled Climate Models

NASA Astrophysics Data System (ADS)

Gnanadesikan, A.; Russell, A.; Pradal, M. A. S.; Abernathey, R. P.

2016-02-01

Given the large number of processes that can affect El Nino, it is difficult to understand why different climate models simulate El Nino differently. This paper focusses on the role of lateral mixing by mesoscale eddies. There is significant disagreement about the value of the mixing coefficient ARedi which parameterizes the lateral mixing of tracers. Coupled climate models usually prescribe small values of this coefficient, ranging between a few hundred and a few thousand m2/s. Observations, however, suggest values that are much larger. We present a sensitivity study with a suite of Earth System Models that examines the impact of varying ARedi on the amplitude of El Nino. We examine the effect of varying a spatially constant ARedi over a range of values similar to that seen in the IPCC AR5 models, as well as looking at two spatially varying distributions based on altimetric velocity estimates. While the expectation that higher values of ARedi should damp anomalies is borne out in the model, it is more than compensated by a weaker damping due to vertical mixing and a stronger response of atmospheric winds to SST anomalies. Under higher mixing, a weaker zonal SST gradient causes the center of convection over the Warm pool to shift eastward and to become more sensitive to changes in cold tongue SSTs . Changes in the SST gradient also explain interdecadal ENSO variability within individual model runs.

The future of scenarios: issues in developing new climate change scenarios

NASA Astrophysics Data System (ADS)

Pitcher, Hugh M.

2009-04-01

In September, 2007, the IPCC convened a workshop to discuss how a new set of scenarios to support climate model runs, mitigation analyses, and impact, adaptation and vulnerability research might be developed. The first phase of the suggested new approach is now approaching completion. This article discusses some of the issues raised by scenario relevant research and analysis since the last set of IPCC scenarios were created (IPCC SRES, 2000) that will need to be addressed as new scenarios are developed by the research community during the second phase. These include (1) providing a logic for how societies manage to transition from historical paths to the various future development paths foreseen in the scenarios, (2) long-term economic growth issues, (3) the appropriate GDP metric to use (purchasing power parity or market exchange rates), (4) ongoing issues with moving from the broad geographic and time scales of the emission scenarios to the finer scales needed for impacts, adaptation and vulnerability analyses and (5) some possible ways to handle the urgent request from the policy community for some guidance on scenario likelihoods. The challenges involved in addressing these issues are manifold; the reward is greater credibility and deeper understanding of an analytic tool that does much to form the context within which many issues in addition to the climate problem will need to be addressed.

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How to `Elk-test' biogeochemical models in a data rich world? (Invited)

NASA Astrophysics Data System (ADS)

Reichstein, M.; Ciais, P.; Seneviratne, S. I.; Carvalhais, N.; Dalmonech, D.; Jung, M.; Luo, Y.; Mahecha, M. D.; Moffat, A. M.; Tomelleri, E.; Zaehle, S.

2010-12-01

Process-oriented biogeochemical models are a primary tool that has been used to project future states of climate and ecosystems in the earth system in response to anthropogenic and other forcing, and receive tremendous attention also in the context us the planned assessment report AR5 by the IPCC. However, model intercomparison and data-model comparison studies indicate large uncertainties regarding predictions of global interactions between atmosphere and biosphere. Rigorous scientific testing of these models is essential but very challenging, largely because neither it is technically and ethically possible to perform global earth-scale experiments, nor do we have replicate Earths for hypothesis testing. Hence, model evaluations have to rely on monitoring data such as ecological observation networks, global remote sensing or short-term and small-scale experiments. Here, we critically examine strategies of how model evaluations have been performed with a particular emphasis on terrestrial ecosystems. Often weak ‘validations’ are being presented which do not take advantage of all the relevant information in the observed data, but also apparent falsifications are made, that are hampered by a confusion of system processes with system behavior. We propose that a stronger integration of recent advances in pattern-oriented and system-oriented methodologies will lead to more satisfying earth system model evaluation and development, and show a few enlightening examples from terrestrial biogeochemical modeling and other disciplines. Moreover it is crucial to take advantage of the multidimensional nature of arising earth observation data sets which should be matched by models simultaneously, instead of relying on univariate simple comparisons. A new critical model evaluation is needed to improve future IPCC assessments in order to reduce uncertainties by distinguishing plausible simulation trajectories from fairy tales.

Quantifying Climate Change Hydrologic Risk at NASA Ames Research Center

NASA Astrophysics Data System (ADS)

Mills, W. B.; Bromirski, P. D.; Coats, R. N.; Costa-Cabral, M.; Fong, J.; Loewenstein, M.; Milesi, C.; Miller, N.; Murphy, N.; Roy, S.

2013-12-01

In response to 2009 Executive Order 13514 mandating U.S. federal agencies to evaluate infrastructure vulnerabilities due to climate variability and change we provide an analysis of future climate flood risk at NASA Ames Research Center (Ames) along South S.F. Bay. This includes likelihood analysis of large-scale water vapor transport, statistical analysis of intense precipitation, high winds, sea level rise, storm surge, estuary dynamics, saturated overland flooding, and likely impacts to wetlands and habitat loss near Ames. We use the IPCC CMIP5 data from three Atmosphere-Ocean General Circulation Models with Radiative Concentration Pathways of 8.5 Wm-2 and 4.5 Wm-2 and provide an analysis of climate variability and change associated with flooding and impacts at Ames. Intense storms impacting Ames are due to two large-scale processes, sub-tropical atmospheric rivers (AR) and north Pacific Aleutian low-pressure (AL) storm systems, both of which are analyzed here in terms of the Integrated Water Vapor (IWV) exceeding a critical threshold within a search domain and the wind vector transporting the IWV from southerly to westerly to northwesterly for ARs and northwesterly to northerly for ALs and within the Ames impact area during 1970-1999, 2040-2069, and 2070-2099. We also include a statistical model of extreme precipitation at Ames based on large-scale climatic predictors, and characterize changes using CMIP5 projections. Requirements for levee height to protect Ames are projected to increase and continually accelerate throughout this century as sea level rises. We use empirical statistical and analytical methods to determine the likelihood, in each year from present through 2099, of water level surpassing different threshold values in SF Bay near NASA Ames. We study the sensitivity of the water level corresponding to a 1-in-10 and 1-in-100 likelihood of exceedance to changes in the statistical distribution of storm surge height and ENSO height, in addition to increasing mean sea level. We examine the implications in the face of the CMIP5 projections. Storm intensification may result in increased flooding hazards at Ames. We analyze how the changes in precipitation intensity will impact the storm drainage system at Ames through continuous stormwater modeling of runoff with the EPA model SWMM 5 and projected downscaled daily precipitation data. Although extreme events will not adversely affect wetland habitats, adaptation projects--especially levee construction and improvement--will require filling of wetlands. Federal law mandates mitigation for fill placed in wetlands. We are currently calculating the potential mitigation burden by habitat type.

Light-weight Parallel Python Tools for Earth System Modeling Workflows

NASA Astrophysics Data System (ADS)

Mickelson, S. A.; Paul, K.; Xu, H.; Dennis, J.; Brown, D. I.

2015-12-01

With the growth in computing power over the last 30 years, earth system modeling codes have become increasingly data-intensive. As an example, it is expected that the data required for the next Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR6) will increase by more than 10x to an expected 25PB per climate model. Faced with this daunting challenge, developers of the Community Earth System Model (CESM) have chosen to change the format of their data for long-term storage from time-slice to time-series, in order to reduce the required download bandwidth needed for later analysis and post-processing by climate scientists. Hence, efficient tools are required to (1) perform the transformation of the data from time-slice to time-series format and to (2) compute climatology statistics, needed for many diagnostic computations, on the resulting time-series data. To address the first of these two challenges, we have developed a parallel Python tool for converting time-slice model output to time-series format. To address the second of these challenges, we have developed a parallel Python tool to perform fast time-averaging of time-series data. These tools are designed to be light-weight, be easy to install, have very few dependencies, and can be easily inserted into the Earth system modeling workflow with negligible disruption. In this work, we present the motivation, approach, and testing results of these two light-weight parallel Python tools, as well as our plans for future research and development.

Climatic and ecological future of the Amazon: likelihood and causes of change

NASA Astrophysics Data System (ADS)

Cook, B.; Zeng, N.; Yoon, J.-H.

2010-05-01

Some recent climate modeling results suggested a possible dieback of the Amazon rainforest under future climate change, a prediction that raised considerable interest as well as controversy. To determine the likelihood and causes of such changes, we analyzed the output of 15 models from the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC/AR4) and a dynamic vegetation model VEGAS driven by these climate output. Our results suggest that the core of the Amazon rainforest should remain largely stable as rainfall is projected to increase in nearly all models. However, the periphery, notably the southern edge of the Amazon and further south in central Brazil, are in danger of drying out, driven by two main processes. Firstly, a decline in precipitation of 22% in the southern Amazon's dry season (May-September) reduces soil moisture, despite an increase in precipitation during the wet season, due to nonlinear responses in hydrology and ecosystem dynamics. Two dynamical mechanisms may explain the lower dry season rainfall: (1) a general subtropical drying under global warming when the dry season southern Amazon is under the control of the subtropical high pressure; (2) a stronger north-south tropical Atlantic sea surface temperature gradient, and to lesser degree a warmer eastern equatorial Pacific. Secondly, evaporation demand will increase due to the general warming, further reducing soil moisture. In terms of ecosystem response, higher maintenance cost and reduced productivity under warming may also have additional adverse impact. The drying corresponds to a lengthening of the dry season by 11 days. As a consequence, the median of the models projects a reduction of 20% in vegetation carbon stock in the southern Amazon, central Brazil, and parts of the Andean Mountains. Further, VEGAS predicts enhancement of fire risk by 10-15%. The increase in fire is primarily due to the reduction in soil moisture, and the decrease in dry season rainfall, which is when fire danger reaches its peak. Because the southern Amazon is also under intense human influence as a result of deforestation and land use, added pressure to the region's ecosystems from climate change may subject the region to profound changes in the 21st century.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

Global Air Quality and Climate

NASA Technical Reports Server (NTRS)

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

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

DOE PAGES

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

2017-03-28

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

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

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

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

Projected Changes to Streamflow Characteristics in Quebec Basins as Simulated by the Canadian Regional Climate Model (CRCM4)

NASA Astrophysics Data System (ADS)

Huziy, O.; Sushama, L.; Khaliq, M.; Lehner, B.; Laprise, R.; Roy, R.

2011-12-01

According to the Intergovernmental Panel on Climate Change (IPCC, 2007), an intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high-latitudes, is expected in future climate. This will have an impact on mean and extreme flow characteristics, which need to be assessed for better development of adaptation strategies. Analysis of the mean and extreme streamflow characteristics for Quebec (North-eastern Canada) basins in current climate and their projected changes in future climate are assessed using a 10 member ensemble of current (1970 - 1999) and future (2041 - 2070) Canadian RCM (CRCM4) simulations. Validation of streamflow characteristics, performed by comparing modeled values with those observed, available from the Centre d'expertise hydrique du Quebec (CEHQ) shows that the model captures reasonably well the high flows. Results suggest increase in mean and 10 year return levels of 1 day high flows, which appear significant for most of the northern basins.

Maynard Participation in Alaska Forum on the Environment Panel Discussion on Increasing Input to the US National Climate Assessment (NCA) and the Intergovernmental Panel on Climate Change (IPCC) Processes from Alaska, with Emphasis on Indigenous Peoples Issues

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.

2012-01-01

Dr. Nancy Maynard was invited by the Alaska Forum on the Environment to participate in a Panel Discussion to discuss (1) background about what the US NCA and International IPCC assessments are, (2) the impact the assessments have on policy-making, (3) the process for participation in both assessments, (4) how we can increase participation by Indigenous Peoples such as Native Americans and Alaska Natives, (5) How we can increase historical and current impacts input from Native communities through stories, oral history, "grey" literature, etc. The session will be chaired by Dr. Bull Bennett, a cochair of the US NCA's chapter on "Native and Tribal Lands and Resources" and Dr. Maynard is the other co-chair of that chapter and they will discuss the latest activities under the NCA process relevant to Native Americans and Alaska Natives. Dr. Maynard is also a Lead Author of the "Polar Regions" chapter of the IPCC WG2 (5th Assessment) and she will describes some of the latest approaches by the IPCC to entrain more Indigenous peoples into the IPCC process.

Extreme European heat waves since 1950 with Heat Wave Magnitude Index and their occurrence in the future

NASA Astrophysics Data System (ADS)

Russo, Simone; Dosio, Alessandro; Sillmann, Jana

2015-04-01

Heat waves are defined as prolonged periods of extremely hot weather and their magnitude and frequency are expected to increase in the future under climate change. Here we grade the heat waves occurred in Europe since 1950, by means of the Heat Wave Magnitude Index (HWMI) applied to daily maximum temperature from European Observation dataset (E-OBS). As shown in many studies the worst event in the last decades occurred in Russia in 2010. However many other heat waves, as shown here and documented in literature and also in newspapers, occurred in different European regions in the past 64 years. In addition, predictions from ten models from the COordinated Regional climate Downscaling EXperiment (CORDEX) under different IPCC AR5 scenarios, suggest an increased probability of occurrence of extreme heat waves by the end of the century. In particular, under the most severe scenario, events of the same severity, as the 2010 Russian heat wave, will become the norm and are projected to occur as often as every two years in the studied region.

Human contribution to the United States extreme heatwaves in the coming decades

NASA Astrophysics Data System (ADS)

Russo, E.; Marchese, A. F.; Immè, G.; Russo, S.

2015-12-01

In the past decades many intense and long heatwaves have hit large areas across the United States producing notable impacts on human mortality,regional economies, and natural ecosystems.Evidence indicates that anthropogenic climate change will alter the magnitude and frequency of these events. Here, by means of the Heat Wave Magnitude Index daily (HWMId) applied to daily maximum temperature from the United States reanalysis dataset (NLDAS-2), we grade the heat waves occurred in the U.S. since 1980, demonstrating that the two worst events within the studied period occurred in the summer of 1980 and 2011. Moreover, by referring to these two events as extremes, we show that model predictions from the North American COordinated Regional climate Downscaling EXperiment (CORDEX) under different IPCC AR5 scenarios, suggest an increased risk of occurrence of extreme heat waves in the near future (2021-2050). In particular, under the most severe scenario, events of the same severity, as the 1980 and 2011 U.S. heat waves, will become more likely in the studied region.

A history of the science and politics of climate change: the role of the Intergovernmental Panel on Climate Change

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

Bolin, B.

2007-11-15

In response to growing concern about human-induced global climate change, the UN Intergovernmental Panel on Climate Change (IPCC) was formed in 1988. Written by its first Chairman, this book is a unique overview of the history of the IPCC. It describes and evaluates the intricate interplay between key factors in the science and politics of climate change, the strategy that has been followed, and the regretfully slow pace in getting to grips with the uncertainties that have prevented earlier action being taken. The book also highlights the emerging conflict between establishing a sustainable global energy system and preventing a seriousmore » change in global climate. Contents are: Part I. The Early History of the Climate Change Issue: 1. Nineteenth century discoveries; 2. The natural carbon cycle and life on earth; 3. Global research initiatives in meteorology and climatology; 4. Early international assessments of climate change; Part II. The Climate Change Issue Becomes One of Global Concern: 5. Setting the stage; 6. The scientific basis for a climate convention; 7. Serving the Intergovernmental Negotiating Committee; 8. The Second IPP Assessment Report; 9. In the aftermath of the IPCC Second Assessment; 10. The Kyoto Protocol is agreed and a third assessment begun; 11. A decade of hesitance and slow progress; Part III. A Turning Point in Addressing Climate Change?: 12. Key scientific finding of prime political relevance; 13. Climate change and the future global energy supply system; Concluding remarks. 9 figs.« less

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

PubMed

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

2018-01-17

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

Emergent constraint on equilibrium climate sensitivity from global temperature variability

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Climate change impacts on yields and soil carbon in dryland agriculture

USDA-ARS?s Scientific Manuscript database

Dryland agroecosystems could be a sizable sink for atmospheric carbon (C) due to their spatial extent and level of degradation, providing climate change mitigation. We examined productivity and soil C dynamics under two IPCC climate change scenarios (RCP 4.5; RCP 8.5), utilizing long-term experiment...

Towards the IPCC Special Report on Global Warming of 1.5°C

NASA Astrophysics Data System (ADS)

Masson-Delmotte, Valérie

2017-04-01

The Intergovernemental Panel on Climate Change (IPCC) has accepted the invitation from the Paris Agreement to prepare a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. This special report is prepared under the scientific leadership of the co-chairs of the IPCC Working Groups I, II and III, and with operational support from the Technical Support Unit of Working Group I. It will consist of 5 chapters, providing (i) framing and context, (ii) exploring mitigation pathways compatible with 1.5°C in the context of sustainable development, (iii) assessing impacts of 1.5°C global warming on natural and human systems, and (iv) options for strengthening and implementing the global response to the threat of climate change, with a final chapter on sustainable development, poverty eradication and reducing inequalities. The timeline of preparation of the report is extremely short, with four lead author meetings taking place from March 2017 to April 2018, and an approval session scheduled in September 2018. It is crucial that new knowledge is being produced and submitted / published in the literature in time for contributing new material to be assessed by the authors of the report (with deadlines in late fall 2017 and spring 2018). With respect to the additional impacts expected for 1.5°C warming compared to present-day, and impacts avoided with respect to larger warming, new research is expected to build on existing CMIP5 projections, including new information on regional change, methods to provide knowledge for the most vulnerable ecosystems and regions, but also information from ongoing projects aiming to produce large ensembles of simulations, and new simulations driven by low carbon pathways. This is important for identifying climate change signals from climate variability (e.g. changes in water cycle, extremes...), for assessing strengths and limitations of methodologies using high end climate scenarios versus true stabilisation pathways, and for exploring long term risks beyond transient response, with consideration for overshoots and the full timescale of Earth system feedbacks. Lessons learnt from past warm climatic phases may also provide insights complementary to projections, albeit without the perspective of rates of changes that is specific to the issue of 1.5°C global warming. This special report is also designed to be complementary from the other reports in preparation for the IPCC Sixth Assessment cycle (AR6), including the special reports on the ocean and the cryosphere, on land use issues, both scheduled for 2019, and the Working Group main assessment reports, scheduled for 2021-2022.

Uncertainty of tipping elements on risk analysis in hydrology under climate change

NASA Astrophysics Data System (ADS)

Kiguchi, M.; Iseri, Y.; Tawatari, R.; Kanae, S.; Oki, T.

2015-12-01

Risk analysis in this study characterizes the events that could be caused by climate change and estimates their effects on society. In order to characterize climate change risks, events that might be caused by climate change will be investigated focusing on critical geophysical phenomena such as changes in thermohaline circulation (THC) in oceans and the large-scale melting of the Greenland and other ice sheets. The results of numerical experiments with climate models and paleoclimate studies will be referenced in listing up these phenomena. The trigger mechanisms, tendency to occur and relationship of these phenomena to global climate will be clarified. To clarify that relationship between the RCP scenarios and tipping elements, we identified which year tipping elements in case of "Arctic summer sea ice" and "Greenland ice sheet" are appeared using the increase of global average temperature in 5 GCMs under RCP (2.6, 4.5, 6.0, and 8.5) from Zickfeld et al. (2013) and IPCC (2013), and tipping point of each tipping elements from IPCC (2013). In case of "Greenland ice sheet" (Tipping point takes a value within the range of 1.0oC and 4.0oC), we found that "Greenland ice sheet" may melt down when the tipping point is 1.0oC as lowest value. On the other hand, when tipping point sets as 4.0oC, it may not melt down except for RCP 8.5. As above, we show the uncertainty of tipping point itself. In future, it is necessary how to reflect such uncertainty in risk analysis in hydrology.

Atmospheric river influence on the intensification of extreme hydrologic events over the Western United States under climate change scenarios

NASA Astrophysics Data System (ADS)

Pagán, Brianna; Ashfaq, Moetasim; Nayak, Munir; Rastogi, Deeksha; Margulis, Steven; Pal, Jeremy

2017-04-01

The Western United States shares limited snowmelt driven water supplies amongst millions of people, a multi-billion dollar agriculture industry and fragile ecosystems. The climatology of the region is highly variable, characterized by the frequent occurrences of both flood and drought conditions that cause increasingly challenging water management issues. Although variable year to year, up to half of California's total precipitation can be linked to atmospheric rivers (ARs). Most notably, ARs have been connected to nearly every major historic flood in the region, establishing its critical role to water supply. Numerous prior studies have considered potential climate change impacts over the Western United States and have generally concluded that warmer temperatures will reduce snowpack and shift runoff timing, causing reductions to water supply. Here we examine the role of ARs as one mechanism for explaining projected increases in flood and drought frequency and intensity under climate change scenarios, vital information for water resource managers. A hierarchical modeling framework to downscale 11 coupled global climate models from CMIP5 is used to form an ensemble of high-resolution dynamically downscaled regional climate model (via RegCM4) simulations at 18-km and hydrological (via VIC) simulations at a 4-km resolution for baseline (1965-2005) and future (2010-2050) periods under RCP 8.5. Each ensemble member's ability to capture observational AR climatology over the baseline period is evaluated. Baseline to future period changes to AR size, duration, seasonal timing, trajectory, magnitude and frequency are presented. These changes to the characterizations of ARs in the region are used to determine if any links exist to changes in snowpack volume, runoff timing, and the occurrence of daily and annual cumulative extreme precipitation and runoff events. Shifts in extreme AR frequency and magnitude are expected to increase flood risks, which without adequate multi-year reservoir storage solutions could further strain water supply resources.

High resolution modeling of the upper troposphere and lower stratosphere region over the Arctic - GEM-AC simulations for the future climate with and without aviation emissions.

NASA Astrophysics Data System (ADS)

Porebska, Magdalena; Struzewska, Joanna; Kaminski, Jacek W.

2016-04-01

Upper troposphere and lower stratosphere (UTLS) region is a layer around the tropopause. Perturbation of the chemical composition in the UTLS region can impact physical and dynamical processes that can lead to changes in cloudiness, precipitation, radiative forcing, stratosphere-troposphere exchange and zonal flow. The objective of this study is to investigate the potential impacts of aviation emissions on the upper troposphere and lower stratosphere. In order to assess the impact of the aviation emissions we will focus on changes in atmospheric dynamic due to changes in chemical composition in the UTLS over the Arctic. Specifically, we will assess perturbations in the distribution of the wind, temperature and pressure fields in the UTLS region. Our study will be based on simulations using a high resolution chemical weather model for four scenarios of current (2006) and future (2050) climate: with and without aircraft emissions. The tool that we use is the GEM-AC (Global Environmental Multiscale with Atmospheric Chemistry) chemical weather model where air quality, free tropospheric and stratospheric chemistry processes are on-line and interactive in an operational weather forecast model of Environment Canada. In vertical, the model domain is defined on 70 hybrid levels with model top at 0.1 mb. The gas-phase chemistry includes detailed reactions of Ox, NOx, HOx, CO, CH4, ClOx and BrO. Also, the model can address aerosol microphysics and gas-aerosol partitioning. Aircraft emissions are from the AEDT 2006 database developed by the Federal Aviation Administration (USA) and the future climate simulations are based on RCP8.5 projection presented by the IPCC in the fifth Assessment Report AR5. Results from model simulations on a global variable grid with 0.5o x 0.5o uniform resolution over the Arctic will be presented.

Evaluation of Water Quality Change of Brackish Lake in Snowy Cold Regions Accompanying Climate Change

NASA Astrophysics Data System (ADS)

Kudo, K.; Hasegawa, H.; Nakatsugawa, M.

2017-12-01

This study addresses evaluation of water quality change of brackish lake based on the estimation of hydrological quantities resulting from long-term hydrologic process accompanying climate change. For brackish lakes, such as Lake Abashiri in Eastern Hokkaido, there are concerns about water quality deterioration due to increases in water temperature and salinity. For estimating some hydrological quantities in the Abashiri River basin, including Lake Abashiri, we propose the following methods: 1) MRI-NHRCM20, a regional climate model based on the Representative Concentration Pathways adopted by IPCC AR5, 2) generalized extreme value distribution for correcting bias, 3) kriging adopted variogram for downscaling and 4) Long term Hydrologic Assessment model considering Snow process (LoHAS). In addition, we calculate the discharge from Abashiri River into Lake Abashiri by using estimated hydrological quantities and a tank model, and simulate impacts on water quality of Lake Abashiri due to climate change by setting necessary conditions, including the initial conditions of water temperature and water quality, the pollution load from the inflow rivers, the duration of ice cover and salt pale boundary. The result of the simulation of water quality indicates that climate change is expected to raise the water temperature of the lake surface by approximately 4°C and increase salinity of surface of the lake by approximately 4psu, also if salt pale boundary in the lake raises by approximately 2-m, the concentration of COD, T-N and T-P in the bottom of the lake might increase. The processes leading to these results are likely to be as follows: increased river water flows in along salt pale boundary in lake, causing dynamic flow of surface water; saline bottom water is entrained upward, where it mixes with surface water; and the shear force acting at salt pale boundary helps to increase the supply of salts from bottom saline water to the surface water. In the future, we will conduct similar simulations for a larger area that includes the mouth of Abashiri River. The accuracy of flow field simulation for Lake Abashiri will increase when calculations incorporate the effects of climate change on tide level, water temperature and salinity at the river mouth.

Tropical climate trends inferred from coral δ18O: a comparison of CMIP5 forward-model results with paleoclimatic observations

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Evans, M. N.; Cole, J. E.; Ault, T. R.; Emile-Geay, J.

2011-12-01

The response of the tropical Pacific Ocean to anthropogenic climate change remains highly uncertain, in part because of the disagreement among 20th-century trends derived from observations and coupled general circulation models (CGCMs). We use a model of reef coral oxygen isotopic composition (δ18O) to compare the observational coral network with synthetic corals ('pseudocorals') modeled from CGCM sea-surface temperature (SST) and sea-surface salinity (SSS). When driven with historical data, we found that a linear temperature and salinity driven model for δ18Ocoral was able to capture the spatial and temporal pattern of ENSO and the linear trend observed in 23 Indo-Pacific coral records between 1958 and 1990. However, we found that none of the pseudocoral networks obtained from a subset of 20th-century AR4 CGCM runs reproduced the magnitude of the secular trend, the change in mean state, or the change in ENSO-related variance observed in the coral network from 1890 to 1990 (Thompson et al., 2011). We believe differences between corals and AR4 CGCM simulated pseudocorals arose from uncertainties in the observed coral network or linear bivariate coral model, undersensitivity of AR4 CGCMs to radiative forcing during the 20th century, and/or biases in the simulated AR4 CGCM SSS fields. Here we apply the same approach to an extended temperature and salinity reanalysis product (SODA v2.2.4, 1871-2008) and CMIP 5 historical simulations to further address 20th-century tropical climate trends and assess remaining uncertainties in both the proxies and models. We explore whether model improvements in the tropical Pacific have led to a stronger agreement between simulated and observed tropical climate trends. [Thompson, D. M., T. R. Ault, M. N. Evans, J. E. Cole, and J. Emile-Geay (2011), Comparison of observed and simulated tropical climate trends using a forward model of coral δ18O, Geophys. Res. Lett., 38, L14706, doi:10.1029/2011GL048224.

Informing Adaptation Decisions: What Do We Need to Know and What Do We Need to Do?

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.; Webb, R. S.

2014-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC Reports (SREX, AR5) and other assessments, this demand has increased pressure for better information to support planning under changing rates of extremes event occurrence. This demand has focused on mechanisms used to respond to past variability and change, including, integrated resource management (watersheds, coasts), infrastructure design, information systems, technological optimization, financial risk management, and behavioral and institutional change. Climate inputs range from static site design statistics (return periods) to dynamic, emergent thresholds and transitions preceded by steep response curves and punctuated equilibria. Tradeoffs are evident in the use of risk-based anticipatory strategies vs. resilience measures. In such settings, annual decision calendars for operational requirements can confound adaptation expectations. Key knowledge assessment questions include: (1) How predictable are potential impacts of events in the context of other stressors, (2) how is action to anticipate such impacts informed, and (3) How often should criteria for "robustness" be reconsidered? To illustrate, we will discuss the climate information needs and uses for two areas of concern for both short and long-term risks (i) climate and disaster risk financing, and (ii) watershed management. The presentation will focus on the climate information needed for (1) improved monitoring, modeling and methods for understanding and analyzing exposure risks, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds across climate time and space scales, (4) embedding annual decision calendars in the context of longer-term risk management, (5) gaming experiments to show the net benefits of new information. We will conclude with a discussion of the essential climate variables needed to implement services-delivery and development efforts such as the Global Framework for Climate Services and the Pilot Program on Climate Resilience.

Sensitivity Analysis Tailored to Constrain 21st Century Terrestrial Carbon-Uptake

NASA Astrophysics Data System (ADS)

Muller, S. J.; Gerber, S.

2013-12-01

The long-term fate of terrestrial carbon (C) in response to climate change remains a dominant source of uncertainty in Earth-system model projections. Increasing atmospheric CO2 could be mitigated by long-term net uptake of C, through processes such as increased plant productivity due to "CO2-fertilization". Conversely, atmospheric conditions could be exacerbated by long-term net release of C, through processes such as increased decomposition due to higher temperatures. This balance is an important area of study, and a major source of uncertainty in long-term (>year 2050) projections of planetary response to climate change. We present results from an innovative application of sensitivity analysis to LM3V, a dynamic global vegetation model (DGVM), intended to identify observed/observable variables that are useful for constraining long-term projections of C-uptake. We analyzed the sensitivity of cumulative C-uptake by 2100, as modeled by LM3V in response to IPCC AR4 scenario climate data (1860-2100), to perturbations in over 50 model parameters. We concurrently analyzed the sensitivity of over 100 observable model variables, during the extant record period (1970-2010), to the same parameter changes. By correlating the sensitivities of observable variables with the sensitivity of long-term C-uptake we identified model calibration variables that would also constrain long-term C-uptake projections. LM3V employs a coupled carbon-nitrogen cycle to account for N-limitation, and we find that N-related variables have an important role to play in constraining long-term C-uptake. This work has implications for prioritizing field campaigns to collect global data that can help reduce uncertainties in the long-term land-atmosphere C-balance. Though results of this study are specific to LM3V, the processes that characterize this model are not completely divorced from other DGVMs (or reality), and our approach provides valuable insights into how data can be leveraged to be better constrain projections for the land carbon sink.

Objectively combining AR5 instrumental period and paleoclimate climate sensitivity evidence

NASA Astrophysics Data System (ADS)

Lewis, Nicholas; Grünwald, Peter

2018-03-01

Combining instrumental period evidence regarding equilibrium climate sensitivity with largely independent paleoclimate proxy evidence should enable a more constrained sensitivity estimate to be obtained. Previous, subjective Bayesian approaches involved selection of a prior probability distribution reflecting the investigators' beliefs about climate sensitivity. Here a recently developed approach employing two different statistical methods—objective Bayesian and frequentist likelihood-ratio—is used to combine instrumental period and paleoclimate evidence based on data presented and assessments made in the IPCC Fifth Assessment Report. Probabilistic estimates from each source of evidence are represented by posterior probability density functions (PDFs) of physically-appropriate form that can be uniquely factored into a likelihood function and a noninformative prior distribution. The three-parameter form is shown accurately to fit a wide range of estimated climate sensitivity PDFs. The likelihood functions relating to the probabilistic estimates from the two sources are multiplicatively combined and a prior is derived that is noninformative for inference from the combined evidence. A posterior PDF that incorporates the evidence from both sources is produced using a single-step approach, which avoids the order-dependency that would arise if Bayesian updating were used. Results are compared with an alternative approach using the frequentist signed root likelihood ratio method. Results from these two methods are effectively identical, and provide a 5-95% range for climate sensitivity of 1.1-4.05 K (median 1.87 K).

EDITORIAL: Tropical deforestation and greenhouse gas emissions

NASA Astrophysics Data System (ADS)

Gibbs, Holly K.; Herold, Martin

2007-10-01

Carbon emissions from tropical deforestation have long been recognized as a key component of the global carbon budget, and more recently of our global climate system. Tropical forest clearing accounts for roughly 20% of anthropogenic carbon emissions and destroys globally significant carbon sinks (IPCC 2007). Global climate policy initiatives are now being proposed to address these emissions and to more actively include developing countries in greenhouse gas mitigation (e.g. Santilli et al 2005, Gullison et al 2007). In 2005, at the Conference of the Parties (COP) in Montreal, the United Nations Framework Convention on Climate Change (UNFCCC) launched a new initiative to assess the scientific and technical methods and issues for developing policy approaches and incentives to reduce emissions from deforestation and degradation (REDD) in developing countries (Gullison et al 2007). Over the last two years the methods and tools needed to estimate reductions in greenhouse gas emissions from deforestation have quickly evolved, as the scientific community responded to the UNFCCC policy needs. This focus issue highlights those advancements, covering some of the most important technical issues for measuring and monitoring emissions from deforestation and forest degradation and emphasizing immediately available methods and data, as well as future challenges. Elements for effective long-term implementation of a REDD mechanism related to both environmental and political concerns are discussed in Mollicone et al. Herold and Johns synthesize viewpoints of national parties to the UNFCCC on REDD and expand upon key issues for linking policy requirements and forest monitoring capabilities. In response to these expressed policy needs, they discuss a remote-sensing-based observation framework to start REDD implementation activities and build historical deforestation databases on the national level. Achard et al offer an assessment of remote sensing measurements across the world's tropical forests that can provide key consistency and prioritization for national-level efforts. Gibbs et al calculate a range of national-level forest carbon stock estimates that can be used immediately, and also review ground-based and remote sensing approaches to estimate national-level tropical carbon stocks with increased accuracy. These papers help illustrate that methodologies and tools are indeed available to estimate emissions from deforestation. Clearly, important technical challenges remain (e.g. quantifying degradation, assessing uncertainty, verification procedures, capacity building, and Landsat data continuity) but we now have a sufficient technical base to support REDD early actions and readiness mechanisms for building national monitoring systems. Thus, we enter the COP 13 in Bali, Indonesia with great hope for a more inclusive climate policy encompassing all countries and emissions sources from both land-use and energy sectors. Our understanding of tropical deforestation and carbon emissions is improving and with that, opportunities to conserve tropical forests and the host of ecosystem services they provide while also increasing revenue streams in developing countries through economic incentives to avoid deforestation and degradation. References Gullison R E et al 2007 Tropical forests and climate policy Science 316 985 6 Intergovernmental Panel on Climate Change (IPCC) 2007 Climate Change 2007: The Physical Science Basis: Summary for Policymakers http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf Santilli M et al 2005 Tropical deforestation and the Kyoto Protocol: an editorial essay Clim. Change 71 267 76 Focus on Tropical Deforestation and Greenhouse Gas Emissions Contents The articles below represent the first accepted contributions and further additions will appear in the near future. Pan-tropical monitoring of deforestation F Achard, R DeFries, H Eva, M Hansen, P Mayaux and H-J Stibig Monitoring and estimating tropical forest carbon stocks: making REDD a reality Holly K Gibbs, Sandra Brown, John O Niles and Jonathan A Foley Elements for the expected mechanisms on 'reduced emissions from deforestation and degradation, REDD' under UNFCCC D Mollicone, A Freibauer, E D Schulze, S Braatz, G Grassi and S Federici

Remote Sensing for Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2011-01-01

Remote sensing is being used more and more for decision-making and policy development. Specific examples are: (1) Providing constraints on climate models used in IPCC assessments (2) Framing discussions about greenhouse gas monitoring (3) Providing support for hazard assessment and recovery.

Activities of NASA's Global Modeling Initiative (GMI) in the Assessment of Subsonic Aircraft Impact

NASA Technical Reports Server (NTRS)

Rodriquez, J. M.; Logan, J. A.; Rotman, D. A.; Bergmann, D. J.; Baughcum, S. L.; Friedl, R. R.; Anderson, D. E.

2004-01-01

The Intergovernmental Panel on Climate Change estimated a peak increase in ozone ranging from 7-12 ppbv (zonal and annual average, and relative to a baseline with no aircraft), due to the subsonic aircraft in the year 2015, corresponding to aircraft emissions of 1.3 TgN/year. This range of values presumably reflects differences in model input (e.g., chemical mechanism, ground emission fluxes, and meteorological fields), and algorithms. The model implemented by the Global Modeling Initiative allows testing the impact of individual model components on the assessment calculations. We present results of the impact of doubling the 1995 aircraft emissions of NOx, corresponding to an extra 0.56 TgN/year, utilizing meteorological data from NASA's Data Assimilation Office (DAO), the Goddard Institute for Space Studies (GISS), and the Middle Atmosphere Community Climate Model, version 3 (MACCM3). Comparison of results to observations can be used to assess the model performance. Peak ozone perturbations ranging from 1.7 to 2.2 ppbv of ozone are calculated using the different fields. These correspond to increases in total tropospheric ozone ranging from 3.3 to 4.1 Tg/Os. These perturbations are consistent with the IPCC results, due to the difference in aircraft emissions. However, the range of values calculated is much smaller than in IPCC.

Climate Change Projection for the Department of Energy's Savannah River Site

NASA Astrophysics Data System (ADS)

Werth, D. W.

2014-12-01

As per recent Department of Energy (DOE) sustainability requirements, the Savannah River National Laboratory (SRNL) is developing a climate projection for the DOE's Savannah River Site (SRS) near Aiken, SC. This will comprise data from both a statistical and a dynamic downscaling process, each interpolated to the SRS. We require variables most relevant to operational activities at the site (such as the US Forest Service's forest management program), and select temperature, precipitation, wind, and humidity as being most relevant to energy and water resource requirements, fire and forest ecology, and facility and worker safety. We then develop projections of the means and extremes of these variables, estimate the effect on site operations, and develop long-term mitigation strategies. For example, given that outdoor work while wearing protective gear is a daily facet of site operations, heat stress is of primary importance to work planning, and we use the downscaled data to estimate changes in the occurrence of high temperatures. For the statistical downscaling, we use global climate model (GCM) data from the Climate Model Intercomparison Project, version 5 (CMIP-5), which was used in the IPCC Fifth Assessment Report (AR5). GCM data from five research groups was selected, and two climate change scenarios - RCP 4.5 and RCP 8.5 - are used with observed data from site instruments and other databases to produce the downscaled projections. We apply a quantile regression downscaling method, which involves the use of the observed cumulative distribution function to correct that of the GCM. This produces a downscaled projection with an interannual variability closer to that of the observed data and allows for more extreme values in the projections, which are often absent in GCM data. The statistically downscaled data is complemented with dynamically downscaled data from the NARCCAP database, which comprises output from regional climate models forced with GCM output from the CMIP-3 database of GCM simulations. Applications of the downscaled climate projections to some of the unique operational needs of a large DOE weapons complex site are described.

Thermal growth potential of Atlantic cod by the end of the 21st century.

PubMed

Butzin, Martin; Pörtner, Hans-Otto

2016-12-01

Ocean warming may lead to smaller body sizes of marine ectotherms, because metabolic rates increase exponentially with temperature while the capacity of the cardiorespiratory system to match enhanced oxygen demands is limited. Here, we explore the impact of rising sea water temperatures on Atlantic cod (Gadus morhua), an economically important fish species. We focus on changes in the temperature-dependent growth potential by a transfer function model combining growth observations with climate model ensemble temperatures. Growth potential is expressed in terms of asymptotic body weight and depends on water temperature. We consider changes between the periods 1985-2004 and 2081-2100, assuming that future sea water temperatures will evolve according to climate projections for IPCC AR5 scenario RCP8.5. Our model projects a response of Atlantic cod to future warming, differentiated according to ocean regions, leading to increases of asymptotic weight in the Barents Sea, while weights are projected to decline at the southern margin of the biogeographic range. Southern spawning areas will disappear due to thermal limitation of spawning stages. These projections match the currently observed biogeographic shifts and the temperature- and oxygen-dependent decline in routine aerobic scope at southern distribution limits. © 2016 John Wiley & Sons Ltd.

Predicting the Arctic Ocean Environment in the 21st century

NASA Astrophysics Data System (ADS)

Aksenov, Yevgeny; Popova, Ekaterina; Yool, Andrew; Nurser, George

2015-04-01

Recent environmental changes in the Arctic have clearly demonstrated that climate change is faster and more vigorously in the Polar Regions than anywhere else. Significantly, change in the Arctic Ocean (AO) environment presents a variety of impacts, from ecological to social-economic and political. Mitigation of this change and adaptation to it requires detailed and robust environmental predictions. Here we present a detailed projection of ocean circulation and sea ice from the present until 2099, based on an eddy-permitting high-resolution global simulation of the NEMO ¼ degree ocean model. The model is forced at the surface with HadGEM2-ES atmosphere model output from the UK Met. Office IPCC Assessment Report 5 (AR5) Representative Concentration Pathways 8.5 (RCP8.5) scenario. The HadGEM2-ES simulations span 1860-2099 and are one of an ensemble of runs performed for the Coupled Model Intercomparison Project 5 (CMIP5) and IPCC AR5. Between 2000-2009 and 2090-2099 the AO experiences a significant warming, with sea surface temperature increasing on average by about 4° C, particularly in the Barents and Kara Seas, and in the Greenland Sea and Hudson Bay. By the end of the simulation, Arctic sea ice has an average annual thickness of less than 10 cm in the central AO, and less than 0.5 m in the East-Siberian Sea and Canadian Archipelago, and disappears entirely during the Arctic summer. In summer, opening of large areas of the Arctic Ocean to the wind and surface waves leads to the Arctic pack ice cover evolving into the Marginal Ice Zone (MIZ). In winter, sea ice persists until the 2030s; then it sharply declines and disappears from the Central Arctic Ocean by the end of the 21st century, with MIZ provinces remaining in winter along the Siberian, Alaskan coasts and in the Canadian Arctic Archipelago. Analysis of the AO circulation reveals evidence of (i) the reversal of the Arctic boundary currents in the Canadian Basin, from a weak cyclonic current in 2040-2049 to a strong anti-cyclonic current in 2090-2099, and (ii) increased anti-cyclonic surface ocean circulation in the eastern part of the AO, while the surface circulation in the western Arctic becomes more cyclonic. We relate the shift in the circulation to changes in the winds and reduction of sea ice cover, which modify momentum transfer from atmosphere to the ocean. Our simulation suggests a potentially complex picture of future AO change, and highlights the importance of high resolution modelling in forecasting it.

An Inter-calibrated Passive Microwave Brightness Temperature Data Record and Ocean Products

NASA Astrophysics Data System (ADS)

Hilburn, K. A.; Wentz, F. J.

2014-12-01

Inter-calibration of passive microwave sensors has been the subject of on-going activity at Remote Sensing Systems (RSS) since 1974. RSS has produced a brightness temperature TB data record that spans the last 28 years (1987-2014) from inter-calibrated passive microwave sensors on 14 satellites: AMSR-E, AMSR2, GMI, SSMI F08-F15, SSMIS F16-F18, TMI, WindSat. Accompanying the TB record are a suite of ocean products derived from the TBs that provide a 28-year record of wind speed, water vapor, cloud liquid, and rain rate; and 18 years (1997-2014) of sea surface temperatures, corresponding to the period for which 6 and/or 10 GHz measurements are available. Crucial to the inter-calibration and ocean product retrieval are a highly accurate radiative transfer model RTM. The RSS RTM has been continually refined for over 30 years and is arguably the most accurate model in the 1-100 GHz spectrum. The current generation of TB and ocean products, produced using the latest version of the RTM, is called Version-7. The accuracy of the Version-7 inter-calibration is estimated to be 0.1 K, based on inter-satellite comparisons and validation of the ocean products against in situ measurements. The data record produced by RSS has had a significant scientific impact. Over just the last 14 years (2000-2013) RSS data have been used in 743 peer-reviewed journal articles. This is an average of 4.5 peer-reviewed papers published every month made possible with RSS data. Some of the most important scientific contributions made by RSS data have been to the study of the climate. The AR5 Report "Climate Change 2013: The Physical Science Basis" by the Intergovernmental Panel on Climate Change (IPCC), the internationally accepted authority on climate change, references 20 peer-reviewed journal papers from RSS scientists. The report makes direct use of RSS water vapor data, RSS atmospheric temperatures from MSU/AMSU, and 9 other datasets that are derived from RSS data. The RSS TB data record is used to produce the NSIDC Sea Ice, NASA Sea Ice, and NASA GPCP Rain Rate datasets. The RSS ocean products are used to produce the NCDC ERSST, CCMP Winds, NOAA Sea Winds, WHOI OA Flux, OSU Wind Stress, and UWISC Cloud Water datasets. The large number of scientific articles and significant impact on the IPCC report demonstrate the success of RSS inter-calibration methodology.

Continuously on-­going regional climate hindcast simulations for impact applications

NASA Astrophysics Data System (ADS)

Anders, Ivonne; Piringer, Martin; Kaufmann, Hildegard; Knauder, Werner; Resch, Gernot; Andre, Konrad

2017-04-01

Observational data for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation performed with the regional climate model COSMO-CLM is forced by ERAinterim and optimized for the Alpine Region. The simulation available for the period of 1979-2015 in a spatial resolution of about 10km is prolonged ongoing and fullfils the customer's needs with respect of output variables, levels, intervals and statistical measures. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the Northeast. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure or the calculation the separation distances between livestock farming and residential area.

Influence of updating global emission inventory of black carbon on evaluation of the climate and health impact

NASA Astrophysics Data System (ADS)

Wang, Rong; Tao, Shu; Balkanski, Yves; Ciais, Philippe

2013-04-01

Black carbon (BC) is an air component of particular concern in terms of air quality and climate change. Black carbon emissions are often estimated based on the fuel data and emission factors. However, large variations in emission factors reported in the literature have led to a high uncertainty in previous inventories. Here, we develop a new global 0.1°×0.1° BC emission inventory for 2007 with full uncertainty analysis based on updated source and emission factor databases. Two versions of LMDz-OR-INCA models, named as INCA and INCA-zA, are run to evaluate the new emission inventory. INCA is built up based on a regular grid system with a resolution of 1.27° in latitude and 2.50° in longitude, while INCA-zA is specially zoomed to 0.51°×0.66° (latitude×longitude) in Asia. By checking against field observations, we compare our inventory with ACCMIP, which is used by IPCC in the 5th assessment report, and also evaluate the influence of model resolutions. With the newly calculated BC air concentrations and the nested model, we estimate the direct radiative forcing of BC and the premature death and mortality rate induced by BC exposure with Asia emphasized. Global BC direct radiative forcing at TOA is estimated to be 0.41 W/m2 (0.2 - 0.8 as inter-quartile range), which is 17% higher than that derived from the inventory adopted by IPCC-AR5 (0.34 W/m2). The estimated premature deaths induced by inhalation exposure to anthropogenic BC (0.36 million in 2007) and the percentage of high risk population are higher than those previously estimated. Ninety percents of the global total anthropogenic PD occur in Asia with 0.18 and 0.08 million deaths in China and India, respectively.

78 FR 19565 - Call for Expert Reviewers to the U.S. Government Review of the Working Group II Contribution to...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-01

... Climate Change (IPCC), Impacts, Adaptation & Vulnerability. SUMMARY: The United States Global Change... on Climate Change (IPCC), Impacts, Adaptation & Vulnerability. The United Nations Environment... socio-economic information for understanding the scientific basis of climate change, potential impacts...

Attributing Contributions of Climate Feedbacks to the Seasonal Cycle of Surface Warming due to CO2 Increase

NASA Astrophysics Data System (ADS)

Sejas, S.; Cai, M.

2012-12-01

Surfing warming due to CO2 doubling is a robust feature of coupled general circulation models (GCM), as noted in the IPCC AR4 assessment report. In this study, the contributions of different climate feedbacks to the magnitude, spatial distribution, and seasonality of the surface warming is examined using data from NCAR's CCSM4. In particular, a focus is placed on polar regions to see which feedbacks play a role in polar amplification and its seasonal pattern. A new climate feedback analysis method is used to isolate the surface warming or cooling contributions of both radiative and non-radiative (dynamical) climate feedbacks to the total (actual) surface temperature change given by the CCSM4. These contributions (or partial surface temperature changes) are additive and their total is approximately equal to the actual surface temperature change. What is found is that the effects of CO2 doubling alone warms the surface throughout with a maximum in polar regions, which indicates the CO2 forcing alone has a degree of polar warming amplification. Water vapor feedback is a positive feedback throughout but is most responsible for the surface warming found in the tropics. Polar warming amplification is found to be strongest away from summer (especially in NH), which is primarily caused by a positive feedback due to cloud feedbacks but with the surface temperature change due to the CO2 forcing alone and the ocean dynamics and storage feedback also playing an important role. Contrary to popular belief, surface albedo feedback (SAF) does not account for much of the polar amplification. SAF tries to amplify polar warming, but in summer. No major polar amplification is seen in summer for the actual surface temperature, so SAF is not the feedback responsible for polar amplification. This is actually a consequence of the ocean dynamics and storage feedback, which negates the effects of SAF to a large degree.

Cloud Ice: A Climate Model Challenge With Signs and Expectations of Progress

NASA Astrophysics Data System (ADS)

Li, F.; Waliser, D.; Bacmeister, J.; Chern, J.; Del Genio, T.; Jiang, J.; Kharitondov, M.; Liou, K.; Meng, H.; Minnis, P.; Rossow, B.; Stephens, G.; Sun-Mack, S.; Tao, W.; Vane, D.; Woods, C.; Tompkins, A.; Wu, D.

2007-12-01

Global climate models (GCMs), including those assessed in the IPCC AR4, exhibit considerable disagreement in the amount of cloud ice - both in terms of the annual global mean as well as their spatial variability. Global measurements of cloud ice have been difficult due to the challenges involved in remotely sensing ice water content (IWC) and its vertical profile - including complications associated with multi-level clouds, mixed-phases and multiple hydrometer types, the uncertainty in classifying ice particle size and shape for remote retrievals, and the relatively small time and space scales associated with deep convection. Together, these measurement difficulties make it a challenge to characterize and understand the mechanisms of ice cloud formation and dissipation. Fortunately, there are new observational resources recently established that can be expected to lead to considerable reduction in the observational uncertainties of cloud ice, and in turn improve the fidelity of model representations. Specifically, these include the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, and the CloudSat and Calipso satellite missions, all of which fly in formation in what is referred to as the A-Train. Based on radar and limb-sounding techniques, these new satellite measurements provide a considerable leap forward in terms of the information gathered regarding upper-tropospheric cloud IWC as well as other macrophysical and microphysical properties. In this presentation, we describe the current state of GCM representations of cloud ice and their associated uncertainties, the nature of the new observational resources for constraining cloud ice values in GCMs, the challenges in making model-data comparisons with these data resources, and prospects for near-term improvements in model representations.

Examining the last few decades of global hydroclimate for evidence of anthropogenic change amidst natural variability

NASA Astrophysics Data System (ADS)

Seager, R.; Naik, N.; Ting, M.; Kushnir, Y.; Kelley, C. P.

2011-12-01

Climate models robustly predict that the deep tropics and mid-latitude-to-subpolar regions will moisten, and the subtropical dry zones both dry and expand, as a consequence of global warming driven by rising greenhouse gases. The models also predict that this transition to a more extreme climatological mean global hydroclimate should already be underway. Given the importance of these predictions it is an imperative that the climate science community assess whether there is evidence within the observational record that they are correct. This task is made difficult by the tremendous natural variability of the hydrological cycle on seasonal to multidecadal timescales. Here we will use instrumental observations, reanalyses, sea surface temperature forced atmosphere models and coupled model simulations, and a variety of methodologies, to attempt to separate global radiatively-forced hydroclimate change from ongoing natural variability. The results will be applied to explain trends and recent events in key regions such as Mexico, the United States and the Mediterranean. It is concluded that the signal of anthropogenic change is small compared to the amplitude of natural variability but that it is a discernible contributor. Globally the evidence reveals that radiatively-forced hydroclimate change is occurring with an amplitude and spatial pattern largely consistent with the predictions by IPCC AR4 models of hydroclimate change to date. However it will also be shown that the radiatively-forced component does not in and of itself provide a useful prediction of near term hydroclimate change because for many regions the amplitude of natural decadal variability is as large or larger. Useful predictions need to account for how natural variability may evolve as well as forced change.

Assessing the capability of high resolution climatic model experiments to simulate Mediterranean cyclonic tracks

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Giannakopoulos, C.; Kostopoulou, E.; Kouroutzoglou, I.; Keay, K.; Simmonds, I.

2010-09-01

In this study, a comparison of a reanalysis driven simulation to a GCM driven simulation of a regional climate model is performed in order to assess the model's ability to capture the climatic characteristics of cyclonic tracks in the Mediterranean in the present climate. The ultimate scope of the study will be to perform a future climate projection related to cyclonic tracks in order to better understand and assess climate change in the Mediterranean. The climatology of the cyclonic tracks includes inter-monthly variations, classification of tracks according to their origin domain, dynamic and kinematic characteristics, as well as trend analysis. For this purpose, the ENEA model is employed based on PROTHEUS system composed of the RegCM atmospheric regional model and the MITgcm ocean model, coupled through the OASIS3 flux coupler. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. Two experiments are employed; a) the ERA402 with lateral Boundary conditions from ERA40 for the 43-year period 1958-2000, and b) the EH5OM_20C3M where the lateral boundary conditions for the atmosphere (1951-2000) are taken from the ECHAM5-MPIOM 20c3m global simulation (run3) included in the IPCC-AR4. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. This approach is considered to be crucial, since open lows are also incorporated into the storm life-cycle, preventing possible inappropriate time series breaks, if a temporary weakening to an open-low state occurs. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region, consistent with previous studies. The classification of the tracks according to their origin domain show that the vast majority originate within the examined area itself. The study of the kinematic and dynamic parameters of tracks according to their origin demonstrate that deeper cyclones follow the SW track. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged.

Response of streamflow to projected climate change scenarios in an eastern Himalayan catchment of India

NASA Astrophysics Data System (ADS)

Senzeba, K. T.; Rajkumari, S.; Bhadra, A.; Bandyopadhyay, A.

2016-04-01

Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios for an eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of Arunachal Pradesh with an area of 52 km2 is selected for the present study with an elevation range of 3143-4946 m above mean sea level. Satellite images from October to June of the selected hydrological year 2006-2007 were procured from National Remote Sensing Centre, Hyderabad. Snow cover mapping is done using NDSI method. Based on long term meteorological data, temperature and precipitation data of selected hydrological year are normalized to represent present climatic condition. The projected temperature and precipitation data are downloaded from NCAR's GIS data portal for different emission scenarios (SRES), viz., A1B, A2, B1; and IPCC commitment (non-SRES) scenario for different future years (2020, 2030, 2040 and 2050). Projected temperature and precipitation data are obtained at desired location by spatially interpolating the gridded data and then by statistical downscaling using linear regression. Snow depletion curves for all projected scenarios are generated for the study area and compared with conventional depletion curve for present climatic condition. Changes in cumulative snowmelt depth for different future years are highest under A1B and lowest under IPCC commitment, whereas A2 and B1 values are in-between A1B and IPCC commitment. Percentage increase in streamflow for different future years follows almost the same trend as change in precipitation from present climate under all projected climatic scenarios. Hence, it was concluded that for small catchments having seasonal snow cover, the total streamflow under projected climatic scenarios in future years will be primarily governed by the change in precipitation and not by change in snowmelt depth. Advancing of depletion curves for different future years are highest under A1B and lowest under IPCC commitment. A2 and B1 values are in-between A1B and IPCC commitment.

Modelling adaptation to climate change of Ecuadorian agriculture and associated water resources: uncertainties in coastal and highland cropping systems

NASA Astrophysics Data System (ADS)

Ruiz-Ramos, Margarita; Bastidas, Wellington; Cóndor, Amparo; Villacís, Marcos; Calderón, Marco; Herrera, Mario; Zambrano, José Luis; Lizaso, Jon; Hernández, Carlos; Rodríguez, Alfredo; Capa-Morocho, Mirian

2016-04-01

Climate change threatens sustainability of farms and associated water resources in Ecuador. Although the last IPCC report (AR5) provides a general framework for adaptation, , impact assessment and especially adaptation analysis should be site-specific, taking into account both biophysical and social aspects. The objective of this study is to analyse the climate change impacts and to sustainable adaptations to optimize the crop yield. Furthermore is also aimed to weave agronomical and hydrometeorological aspects, to improve the modelling of the coastal ("costa") and highland ("sierra") cropping systems in Ecuador, from the agricultural production and water resources points of view. The final aim is to support decision makers, at national and local institutions, for technological implementation of structural adaptation strategies, and to support farmers for their autonomous adaptation actions to cope with the climate change impacts and that allow equal access to resources and appropriate technologies. . A diagnosis of the current situation in terms of data availability and reliability was previously done, and the main sources of uncertainty for agricultural projections have been identified: weather data, especially precipitation projections, soil data below the upper 30 cm, and equivalent experimental protocol for ecophysiological crop field measurements. For reducing these uncertainties, several methodologies are being discussed. This study was funded by PROMETEO program from Ecuador through SENESCYT (M. Ruiz-Ramos contract), and by the project COOP-XV-25 funded by Universidad Politécnica de Madrid.

Changes in continental Europe water cycle in a changing climate

NASA Astrophysics Data System (ADS)

Rouholahnejad, Elham; Schirmer, Mario; Abbaspour, Karim

2015-04-01

Changes in atmospheric water vapor content provide strong evidence that the water cycle is already responding to a warming climate. According to IPCC's last report on Climate Change (AR5), the water cycle is expected to intensify in a warmer climate as the atmosphere can hold more water vapor. This changes the frequency of precipitation extremes, increases evaporation and dry periods, and effects the water redistribution in land. This process is represented by most global climate models (GCMs) by increased summer dryness and winter wetness over large areas of continental mid to high latitudes in the Northern Hemisphere, associated with a reduction in water availability at continental scale. Observing changes in precipitation and evaporation directly and at continental scale is difficult, because most of the exchange of fresh water between the atmosphere and the surface happens the oceans. Long term precipitation records are available only from over the land and there are no measurement of evaporation or redistribution of precipitation over the land area. On the other hand, understanding the extent of climate change effects on various components of the water cycle is of strategic importance for public, private sectors, and policy makers when it comes to fresh water management. In order to better understand the extent of climate change impacts on water resources of continental Europe, we developed a distributed hydrological model of Europe at high spatial and temporal resolution using the Soil and Water Assessment Tool (SWAT). The hydrological model was calibrated for 1970 to 2006 using daily observation of streamflow and nitrate loads from 360 gauging stations across Europe. A vegetation growth routine was added to the model to better simulate evapotranspiration. The model results were calibrated with available agricultural crop yield data from other sources. As of future climate scenarios, we used the ISI-MIP project results which provides bias-corrected climate data from the GCMs participating in the CMIP5 at 0.5° x 0.5° resolution. Data cover the time period from 1901 to 2099, i.e. the historical period, and future projections for all Representative Concentration Pathways (RCP2.6, RCP 4.5, RCP 6.0, and RCP 8.5). We used four different models output (GFDL, HADGEMES, MIROC, and IPSL) for all RCPs for near (2006-2035) and far (3065-2099) future. Multi-model ensembles (16 scenarios) are then used to study the potential impacts of future climate change on fresh water availability across Europe.

Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

NASA Astrophysics Data System (ADS)

Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

2014-05-01

A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

Insight into runoff characteristics using hydrological modeling in the data-scarce southern Tibetan Plateau: Past, present, and future

PubMed Central

Cai, Mingyong; Yang, Shengtian; Zhao, Changsen; Zhou, Qiuwen; Hou, Lipeng

2017-01-01

Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960–2000) at Nuxia and model simulations for two periods (2006–2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960–2000), the present period (2006–2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in the future (2050). PMID:28486483

Insight into runoff characteristics using hydrological modeling in the data-scarce southern Tibetan Plateau: Past, present, and future.

PubMed

Cai, Mingyong; Yang, Shengtian; Zhao, Changsen; Zhou, Qiuwen; Hou, Lipeng

2017-01-01

Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960-2000) at Nuxia and model simulations for two periods (2006-2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960-2000), the present period (2006-2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in the future (2050).

On avoiding dangerous anthropogenic interference with the climate system: formidable challenges ahead.

PubMed

Ramanathan, V; Feng, Y

2008-09-23

The observed increase in the concentration of greenhouse gases (GHGs) since the preindustrial era has most likely committed the world to a warming of 2.4 degrees C (1.4 degrees C to 4.3 degrees C) above the preindustrial surface temperatures. The committed warming is inferred from the most recent Intergovernmental Panel on Climate Change (IPCC) estimates of the greenhouse forcing and climate sensitivity. The estimated warming of 2.4 degrees C is the equilibrium warming above preindustrial temperatures that the world will observe even if GHG concentrations are held fixed at their 2005 concentration levels but without any other anthropogenic forcing such as the cooling effect of aerosols. The range of 1.4 degrees C to 4.3 degrees C in the committed warming overlaps and surpasses the currently perceived threshold range of 1 degrees C to 3 degrees C for dangerous anthropogenic interference with many of the climate-tipping elements such as the summer arctic sea ice, Himalayan-Tibetan glaciers, and the Greenland Ice Sheet. IPCC models suggest that approximately 25% (0.6 degrees C) of the committed warming has been realized as of now. About 90% or more of the rest of the committed warming of 1.6 degrees C will unfold during the 21st century, determined by the rate of the unmasking of the aerosol cooling effect by air pollution abatement laws and by the rate of release of the GHGs-forcing stored in the oceans. The accompanying sea-level rise can continue for more than several centuries. Lastly, even the most aggressive CO(2) mitigation steps as envisioned now can only limit further additions to the committed warming, but not reduce the already committed GHGs warming of 2.4 degrees C.

On avoiding dangerous anthropogenic interference with the climate system: Formidable challenges ahead

PubMed Central

Ramanathan, V.; Feng, Y.

2008-01-01

The observed increase in the concentration of greenhouse gases (GHGs) since the preindustrial era has most likely committed the world to a warming of 2.4°C (1.4°C to 4.3°C) above the preindustrial surface temperatures. The committed warming is inferred from the most recent Intergovernmental Panel on Climate Change (IPCC) estimates of the greenhouse forcing and climate sensitivity. The estimated warming of 2.4°C is the equilibrium warming above preindustrial temperatures that the world will observe even if GHG concentrations are held fixed at their 2005 concentration levels but without any other anthropogenic forcing such as the cooling effect of aerosols. The range of 1.4°C to 4.3°C in the committed warming overlaps and surpasses the currently perceived threshold range of 1°C to 3°C for dangerous anthropogenic interference with many of the climate-tipping elements such as the summer arctic sea ice, Himalayan–Tibetan glaciers, and the Greenland Ice Sheet. IPCC models suggest that ≈25% (0.6°C) of the committed warming has been realized as of now. About 90% or more of the rest of the committed warming of 1.6°C will unfold during the 21st century, determined by the rate of the unmasking of the aerosol cooling effect by air pollution abatement laws and by the rate of release of the GHGs-forcing stored in the oceans. The accompanying sea-level rise can continue for more than several centuries. Lastly, even the most aggressive CO2 mitigation steps as envisioned now can only limit further additions to the committed warming, but not reduce the already committed GHGs warming of 2.4°C. PMID:18799733

High resolution interpolation of climate scenarios for the conterminous USA and Alaska derived from general circulation model simulations

Treesearch

Linda A. Joyce; David T. Price; Daniel W. McKenney; R. Martin Siltanen; Pia Papadopol; Kevin Lawrence; David P. Coulson

2011-01-01

Projections of future climate were selected for four well-established general circulation models (GCM) forced by each of three greenhouse gas (GHG) emissions scenarios, namely A2, A1B, and B1 from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). Monthly data for the period 1961-2100 were downloaded mainly from the web...

The Urban Climate Change Research Network (UCCRN) Second Assessment Report on Climate Change and Cities (ARC3-2), and the UCCRN Hubs

NASA Astrophysics Data System (ADS)

Rosenzweig, C.; Ali Ibrahim, S.

2015-12-01

The objective of this session is to foster a dialogue between experts working on global-scale, climate change and cities assessments in order to simultaneously present state-of-the-art knowledge on how cities are responding to climate change and to define emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers. We will present the UCCRN and the Second UCCRN Assessment Report on Climate Change and Cities (ARC3-2), the second in an ongoing series of global, interdisciplinary, cross-regional, science-based assessments to address climate risks, adaptation, mitigation, and policy mechanisms relevant to cities. This is an especially important time to examine these issues. Cities continue to act as world leaders in climate action. Several major climate change assessment efforts are in full swing, at a crucial stage where significant opportunities for the co-production of knowledge between researchers and stakeholders exist. The IPCC AR5 Working Group II and III Reports have placed unprecedented attention on cities and urbanization and their connection to the issue of climate change. Concurrently several major, explicitly city-focused efforts have emerged from the Urban Climate Change Research Network (UCCRN), ICLEI, the Durban Adaptation Charter (DAC), C40, Future Earth, and the Urbanization and Global Environmental Change (UGEC) Project, among others. The underlying rationale for the discussion will be to identify methods and approaches to further foster the development and dissemination of new climate change knowledge and information that will be useful for cities, especially in small and medium-sized cities and in the developing country context where the demand is particularly acute. Participants will leave this session with: · The latest scientific data and state-of-the-knowledge on how cities are responding to climate change · Emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers and for urban resilience and adaptation action · How practitioner-scientist interactions can work best · Synergies between the IPCC, ARC3, and other climate and cities assessments

Variability of western Amazon dry-season precipitation extremes: importance of decadal fluctuations and implications for predictability

NASA Astrophysics Data System (ADS)

Fernandes, K.; Baethgen, W.; Verchot, L. V.; Giannini, A.; Pinedo-Vasquez, M.

2014-12-01

A complete assessment of climate change projections requires understanding the combined effects of decadal variability and long-term trends and evaluating the ability of models to simulate them. The western Amazon severe droughts of the 2000s were the result of a modest drying trend enhanced by reduced moisture transport from the tropical Atlantic. Most of the WA dry-season precipitation decadal variability is attributable to decadal fluctuations of the north-south gradient (NSG) in Atlantic sea surface temperature (SST). The observed WA and NSG decadal co-variability is well reproduced in Global Climate Models (GCMs) pre-industrial control (PIC) and historical (HIST) experiments that were part of the Intergovernmental Panel on Climate Change fifth assessment report (IPCC-AR5). This suggests that unforced or natural climate variability, characteristic of the PIC simulations, determines the nature of this coupling, as the results from HIST simulations (forced with greenhouse gases (GHG) and natural and anthropogenic aerosols) are comparable in magnitude and spatial distribution. Decadal fluctuation in the NSG also determines shifts in the probability of repeated droughts and pluvials in WA, as there is a 65% chance of 3 or more years of droughts per decade when NSG>0 compared to 18% when NSG<0. The HIST and PIC model simulations also reproduce the observed shifts in probability distribution of droughts and pluvials as a function of the NSG decadal phase, suggesting there is great potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase may lead to continuing above normal frequencies of western Amazon dry-season droughts.

Assessing water resources under climate change in high-altitude catchments: a methodology and an application in the Italian Alps

NASA Astrophysics Data System (ADS)

Aili, T.; Soncini, A.; Bianchi, A.; Diolaiuti, G.; D'Agata, C.; Bocchiola, D.

2018-01-01

Assessment of the future water resources in the Italian Alps under climate change is required, but the hydrological cycle of the high-altitude catchments therein is poorly studied and little understood. Hydrological monitoring and modeling in the Alps is difficult, given the lack of first hand, site specific data. Here, we present a method to model the hydrological cycle of poorly monitored high-altitude catchments in the Alps, and to project forward water resources availability under climate change. Our method builds on extensive experience recently and includes (i) gathering data of climate, of cryospheric variables, and of hydrological fluxes sparsely available; (ii) robust physically based glacio-hydrological modeling; and (iii) using glacio-hydrological projections from GCM models. We apply the method in the Mallero River, in the central (Retiche) Alps of Italy. The Mallero river covers 321 km2, with altitude between 310 and 4015 m a.s.l., and it has 27 km2 of ice cover. The glaciers included in the catchment underwent large mass loss recently, thus Mallero is largely paradigmatic of the present situation of Alpine rivers. We set up a spatially explicit glacio-hydrological model, describing the cryospheric evolution and the hydrology of the area during a control run CR, from 1981 to 2007. We then gather climate projections until 2100 from three Global Climate Models of the IPCC AR5 under RCP2.6, RCP4.5, and RCP8.5. We project forward flow statistics, flow components (rainfall, snow melt, ice melt), ice cover, and volume for two reference decades, namely 2045-2054 and 2090-2099. We foresee reduction of the ice bodies from - 62 to - 98% in volume (year 2100 vs year 1981), and subsequent large reduction of ice melt contribution to stream flows (from - 61 to - 88%, 2100 vs CR). Snow melt, now covering 47% of the stream flows yearly, would also be largely reduced (from - 19 to - 56%, 2100 vs CR). The stream flows will decrease on average at 2100 (from + 1 to - 25%, with - 7%), with potential for increased flows during fall, and winter, and large decrease in summer. Our results provide a tool for consistent modeling of the cryospheric, and hydrologic behavior, and can be used for further investigation of the high-altitude catchments in the Alps.

Statistical downscaling of regional climate scenarios for the French Alps : Impacts on snow cover

NASA Astrophysics Data System (ADS)

Rousselot, M.; Durand, Y.; Giraud, G.; Mérindol, L.; Déqué, M.; Sanchez, E.; Pagé, C.; Hasan, A.

2010-12-01

Mountain areas are particularly vulnerable to climate change. Owing to the complexity of mountain terrain, climate research at scales relevant for impacts studies and decisive for stakeholders is challenging. A possible way to bridge the gap between these fine scales and those of the general circulation models (GCMs) consists of combining high-resolution simulations of Regional Climate Models (RCMs) to statistical downscaling methods. The present work is based on such an approach. It aims at investigating the impacts of climate change on snow cover in the French Alps for the periods 2021-2050 and 2071-2100 under several IPCC hypotheses. An analogue method based on high resolution atmospheric fields from various RCMs and climate reanalyses is used to simulate local climate scenarios. These scenarios, which provide meteorological parameters relevant for snowpack evolution, subsequently feed the CROCUS snow model. In these simulations, various sources of uncertainties are thus considered (several greenhouse gases emission scenarios and RCMs). Results are obtained for different regions of the French Alps at various altitudes. For all scenarios, temperature increase is relatively uniform over the Alps. This regional warming is larger than that generally modeled at the global scale (IPCC, 2007), and particularly strong in summer. Annual precipitation amounts seem to decrease, mainly as a result of decreasing precipitation trends in summer and fall. As a result of these climatic evolutions, there is a general decrease of the mean winter snow depth and seasonal snow duration for all massifs. Winter snow depths are particularly reduced in the Northern Alps. However, the impact on seasonal snow duration is more significant in the Southern and Extreme Southern Alps, since these regions are already characterized by small winter snow depths at low elevations. Reference : IPCC (2007a). Climate change 2007 : The physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. In : Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H.L. Miller (eds.). Cambridge University Press, Cambridge, UK and New York, NY, USA. This work is performed in the framework of the SCAMPEI ANR (French research project).

Relative importance of thermal versus carbon dioxide induced warming from fossil-fuel combustion

NASA Astrophysics Data System (ADS)

Zhang, X.; Caldeira, K.

2015-12-01

The Earth is heated both when reduced carbon is oxidized to carbon dioxide and when outgoing longwave radiation is trapped by carbon dioxide in the atmosphere (CO2 greenhouse effect). The purpose of this study is to improve our understanding of time scales and relative magnitudes of climate forcing increase over time from pulse, continuous, and historical CO2 and thermal emissions. To estimate the amount of global warming that would be produced by thermal and CO2 emissions from fossil fuel combustion, we calculate thermal emissions with thermal contents of fossil fuels and estimate CO2 emissions with emission factors from Intergovernmental Panel on Climate Change (IPCC) AR5. We then use a schematic climate model mimicking Coupled Model Intercomparison Project Phase 5 to investigate the climate forcing and the time-integrated climate forcing. We show that, considered globally, direct thermal forcing from fossil fuel combustion is about 1.71% the radiative forcing from CO2 that has accumulated in the atmosphere from past fossil fuel combustion. When a new power plant comes on line, the radiative forcing from the accumulation of released CO2 exceeds the thermal emissions from the power plant in less than half a year (and about 3 months for coal plants). Due to the long lifetime of CO2 in the atmosphere, CO2 radiative forcing greatly overwhelms direct thermal forcing on longer time scales. Ultimately, the cumulative radiative forcing from the CO2 exceeds the direct thermal forcing by a factor of ~100,000.

Global trends and variability in integrated water vapour from ground-based GPS data and atmospheric models

NASA Astrophysics Data System (ADS)

Bock, Olivier; Parracho, Ana; Bastin, Sophie; Hourdin, Frededic; Mellul, Lidia

2016-04-01

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

Satellite bulk tropospheric temperatures as a metric for climate sensitivity

NASA Astrophysics Data System (ADS)

Christy, John R.; McNider, Richard T.

2017-11-01

We identify and remove the main natural perturbations (e.g. volcanic activity, ENSOs) from the global mean lower tropospheric temperatures ( T LT ) over January 1979 - June 2017 to estimate the underlying, potentially human-forced trend. The unaltered value is +0.155 K dec-1 while the adjusted trend is +0.096 K dec-1, related primarily to the removal of volcanic cooling in the early part of the record. This is essentially the same value we determined in 1994 (+0.09 K dec-1, Christy and McNider, 1994) using only 15 years of data. If the warming rate of +0.096 K dec-1 represents the net T LT response to increasing greenhouse radiative forcings, this implies that the T LT tropospheric transient climate response (Δ T LT at the time CO2 doubles) is +1.10 ± 0.26 K which is about half of the average of the IPCC AR5 climate models of 2.31 ± 0.20 K. Assuming that the net remaining unknown internal and external natural forcing over this period is near zero, the mismatch since 1979 between observations and CMIP-5 model values suggests that excessive sensitivity to enhanced radiative forcing in the models can be appreciable. The tropical region is mainly responsible for this discrepancy suggesting processes that are the likely sources of the extra sensitivity are (a) the parameterized hydrology of the deep atmosphere, (b) the parameterized heat-partitioning at the oceanatmosphere interface and/or (c) unknown natural variations.

An evaluation of the treatment of risk and uncertainties in the IPCC reports on climate change.

PubMed

Aven, Terje; Renn, Ortwin

2015-04-01

Few global threats rival global climate change in scale and potential consequence. The principal international authority assessing climate risk is the Intergovernmental Panel on Climate Change (IPCC). Through repeated assessments the IPCC has devoted considerable effort and interdisciplinary competence to articulating a common characterization of climate risk and uncertainties. We have reviewed the assessment and its foundation for the Fifth Assessment Reports published in 2013 and 2014, in particular the guidance note for lead authors of the fifth IPCC assessment report on consistent treatment of uncertainties. Our analysis shows that the work carried out by the ICPP is short of providing a theoretically and conceptually convincing foundation on the treatment of risk and uncertainties. The main reasons for our assessment are: (i) the concept of risk is given a too narrow definition (a function of consequences and probability/likelihood); and (ii) the reports lack precision in delineating their concepts and methods. The goal of this article is to contribute to improving the handling of uncertainty and risk in future IPCC studies, thereby obtaining a more theoretically substantiated characterization as well as enhanced scientific quality for risk analysis in this area. Several suggestions for how to improve the risk and uncertainty treatment are provided. © 2014 Society for Risk Analysis.

Global air quality and climate.

PubMed

Fiore, Arlene M; Naik, Vaishali; Spracklen, Dominick V; Steiner, Allison; Unger, Nadine; Prather, Michael; Bergmann, Dan; Cameron-Smith, Philip J; Cionni, Irene; Collins, William J; Dalsøren, Stig; Eyring, Veronika; Folberth, Gerd A; Ginoux, Paul; Horowitz, Larry W; Josse, Béatrice; Lamarque, Jean-François; MacKenzie, Ian A; Nagashima, Tatsuya; O'Connor, Fiona M; Righi, Mattia; Rumbold, Steven T; Shindell, Drew T; Skeie, Ragnhild B; Sudo, Kengo; Szopa, Sophie; Takemura, Toshihiko; Zeng, Guang

2012-10-07

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.

Implementation Targets for the Paris Climate Agreement

NASA Astrophysics Data System (ADS)

Bennett, B.; Hope, A. P.; Tribett, W. R.; Salawitch, R. J.; Canty, T. P.

2016-12-01

We provide an overview of reductions in the emission of greenhouse gases (GHGs) needed to achieve either the target (1.5 °C warming) or upper limit (2.0 °C warming) of the Paris Climate Agreement. We will show how much energy must be produced, either by renewables that do not emit significant levels of atmospheric GHGs or via carbon capture and sequestration (CCS) coupled to fossil fuel power plants, to meet forecast global energy demand out to 2060. These projections will be based on two modeling frameworks: our empirical model of global climate (EM-GC) and the CMIP 5 GCMs used throughout IPCC (2013). For each framework, we will show estimates of transient climate response to cumulative emission of carbon to place limits on future emission of CO2 via the combustion of fossil fuel. We will also quantify the impact of future atmospheric CH4 on achieving the goals of the Paris Climate Agreement.

Aerosol–climate interactions in the Norwegian Earth System Model – NorESM1-M

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

Kirkevåg, A.; Iversen, T.; Seland, Ø.

2013-01-01

The objective of this study is to document and evaluate recent changes and updates to the module for aerosols and aerosol–cloud–radiation interactions in the atmospheric module CAM4-Oslo of the core version of the Norwegian Earth System Model (NorESM), NorESM1-M. Particular attention is paid to the role of natural organics, sea salt, and mineral dust in determining the gross aerosol properties as well as the anthropogenic contribution to these properties and the associated direct and indirect radiative forcing. The aerosol module is extended from earlier versions that have been published, and includes life-cycling of sea salt, mineral dust, particulate sulphate, blackmore » carbon, and primary and secondary organics. The impacts of most of the numerous changes since previous versions are thoroughly explored by sensitivity experiments. The most important changes are: modified prognostic sea salt emissions; updated treatment of precipitation scavenging and gravitational settling; inclusion of biogenic primary organics and methane sulphonic acid (MSA) from oceans; almost doubled production of land-based biogenic secondary organic aerosols (SOA); and increased ratio of organic matter to organic carbon (OM/OC) for biomass burning aerosols from 1.4 to 2.6. Compared with in situ measurements and remotely sensed data, the new treatments of sea salt and dust aerosols give smaller biases in near-surface mass concentrations and aerosol optical depth than in the earlier model version. The model biases for mass concentrations are approximately unchanged for sulphate and BC. The enhanced levels of modeled OM yield improved overall statistics, even though OM is still underestimated in Europe and overestimated in North America. The global anthropogenic aerosol direct radiative forcing (DRF) at the top of the atmosphere has changed from a small positive value to -0.08 W m-2 in CAM4-Oslo. The sensitivity tests suggest that this change can be attributed to the new treatment of biomass burning aerosols and gravitational settling. Although it has not been a goal in this study, the new DRF estimate is closer both to the median model estimate from the AeroCom intercomparison and the best estimate in IPCC AR4. Estimated DRF at the ground surface has increased by ca. 60%, to -1.89 W m-2. We show that this can be explained by new emission data and omitted mixing of constituents between updrafts and downdrafts in convective clouds. The increased abundance of natural OM and the introduction of a cloud droplet spectral dispersion formulation are the most important contributions to a considerably decreased estimate of the indirect radiative forcing (IndRF). The IndRF is also found to be sensitive to assumptions about the coating of insoluble aerosols by sulphate and OM. The IndRF of -1.2 W m-2, which is closer to the IPCC AR4 estimates than the previous estimate of -1.9 W m-2, has thus been obtained without imposing unrealistic artificial lower bounds on cloud droplet number concentrations.« less

Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.

Climate Benchmark Missions: CLARREO

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, David F.

2010-01-01

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.

Estimating Amazonian rainforest stability and the likelihood for large-scale forest dieback

NASA Astrophysics Data System (ADS)

Rammig, Anja; Thonicke, Kirsten; Jupp, Tim; Ostberg, Sebastian; Heinke, Jens; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter

2010-05-01

Annually, tropical forests process approximately 18 Pg of carbon through respiration and photosynthesis - more than twice the rate of anthropogenic fossil fuel emissions. Current climate change may be transforming this carbon sink into a carbon source by changing forest structure and dynamics. Increasing temperatures and potentially decreasing precipitation and thus prolonged drought stress may lead to increasing physiological stress and reduced productivity for trees. Resulting decreases in evapotranspiration and therefore convective precipitation could further accelerate drought conditions and destabilize the tropical ecosystem as a whole and lead to an 'Amazon forest dieback'. The projected direction and intensity of climate change vary widely within the region and between different scenarios from climate models (GCMs). In the scope of a World Bank-funded study, we assessed the 24 General Circulation Models (GCMs) evaluated in the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4) with respect to their capability to reproduce present-day climate in the Amazon basin using a Bayesian approach. With this approach, greater weight is assigned to the models that simulate well the annual cycle of rainfall. We then use the resulting weightings to create probability density functions (PDFs) for future forest biomass changes as simulated by the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJmL) to estimate the risk of potential Amazon rainforest dieback. Our results show contrasting changes in forest biomass throughout five regions of northern South America: If photosynthetic capacity and water use efficiency is enhanced by CO2, biomass increases across all five regions. However, if CO2-fertilisation is assumed to be absent or less important, then substantial dieback occurs in some scenarios and thus, the risk of forest dieback is considerably higher. Particularly affected are regions in the central Amazon basin. The range of potential biomass change arising from the weighting of rainfall patterns is smaller than the uncertainty arising from CO2-fertilisation effects, which highlights the importance of reducing the uncertainties in the direct effects of CO2 on tropical ecosystems. Strong biomass changes also imply changes in forest structure and thus, forest stability. Our results display shifts in forest composition from closed rainforest to more open forest or even shrubland. Our probability-based risk analysis could be used to advise regional forest protection.

Cost analysis of impacts of climate change on regional air quality.

PubMed

Liao, Kuo-Jen; Tagaris, Efthimios; Russell, Armistead G; Amar, Praveen; He, Shan; Manomaiphiboon, Kasemsan; Woo, Jung-Hun

2010-02-01

Climate change has been predicted to adversely impact regional air quality with resulting health effects. Here a regional air quality model and a technology analysis tool are used to assess the additional emission reductions required and associated costs to offset impacts of climate change on air quality. Analysis is done for six regions and five major cities in the continental United States. Future climate is taken from a global climate model simulation for 2049-2051 using the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario, and emission inventories are the same as current ones to assess impacts of climate change alone on air quality and control expenses. On the basis of the IPCC A1B emission scenario and current control technologies, least-cost sets of emission reductions for simultaneously offsetting impacts of climate change on regionally averaged 4th highest daily maximum 8-hr average ozone and yearly averaged PM2.5 (particulate matter [PM] with an aerodynamic diameter less than 2.5 microm) for the six regions examined are predicted to range from $36 million (1999$) yr(-1) in the Southeast to $5.5 billion yr(-1) in the Northeast. However, control costs to offset climate-related pollutant increases in urban areas can be greater than the regional costs because of the locally exacerbated ozone levels. An annual cost of $4.1 billion is required for offsetting climate-induced air quality impairment in 2049-2051 in the five cities alone. Overall, an annual cost of $9.3 billion is estimated for offsetting climate change impacts on air quality for the six regions and five cities examined. Much of the additional expense is to reduce increased levels of ozone. Additional control costs for offsetting the impacts everywhere in the United States could be larger than the estimates in this study. This study shows that additional emission controls and associated costs for offsetting climate impacts could significantly increase currently estimated control requirements and should be considered in developing control strategies for achieving air quality targets in the future.

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

PubMed

Xie, Gisselle Yang; Olson, Deanna H; Blaustein, Andrew R

2016-01-01

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

Constraints on Global Aerosol Types: Past, Present, and Near-Future

NASA Astrophysics Data System (ADS)

Kahn, Ralph

2014-05-01

Although the recent IPCC fifth assessment report (AR5) suggests that confidence in estimated direct aerosol radiative forcing (DARF) is high, indications are that there is little agreement among current climate models about the global distribution of aerosol single-scattering albedo (SSA). SSA must be associated with specific surface albedo and aerosol optical depth (AOD) values to calculate DARF with confidence, and global-scale constraints on aerosol type, including SSA, are poor at present. Yet, some constraints on aerosol type have been demonstrated for several satellite instruments, including the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR). The time-series of approximately once-weekly, global MISR observations has grown to about 14 years. The MISR capability amounts to three-to-five bins in particle size, two-to-four bins in SSA, and spherical vs. non-spherical particle distinctions, under good retrieval conditions. As the record of coincident, suborbital validation data has increased steadily, it has become progressively more feasible to assess and to improve the operational algorithm constraints on aerosol type. This presentation will discuss planned refinements to the MISR operational algorithm, and will highlight recent efforts at using MISR results to help better represent wildfire smoke, volcanic ash, and urban pollution in climate models.

Rebased Global Mean Temperature comparisons between Global Climate Models and observed Global Mean Temperature: constraints and implications

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2017-12-01

One of the benchmarks of global climate models (GCMs) is that their slow, decadal or longer timescale variations in past changes in Global Mean Temperature (GMT) track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other by as much as 3 degrees [2]. Subtracting these offsets, or rebasing, is an integral part of comparisons between observed past GMT and the GMT anomalies generated by ensembles of GCMs. We will formalize how rebasing introduces constraints in how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear. Feedbacks in the different models when expressed through GMT are then to leading order linear. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, given the appropriate effective heat capacity and feedback parameters. As a consequence, the GMT timeseries future projections generated by the GCMs may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8, IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012]4, IPCC SPM.6

Final Technical Report for Project "Improving the Simulation of Arctic Clouds in CCSM3"

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

Stephen J. Vavrus

2008-11-15

This project has focused on the simulation of Arctic clouds in CCSM3 and how the modeled cloud amount (and climate) can be improved substantially by altering the parameterized low cloud fraction. The new formula, dubbed 'freeezedry', alleviates the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic (Fig. 1). The cloud reduction causes an Arctic-wide drop of 15 W m{sup -2} in surface cloud radiativemore » forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2-8 K over the Arctic Ocean, thus significantly reducing the model's pronounced warm bias (Fig. 1). While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions (Fig. 2) or during summer (Fig. 3), which are space and time domains that were not targeted. Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness, based on the results from the CMIP3 archive (Vavrus et al., 2008). Freezedry also affects CCSM3's sensitivity to greenhouse forcing. In a transient-CO{sub 2} experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5 K and 0.5 K smaller warming, respectively) (Fig. 4). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during non-summer months (when clouds warm the surface), apparently because of the colder modern reference climate. These results of the freezedry parameterization have recently been published (Vavrus and D. Waliser, 2008: An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model. J. Climate, 21, 5673-5687.). The article also provides a novel synthesis of surface- and satellite-based Arctic cloud observations that show how much the new freezedry parameterization improves the simulated cloud amount in high latitudes (Fig. 3). Freezedry has been incorporated into the CCSM3.5 version, in which it successfully limits the excessive polar clouds, and may be used in CCSM4. Material from this work is also appearing in a synthesis article on future Arctic cloud changes (Vavrus, D. Waliser, J. Francis, and A. Schweiger, 'Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4', accepted in Climate Dynamics) and was used in a collaborative paper on Arctic cloud-sea ice coupling (Schweiger, A., R. Lindsay, S. Vavrus, and J. Francis, 2008: Relationships between Arctic sea ice and clouds during autumn. J. Climate, 21, 4799-4810.). This research was presented at the 2007 CCSM Annual Workshop, as well as the CCSM's 2007 Atmospheric Model Working Group and Polar Working Group Meetings. The findings were also shown at the 2007 Climate Change Prediction Program's Science Team Meeting. In addition, I served as an instructor at the International Arctic Research Center's (IARC) Summer School on Arctic Climate Modeling in Fairbanks this summer, where I presented on the challenges and techniques used in simulating polar clouds. I also contributed to the development of a new Arctic System Model by attending a workshop in Colorado this summer on this fledgling project. Finally, an outreach activity for the general public has been the development of an interactive web site () that displays Arctic cloud amount in the CMIP3 climate model archive under present and future scenarios. This site allows users to make polar and global maps of a variety of climate variables to investigate the individual and ensemble-mean GCM response to greenhouse warming and the extent to which models adequately represent Arctic clouds in the modern climate. This site was used extensively in the IARC summer school projects. This work has also led to a collaboration this year during a 4-month visit I made to NCAR through its Faculty Fellowship Program. I worked with scientists Marika Holland, David Bailey, Andrew Gettleman, and Jen Kay, who are researching polar climate and/or clouds. I met with this group frequently during my visit, leading to some fruitful interactions. This work led to the discovery of a tightly coupled response of clouds and sea ice during intervals of rapid sea ice loss in greenhouse simulations, as well as advising on the evolving CCSM3.5 to CCSM4 model development. This involvement with NCAR also led to a longer-term connection, as I have recently begun a two-year stint on the SSC for CCSM.« less

Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia

NASA Astrophysics Data System (ADS)

Anisimov, Oleg; Kokorev, Vasily

2013-04-01

Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections.

Aquatic Ecosystem Services in the 21st Century Northeast Corridor: Assessment Using a Regional Earth System Model

NASA Astrophysics Data System (ADS)

Rosenzweig, B.; Miara, A.; Stewart, R. J.; Wollheim, W. M.; Vorosmarty, C. J.

2012-12-01

Aquatic ecosystems of the Northeast United States will be significantly impacted by both global climate change and the regional-scale strategic management decisions made in the next few years. We have developed a Regional Earth System Model for the Northeast Corridor (NE-RESM) that simulates the impacts of climate, land use, and development policy on the interacting cycles of energy, water, carbon and nutrients. The NE-RESM will provide a unique and critically needed tool for policymakers to understand how their current decisions will impact ecosystem services over the 21st Century. To test our modeling framework, we conducted a retrospective experiment focusing on the water-energy-economy nexus during the period 2000-2010. Component models were developed to 'translate' physical outputs from the NE-RESM - such as stream discharge and water temperature - into ecosystem services including water regulation for thermoelectric cooling and the ability for streams to serve as a refugia for wildlife. Simulations were performed both with and without Clean Water Act limits on thermal pollution. Through this work, we were able to obtain spatially distributed information on how these laws impact power generation by the thermoelectric sector but also enable Northeast streams to serve as habitat for temperature-sensitive aquatic species (Brook Trout, Atlantic Salmon, River Herring and the American Eel). Our ongoing research examines future climate and policy scenarios through 2100. We are considering the impact of changing land cover patterns (a return to agriculture vs. suburban sprawl) and various strategies to meet energy and municipal water needs under different Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change's Fifth Assessment Report (IPCC AR5).

IPCC reasons for concern regarding climate change risks

NASA Astrophysics Data System (ADS)

O'Neill, Brian C.; Oppenheimer, Michael; Warren, Rachel; Hallegatte, Stephane; Kopp, Robert E.; Pörtner, Hans O.; Scholes, Robert; Birkmann, Joern; Foden, Wendy; Licker, Rachel; Mach, Katharine J.; Marbaix, Phillippe; Mastrandrea, Michael D.; Price, Jeff; Takahashi, Kiyoshi; van Ypersele, Jean-Pascal; Yohe, Gary

2017-01-01

The reasons for concern framework communicates scientific understanding about risks in relation to varying levels of climate change. The framework, now a cornerstone of the IPCC assessments, aggregates global risks into five categories as a function of global mean temperature change. We review the framework's conceptual basis and the risk judgments made in the most recent IPCC report, confirming those judgments in most cases in the light of more recent literature and identifying their limitations. We point to extensions of the framework that offer complementary climate change metrics to global mean temperature change and better account for possible changes in social and ecological system vulnerability. Further research should systematically evaluate risks under alternative scenarios of future climatic and societal conditions.

Creating Near-Term Climate Scenarios for AgMIP

NASA Astrophysics Data System (ADS)

Goddard, L.; Greene, A. M.; Baethgen, W.

2012-12-01

For the next assessment report of the IPCC (AR5), attention is being given to development of climate information that is appropriate for adaptation, such as decadal-scale and near-term predictions intended to capture the combined effects of natural climate variability and the emerging climate change signal. While the science and practice evolve for the production and use of dynamic decadal prediction, information relevant to agricultural decision-makers can be gained from analysis of past decadal-scale trends and variability. Statistical approaches that mimic the characteristics of observed year-to-year variability can indicate the range of possibilities and their likelihood. In this talk we present work towards development of near-term climate scenarios, which are needed to engage decision-makers and stakeholders in the regions in current decision-making. The work includes analyses of decadal-scale variability and trends in the AgMIP regions, and statistical approaches that capture year-to-year variability and the associated persistence of wet and dry years. We will outline the general methodology and some of the specific considerations in the regional application of the methodology for different AgMIP regions, such those for Western Africa versus southern Africa. We will also show some examples of quality checks and informational summaries of the generated data, including (1) metrics of information quality such as probabilistic reliability for a suite of relevant climate variables and indices important for agriculture; (2) quality checks relative to the use of this climate data in crop models; and, (3) summary statistics (e.g., for 5-10-year periods or across given spatial scales).

Scientific Integrity and Consensus in the Intergovernmental Panel on Climate Change Assessment Process

NASA Astrophysics Data System (ADS)

Barrett, K.

2017-12-01

Scientific integrity is the hallmark of any assessment and is a paramount consideration in the Intergovernmental Panel on Climate Change (IPCC) assessment process. Procedures are in place for rigorous scientific review and to quantify confidence levels and uncertainty in the communication of key findings. However, the IPCC is unique in that its reports are formally accepted by governments through consensus agreement. This presentation will present the unique requirements of the IPCC intergovernmental assessment and discuss the advantages and challenges of its approach.

Impact of climate change on Precipitation and temperature under the RCP 8.5 and A1B scenarios in an Alpine Cathment (Alto-Genil Basin,southeast Spain). A comparison of statistical downscaling methods

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Juan Collados-Lara, Antonio; Pardo-Iguzquiza, Eulogio; Jimeno-Saez, Patricia; Fernandez-Chacon, Francisca

2016-04-01

In order to design adaptive strategies to global change we need to assess the future impact of climate change on water resources, which depends on precipitation and temperature series in the systems. The objective of this work is to generate future climate series in the "Alto Genil" Basin (southeast Spain) for the period 2071-2100 by perturbing the historical series using different statistical methods. For this targeted we use information coming from regionals climate model simulations (RCMs) available in two European projects, CORDEX (2013), with a spatial resolution of 12.5 km, and ENSEMBLES (2009), with a spatial resolution of 25 km. The historical climate series used for the period 1971-2000 have been obtained from Spain02 project (2012) which has the same spatial resolution that CORDEX project (both use the EURO-CORDEX grid). Two emission scenarios have been considered: the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC), and the A1B emission scenario of fourth Assessment Report (AR4). We use the RCM simulations to create an ensemble of predictions weighting their information according to their ability to reproduce the main statistic of the historical climatology. A multi-objective analysis has been performed to identify which models are better in terms of goodness of fit to the cited statistic of the historical series. The ensemble of the CORDEX and the ENSEMBLES projects has been finally created with nine and four models respectively. These ensemble series have been used to assess the anomalies in mean and standard deviation (differences between the control and future RCM series). A "delta-change" method (Pulido-Velazquez et al., 2011) has been applied to define future series by modifying the historical climate series in accordance with the cited anomalies in mean and standard deviation. A comparison between results for scenario A1B and RCP8.5 has been performed. The reduction obtained for the mean rainfall respect to the historical are 24.2 % and 24.4 % respectively, and the increment in the temperature are 46.3 % and 31.2 % respectively. A sensitivity analysis of the results to the statistical downscaling techniques employed has been performed. The next techniques have been explored: Perturbation method or "delta-change"; Regression method (a regression function which relates the RCM and the historic information will be used to generate future climate series for the fixed period); Quantile mapping, (it attempts to find a transformation function which relates the observed variable and the modeled variable maintaining an statistical distribution equals the observed variable); Stochastic weather generator (SWG): They can be uni-site or multi-site (which considers the spatial correlation of climatic series). A comparative analysis of these techniques has been performed identifying the advantages and disadvantages of each of them. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02, ENSEMBLES and CORDEX projects for the data provided for this study.

Bias correction in Global Mean Temperature comparisons between Global Climate Models and implications for the deterministic and stochastic dynamics

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2017-04-01

Global mean temperature (GMT) provides a simple means of benchmarking a broad ensemble of global climate models (GCMs) against past observed GMT which in turn provide headline assessments of the consequences of possible future forcing scenarios. The slow variations of past changes in GMT seen in different GCMs track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other [2]. Subtracting these offsets is an integral part of comparisons between ensembles of GCMs and observed past GMT. We will discuss how this constrains how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same, subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear; any feedback is to leading order linear in GMT. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, provided that the appropriate effective heat capacity and feedback parameters are known. As a consequence, the GCM's GMT timeseries may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8,IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012] 4, IPCC SPM.6

Intergovernmental Panel on Climate Change. First Assessment Report Overview.

ERIC Educational Resources Information Center

International Environmental Affairs, 1991

1991-01-01

Presented are policymakers' summaries of the three working groups of the Intergovernmental Panel on Climate Change (IPCC)--science, impacts, and response strategies, the report of the IPCC Special Committee on the Participation of Developing Countries, and a discussion of international cooperation and future work. (CW)

IPCC Methodologies for the Waste Sector: Past, Present, and Future

USDA-ARS?s Scientific Manuscript database

The reporting of national greenhouse gas (GHG) emissions began more than a decade ago by the signatory countries of the United Nations Framework Convention on Climate Change (UNFCCC). National GHG inventories rely on the evolving Intergovernmental Panel on Climate Change (IPCC) national GHG inventor...

Climate Change Policy

NASA Astrophysics Data System (ADS)

Jepma, Catrinus J.; Munasinghe, Mohan; Bolin, Foreword By Bert; Watson, Robert; Bruce, James P.

1998-03-01

There is increasing scientific evidence to suggest that humans are gradually but certainly changing the Earth's climate. In an effort to prevent further damage to the fragile atmosphere, and with the belief that action is required now, the scientific community has been prolific in its dissemination of information on climate change. Inspired by the results of the Intergovernmental Panel on Climate Change's Second Assessment Report, Jepma and Munasinghe set out to create a concise, practical, and compelling approach to climate change issues. They deftly explain the implications of global warming, and the risks involved in attempting to mitigate climate change. They look at how and where to start action, and what organization is needed to be able to implement the changes. This book represents a much needed synopsis of climate change and its real impacts on society. It will be an essential text for climate change researchers, policy analysts, university students studying the environment, and anyone with an interest in climate change issues. A digestible version of the IPCC 1995 Economics Report - written by two of IPCC contributors with a Foreword by two of the editors of Climate Change 1995: Economics of Climate Change: i.e. has unofficial IPCC approval Focusses on policy and economics - important but of marginal interest to scientists, who are more likely to buy this summary than the full IPCC report itself Has case-studies to get the points across Separate study guide workbook will be available, mode of presentation (Web or book) not yet finalized

The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution

NASA Astrophysics Data System (ADS)

Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.

2012-12-01

Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately. These results will strengthen our understanding of the impacts of climate change today, and in future years considering different plausible scenarios.

U.S. ozone air quality under changing climate and anthropogenic emissions.

PubMed

Racherla, Pavan N; Adams, Peter J

2009-02-01

We examined future ozone (O3) air quality in the United States (U.S.) under changing climate and anthropogenic emissions worldwide by performing global climate-chemistry simulations, utilizing various combinations of present (1990s) and future (Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 2050s) climates, and present and future (2050s; IPCC SRES A2 and B1) anthropogenic emissions. The A2 climate scenario is employed here because it lies at the upper extreme of projected climate change for the 21st century. To examine the sensitivity of U.S. O3 to regional emissions increases (decreases), the IPCC SRES A2 and B1 scenarios, which have overall higher and lower O3-precursor emissions for the U.S., respectively, have been chosen. We find that climate change, by itself, significantly worsens the severity and frequency of high-O3 events ("episodes") over most locations in the U.S., with relatively small changes in average O3 air quality. These high-O3 increases due to climate change alone will erode moderately the gains made under a U.S. emissions reduction scenario (e.g., B1). The effect of climate change on high- and average-O3 increases with anthropogenic emissions. Insofar as average O3 air quality is concerned, changes in U.S. anthropogenic emissions will play the most important role in attaining (or not) near-term U.S. O3 air quality standards. However, policy makers must plan appropriately for O3 background increases due to projected increases in global CH4 abundance and non-U.S. anthropogenic emissions, as well as potential local enhancements that they could cause. These findings provide strong incentives for more-than-planned emissions reductions at locations that are currently O3-nonattainment.

Climate-suitable planting as a strategy for maintaining forest productivity and functional diversity.

PubMed

Duveneck, Matthew J; Scheller, Robert M

2015-09-01

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass).

European drought under climate change and an assessment of the uncertainties in projections

NASA Astrophysics Data System (ADS)

Yu, R. M. S.; Osborn, T.; Conway, D.; Warren, R.; Hankin, R.

2012-04-01

Extreme weather/climate events have significant environmental and societal impacts, and anthropogenic climate change has and will continue to alter their characteristics (IPCC, 2011). Drought is one of the most damaging natural hazards through its effects on agricultural, hydrological, ecological and socio-economic systems. Climate change is stimulating demand, from public and private sector decision-makers and also other stakeholders, for better understanding of potential future drought patterns which could facilitate disaster risk management. There remain considerable levels of uncertainty in climate change projections, particularly in relation to extreme events. Our incomplete understanding of the behaviour of the climate system has led to the development of various emission scenarios, carbon cycle models and global climate models (GCMs). Uncertainties arise also from the different types and definitions of drought. This study examines climate change-induced changes in European drought characteristics, and illustrates the robustness of these projections by quantifying the effects of using different emission scenarios, carbon cycle models and GCMs. This is achieved by using the multi-institutional modular "Community Integrated Assessment System (CIAS)" (Warren et al., 2008), a flexible integrated assessment system for modelling climate change. Simulations generated by the simple climate model MAGICC6.0 are assessed. These include ten C4MIP carbon cycle models and eighteen CMIP3 GCMs under five IPCC SRES emission scenarios, four Representative Concentration Pathway (RCP) scenarios, and three mitigation scenarios with CO2-equivalent levels stabilising at 550 ppm, 500 ppm and 450 ppm. Using an ensemble of 2160 future precipitation scenarios, we present an analysis on both short (3-month) and long (12-month) meteorological droughts based on the Standardised Precipitation Index (SPI) for the baseline period (1951-2000) and two future periods of 2001-2050 and 2051-2100. Results indicate, with the exception of high latitude regions, a marked increase in drought condition across Europe especially in the second half of 21st century. Patterns, however, vary substantially depending on the model, emission scenario, region and season. While the variance introduced by choice of carbon cycle model is of minor importance, contribution of emission scenario becomes more important in the second half of the century; nevertheless, GCM uncertainty remains the dominant source throughout the 21st century and across all regions.

Finding the CO[subscript 2] Culprit

ERIC Educational Resources Information Center

Clary, Renee; Wandersee, James

2015-01-01

In 2013, the Intergovernmental Panel on Climate Change (IPCC) released its fifth report, attributing 95% of "all" climate warming--from the 1950s through today--to humans. Not only did the report--like previous IPCC reports dating back to 1990--accredit global warming to anthropogenic carbon dioxide emissions, but over time the vast…

Evaluating the use of verbal probability expressions to communicate likelihood information in IPCC reports

NASA Astrophysics Data System (ADS)

Harris, Adam

2014-05-01

The Intergovernmental Panel on Climate Change (IPCC) prescribes that the communication of risk and uncertainty information pertaining to scientific reports, model predictions etc. be communicated with a set of 7 likelihood expressions. These range from "Extremely likely" (intended to communicate a likelihood of greater than 99%) through "As likely as not" (33-66%) to "Extremely unlikely" (less than 1%). Psychological research has investigated the degree to which these expressions are interpreted as intended by the IPCC, both within and across cultures. I will present a selection of this research and demonstrate some problems associated with communicating likelihoods in this way, as well as suggesting some potential improvements.

Losing ground: past history and future fate of Arctic small mammals in a changing climate.

PubMed

Prost, Stefan; Guralnick, Robert P; Waltari, Eric; Fedorov, Vadim B; Kuzmina, Elena; Smirnov, Nickolay; van Kolfschoten, Thijs; Hofreiter, Michael; Vrieling, Klaas

2013-06-01

According to the IPCC, the global average temperature is likely to increase by 1.4-5.8 °C over the period from 1990 to 2100. In Polar regions, the magnitude of such climatic changes is even larger than in temperate and tropical biomes. This amplified response is particularly worrisome given that the so-far moderate warming is already impacting Arctic ecosystems. Predicting species responses to rapid warming in the near future can be informed by investigating past responses, as, like the rest of the planet, the Arctic experienced recurrent cycles of temperature increase and decrease (glacial-interglacial changes) in the past. In this study, we compare the response of two important prey species of the Arctic ecosystem, the collared lemming and the narrow-skulled vole, to Late Quaternary climate change. Using ancient DNA and Ecological Niche Modeling (ENM), we show that the two species, which occupy similar, but not identical ecological niches, show markedly different responses to climatic and environmental changes within broadly similar habitats. We empirically demonstrate, utilizing coalescent model-testing approaches, that collared lemming populations decreased substantially after the Last Glacial Maximum; a result consistent with distributional loss over the same period based on ENM results. Given this strong association, we projected the current niche onto future climate conditions based on IPCC 4.0 scenarios, and forecast accelerating loss of habitat along southern range boundaries with likely associated demographic consequences. Narrow-skulled vole distribution and demography, by contrast, was only moderately impacted by past climatic changes, but predicted future changes may begin to affect their current western range boundaries. Our work, founded on multiple lines of evidence suggests a future of rapidly geographically shifting Arctic small mammal prey communities, some of whom are on the edge of existence, and whose fate may have ramifications for the whole Arctic food web and ecosystem. © 2013 Blackwell Publishing Ltd.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Toward server-side, high performance climate change data analytics in the Earth System Grid Federation (ESGF) eco-system

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Williams, Dean; Aloisio, Giovanni

2016-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated (e.g., the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Most of the tools currently available for scientific data analysis in the climate domain fail at large scale since they: (1) are desktop based and need the data locally; (2) are sequential, so do not benefit from available multicore/parallel machines; (3) do not provide declarative languages to express scientific data analysis tasks; (4) are domain-specific, which ties their adoption to a specific domain; and (5) do not provide a workflow support, to enable the definition of complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes ("datacubes"). The project relies on a strong background of high performance database management and OLAP systems to manage large scientific data sets. It also provides a native workflow management support, to define processing chains and workflows with tens to hundreds of data analytics operators to build real scientific use cases. With regard to interoperability aspects, the talk will present the contribution provided both to the RDA Working Group on Array Databases, and the Earth System Grid Federation (ESGF) Compute Working Team. Also highlighted will be the results of large scale climate model intercomparison data analysis experiments, for example: (1) defined in the context of the EU H2020 INDIGO-DataCloud project; (2) implemented in a real geographically distributed environment involving CMCC (Italy) and LLNL (US) sites; (3) exploiting Ophidia as server-side, parallel analytics engine; and (4) applied on real CMIP5 data sets available through ESGF.

Accounting for wetlands loss in a changing climate in the estimation of long-term flood risks of Devils Lake, North Dakota

NASA Astrophysics Data System (ADS)

Gulbin, S.; Kirilenko, A.; Zhang, X.

2016-12-01

Endorheic (terminal) lakes with no water outlets are sensitive indicators of changes in climate and land cover in the watershed. Regional variation in precipitation pattern in the US Northern Great Plaines lead to a long term flooding of Devils Lake (DL), ND, leading to a 10-m water level rise in just two decades, with estimated flood mitigation costs of over $1 billion. While the climate change contribution to flooding has been established, the role of large scale land conversion to agriculture has not been researched. Wetlands play a very important part in hydrological balance by storing, absorbing and slowing peak water discharge. In ND, 49 % of wetlands are drained and converted to agriculture. We investigated the role of wetlands loss in DL flooding in current and future climate. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow in all DL watershed subbasins. The model was calibrated using the 1991-2000 USGS gauge data for the first 10 years of study period and validated for the second 10 years (2001-2010), resulting in a satisfactory model performance compared against the measured water discharge in five streams in the watershed and against observed DL water level. A set of wetland loss scenarios were created based on the historical data and the Compound Topographic Index. To emulate the historical and future climate conditions, an ensemble of CMIP5 weather integrations based on IPCC AR5 RCP scenarios was downscaled with the MarkSim weather simulator. Model simulations indicate that the land use change in the DL watershed increased the impacts of climate change on hydrology by further elevating DL water level. Conversely, wetland restoration reduce the flooding and moderates risks of a potential high-impact DL overspill to the Sheyenne River watershed. Further research will concentrate on differentiation of climate change impacts under different types of land use change scenarios.

Assessment of the aerosol distribution over Indian subcontinent in CMIP5 models

NASA Astrophysics Data System (ADS)

Sanap, S. D.; Ayantika, D. C.; Pandithurai, G.; Niranjan, K.

2014-04-01

This paper examines the aerosol distribution over Indian subcontinent as represented in 21 models from Coupled Model Inter-comparison Project Phase 5 (CMIP5) simulations, wherein model simulated aerosol optical depth (AOD) is compared with Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite observations. The objective of the study is to provide an assessment of the capability of various global models, participating in CMIP5 project, in capturing the realistic spatial and temporal distribution of aerosol species over the Indian subcontinent. Results from our analysis show that majority of the CMIP5 models (excepting HADGEM2-ES, HADGEM2-CC) seriously underestimates the spatio-temporal variability of aerosol species over the Indian subcontinent, in particular over Indo-Gangetic Plains (IGP). Since IGP region is dominated by anthropogenic activities, high population density, and wind driven transport of dust and other aerosol species, MODIS observations reveal high AOD values over this region. Though the representation of black carbon (BC) loading in many models is fairly good, the dust loading is observed to be significantly low in majority of the models. The presence of pronounced dust activity over northern India and dust being one of the major constituent of aerosol species, the biases in dust loading has a great impact on the AOD of that region. We found that considerable biases in simulating the 850 hPa wind field (which plays important role in transport of dust from adjacent deserts) would be the possible reason for poor representation of dust AOD and in turn total AOD over Indian region in CMIP5 models. In addition, aerosol radiative forcing (ARF) underestimated/overestimated in most of the models. However, spatial distribution of ARF in multi-model ensemble mean is comparable reasonably well with observations with bias in magnitudes. This analysis emphasizes the fundamental need to improve the representation of aerosol species in current state of the art climate models. As reported in Intergovernmental Panel on Climate Change (IPCC) fourth assessment report (AR4), the level of scientific understanding (LOSU) of climatic impact of aerosols is medium-low. For better understanding of short and long term implications of changing concentrations of aerosol species on climate, it is imperative to have a realistic representation of aerosol distribution over regions with high aerosol loading.

Avoiding drift related to linear analysis update with Lagrangian coordinate models

NASA Astrophysics Data System (ADS)

Wang, Yiguo; Counillon, Francois; Bertino, Laurent

2015-04-01

When applying data assimilation to Lagrangian coordinate models, it is profitable to correct its grid (position, volume). In isopycnal ocean coordinate model, such information is provided by the layer thickness that can be massless but must remains positive (truncated Gaussian distribution). A linear gaussian analysis does not ensure positivity for such variable. Existing methods have been proposed to handle this issue - e.g. post processing, anamorphosis or resampling - but none ensures conservation of the mean, which is imperative in climate application. Here, a framework is introduced to test a new method, which proceed as following. First, layers for which analysis yields negative values are iteratively grouped with neighboring layers, resulting in a probability density function with a larger mean and smaller standard deviation that prevent appearance of negative values. Second, analysis increments of the grouped layer are uniformly distributed, which prevent massless layers to become filled and vice-versa. The new method is proved fully conservative with e.g. OI or 3DVAR but a small drift remains with ensemble-based methods (e.g. EnKF, DEnKF, …) during the update of the ensemble anomaly. However, the resulting drift with the latter is small (an order of magnitude smaller than with post-processing) and the increase of the computational cost moderate. The new method is demonstrated with a realistic application in the Norwegian Climate Prediction Model (NorCPM) that provides climate prediction by assimilating sea surface temperature with the Ensemble Kalman Filter in a fully coupled Earth System model (NorESM) with an isopycnal ocean model (MICOM). Over 25-year analysis period, the new method does not impair the predictive skill of the system but corrects the artificial steric drift introduced by data assimilation, and provide estimate in good agreement with IPCC AR5.

Representing Extremes in Agricultural Models

NASA Technical Reports Server (NTRS)

Ruane, Alex

2015-01-01

AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

Great Plains Drought in Simulations of Twentieth Century

NASA Astrophysics Data System (ADS)

McCrary, R. R.; Randall, D. A.

2008-12-01

The Great Plains region of the United States was influenced by a number of multi-year droughts during the twentieth century. Most notable were the "Dust Bowl" drought of the 1930s and the 1950s Great Plains drought. In this study we evaluate the ability of three of the Coupled Global Climate Models (CGCMs) used in the Fourth Assessment Report (AR4) of the IPCC to simulate Great Plains drought with the same frequency and intensity as was observed during the twentieth century. The models chosen for this study are: GFDL CM 2.0, NCAR CCSM3, and UKMO HadCM3. We find that the models accurately capture the climatology of the hydrologic cycle of the Great Plains, but that they tend to overestimate the variability in Great Plains precipitation. We also find that in each model simulation at least one long-term drought occurs over the Great Plains region during their representations 20th Century Climate. The multi-year droughts produced by the models exhibit similar magnitudes and spatial scales as was observed during the twentieth century. This study also investigates the relative roles that external forcing from the tropical Pacific and local feedbacks between the land surface and the atmosphere have in the initiation and perpetuation of Great Plains drought in each model. We find that cool, La Nina-like conditions in the tropical pacific are often associated with long-term drought conditions over the Great Plains in GFDL CM 2.0 and UKMO HadCM3, but there appears to be no systematic relationship between tropical Pacific SST variability and Great Plains drought in CCSM3. It is possible the strong coupling between the land surface and the atmosphere in the NCAR model causes precipitation anomalies to lock into phase over the Great Plains thereby perpetuating drought conditions. Results from this study are intended to help assess whether or not these climate models are credible for use in the assessment of future drought over the Great Plains region of the United States.

The highs and lows of cloud radiative feedback: Comparing observational data and CMIP5 models

NASA Astrophysics Data System (ADS)

Jenney, A.; Randall, D. A.

2014-12-01

Clouds play a complex role in the climate system, and remain one of the more difficult aspects of the future climate to predict. Over subtropical eastern ocean basins, particularly next to California, Peru, and Southwest Africa, low marine stratocumulus clouds (MSC) help to reduce the amount of solar radiation that reaches the surface by reflecting incident sunlight. The climate feedback associated with these clouds is thought to be positive. This project looks at CMIP5 models and compares them to observational data from CERES and ERA-Interim to try and find observational evidence and model agreement for low, marine stratocumulus cloud feedback. Although current evidence suggests that the low cloud feedback is positive (IPCC, 2014), an analysis of the simulated relationship between July lower tropospheric stability (LTS) and shortwave cloud forcing in MSC regions suggests that this feedback is not due to changes in LTS. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.

Advanced Regional and Decadal Predictions of Coastal Inundation for the U.S. Atlantic and Gulf Coasts (Invited)

NASA Astrophysics Data System (ADS)

Horton, B.; Corbett, D. R.; Donnelly, J. P.; Kemp, A.; Lin, N.; Lindeman, K.; Mann, M. E.; Peltier, W. R.; Rahmstorf, S.

2013-12-01

Future inundation of the U.S. Atlantic and Gulf coasts will depend upon sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. Through ongoing, collaborative research we are employing new interdisciplinary approaches to bring about a step change in the reliability of predictions of such inundation. The rate of sea level rise along the U.S. Atlantic and Gulf coasts increased throughout the 20th century. Whilst there is widespread agreement that it continue to accelerate during the 21st century, great uncertainty surrounds its magnitude and geographic variability. Key uncertainties include the role of continental ice sheets, mountain glaciers, and ocean density changes. Insufficient understanding of these complex physical processes precludes accurate prediction of sea-level rise. New approaches using semi-empirical models that relate instrumental records of climate and sea-level rise have projected up to 2 m of sea-level rise by AD 2100. But the time span of instrumental sea-level records is insufficient to adequately constrain the climate:sea-level relationship. We produced new, high-resolution proxy sea-level reconstructions to provide crucial additional constraints to such semi-empirical models. Our dataset spans the alternation between the 'Medieval Climate Anomaly' and 'Little Ice Age'. Before the models can provide appropriate data for coastal management and planning, they must be complemented with regional estimates of sea-level rise. Therefore, the proxy sea-level data has been collected from four study areas (Connecticut, New Jersey, North Carolina and Florida) to accommodate the required extent of regional variability. In the case of inundation arising from tropical cyclones, the historical and observational records are insufficient for predicting their nature and recurrence, because they are such extreme and rare events. Moreover, future storm surges will be superimposed on background sea-level rise. To overcome these problems, we coupled regional sea-level rise projections with hurricane simulations and storm surge models to map coastal inundation for the current climate and the best and worst case climate scenarios of the IPCC AR4. With agency, NGO, and business partners, we have integrated these findings into coastal policy initiatives, including the first ever adoption of sea level Adaptation Action Areas in a Florida city land use plan.

Climate for women in climate science: Women scientists and the Intergovernmental Panel on Climate Change.

PubMed

Gay-Antaki, Miriam; Liverman, Diana

2018-02-27

The Intergovernmental Panel on Climate Change (IPCC) is an authoritative and influential source of reports on climate change. The lead authors of IPCC reports include scientists from around the world, but questions have been raised about the dominance of specific disciplines in the report and the disproportionate number of scholars from the Global North. In this paper, we analyze the as-yet-unexamined issue of gender and IPCC authorship, looking at changes in gender balance over time and analyzing women's views about their experience and barriers to full participation, not only as women but also at the intersection of nationality, race, command of English, and discipline. Over time, we show that the proportion of female IPCC authors has seen a modest increase from less than 5% in 1990 to more than 20% in the most recent assessment reports. Based on responses from over 100 women IPCC authors, we find that many women report a positive experience in the way in which they are treated and in their ability to influence the report, although others report that some women were poorly represented and heard. We suggest that an intersectional lens is important: not all women experience the same obstacles: they face multiple and diverse barriers associated with social identifiers such as race, nationality, command of English, and disciplinary affiliation. The scientific community benefits from including all scientists, including women and those from the Global South. This paper documents barriers to participation and identifies opportunities to diversify climate science. Copyright © 2018 the Author(s). Published by PNAS.

Climate for women in climate science: Women scientists and the Intergovernmental Panel on Climate Change

PubMed Central

Gay-Antaki, Miriam; Liverman, Diana

2018-01-01

The Intergovernmental Panel on Climate Change (IPCC) is an authoritative and influential source of reports on climate change. The lead authors of IPCC reports include scientists from around the world, but questions have been raised about the dominance of specific disciplines in the report and the disproportionate number of scholars from the Global North. In this paper, we analyze the as-yet-unexamined issue of gender and IPCC authorship, looking at changes in gender balance over time and analyzing women’s views about their experience and barriers to full participation, not only as women but also at the intersection of nationality, race, command of English, and discipline. Over time, we show that the proportion of female IPCC authors has seen a modest increase from less than 5% in 1990 to more than 20% in the most recent assessment reports. Based on responses from over 100 women IPCC authors, we find that many women report a positive experience in the way in which they are treated and in their ability to influence the report, although others report that some women were poorly represented and heard. We suggest that an intersectional lens is important: not all women experience the same obstacles: they face multiple and diverse barriers associated with social identifiers such as race, nationality, command of English, and disciplinary affiliation. The scientific community benefits from including all scientists, including women and those from the Global South. This paper documents barriers to participation and identifies opportunities to diversify climate science. PMID:29440422

Herding cats? A multi-model perspective on tropospheric ozone

NASA Astrophysics Data System (ADS)

Young, P. J.

2015-12-01

Various global multi-model studies have investigated tropospheric ozone changes over multi-decadal timescales. Several robust features emerge, which - for instance - allows the IPCC to associate high confidence in the radiative forcing associated with ozone increases between 1750 and the present day. However, such quantities hide the spread in results between different models, particularly when looking at seasonal and regional scales, and including for comparisons with observations. What can we learn about our scientific understanding from the model spread? What can we learn about models from the model spread? And can we make recommendations for deficient or missing processes if we wish to use our models for environmental prediction? Of course, these questions also have to be asked in the context of what we want the model(s) to do (air quality, climate, stratospheric ozone depletion etc.). This poster will report ongoing work in my group which draws on results from multi-model experiments conducted in support of the most recent IPCC report (CMIP5 and ACCMIP), with an eye to the expected outcomes from the ongoing Chemistry-Climate Model Initiative (CCMI) model simulations.

Southern United States climate, land use, and forest conditions

Treesearch

David N. Wear; Thomas L. Mote; J. Marshall Shepherd; K. C. Benita; Christopher W. Strother

2014-01-01

The Intergovernmental Panel on Climate Change (IPCC) has concluded, with 90% certainty, that human or "anthropogenic" activities (emissions of greenhouse gases, aerosols and pollution, landuse/land-cover change) have altered global temperature patterns over the past 100-150 years (IPCC 2007a). Such temperature changes have a set of cascading, and sometimes...

ENSO Simulation in Coupled Ocean-Atmosphere Models: Are the Current Models Better?

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

AchutaRao, K; Sperber, K R

Maintaining a multi-model database over a generation or more of model development provides an important framework for assessing model improvement. Using control integrations, we compare the simulation of the El Nino/Southern Oscillation (ENSO), and its extratropical impact, in models developed for the 2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report with models developed in the late 1990's (the so-called Coupled Model Intercomparison Project-2 [CMIP2] models). The IPCC models tend to be more realistic in representing the frequency with which ENSO occurs, and they are better at locating enhanced temperature variability over the eastern Pacific Ocean. When compared withmore » reanalyses, the IPCC models have larger pattern correlations of tropical surface air temperature than do the CMIP2 models during the boreal winter peak phase of El Nino. However, for sea-level pressure and precipitation rate anomalies, a clear separation in performance between the two vintages of models is not as apparent. The strongest improvement occurs for the modeling groups whose CMIP2 model tended to have the lowest pattern correlations with observations. This has been checked by subsampling the multi-century IPCC simulations in a manner to be consistent with the single 80-year time segment available from CMIP2. Our results suggest that multi-century integrations may be required to statistically assess model improvement of ENSO. The quality of the El Nino precipitation composite is directly related to the fidelity of the boreal winter precipitation climatology, highlighting the importance of reducing systematic model error. Over North America distinct improvement of El Nino forced boreal winter surface air temperature, sea-level pressure, and precipitation rate anomalies in the IPCC models occurs. This improvement, is directly proportional to the skill of the tropical El Nino forced precipitation anomalies.« less

76 FR 6651 - Intergovernmental Panel on Climate Change Special Report Review

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-07

... time that they accept the overall report. Principles and procedures for the IPCC and its preparation of..._documents/ipcc-principles-appendix-a.pdf (pdf) http://ipcc.ch/organization/organization_procedures.shtml In.... The following section of the report discusses risk management at the local, national and international...

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

Determing Credibility of Regional Simulations of Future Climate

NASA Astrophysics Data System (ADS)

Mearns, L. O.

2009-12-01

Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach is being attempted in the North American Climate Change Assessment Program (NARCCAP) whereby multiple global models are used to drive multiple regional models for the current period and the mid-21st century over the continent. Progress in this endeavor will be reported.

A public health approach to the impact of climate change on health in southern Africa - identifying priority modifiable risks.

PubMed

Myers, J; Young, T; Galloway, M; Manyike, P; Tucker, T

2011-11-01

Anthropogenic climate change and anticipated adverse impacts on human health as outlined by the Intergovernmental Panel on Climate Change (IPCC) are taken as given. A conceptual model for thinking about the spectrum of climate-related health risks ranging from distal and infrastructural to proximal and behavioural and their relation to the burden of disease pattern typical of sub-Saharan Africa is provided. The model provides a tool for identifying modifiable risk factors with a view to future research, specifically into the performance of interventions to reduce the impact of climate change.

The BGC Feedbacks Scientific Focus Area 2016 Annual Progress Report

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

Hoffman, Forrest M.; Riley, William J.; Randerson, James T.

2016-06-01

The BGC Feedbacks Project will identify and quantify the feedbacks between biogeochemical cycles and the climate system, and quantify and reduce the uncertainties in Earth System Models (ESMs) associated with those feedbacks. The BGC Feedbacks Project will contribute to the integration of the experimental and modeling science communities, providing researchers with new tools to compare measurements and models, thereby enabling DOE to contribute more effectively to future climate assessments by the U.S. Global Change Research Program (USGCRP) and the Intergovernmental Panel on Climate Change (IPCC).

Temporary refugia for coral reefs in a warming world

NASA Astrophysics Data System (ADS)

van Hooidonk, R.; Maynard, J. A.; Planes, S.

2013-05-01

Climate-change impacts on coral reefs are expected to include temperature-induced spatially extensive bleaching events. Bleaching causes mortality when temperature stress persists but exposure to bleaching conditions is not expected to be spatially uniform at the regional or global scale. Here we show the first maps of global projections of bleaching conditions based on ensembles of IPCC AR5 (ref. ) models forced with the new Representative Concentration Pathways (RCPs). For the three RCPs with larger CO2 emissions (RCP 4.5, 6.0 and 8.5) the onset of annual bleaching conditions is associated with ~ 510ppm CO2 equivalent; the median year of all locations is 2040 for the fossil-fuel aggressive RCP 8.5. Spatial patterns in the onset of annual bleaching conditions are similar for each of the RCPs. For RCP 8.5, 26% of reef cells are projected to experience annual bleaching conditions more than 5 years later than the median. Some of these temporary refugia include the western Indian Ocean, Thailand, the southern Great Barrier Reef and central French Polynesia. A reduction in the growth of greenhouse-gas emissions corresponding to the difference between RCP 8.5 and 6.0 delays annual bleaching in ~ 23% of reef cells more than two decades, which might conceivably increase the potential for these reefs to cope with these changes.

Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future

USGS Publications Warehouse

Homer, Collin G.; Xian, George Z.; Aldridge, Cameron L.; Meyer, Debra K.; Loveland, Thomas R.; O'Donnell, Michael S.

2015-01-01

Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus urophasianus) habitat models to evaluate the effects of potential climate-induced habitat change. Under the 2050 IPCC A1B scenario, 11.6% of currently identified nesting habitat was lost, and 0.002% of new potential habitat was gained, with 4% of summer habitat lost and 0.039% gained. Our results demonstrate the successful ability of remote sensing based sagebrush components, when coupled with precipitation, to forecast future component response using IPCC precipitation scenarios. Our approach also enables future quantification of greater sage-grouse habitat under different precipitation scenarios, and provides additional capability to identify regional precipitation influence on sagebrush component response.

Changes in climate extremes and their impacts on the natural physical environment: An overview of the IPCC SREX report

NASA Astrophysics Data System (ADS)

Seneviratne, S. I.; Nicholls, N.; Easterling, D.; Goodess, C. M.; Kanae, S.; Kossin, J.; Luo, Y.; Marengo, J.; McInnes, K.; Rahimi, M.; Reichstein, M.; Sorteberg, A.; Vera, C.; Zhang, X.

2012-04-01

In April 2009, the Intergovernmental Panel on Climate Change (IPCC) decided to prepare a new special report with involvement of the UN International Strategy for Disaster Reduction (ISDR) on the topic "Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation" (SREX, http://ipcc-wg2.gov/SREX/). This special report reviews the scientific literature on past and projected changes in weather and climate extremes, and the relevance of such changes to disaster risk reduction and climate change adaptation. The SREX Summary for Policymakers was approved at an IPCC Plenary session on November 14-18, 2011, and the full report is planned for release in February 2012. This presentation will provide an overview on the structure and contents of the SREX, focusing on Chapter 3: "Changes in climate extremes and their impacts on the natural physical environment" [1]. It will in particular present the main findings of the chapter, including differences between the SREX's conclusions and those of the IPCC Fourth Assessment of 2007, and the implications of this new assessment for disaster risk reduction. Finally, aspects relevant to impacts on the biogeochemical cycles will also be addressed. [1] Seneviratne, S.I., N. Nicholls, D. Easterling, C.M. Goodess, S. Kanae, J. Kossin, Y. Luo, J. Marengo, K. McInnes, M. Rahimi, M. Reichstein, A. Sorteberg, C. Vera, and X. Zhang, 2012: Changes in climate extremes and their impacts on the natural physical environment. In: Intergovernmental Panel on Climate Change Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C. B., Barros, V., Stocker, T.F., Qin, D., Dokken, D., Ebi, K.L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M. and P. M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA

Future hydrological regimes and glacier cover in the Everest region: The case study of the upper Dudh Koshi basin.

PubMed

Soncini, Andrea; Bocchiola, Daniele; Confortola, Gabriele; Minora, Umberto; Vuillermoz, Elisa; Salerno, Franco; Viviano, Gaetano; Shrestha, Dibas; Senese, Antonella; Smiraglia, Claudio; Diolaiuti, Guglielmina

2016-09-15

Assessment of future water resources under climate change is required in the Himalayas, where hydrological cycle is poorly studied and little understood. This study focuses on the upper Dudh Koshi river of Nepal (151km(2), 4200-8848ma.s.l.) at the toe of Mt. Everest, nesting the debris covered Khumbu, and Khangri Nup glaciers (62km(2)). New data gathered during three years of field campaigns (2012-2014) were used to set up a glacio-hydrological model describing stream flows, snow and ice melt, ice cover thickness and glaciers' flow dynamics. The model was validated, and used to assess changes of the hydrological cycle until 2100. Climate projections are used from three Global Climate Models used in the recent IPCC AR5 under RCP2.6, RCP4.5 and RCP8.5. Flow statistics are estimated for two reference decades 2045-2054, and 2090-2099, and compared against control run CR, 2012-2014. During CR we found a contribution of ice melt to stream flows of 55% yearly, with snow melt contributing for 19%. Future flows are predicted to increase in monsoon season, but to decrease yearly (-4% vs CR on average) at 2045-2054. At the end of century large reduction would occur in all seasons, i.e. -26% vs CR on average at 2090-2099. At half century yearly contribution of ice melt would be on average 45%, and snow melt 28%. At the end of century ice melt would be 31%, and snow contribution 39%. Glaciers in the area are projected to thin largely up to 6500ma.s.l. until 2100, reducing their volume by -50% or more, and their ice covered area by -30% or more. According to our results, in the future water resources in the upper Dudh Koshi would decrease, and depend largely upon snow melt and rainfall, so that adaptation measures to modified water availability will be required. Copyright © 2016 Elsevier B.V. All rights reserved.

75 FR 77475 - Endangered and Threatened Species; Proposed Threatened Status for Subspecies of the Ringed Seal

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-10

... ice area are linked in the IPCC climate models to GHG emissions by the physics of radiation processes... scenario), a model that is known for incorporating advanced sea ice physics, and for which snow data were...

Is Planetary-Scale High Tech Civilization Climatically Sustainable?: The Geophysics v Economics Paradigm War

NASA Astrophysics Data System (ADS)

Hoffert, M.

2012-12-01

Climate/energy policy is gridlocked between (1) a geophysics perspective revealing long-term instabilities from continued energy consumption growth, of which the fossil fuel greenhouse an early symptom; and (2) short-term, fossil-fuel energized-rapid-economic-growth-driven policies likely adaptive for hunter-gatherers competing for scarce food, but climatically fatal to planetary-scale economies dependent on agriculture and "energy slaves." Incorporating social science into climate/energy policy formulation has focused on integrated assessment models (IAMs) exploring scenarios (parallel universes making different social choices) depicting the evolution of GDP, energy consumed, the energy technology mixture, land use, greenhouse gas and aerosol emissions, and radiative forcing). Representative concentration pathways (RCP) scenarios developed for the IPCC AR5 report imply 5-10 degree C warming from fossil fuel burning unless unprecedentedly fast decarbonization rates ~ 7 %/yr are implemented from 2020 to 2100. A massive transition to carbon neutrality by midcentury is needed to keep warming < 2 degrees C (FIG. 1).Fossil fuel greenhouse warming is leveraged by two orders of magnitude relative to heating from human energy consumption. Even if civilization successfully transitions to carbon-neutrality in time, but energy use continues growing at 2%/year, fossil-fuel-greenhouse level warming would be generated by heat rejecting in only 200-300 years underscoring that sustainability implies a steady state planetary economy (FIG.2). Evolutionary psychology and neuroeconomics are emergent disciplines that may illuminate the physical v social science paradigm conflict threatening human survivability.

Projected Risk of Flooding Disaster over China in 21st Century Based on CMIP5 Models

NASA Astrophysics Data System (ADS)

Li, Rouke; Xu, Ying

2016-04-01

Based on the simulations from CMIP5 models, using climate indices which have high correlation with historical disaster data, and in combination with terrain elevation data and the socio-economic data, to project the flooding disaster risk, the vulnerability of flooding hazard affected body and the risk of flooding hazard respectively during the near term(2015-2039), medium term(2045-2069) and long term(2075-2099) under RCP8.5. According to the IPCC AR5 WGII, we used risk evaluation model of disaster: R=E*H*V. R on behalf of disaster risk index. H, E and V express risk, exposure and vulnerability respectively. The results show that the extreme flooding disaster risk will gradually increase during different terms in the future, and regions with high risk level of flooding hazard are might mainly located in southeastern and eastern China. Under the RCP8.5 greenhouse gas emissions scenario, the high risk of flooding disaster in future might mainly appear in eastern part of Sichuan, most of North China, and major of East China. Compared with the baseline period,21st century forward, although the occurrence of floods area changes little, the regional strong risk will increase during the end of the 21st century. Due to the coarse resolution of climate models and the methodology for determining weight coefficients, large uncertainty still exists in the projection of the flooding disaster risk.

Treatment of uncertainties in the IPCC: a philosophical analysis

NASA Astrophysics Data System (ADS)

Jebeile, J.; Drouet, I.

2014-12-01

The IPCC produces scientific reports out of findings on climate and climate change. Because the findings are uncertain in many respects, the production of reports requires aggregating assessments of uncertainties of different kinds. This difficult task is currently regulated by the Guidance note for lead authors of the IPCC fifth assessment report on consistent treatment of uncertainties. The note recommends that two metrics—i.e. confidence and likelihood— be used for communicating the degree of certainty in findings. Confidence is expressed qualitatively "based on the type, amount, quality, and consistency of evidence […] and the degree of agreement", while likelihood is expressed probabilistically "based on statistical analysis of observations or model results, or expert judgment". Therefore, depending on the evidence evaluated, authors have the choice to present either an assigned level of confidence or a quantified measure of likelihood. But aggregating assessments of uncertainties of these two different kinds express distinct and conflicting methodologies. So the question arises whether the treatment of uncertainties in the IPCC is rationally justified. In order to answer the question, it is worth comparing the IPCC procedures with the formal normative theories of epistemic rationality which have been developed by philosophers. These theories—which include contributions to the philosophy of probability and to bayesian probabilistic confirmation theory—are relevant for our purpose because they are commonly used to assess the rationality of common collective jugement formation based on uncertain knowledge. In this paper we make the comparison and pursue the following objectives: i/we determine whether the IPCC confidence and likelihood can be compared with the notions of uncertainty targeted by or underlying the formal normative theories of epistemic rationality; ii/we investigate whether the formal normative theories of epistemic rationality justify treating uncertainty along those two dimensions, and indicate how this can be avoided.

Five millennia of frozen vegetation and fire dynamics from an ice core in the Mongolian Altai

NASA Astrophysics Data System (ADS)

Brügger, S. O.; Gobet, E.; Sigl, M.; Osmont, D.; Papina, T.; Rudaya, N.; Schwikowski, M.; Tinner, W.

2017-12-01

The steppes of the Altai region in Central Asia are highly vulnerable to e.g. drought and overgrazing. Degradation during the past decades may undermine their resilience under global change conditions. Knowledge about past vegetation and fire dynamics in Mongolian Altai may contribute to a better understanding of future climate and human impact responses, however, paleo records are scarce in the area. Our novel high-alpine ice record from Tsambagarav glacier (48°39.338'N, 90°50.826'E, 4130m asl) in the Mongolian Altai provides unique paleoenvironmental informations at the landscape scale. The site is surrounded by dry steppes with scattered boreal tree stands. We assume that the site collects pollen and spores within several hundred km. The archive provides an exceptional temporal resolution with a sound chronology covering the past 5500 years (Herren et al. 2013). Microfossil analysis allows to reconstruct large-scale fire and vegetation dynamics to gain a better understanding of the timing and causes of late Holocene response variability. We use pollen as proxies for vegetation composition and structure, microscopic charcoal as a proxy for fire activity (Eichler et al. 2011), and spheroidal carbonaceous particles (SCPs or soots) as a proxy for fossil fuel combustion. Here we present the first microscopic charcoal record from Mongolia and link it to vegetation dynamics of the past. The reconstructed mid to late Holocene forest collapses likely in response to climate change underscore the vulnerability of relict forest ecosystems in the Mongolian Altai. Our multiproxy-study suggests that moisture is more important than temperature for forest preservation. The lacking resilience of vegetation to moisture changes in the past emphasizes the vulnerability of large forests in neighboring dry areas such as the Russian Altai, if global warming is associated to moisture declines as future projections forecast (IPCC; Climate Change 2013). References: Eichler et al. (2011). An ice-core based history of Siberian forest fires since AD 1250. Quat Sci Rev 30(9) Herren et al. (2013). The onset of Neoglaciation 6000 years ago in western Mongolia revealed by an ice core from the Tsambagarav mountain range. Quat Sci Rev 69 IPCC; Climate Change (2013): The Physical Science Basis. IPCC Working Group I Contribution to AR5

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

PubMed Central

Olson, Deanna H.; Blaustein, Andrew R.

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. PMID:27513565

Effects of crop management, soil type, and climate on N2O emissions from Austrian Soils

NASA Astrophysics Data System (ADS)

Zechmeister-Boltenstern, Sophie; Sigmund, Elisabeth; Kasper, Martina; Kitzler, Barbara; Haas, Edwin; Wandl, Michael; Strauss, Peter; Poetzelsberger, Elisabeth; Dersch, Georg; Winiwarter, Wilfried; Amon, Barbara

2015-04-01

Within the project FarmClim ("Farming for a better climate") we assessed recent N2O emissions from two selected regions in Austria. Our aim was to deepen the understanding of Austrian N2O fluxes regarding region specific properties. Currently, N2O emissions are estimated with the IPCC default emission factor which only considers the amount of N-input as an influencing factor for N2O emissions. We evaluated the IPCC default emission factor for its validity under spatially distinct environmental conditions. For this two regions for modeling with LandscapeDNDC have been identified in this project. The benefit of using LandscapeDNDC is the detailed illustration of microbial processes in the soil. Required input data to run the model included daily climate data, vegetation properties, soil characteristics and land management. The analysis of present agricultural practices was basis for assessing the hot spots and hot moments of nitrogen emissions on a regional scale. During our work with LandscapeDNDC we were able to adapt specific model algorithms to Austrian agricultural conditions. The model revealed a strong dependency of N2O emissions on soil type. We could estimate how strongly soil texture affects N2O emissions. Based on detailed soil maps with high spatial resolution we calculated region specific contribution to N2O emissions. Accordingly we differentiated regions with deviating gas fluxes compared to the predictions by the IPCC inventory methodology. Taking region specific management practices into account (tillage, irrigation, residuals) calculation of crop rotation (fallow, catch crop, winter wheat, barley, winter barley, sugar beet, corn, potato, onion and rapeseed) resulted in N2O emissions differing by a factor of 30 depending on preceding crop and climate. A maximum of 2% of N fertilizer input was emitted as N2O. Residual N in the soil was a major factor stimulating N2O emissions. Interannual variability was affected by varying N-deposition even in case of constant management practices. High temporal resolution of model outputs enabled us to identify hot moments of N-turnover and total N2O emissions according to extreme weather events. We analysed how strongly these event based emissions, which are not accounted for by classical inventories, affect emission factors. The evaluation of the IPCC default emission factor for its validity under spatially distinct environmental conditions revealed which environmental conditions are responsible for major deviations of actual emissions from the theoretical values. Scrutinizing these conditions can help to improve climate reporting and greenhouse gas mitigation measures.

Simulated versus observed patterns of warming over the extratropical Northern Hemisphere continents during the cold season

PubMed Central

Wallace, John M.; Fu, Qiang; Smoliak, Brian V.; Lin, Pu; Johanson, Celeste M.

2012-01-01

A suite of the historical simulations run with the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models forced by greenhouse gases, aerosols, stratospheric ozone depletion, and volcanic eruptions and a second suite of simulations forced by increasing CO2 concentrations alone are compared with observations for the reference interval 1965–2000. Surface air temperature trends are disaggregated by boreal cold (November-April) versus warm (May-October) seasons and by high latitude northern (N: 40°–90 °N) versus southern (S: 60 °S–40 °N) domains. A dynamical adjustment is applied to remove the component of the cold-season surface air temperature trends (over land areas poleward of 40 °N) that are attributable to changing atmospheric circulation patterns. The model simulations do not simulate the full extent of the wintertime warming over the high-latitude Northern Hemisphere continents during the later 20th century, much of which was dynamically induced. Expressed as fractions of the concurrent trend in global-mean sea surface temperature, the relative magnitude of the dynamically induced wintertime warming over domain N in the observations, the simulations with multiple forcings, and the runs forced by the buildup of greenhouse gases only is 7∶2∶1, and roughly comparable to the relative magnitude of the concurrent sea-level pressure trends. These results support the notion that the enhanced wintertime warming over high northern latitudes from 1965 to 2000 was mainly a reflection of unforced variability of the coupled climate system. Some of the simulations exhibit an enhancement of the warming along the Arctic coast, suggestive of exaggerated feedbacks. PMID:22847408

Some Good Practices for Integration and Outreach and their Implementation in the Community Integrated Assessment System (CIAS) and its associated web portal CLIMASCOPE

NASA Astrophysics Data System (ADS)

Warren, R. F.; Price, J. T.; Goswami, S.

2010-12-01

Successful communication of knowledge to climate change policy makers requires the careful integration of scientific knowledge in an integrated assessment that can be clearly communicated to stakeholders, and which encapsulates the uncertainties in the analysis and conveys the need for using a risk assessment approach. It is important that (i) the system is co-designed with the users (ii) relevant disciplines are included (iii) assumptions made are clear (iv) the robustness of outputs to uncertainties is demonstrated (v) the system is flexible so that it can keep up with changing stakeholder needs and (vi) the results are communicated clearly and are readily accessible. The “Community Integrated Assessment System” (CIAS) is a unique multi-institutional, modular, and flexible integrated assessment system for modeling climate change which fulfils the above six criteria. It differs from other integrated models in being a flexible system allowing various combinations of component modules, to be connected together into alternative integrated assessment models. These modules may be written at different institutions in different computer languages and/or based on different operating systems. Scientists are able determine which particular CIAS coupled model they wish to use through a web portal. This includes the facility to implement Latin hypercube experimental design facilitating formal uncertainty analysis. Further exploration of robustness is possible through the ability to select, for example, alternative hyrdrological or climate models to address the same questions. It has been applied to study future scenarios of climate change mitigation, through for example the AVOIDing dangerous climate change project for DEFRA, in which the avoided impacts (benefits) of alternative climate policies were compared to no-policy baselines. These highlight the potential for mitigation to remove a substantial fraction of the climate change impacts that would otherwise occur; but also show that is not possible to avoid all the impacts, and hence that adaptation will still be required. For example, this has been shown for projections of future European drought. CIAS has also been used for analyses used in the IPCC 4AR and the Stern review. Recent applications include a study of the role of avoided deforestation in climate mitigation, and a study of the impacts of climate change on biodiversity. A second web portal, CLIMASCOPE, is being developed for use by stakeholders, currently focusing on the needs of adaptation planners. This will benefit communication by allowing a wide range of users free access to regional climate change projections in simple manner, yet one which encourages risk assessment through encapsulation of the uncertainties in climate change projection. Examples of CLIMASCOPE output that is being made available to stakeholders will be shown.

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 Golden Age or Greenhouse Gas Dark Age Legacy?

NASA Astrophysics Data System (ADS)

Carter, P.

2016-12-01

Relying on the IPCC Assessments, this paper assesses legacy from total committed global warming over centuries, correlated with comprehensive projected impacts. Socio-economic inertia, climate system inertia, atmospheric greenhouse gas (GHG) concentrations, amplifying feedback emissions, and unmasking of cooling aerosols are determinants. Stabilization of global temperature (and ocean acidification for CO2) requires emissions of "long lived greenhouse gases" to be "about zero," including feedbacks. "The feedback … is positive" this century; many large feedback sources tend to be self- and inter-reinforcing. Only timely total conversion of all fossil fuel power to clean, virtually zero-carbon renewable power can achieve virtual zero carbon emissions. This results in multiple, increasing benefits for the entire world population of today's and all future generations, as laid out here. Conversions of methane- and nitrous oxide-emitting sources have large benefits. Without timely conversion to virtual zero emissions, the global climate and ocean disruptions are predicted to become progressively more severe and practically irreversible. "Continued emission of greenhouse gases will increase the likelihood of severe, pervasive and irreversible impacts for people and ecosystems." Crop yields in all main food-producing regions are projected to decline progressively with rising temperature (as proxy to multiple adverse effects) (AR5). Ocean heating, acidification, and de-oxygenation are projected to increase under all scenarios, as is species extinction. The legacy for humanity depends on reducing long-lived global emissions fast enough to virtual zero. Today's surface warming with unprecedented and accelerating atmospheric GHG concentrations requires an immediate response. The only IPCC scenario to possibly meet this and not exceed 2ºC by and after 2100 is the best-case RCP2.6, which requires CO2 eq. emissions to peak right away and decline at the latest by 2020.

The Climate-G testbed: towards a large scale data sharing environment for climate change

NASA Astrophysics Data System (ADS)

Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

2009-04-01

The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for data visualization; metadata search/discovery across several countries/institutions; open environment for climate change data sharing.

The 'Blue-Shift' in midlatitude dynamics in a Changing Climate

NASA Astrophysics Data System (ADS)

Carvalho, L. V.

2013-12-01

Global surface temperature variations and changes result from intricate interplay of phenomena varying on scales ranging from fraction of seconds (turbulence) to thousands of years (e.g. glaciations). To complicate these issues further, the contribution of the anthropogenic forcing on the observed changes in surface temperatures varies over time and is spatially non-uniform. While evaluating all individual bands of this broad spectrum is virtually impossible, the availability of global daily datasets in the last few decades from reanalyses and Global Climate Models (GCMs) simulations allows estimating the contribution of phenomena varying on synoptic-to-interannual timescales. Previous studies using GCM simulations for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (IPCC AR4) have documented a consistent poleward shift in the storm tracks related to changes in baroclinicity resulting from global warming. However, our recent research (Cannon et al. 2013) indicated that the pattern of changes in the storm tracks observed in the last few decades is much more complex in both space and time. Complex terrain and the relative distribution of continents, oceans and icecaps play a significant role for changes in synoptic activity. Coupled modes such as the Northern and Southern annular modes, the El Nino-Southern Oscillation (ENSO) and respective teleconnections with changes in baroclinicity have been identified as relevant dynamical forcings for variations of the midlatitude storm tracks, increasing the uncertainties in future projections. Moreover, global warming has modified the amplitude of the annual cycles of temperature, moisture and circulation throughout the planet and there is strong indication that these changes have mostly affected the tropics and Polar Regions. The present study advances these findings by investigating the 'blue-shift' in the underlying dynamics causing surface temperature anomalies and investigates relationships with low and upper level circulation. This research uses two sources of data: global daily Climate Forecast System Reanalysis (CFSR) (1979- 2010) and the Geophysical Fluid Dynamics Laboratory (GFDL) global daily simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Two sets of simulations are investigated: the Historic and Pi-control runs. Here the term ';blue-shift' is used to indicate long-term increase in the amplitude of the synoptic scale relatively to the annual cycle amplitude derived from wavelet analysis as an analogy to the definition commonly used in physics (i.e., a shift toward shorter wavelengths of the spectral lines). It is shown that the blue-shift has been observed in midlatitudes of some continental areas of the Northern Hemisphere and North Pacific but in relatively higher latitudes in the Southern Hemisphere. Tropical areas and high latitudes of the Northern Hemisphere have experienced opposite trend (red-shift). Moreover, the pattern of the blue and red-shifts exhibits seasonal changes. References: Cannon, F., L. M. V. Carvalho, C. Jones, B. Bookhagen, 2013: Multi-Annual Variations in Winter Westerly Disturbance Activity Affecting the Himalaya. Submitted to Climate Dynamics

Evaluation of hydrological cycle in the major European midlatitude river basins in the frame of the CORDEX project

NASA Astrophysics Data System (ADS)

Georgievski, Goran; Keuler, Klaus

2013-04-01

Water supply and its potential to increase social, economic and environmental risks are among the most critical challenges for the upcoming decades. Therefore, the assessment of the reliability of regional climate models (RCMs) to represent present-day hydrological balance of river basins is one of the most challenging tasks with high priority for climate modelling in order to estimate range of possible socio-economic impacts of the climate change. However, previous work in the frame of 4th IPCC AR and corresponding regional downscaling experiments (with focus on Europe and Danube river basin) showed that even the meteorological re-analyses provide unreliable data set for evaluations of climate model performance. Furthermore, large discrepancies among the RCMs are caused by internal model deficiencies (for example: systematic errors in dynamics, land-soil parameterizations, large-scale condensation and convection schemes), and in spite of higher resolution RCMs do not always improve much the results from GCMs, but even deteriorate it in some cases. All that has a consequence that capturing impact of climate change on hydrological cycle is not an easy task. Here we present state of the art of RCMs in the frame of the CORDEX project for Europe. First analysis shows again that even the up to date ERA-INTERIM re-analysis is not reliable for evaluation of hydrological cycle in major European midlatitude river basins (Seine, Rhine, Elbe, Oder, Vistula, Danube, Po, Rhone, Garonne and Ebro). Therefore, terrestrial water storage, a quasi observed parameter which is a combination of river discharge (from Global River Discharge Centre data set) and atmospheric moisture fluxes from ERA-INTERIM re-analysis, is used for verification. It shows qualitatively good agreement with COSMO-CLM (CCLM) regional climate simulation (abbreviated CCLM_eval) at 0.11 degrees horizontal resolution forced by ERA-INTERIM re-analysis. Furthermore, intercomparison of terrestrial water storage seasonal cycle averaged in Danube river basin for the ten years (1990-1999) overlapping period between CCLM historical experiment (abbreviated CCLM_hist), its forcing GCM (MPI-ESM-LR, here abbreviated MPI_hist) and CCLM_eval is performed. It reveals that CCLM_hist simulation is in better agreement with quasi observed terrestrial water storage than MPI_hist and CCLM_eval. This result seems promising for the assessment of impact of climate change on hydrological cycle. However, evaluation of the whole ensemble of regional climate downscaling experiments participated in CORDEX-Europe project would provide a more robust estimate.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-01-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We apply support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicts model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures are determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations are the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Climate Change on Twitter: Topics, Communities and Conversations about the 2013 IPCC Working Group 1 Report

PubMed Central

Pearce, Warren; Holmberg, Kim; Hellsten, Iina; Nerlich, Brigitte

2014-01-01

In September 2013 the Intergovernmental Panel on Climate Change published its Working Group 1 report, the first comprehensive assessment of physical climate science in six years, constituting a critical event in the societal debate about climate change. This paper analyses the nature of this debate in one public forum: Twitter. Using statistical methods, tweets were analyzed to discover the hashtags used when people tweeted about the IPCC report, and how Twitter users formed communities around their conversational connections. In short, the paper presents the topics and tweeters at this particular moment in the climate debate. The most used hashtags related to themes of science, geographical location and social issues connected to climate change. Particularly noteworthy were tweets connected to Australian politics, US politics, geoengineering and fracking. Three communities of Twitter users were identified. Researcher coding of Twitter users showed how these varied according to geographical location and whether users were supportive, unsupportive or neutral in their tweets about the IPCC. Overall, users were most likely to converse with users holding similar views. However, qualitative analysis suggested the emergence of a community of Twitter users, predominantly based in the UK, where greater interaction between contrasting views took place. This analysis also illustrated the presence of a campaign by the non-governmental organization Avaaz, aimed at increasing media coverage of the IPCC report. PMID:24718388

Climate change on Twitter: topics, communities and conversations about the 2013 IPCC Working Group 1 report.

PubMed

Pearce, Warren; Holmberg, Kim; Hellsten, Iina; Nerlich, Brigitte

2014-01-01

In September 2013 the Intergovernmental Panel on Climate Change published its Working Group 1 report, the first comprehensive assessment of physical climate science in six years, constituting a critical event in the societal debate about climate change. This paper analyses the nature of this debate in one public forum: Twitter. Using statistical methods, tweets were analyzed to discover the hashtags used when people tweeted about the IPCC report, and how Twitter users formed communities around their conversational connections. In short, the paper presents the topics and tweeters at this particular moment in the climate debate. The most used hashtags related to themes of science, geographical location and social issues connected to climate change. Particularly noteworthy were tweets connected to Australian politics, US politics, geoengineering and fracking. Three communities of Twitter users were identified. Researcher coding of Twitter users showed how these varied according to geographical location and whether users were supportive, unsupportive or neutral in their tweets about the IPCC. Overall, users were most likely to converse with users holding similar views. However, qualitative analysis suggested the emergence of a community of Twitter users, predominantly based in the UK, where greater interaction between contrasting views took place. This analysis also illustrated the presence of a campaign by the non-governmental organization Avaaz, aimed at increasing media coverage of the IPCC report.

Estimating the economic impact of climate change on cardiovascular diseases--evidence from Taiwan.

PubMed

Liao, Shu-Yi; Tseng, Wei-Chun; Chen, Pin-Yu; Chen, Chi-Chung; Wu, Wei-Min

2010-12-01

The main purpose of this study was to investigate how climate change affects blood vessel-related heart disease and hypertension and to estimate the associated economic damage. In this paper, both the panel data model and the contingent valuation method (CVM) approaches are applied. The empirical results indicate that the number of death from cardiovascular diseases would be increased by 0.226% as the variation in temperature increases by 1%. More importantly, the number of death from cardiovascular diseases would be increased by 1.2% to 4.1% under alternative IPCC climate change scenarios. The results from the CVM approach show that each person would be willing to pay US$51 to US$97 per year in order to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change.

Estimating the Economic Impact of Climate Change on Cardiovascular Diseases—Evidence from Taiwan

PubMed Central

Liao, Shu-Yi; Tseng, Wei-Chun; Chen, Pin-Yu; Chen, Chi-Chung; Wu, Wei-Min

2010-01-01

The main purpose of this study was to investigate how climate change affects blood vessel-related heart disease and hypertension and to estimate the associated economic damage. In this paper, both the panel data model and the contingent valuation method (CVM) approaches are applied. The empirical results indicate that the number of death from cardiovascular diseases would be increased by 0.226% as the variation in temperature increases by 1%. More importantly, the number of death from cardiovascular diseases would be increased by 1.2% to 4.1% under alternative IPCC climate change scenarios. The results from the CVM approach show that each person would be willing to pay US$51 to US$97 per year in order to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change. PMID:21318006

Development of a Micro Pulsed Lidar and a Singly-Resonant Optical Parametric Oscillator for CO2 Dial for Use in Atmospheric Studies

NASA Astrophysics Data System (ADS)

Chantjaroen, Chat

According to the Fifth Assessment Report (AR5) from the Intergovernmental Panel on Climate Change (IPCC), aerosols and CO2 are the largest contributors to anthropogenic radiative forcing--net negative for aerosols and positive for CO2. This relates to the amount of impact that aerosols and CO2 can have on our atmosphere and climate system. CO2 is the predominant greenhouse gas in the atmosphere and causes great impacts on our climate system. Recent studies show that a less well known atmospheric component--aerosols, which are solid particles or liquid droplets suspended in air, can cause great impact on our climate system too. They can affect our climate directly by absorbing and scattering sunlight to warm or cool our climate. They can also affect our climate indirectly by affecting cloud microphysical properties. Typically sulfate aerosols or sea salts act as condensation nuclei for clouds to form. Clouds are estimated to shade about 60% of the earth at any given time. They are preventing much of the sunlight from reaching the earth's surface and are helping with the flow of the global water cycle. These are what permit lifeforms on earth. In the IPCC report, both aerosols and CO2 also have the largest uncertainties and aerosols remains at a low level of scientific understanding. These indicate the need of more accurate measurements and that new technologies and instruments needs to be developed. This dissertation focuses on the development of two instruments--a scannable Micro-Pulsed Lidar (MPL) for atmospheric aerosol measurements and an Optical Parametric Oscillator (OPO) for use as a transmitter in a Differential Absorption Lidar (DIAL) for atmospheric CO2 measurements. The MPL demonstrates successful measurements of aerosols. It provides the total aerosol optical depth (AOD) and aerosol lidar ratio (Sa) that agree well with an instrument used by the Aerosol Robotic Network (AERONET). It also successfully provides range-resolved information about aerosols that AERONET instrument is incapable of. The range-resolved information is important in the study of the sources and sinks of aerosols. The OPO results show good promise for its use as a DIAL transmitter.

Climate driven egg and hatchling mortality threatens survival of eastern Pacific leatherback turtles.

PubMed

Santidrián Tomillo, Pilar; Saba, Vincent S; Blanco, Gabriela S; Stock, Charles A; Paladino, Frank V; Spotila, James R

2012-01-01

Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El Niño Southern Oscillation (ENSO). Drier and warmer conditions associated with El Niño increased egg and hatchling mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly decline in the region over the next 100 years by ∼50-60%, due to warming and drying in northwestern Costa Rica, threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in other areas affected by similar climate changes.

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

Duane, Greg; Tsonis, Anastasios; Kocarev, Ljupco

This collaborative reserach has several components but the main idea is that when imperfect copies of a given nonlinear dynamical system are coupled, they may synchronize for some set of coupling parameters. This idea is to be tested for several IPCC-like models each one with its own formulation and representing an “imperfect” copy of the true climate system. By computing the coupling parameters, which will lead the models to a synchronized state, a consensus on climate change simulations may be achieved.

Estimation of CO2 emissions from waste incinerators: Comparison of three methods.

PubMed

Lee, Hyeyoung; Yi, Seung-Muk; Holsen, Thomas M; Seo, Yong-Seok; Choi, Eunhwa

2018-03-01

Climate-relevant CO 2 emissions from waste incineration were compared using three methods: making use of CO 2 concentration data, converting O 2 concentration and waste characteristic data, and using a mass balance method following Intergovernmental Panel on Climate Change (IPCC) guidelines. For the first two methods, CO 2 and O 2 concentrations were measured continuously from 24 to 86 days. The O 2 conversion method in comparison to the direct CO 2 measurement method had a 4.8% mean difference in daily CO 2 emissions for four incinerators where analyzed waste composition data were available. However, the IPCC method had a higher difference of 13% relative to the direct CO 2 measurement method. For three incinerators using designed values for waste composition, the O 2 conversion and IPCC methods in comparison to the direct CO 2 measurement method had mean differences of 7.5% and 89%, respectively. Therefore, the use of O 2 concentration data measured for monitoring air pollutant emissions is an effective method for estimating CO 2 emissions resulting from waste incineration. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Methane emission from ruminants and solid waste: A critical analysis of baseline and mitigation projections for climate and policy studies

NASA Astrophysics Data System (ADS)

Matthews, E.

2012-12-01

Current and projected estimates of methane (CH4) emission from anthropogenic sources are numerous but largely unexamined or compared. Presented here is a critical appraisal of CH4 projections used in climate-chemistry and policy studies. We compare emissions for major CH4 sources from several groups, including our own new data and RCP projections developed for climate-chemistry models for the next IPCC Assessment Report (AR5). We focus on current and projected baseline and mitigation emissions from ruminant animals and solid waste that are both predicted to rise dramatically in coming decades, driven primarily by developing countries. For waste, drivers include increasing urban populations, higher per capita waste generation due to economic growth and increasing landfilling rates. Analysis of a new global data base detailing waste composition, collection and disposal indicates that IPCC-based methodologies and default data overestimate CH4 emission for the current period which cascades into substantial overestimates in future projections. CH4 emission from solid waste is estimated to be ~10-15 Tg CH4/yr currently rather than the ~35 Tg/yr often reported in the literature. Moreover, emissions from developing countries are unlikely to rise rapidly in coming decades because new management approaches, such as sanitary landfills, that would increase emissions are maladapted to infrastructures in these countries and therefore unlikely to be implemented. The low current emission associated with solid waste (~10 Tg), together with future modest growth, implies that mitigation of waste-related CH4 emission is a poor candidate for slowing global warming. In the case of ruminant animals (~90 Tg CH4/yr currently), the dominant assumption driving future trajectories of CH4 emission is a substantial increase in meat and dairy consumption in developing countries to be satisfied by growing animal populations. Unlike solid waste, current ruminant emissions among studies exhibit a narrow range that does not necessarily signal low uncertainty but rather a reliance on similar animal statistics and emission factors. The UN Food and Agriculture Organization (FAO) projects 2000-2030 growth rates of livestock for most developing countries at 2% to >3% annually. However, the assumption of rapidly rising meat consumption is not supported by current trends nor by resource availability. For example, increased meat consumption in China and other developing countries is poultry and pork that do not affect CH4 emissions, suggesting that the rapid growth projected for all animals, boosting growth in CH4 emission, will not occur. From a resource standpoint, large increases in cattle, sheep and goat populations, especially for African countries (~60% by 2030), are not supportable on arid grazing lands that require very low stocking rates and semi-nomadic management. Increases projected for African animal populations would require either that about 2/3 more animals are grazed on increasingly drier lands or that all non-forested areas become grazing lands. Similar to solid waste, future methane emission from ruminant animals is likely to grow modestly although animals are not a likely candidate for CH4 mitigation due to their dispersed distribution throughout widely varying agricultural systems under very local management.

Regional landfills methane emission inventory in Malaysia.

PubMed

Abushammala, Mohammed F M; Noor Ezlin Ahmad Basri; Basri, Hassan; Ahmed Hussein El-Shafie; Kadhum, Abdul Amir H

2011-08-01

The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50-60% methane (CH(4)) and 30-40% carbon dioxide (CO(2)) by volume. CH(4) has a global warming potential 21 times greater than CO(2); thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH(4) emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH(4) that would be emitted from landfills in the period from 1981-2024 using the IPCC 2006 FOD model. The total CH(4) emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH(4) emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH(4) emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH( 4) emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH(4) emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.

Atmospheric River Frequency and Intensity Changes in CMIP5 Climate Model Projections

NASA Astrophysics Data System (ADS)

Warner, M.; Mass, C.; Salathe, E. P., Jr.

2012-12-01

Most extreme precipitation events that occur along the North American west coast are associated with narrow plumes of above-average water vapor concentration that stretch from the tropics or subtropics to the West Coast. These events generally occur during the wet season (October-March) and are referred to as atmospheric rivers (AR). ARs can cause major river management problems, damage from flooding or landslides, and loss of life. It is currently unclear how these events will change in frequency and intensity as a result of climate change in the coming century. While climate model global mean precipitation match observations reasonably well in historical runs, precipitation frequency and intensity is generally poorly represented at local scales; however, synoptic-scale features are more realistically simulated by climate models, and AR events can be identified by extremely high values of integrated water vapor flux at points near the West Coast. There have been many recent studies indicating changes in synoptic-scale features under climate change that could have meaningful impacts on the frequency and intensity of ARs. In this study, a suite of CMIP5 models are used to analyze predicted changes in frequency and intensity of AR events impacting the West Coast from the contemporary period (1970-1999) to the end of this century (2070-2099). Generally, integrated water vapor is predicted to increase in these models (both the mean and extremes) while low-level wind decreases and upper-level wind increases. This study aims to determine the influence of these changes on precipitation intensity in AR events in future climate simulations.

Models of Solar Irradiance Variability and the Instrumental Temperature Record

NASA Technical Reports Server (NTRS)

Marcus, S. L.; Ghil, M.; Ide, K.

1998-01-01

The effects of decade-to-century (Dec-Cen) variations in total solar irradiance (TSI) on global mean surface temperature Ts during the pre-Pinatubo instrumental era (1854-1991) are studied by using two different proxies for TSI and a simplified version of the IPCC climate model.

Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

NASA Astrophysics Data System (ADS)

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

2017-04-01

Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) - a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP, Geosci. Model Dev., 9, 1747-1802, doi:10.5194/gmd-9-1747-2016, 2016.

Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

NASA Astrophysics Data System (ADS)

Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

2018-01-01

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

Translating landfill methane generation parameters among first-order decay models.

PubMed

Krause, Max J; Chickering, Giles W; Townsend, Timothy G

2016-11-01

Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase first-order decay model input parameters by weighted average shows that single-phase models can predict cumulative methane generation within the level of uncertainty of many of the input parameters as defined by the Intergovernmental Panel on Climate Change (IPCC), which indicates that decreasing the uncertainty of the input parameters will make the model more accurate rather than adding multiple phases or input parameters.

Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 earth system models

NASA Astrophysics Data System (ADS)

Cabré, Anna; Marinov, Irina; Leung, Shirley

2015-09-01

We analyze for the first time all 16 Coupled Model Intercomparison Project Phase 5 models with explicit marine ecological modules to identify the common mechanisms involved in projected phytoplankton biomass, productivity, and organic carbon export changes over the twenty-first century in the RCP8.5 scenario (years 2080-2099) compared to the historical scenario (years 1980-1999). All models predict decreases in primary and export production globally of up to 30 % of the historical value. We divide the ocean into biomes using upwelling velocities, sea-ice coverage, and maximum mixed layer depths. Models generally show expansion of subtropical, oligotrophic biomes and contraction of marginal sea-ice biomes. The equatorial and subtropical biomes account for 77 % of the total modern oceanic primary production (PP), but contribute 117 % to the global drop in PP, slightly compensated by an increase in PP in high latitudes. The phytoplankton productivity response to climate is surprisingly similar across models in low latitude biomes, indicating a common set of modeled processes controlling productivity changes. Ecological responses are less consistent across models in the subpolar and sea-ice biomes. Inter-hemispheric asymmetries in physical drivers result in stronger climate-driven relative decreases in biomass, productivity, and export of organic matter in the northern compared to the southern hemisphere low latitudes. The export ratio, a measure of the efficiency of carbon export to the deep ocean, decreases across low and mid-latitude biomes and models with more than one phytoplankton type, particularly in the northern hemisphere. Inter-model variability is much higher for biogeochemical than physical variables in the historical period, but is very similar among predicted 100-year biogeochemical and physical changes. We include detailed biome-by-biome analyses, discuss the decoupling between biomass, productivity and export across biomes and models, and present statistical significance and consistency across models using a novel technique based on bootstrapping combined with a weighting scheme based on similarity across models.

Evaluation of Historical and Projected Surface Air Temperature Simulations over China in CMIP5

NASA Astrophysics Data System (ADS)

Chen, L.; Frauenfeld, O. W.

2013-12-01

Projections of future temperature in China are crucial for assessments of climate change and implementation of appropriate adaptation and mitigation strategies. With the upcoming Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the fifth phase of the Coupled Model Intercomparison Project (CMIP5) was developed for assessing the latest state-of-the-art climate models and their projections. In this study, monthly surface air temperature from 20 CMIP5 models and four experiments (historical, RCP 2.6, RCP 4.5, and RCP 8.5) were used to investigate the temperature variability over China during the 20th century, and future changes for the 21st century. Two observational datasets (CRU TS 3.1 and the global terrestrial air temperature dataset from the University of Delaware) were adopted to evaluate the performance of the CMIP5 multimodel ensemble average, the performance of individual models, as well as the possible improvements in CMIP5 relative to CMIP3. Results show that both CMIP3 and CMIP5 have cold biases over most parts of China. CMIP5 displays a slightly better agreement with the observations than CMIP3, but substantial cold biases still exist over the Tibetan Plateau, especially in the cold season. These biases are also characterized by the greatest discrepancies among the individual models, indicating the models' limitations over this mountainous region. Both CMIP3 and CMIP5 show poor agreement with observed 20th-century temperature trends such that the spatial and seasonal patterns of the trends are not captured in the multimodel ensemble averages. Comparing individual models we find that MPI-ESM-LR, CanESM2, MIROC-ESM, and CCSM4 exhibit better skill than the other models in this part of the world. Projections of future temperature suggest that there will be a gradual increase in annual surface air temperature in China during the 21st century at a rate of 0.60°C/decade and 0.27°C/decade under the RCP 8.5 and RCP 4.5 scenarios, respectively. RCP 2.6 shows the slowest warming at a rate of 0.10°C/decade for the whole 21st century, but temperature will increase until 2040, and then remain stable or even decrease slightly. Based on the three emission scenarios, annual temperatures are projected to rise by 1.7-5.7°C by the end of the 21st century, and the greatest warming will occur over northern China and the Tibetan Plateau.

Projections of the 21st Century Freezing/Thawing Index in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Frauenfeld, O. W.; Zhang, T.; Teng, H.; Etringer, A. J.

2006-12-01

Variability in the ground thermal regime in high-latitude cold regions has important ramifications for surface and subsurface hydrology, carbon exchange, the surface energy and moisture balance, and ecosystem diversity and productivity. However, assessing these variations, particularly in light of reported widespread atmospheric and terrestrial changes over recent decades, remains a challenge due to the sparse observing networks in high latitudes. The annual freezing/thawing (F/T) index can be used to predict and map permafrost and seasonally frozen ground distribution, active layer and seasonal freeze depths, and has important engineering applications, thereby providing important information on climate variability in cold regions. Reliable long-term measurements of the F/T index are thus important variables for understanding and predicting high-latitude climate processes. The F/T index is defined as the cumulative number of degree-days below/above 0°C for a given time period. However, in recent work we have established that long- term monthly air temperature measurements can be used very reliably to approximate the annual F/T index. This has enabled us to produce a 25-km gridded Northern Hemisphere annual F/T index data set for 1901-2002 (see http://nsidc.org/data/ggd649.html). In this current effort we employ model projections of surface air temperatures from the Intergovernmental Panel on Climate Change (IPPC) Fourth Assessment Report (AR4) to provide an estimate of 21st century F/T index changes. This will provide an important analog to recent work on trying to establish near-surface permafrost changes in the Arctic. We will make use of runs for the four emission scenarios ("commit," "SRESA2," "SRESA1B," and "SRESB1") and "20th Century Climate in Coupled Models" (20c3m) from all 16 available models, as well as a multi-model ensemble. We first perform a comparison between our existing historical data base of F/T indices and the overlapping period of the IPCC model runs to assess the correspondence between historical observations and models. Next, we calculate the F/T index based on future scenarios, and apply the 20th century F/T indices to estimate future distributions of frozen ground, as well as active layer and seasonal freeze depths.

Modelling regional climate change and urban planning scenarios and their impacts on the urban environment in two cities with WRF-ACASA

NASA Astrophysics Data System (ADS)

Falk, M.; Pyles, R. D.; Marras, S.; Spano, D.; Paw U, K. T.

2011-12-01

The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 100 km^2. As part of the European Project "BRIDGE", these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers. Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. For two cities four climate change and four urban planning scenarios were simulated: The climate change scenarios include a base scenario (Sc0: 2008 Commit in IPCC), a medium emission scenario (Sc1: IPCC A2), a worst case emission scenario (Sce2: IPCC A1F1) and finally a best case emission scenario (Sce3: IPCC B1). The urban planning scenarios include different development scenarios such as smart growth. The two cities are a high latitude city, Helsinki (Finland) and an historic city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage and a comparatively constant architectural footprint over time. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over urban regions. We present comparisons of observed (EC) tower flux observations from the Florence (Ximeniano) site for 1-9 April, 2008 with results from two sets of high-resolution simulations: the first using dynamically-downscaled input/boundary conditions (Model-0) and the second using fully nested WRF-ACASA (Model-1). In each simulation the model physics are the same; only the WRF domain configuration differs. Preliminary results (Figure 1) indicate a degree of parity (and a slight statistical improvement), in the performances of Model-1 vs. that of Model-0 with respect to observed. Figure 1 (below) shows air temperature values from observed and both model estimates. Additional results indicate that care must be taken to configure the WRF domain, as performance appears to be sensitive to model configuration.

Modeling the influence of climate change on the mass balance of polychlorinated biphenyls in the Adriatic Sea.

PubMed

Lamon, Lara; MacLeod, Matthew; Marcomini, Antonio; Hungerbühler, Konrad

2012-05-01

Climate forcing is forecasted to influence the Adriatic Sea region in a variety of ways, including increasing temperature, and affecting wind speeds, marine currents, precipitation and water salinity. The Adriatic Sea is intensively developed with agriculture, industry, and port activities that introduce pollutants to the environment. Here, we developed and applied a Level III fugacity model for the Adriatic Sea to estimate the current mass balance of polychlorinated biphenyls in the Sea, and to examine the effects of a climate change scenario on the distribution of these pollutants. The model's performance was evaluated for three PCB congeners against measured concentrations in the region using environmental parameters estimated from the 20th century climate scenario described in the Special Report on Emission Scenarios (SRES) by the IPCC, and using Monte Carlo uncertainty analysis. We find that modeled fugacities of PCBs in air, water and sediment of the Adriatic are in good agreement with observations. The model indicates that PCBs in the Adriatic Sea are closely coupled with the atmosphere, which acts as a net source to the water column. We used model experiments to assess the influence of changes in temperature, wind speed, precipitation, marine currents, particulate organic carbon and air inflow concentrations forecast in the IPCC A1B climate change scenario on the mass balance of PCBs in the Sea. Assuming an identical PCBs' emission profile (e.g. use pattern, treatment/disposal of stockpiles, mode of entry), modeled fugacities of PCBs in the Adriatic Sea under the A1B climate scenario are higher because higher temperatures reduce the fugacity capacity of air, water and sediments, and because diffusive sources to the air are stronger. Copyright © 2012 Elsevier Ltd. All rights reserved.

Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing

NASA Astrophysics Data System (ADS)

Etminan, M.; Myhre, G.; Highwood, E. J.; Shine, K. P.

2016-12-01

New calculations of the radiative forcing (RF) are presented for the three main well-mixed greenhouse gases, methane, nitrous oxide, and carbon dioxide. Methane's RF is particularly impacted because of the inclusion of the shortwave forcing; the 1750-2011 RF is about 25% higher (increasing from 0.48 W m-2 to 0.61 W m-2) compared to the value in the Intergovernmental Panel on Climate Change (IPCC) 2013 assessment; the 100 year global warming potential is 14% higher than the IPCC value. We present new simplified expressions to calculate RF. Unlike previous expressions used by IPCC, the new ones include the overlap between CO2 and N2O; for N2O forcing, the CO2 overlap can be as important as the CH4 overlap. The 1750-2011 CO2 RF is within 1% of IPCC's value but is about 10% higher when CO2 amounts reach 2000 ppm, a value projected to be possible under the extended RCP8.5 scenario.

First Global Estimates of Anthropogenic Shortwave Forcing by Methane

NASA Astrophysics Data System (ADS)

Collins, William; Feldman, Daniel; Kuo, Chaincy

2017-04-01

Although the primary well-mixed greenhouse gases (WMGHGs) absorb both shortwave and longwave radiation, to date assessments of the effects from human-induced increases in atmospheric concentrations of WMGHGs have focused almost exclusively on quantifying the longwave radiative forcing of these gases. However, earlier studies have shown that the shortwave effects of WMGHGs are comparable to many less important longwave forcing agents routinely in these assessments, for example the effects of aircraft contrails, stratospheric anthropogenic methane, and stratospheric water vapor from the oxidation of this methane. These earlier studies include the Radiative Transfer Model Intercomparison Project (RTMIP; Collins et al. 2006) conducted using line-by-line radiative transfer codes as well as the radiative parameterizations from most of the global climate models (GCMs) assembled for the Coupled Model Intercomparison Project (CMIP-3). In this talk, we discuss the first global estimates of the shortwave radiative forcing by methane due to the anthropogenic increase in CH4 between pre-industrial and present-day conditions. This forcing is a balance between reduced heating due to absorption of downwelling sunlight in the stratosphere and increased heating due to absorption of upwelling sunlight reflected from the surface as well clouds and aerosols in the troposphere. These estimates are produced using the Observing System Simulation Experiment (OSSE) framework we have developed for NASA's upcoming Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. The OSSE is designed to compute the monthly mean shortwave radiative forcing based upon global gridded atmospheric and surface conditions extracted from either the meteorological reanalyses collected for the Analysis for MIPs (Ana4MIPs) or the CMIP-5 multi-GCM archive analyzed in the Fifth Assessment Report (AR-5) of the Intergovernmental Panel on Climate Change (IPCC). The OSSE combines these atmospheric conditions with an observationally derived prescription for the Earth's spectral surface albedo as inputs to the MODerate resolution atmospheric TRANsmission (MODTRAN) code. MODTRAN is designed to model atmospheric propagation of electromagnetic radiation for the 100-50,000 1/cm (0.2 to 100 micrometers) spectral range. This covers the spectrum from middle ultraviolet to visible light to far infrared. The most recently released version of the code, MODTRAN6, provides a spectral resolution of 0.2 1/cm using its 0.1 1/cm band model algorithm.

Hydrological regime modifications induced by climate change in Mediterranean area

NASA Astrophysics Data System (ADS)

Pumo, Dario; Caracciolo, Domenico; Viola, Francesco; Valerio Noto, Leonardo

2015-04-01

The knowledge of river flow regimes has a capital importance for a variety of practical applications, in water resource management, including optimal and sustainable use. Hydrological regime is highly dependent on climatic factors, among which the most important is surely the precipitation, in terms of frequency, seasonal distribution and intensity of rainfall events. The streamflow frequency regime of river basins are often summarized by flow duration curves (FDCs), that offer a simple and comprehensive graphical view of the overall historical variability associated with streamflow, and characterize the ability of the basin to provide flows of various magnitudes. Climate change is likely to lead shifts in the hydrological regime, and, consequently, in the FDCs. Staring from this premise, the primary objective of the present study is to explore the effects of potential climate changes on the hydrological regime of some small Mediterranean basins. To this aim it is here used a recent hydrological model, the ModABa model (MODel for Annual flow duration curves assessment in ephemeral small BAsins), for the probabilistic characterization of the daily streamflows in small catchments. The model has been calibrated and successively validated in a unique small catchment, where it has shown a satisfactory accuracy in reproducing the empirical FDC starting from easily derivable parameters arising from basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. Thus, this work also represents a first attempt to apply the ModABa to basins different from that used for its preliminary design in order to testing its generality. Different case studies are selected within the Sicily region; the model is first calibrated at the sites and then forced by future climatic scenarios, highlighting the principal differences emerging from the current scenario and future FDCs. The future climate scenarios are generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models (GCMs). The stochastic downscaling is carried out using simulations of GCMs adopted in the IPCC 5AR, for the future periods of 2046-2065 and 2081-2100.

Demographic models and IPCC climate projections predict the decline of an emperor penguin population.

PubMed

Jenouvrier, Stéphanie; Caswell, Hal; Barbraud, Christophe; Holland, Marika; Stroeve, Julienne; Weimerskirch, Henri

2009-02-10

Studies have reported important effects of recent climate change on Antarctic species, but there has been to our knowledge no attempt to explicitly link those results to forecasted population responses to climate change. Antarctic sea ice extent (SIE) is projected to shrink as concentrations of atmospheric greenhouse gases (GHGs) increase, and emperor penguins (Aptenodytes forsteri) are extremely sensitive to these changes because they use sea ice as a breeding, foraging and molting habitat. We project emperor penguin population responses to future sea ice changes, using a stochastic population model that combines a unique long-term demographic dataset (1962-2005) from a colony in Terre Adélie, Antarctica and projections of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report. We show that the increased frequency of warm events associated with projected decreases in SIE will reduce the population viability. The probability of quasi-extinction (a decline of 95% or more) is at least 36% by 2100. The median population size is projected to decline from approximately 6,000 to approximately 400 breeding pairs over this period. To avoid extinction, emperor penguins will have to adapt, migrate or change the timing of their growth stages. However, given the future projected increases in GHGs and its effect on Antarctic climate, evolution or migration seem unlikely for such long lived species at the remote southern end of the Earth.

Demographic models and IPCC climate projections predict the decline of an emperor penguin population

PubMed Central

Jenouvrier, Stéphanie; Caswell, Hal; Barbraud, Christophe; Holland, Marika; Strœve, Julienne; Weimerskirch, Henri

2009-01-01

Studies have reported important effects of recent climate change on Antarctic species, but there has been to our knowledge no attempt to explicitly link those results to forecasted population responses to climate change. Antarctic sea ice extent (SIE) is projected to shrink as concentrations of atmospheric greenhouse gases (GHGs) increase, and emperor penguins (Aptenodytes forsteri) are extremely sensitive to these changes because they use sea ice as a breeding, foraging and molting habitat. We project emperor penguin population responses to future sea ice changes, using a stochastic population model that combines a unique long-term demographic dataset (1962–2005) from a colony in Terre Adélie, Antarctica and projections of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report. We show that the increased frequency of warm events associated with projected decreases in SIE will reduce the population viability. The probability of quasi-extinction (a decline of 95% or more) is at least 36% by 2100. The median population size is projected to decline from ≈6,000 to ≈400 breeding pairs over this period. To avoid extinction, emperor penguins will have to adapt, migrate or change the timing of their growth stages. However, given the future projected increases in GHGs and its effect on Antarctic climate, evolution or migration seem unlikely for such long lived species at the remote southern end of the Earth. PMID:19171908

Seasonal Response of Overland Flow and Sediment Loading to Climate and Land Use Land Cover Change in the Apalachicola River, Florida

NASA Astrophysics Data System (ADS)

Hovenga, P. A.; Wang, D.; Medeiros, S. C.; Hagen, S. C.

2015-12-01

Located in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay within the Northern Gulf of Mexico, resulting in a direct influence on the ecology of the region, in particular seagrass and oyster production. This study examines the seasonal response of overland flow and sediment loading in the Apalachicola River under projected climate change scenarios and land use land cover (LULC) change. A hydrologic model using the Soil Water Assessment Tool (SWAT) was developed for the Apalachicola region to simulate daily discharge and sediment load under present (circa 2000) and future conditions (circa 2100) to understand how parameters respond over a seasonal time frame to changes in climate only, LULC only, and coupled climate / LULC. These physically-based models incorporate digital elevation model (DEM), LULC, soil maps, climate data, and management controls. Long Ashton Research Station-Weather Generator (LARS-WG) was used to create stochastic temperature and precipitation inputs from four Global Climate Models (GCM), each under Intergovernmental Panel on Climate Change (IPCC) carbon emission scenarios for A1B, A2, and B1. These scenarios represent potential future emissions resulting from a range driving forces, e.g. social, economic, environmental, and technologic. Projected 2100 LULC data provided by the United States Geological Survey (USGS) EROS Center was incorporated for each corresponding IPCC scenario. Results from this study can be used to further understand climate and LULC implications to the Apalachicola Bay and surrounding region as well as similar fluvial estuaries while providing tools to better guide management and mitigation practices.

Framing the future in the Southern United States climate, land use, and forest conditions

Treesearch

David N. Wear; Thomas L. Mote; J. Marshall Shepherd; K.C. Binita; Christopher W. Strother

2014-01-01

The Intergovernmental Panel on Climate Change (IPCC) has concluded, with 90% certainty, that human or “anthropogenic” activities (emissions of greenhouse gases, aerosols and pollution, landuse/ land-cover change) have altered global temperature patterns over the past 100-150 years (IPCC 2007a). Such temperature changes have a set of cascading, and sometimes amplifying...

Heat stress-induced effects of photosystem I: an overview of structural and functional responses.

PubMed

Ivanov, Alexander G; Velitchkova, Maya Y; Allakhverdiev, Suleyman I; Huner, Norman P A

2017-09-01

Temperature is one of the main factors controlling the formation, development, and functional performance of the photosynthetic apparatus in all photoautotrophs (green plants, algae, and cyanobacteria) on Earth. The projected climate change scenarios predict increases in air temperature across Earth's biomes ranging from moderate (3-4 °C) to extreme (6-8 °C) by the year 2100 (IPCC in Climate change 2007: The physical science basis: summery for policymakers, IPCC WG1 Fourth Assessment Report 2007; Climate change 2014: Mitigation of Climate Change, IPCC WG3 Fifth Assessment Report 2014). In some areas, especially of the Northern hemisphere, even more extreme warm seasonal temperatures may occur, which possibly will cause significant negative effects on the development, growth, and yield of important agricultural crops. It is well documented that high temperatures can cause direct damages of the photosynthetic apparatus and photosystem II (PSII) is generally considered to be the primary target of heat-induced inactivation of photosynthesis. However, since photosystem I (PSI) is considered to determine the global amount of enthalpy in living systems (Nelson in Biochim Biophys Acta 1807:856-863, 2011; Photosynth Res 116:145-151, 2013), the effects of elevated temperatures on PSI might be of vital importance for regulating the photosynthetic response of all photoautotrophs in the changing environment. In this review, we summarize the experimental data that demonstrate the critical impact of heat-induced alterations on the structure, composition, and functional performance of PSI and their significant implications on photosynthesis under future climate change scenarios.

Projected Changes in Mean and Interannual Variability of Surface Water over Continental China

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

Leng, Guoyong; Tang, Qiuhong; Huang, Maoyi

Five General Circulation Model (GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity (VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Results showed much larger fractional changes of annual mean Evaportranspiration (ET) per unit warming than the corresponding fractional changes of Precipitation (P) per unit warming across the country especially for South China,more » which led to notable decrease of surface water variability (P-E). Specifically, negative trends for annual mean runoff up to -0.33%/decade and soil moisture trends varying between -0.02 to -0.13%/decade were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 38 0.41%/decade and 0.90%/decade, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks (e.g. floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with steady increase of interannual variability throughout the 21st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide muti-scale guidance for assessing effective adaptation strategies for the country on a river basin, regional, or as whole.« less

Species-specific responses to climate change and community composition determine future calcification rates of Florida Keys reefs.

PubMed

Okazaki, Remy R; Towle, Erica K; van Hooidonk, Ruben; Mor, Carolina; Winter, Rivah N; Piggot, Alan M; Cunning, Ross; Baker, Andrew C; Klaus, James S; Swart, Peter K; Langdon, Chris

2017-03-01

Anthropogenic climate change compromises reef growth as a result of increasing temperatures and ocean acidification. Scleractinian corals vary in their sensitivity to these variables, suggesting species composition will influence how reef communities respond to future climate change. Because data are lacking for many species, most studies that model future reef growth rely on uniform scleractinian calcification sensitivities to temperature and ocean acidification. To address this knowledge gap, calcification of twelve common and understudied Caribbean coral species was measured for two months under crossed temperatures (27, 30.3 °C) and CO 2 partial pressures (pCO 2 ) (400, 900, 1300 μatm). Mixed-effects models of calcification for each species were then used to project community-level scleractinian calcification using Florida Keys reef composition data and IPCC AR5 ensemble climate model data. Three of the four most abundant species, Orbicella faveolata, Montastraea cavernosa, and Porites astreoides, had negative calcification responses to both elevated temperature and pCO 2 . In the business-as-usual CO 2 emissions scenario, reefs with high abundances of these species had projected end-of-century declines in scleractinian calcification of >50% relative to present-day rates. Siderastrea siderea, the other most common species, was insensitive to both temperature and pCO 2 within the levels tested here. Reefs dominated by this species had the most stable end-of-century growth. Under more optimistic scenarios of reduced CO 2 emissions, calcification rates throughout the Florida Keys declined <20% by 2100. Under the most extreme emissions scenario, projected declines were highly variable among reefs, ranging 10-100%. Without considering bleaching, reef growth will likely decline on most reefs, especially where resistant species like S. siderea are not already dominant. This study demonstrates how species composition influences reef community responses to climate change and how reduced CO 2 emissions can limit future declines in reef calcification. © 2016 John Wiley & Sons Ltd.

Climate change, atmospheric rivers, and floods in California - a multimodel analysis of storm frequency and magnitude changes

USGS Publications Warehouse

Dettinger, M.

2011-01-01

Recent studies have documented the important role that "atmospheric rivers" (ARs) of concentrated near-surface water vapor above the Pacific Ocean play in the storms and floods in California, Oregon, and Washington. By delivering large masses of warm, moist air (sometimes directly from the Tropics), ARs establish conditions for the kinds of high snowlines and copious orographic rainfall that have caused the largest historical storms. In many California rivers, essentially all major historical floods have been associated with AR storms. As an example of the kinds of storm changes that may influence future flood frequencies, the occurrence of such storms in historical observations and in a 7-model ensemble of historical-climate and projected future climate simulations is evaluated. Under an A2 greenhouse-gas emissions scenario (with emissions accelerating throughout the 21st Century), average AR statistics do not change much in most climate models; however, extremes change notably. Years with many AR episodes increase, ARs with higher-than-historical water-vapor transport rates increase, and AR storm-temperatures increase. Furthermore, the peak season within which most ARs occur is commonly projected to lengthen, extending the flood-hazard season. All of these tendencies could increase opportunities for both more frequent and more severe floods in California under projected climate changes. ?? 2011 American Water Resources Association.

Is 2 Degrees Achievable? The Cold Turkey Experiment

NASA Astrophysics Data System (ADS)

Schwartz, S. E.

2017-12-01

The 2015 Paris Agreement calls for collective international action to hold the increase in global average temperature to well below 2˚C above preindustrial levels and to pursue efforts to limit the increase to 1.5°C. How much would carbon dioxide emissions have to be reduced to achieve these objectives, or can these objectives even be achieved at all? These questions are examined using a global energy balance model to carry out a "cold turkey" experiment in which emissions from fossil fuel combustion are abruptly halted; this is a limiting case for any practically achievable gradual reduction in emissions. The model study halts emissions not just of CO2 but also of atmospheric aerosols and precursor gases. These aerosols are thought to be offsetting a substantial but highly uncertain fraction of the radiative forcing of anthropogenic CO2 by scattering solar radiation and by increasing cloud reflectivity. In contrast to CO2, which would persist in the atmosphere for decades to centuries, aerosols would be removed almost immediately after cessation of emissions. Consequently, at least in the early decades following abrupt cessation of emissions, net forcing and global temperature would likely increase, not decrease. The magnitude of the temperature increase that would ensue depends on Earth's climate sensitivity and current aerosol forcing. These quantities are quite uncertain but are strongly correlated through observational constraints. Within present uncertainty it cannot be stated with confidence whether the 2˚C target could be achieved even if emissions were abruptly halted. Future global CO2 emissions consistent with achieving the 2˚C target range from as much as 100 years at current emission rates if Earth's climate sensitivity is at the low end of the range estimated by the IPCC 2013 Assessment Report, to zero, the committed temperature increase already exceeding the 2˚C limit, if sensitivity is at the high end of the IPCC range. Figure. Global mean forcing and temperature response, for AR5 range of aerosol forcing and climate sensitivity, following abrupt cessation of emissions of CO2 and aerosols and precursor gases from fossil fuel combustion. Solid curves denote time-dependent forcing and response; dashed curves, response for CO2 maintained at its present value; dotted lines, instantaneous response.

Historical and potential future impacts of extreme hydrological events on the Amazonian floodplain hydrology and inundation dynamics

NASA Astrophysics Data System (ADS)

Macedo, M.; Panday, P. K.; Coe, M. T.; Lefebvre, P.; Castello, L.

2015-12-01

The Amazonian floodplains and wetlands cover one fifth of the basin and are highly productive promoting diverse biological communities and sustaining human populations with fisheries. Seasonal inundation of the floodplains fluctuates in response to drought or extreme rainfall as observed in the recent droughts of 2005 and 2010 where river levels dropped to among the lowest recorded. We model and evaluate the historical (1940-2010) and projected future (2010-2100) impacts of droughts and floods on the floodplain hydrology and inundation dynamics in the central Amazon using the Integrated Biosphere Simulator (IBIS) and the Terrestrial Hydrology Model and Biogeochemistry (THMB). Simulated discharge correlates well with observed discharges for tributaries originating in Brazil but underestimates basins draining regions in the non-Brazilian Amazon (Solimões, Japuŕa, Madeira, and Negro) by greater than 30%. A volume bias-correction from the simulated and observed runoff was used to correct the input precipitation across the major tributaries of the Amazon basin that drain the Andes. Simulated hydrological parameters (discharge, inundated area and river height) using corrected precipitation has a strong correlation with field measured discharge at gauging stations, surface water extent data (Global Inundation Extent from Multi-Satellites (GIEMS) and NASA Earth System Data Records (ESDRs) for inundation), and satellite radar altimetry (TOPEX/POSEIDON altimeter data for 1992-1998 and ENVISAT data for 2002-2010). We also used an ensemble of model outputs participating in the IPCC AR5 to drive two sets of simulations with and without carbon dioxide fertilization for the 2006-2100 period, and evaluated the potential scale and variability of future changes in discharge and inundation dynamics due to the influences of climate change and vegetation response to carbon dioxide fertilization. Preliminary modeled results for future scenarios using Representative Concentration Pathways (RCP) 4.5 indicate decreases in projected discharge and extent of inundated area on the mainstem Amazon by the late 21st century owing to influences of future climate change only.

Prediction Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2010-01-01

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.

Methane hydrates and contemporary climate change

USGS Publications Warehouse

Ruppel, Carolyn D.

2011-01-01

As the evidence for warming climate became better established in the latter part of the 20th century (IPCC 2001), some scientists raised the alarm that large quantities of methane (CH4) might be liberated by widespread destabilization of climate-sensitive gas hydrate deposits trapped in marine and permafrost-associated sediments (Bohannon 2008, Krey et al. 2009, Mascarelli 2009). Even if only a fraction of the liberated CH4 were to reach the atmosphere, the potency of CH4 as a greenhouse gas (GHG) and the persistence of its oxidative product (CO2) heightened concerns that gas hydrate dissociation could represent a slow tipping point (Archer et al. 2009) for Earth's contemporary period of climate change.

Comparisons of Radiative Flux Distributions from Satellite Observations and Global Models

NASA Astrophysics Data System (ADS)

Raschke, Ehrhard; Kinne, Stefan; Wild, Martin; Stackhouse, Paul; Rossow, Bill

2014-05-01

Radiative flux distributions at the top of the atmosphere (TOA) and at the surface are compared between typical data from satellite observations and from global modeling. Averages of CERES, ISCCP and SRB data-products (for the same 4-year period) represent satellite observations. Central values of IPCC-4AR output (over a 12-year period) represent global modeling. At TOA, differences are dominated by differences for cloud-effects, which are extracted from the differences between all-sky and clear-sky radiative flux products. As satellite data are considered as TOA reference, these differences document the poor representation of clouds in global modeling, especially for low altitude clouds over oceans. At the surface the differences, caused by the different cloud treatment are overlaid by a general offset. Satellite products suggest a ca 15Wm-2 stronger surface net-imbalance (and with it stronger precipitation). Since surface products of satellite and modeling are based on simulations and many assumptions, this difference has remained an open issue. BSRN surface monitoring is too short and too sparsely distributed for clear answers to provide a reliable basis for validation.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The CLUVA project: Climate-change scenarios and their impact on urban areas in Africa

NASA Astrophysics Data System (ADS)

Di Ruocco, Angela; Weets, Guy; Gasparini, Paolo; Jørgensen, Gertrud; Lindley, Sarah; Pauleit, Stephan; Vahed, Anwar; Schiano, Pasquale; Kabisch, Sigrun; Vedeld, Trond; Coly, Adrien; Tonye, Emmanuel; Touré, Hamidou; Kombe, Wilbard; Yeshitela, Kumelachew

2013-04-01

CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. Its main objective is the estimate of the impacts of climate changes in the next 40 years at urban scale in Africa. The mission of CLUVA is to develop methods and knowledge to assess risks cascading from climate-changes. It downscales IPCC climate projections to evaluate threats to selected African test cities; mainly floods, sea-level rise, droughts, heat waves and desertification. The project evaluates and links: social vulnerability; vulnerability of in-town ecosystems and urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. A multi-scale and multi-disciplinary quantitative, probabilistic, modelling is applied. CLUVA brings together climate experts, risk management experts, urban planners and social scientists with their African counterparts in an integrated research effort focusing on the improvement of the capacity of scientific institutions, local councils and civil society to cope with climate change. The CLUVA approach was set-up in the first year of the project and developed as follows: an ensemble of eight global projections of climate changes is produced for east and west Africa until 2050 considering the new IPCC (International Panel on Climate Changes; http://www.ipcc.ch/) scenarios. These are then downscaled to urban level, where territorial modeling is required to compute hazard effects on the vulnerable physical system (urban ecosystems, informal settlements, lifelines such as transportation and sewer networks) as well as on the social context, in defined time frames, and risk analysis is then employed to assess expected consequences. An investigation of the existing urban planning and governance systems and its interface with climate risks is performed. With the aid of the African partners, the developed approach is currently being applied to selected African case studies: Addis Ababa - Ethiopia; Dar es Salaam - Tanzania, Douala - Cameroun; Ouagadougou - Burkina Faso, St. Louis - Senegal. The poster will illustrate the CLUVA's framework to assess climate-change-related risks at an urban scale in Africa, and will report on the progresses of selected case studies to demonstrate feasibility of a multi-scale and multi-risk quantitative approach for risk management.

How Well Do COP22 Attendees Understand Graphs on Climate Change Health Impacts from the Fifth IPCC Assessment Report?

PubMed

Fischer, Helen; Schütte, Stefanie; Depoux, Anneliese; Amelung, Dorothee; Sauerborn, Rainer

2018-04-27

Graphs are prevalent in the reports of the Intergovernmental Panel on Climate Change (IPCC), often depicting key points and major results. However, the popularity of graphs in the IPCC reports contrasts with a neglect of empirical tests of their understandability. Here we put the understandability of three graphs taken from the Health chapter of the Fifth Assessment Report to an empirical test. We present a pilot study where we evaluate objective understanding (mean accuracy in multiple-choice questions) and subjective understanding (self-assessed confidence in accuracy) in a sample of attendees of the United Nations Climate Change Conference in Marrakesh, 2016 (COP22), and a student sample. Results show a mean objective understanding of M = 0.33 for the COP sample, and M = 0.38 for the student sample. Subjective and objective understanding were unrelated for the COP22 sample, but associated for the student sample. These results suggest that (i) understandability of the IPCC health chapter graphs is insufficient, and that (ii) particularly COP22 attendees lacked insight into which graphs they did, and which they did not understand. Implications for the construction of graphs to communicate health impacts of climate change to decision-makers are discussed.

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

High Spatial Resolution Forecasting of Long-Term Monthly Precipitation and Mean Temperature Trends in Data Scarce Regions

NASA Astrophysics Data System (ADS)

Mosier, T. M.; Hill, D. F.; Sharp, K. V.

2013-12-01

High spatial resolution time-series data are critical for many hydrological and earth science studies. Multiple groups have developed historical and forecast datasets of high-resolution monthly time-series for regions of the world such as the United States (e.g. PRISM for hindcast data and MACA for long-term forecasts); however, analogous datasets have not been available for most data scarce regions. The current work fills this data need by producing and freely distributing hindcast and forecast time-series datasets of monthly precipitation and mean temperature for all global land surfaces, gridded at a 30 arc-second resolution. The hindcast data are constructed through a Delta downscaling method, using as inputs 0.5 degree monthly time-series and 30 arc-second climatology global weather datasets developed by Willmott & Matsuura and WorldClim, respectively. The forecast data are formulated using a similar downscaling method, but with an additional step to remove bias from the climate variable's probability distribution over each region of interest. The downscaling package is designed to be compatible with a number of general circulation models (GCM) (e.g. with GCMs developed for the IPCC AR4 report and CMIP5), and is presently implemented using time-series data from the NCAR CESM1 model in conjunction with 30 arc-second future decadal climatologies distributed by the Consultative Group on International Agricultural Research. The resulting downscaled datasets are 30 arc-second time-series forecasts of monthly precipitation and mean temperature available for all global land areas. As an example of these data, historical and forecast 30 arc-second monthly time-series from 1950 through 2070 are created and analyzed for the region encompassing Pakistan. For this case study, forecast datasets corresponding to the future representative concentration pathways 45 and 85 scenarios developed by the IPCC are presented and compared. This exercise highlights a range of potential meteorological trends for the Pakistan region and more broadly serves to demonstrate the utility of the presented 30 arc-second monthly precipitation and mean temperature datasets for use in data scarce regions.

Land Surface Phenologies of the Northern Great Plains: Possible Futures Arising From Land and Climate Change

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Wimberly, M. C.; Senay, G.; Wang, A.; Chang, J.; Wright, C. R.; Hansen, M. C.

2008-12-01

Land cover change across the Northern Great Plains of North America over the past three decades has been driven by changes in agricultural management (conservation tillage; irrigation), government incentives (Conservation Reserve Program; subsidies to grain-based ethanol), crop varieties (cold-hardy soybean), and market dynamics (increasing world demand). Climate change across the Northern Great Plains over the past three decades has been evident in trends toward earlier warmth in the spring and a longer frost-free season. Together these land and climate changes induce shifts in local and regional land surface phenologies (LSPs). Any significant shift in LSP may correspond to a significant shift in evapotranspiration, with consequences for regional hydrometeorology. We explored possible future scenarios involving land use and climate change in six steps. First, we defined the nominal draw areas of current and future biorefineries in North Dakota, South Dakota, Nebraska, Minnesota, and Iowa and masked those land cover types within the draw areas that were unlikely to change to agricultural use (open water, settlements, forests, etc.). Second, we estimated the proportion of corn and soybean remaining within the masked draw areas using MODIS-derived crop maps. Third, in each draw area, we modified LSPs to simulate crop changes for a control and two treatment scenarios. In the control, we used LSP profiles identified from MODIS Collection 5 NBAR data. In one treatment, we increased the proportion of tallgrass LSPs in the draw areas to represent widespread cultivation of a perennial cellulosic crop, like switchgrass. In a second treatment, we increased the proportion of corn LSPs in the draw areas to represent increased corn cultivation. Fourth, we characterized the seasonal progression of the thermal regime associated with the LSP profiles using MODIS Land Surface Temperature (LST) products. Fifth, we modeled the LSP profile as a quadratic function of accumulated growing degree-days based on the LST time series. Sixth, we used representative IPCC AR4 mid-century projections to force the quadratic models and produce possible future LSPs. The resulting shifts in potential peak vegetation to earlier dates indicate potential seasonal shifts in evapotranspiration.

Why We Don't Collaborate in Response to Climate Change: The Knowledge Deficit, Co-Production, and the Future of the IPCC.

NASA Astrophysics Data System (ADS)

Cook, B. R.; Overpeck, J. T.

2014-12-01

Scientific knowledge production is based on recognizing and filling knowledge deficits or 'gaps' in understanding, but for climate adaptation and mitigation, the applicability of this approach is questionable. The Intergovernmental Panel on Climate Change (IPCC) mandate is an example of this type of 'gap filling,' in which the elimination of uncertainties is presumed to enable rational decision making for individuals and rational governance for societies. Presumed knowledge deficits, though, are unsuited to controversial problems with social, cultural, and economic dimensions; likewise, communication to educate is an ineffective means of inciting behavioural change. An alternative is needed, particularly given the economic, social, and political scale that action on climate change requires. We review the 'deficit-education framing' and show how it maintains a wedge between those affected and those whose knowledge is required. We then review co-production to show how natural and social scientists, as well as the IPCC, might more effectively proceed.

Atmospheric Rivers in Europe: impacts, predictability, and future climate scenarios

NASA Astrophysics Data System (ADS)

Ramos, A. M.; Tome, R.; Sousa, P. M.; Liberato, M. L. R.; Lavers, D.; Trigo, R. M.

2017-12-01

In recent years a strong relationship has been found between Atmospheric Rivers (ARs) and extreme precipitation and floods across western Europe, with some regions having 8 of their top 10 annual maxima precipitation events related to ARs. In the particular case of the Iberian Peninsula, the association between ARs and extreme precipitation days in the western river basins is noteworthy, while for the eastern and southern basins the impact of ARs is reduced. An automated ARs detection algorithm is used for the North Atlantic Ocean Basin, allowing the identification of major ARs affecting western European coasts in the present climate and under different climate change scenarios. We have used both reanalyzes and six General Circulation models under three climate scenarios (the control simulation, the RCP4.5 and RCP8.5 scenarios). The western coast of Europe was divided into five domains, namely the Iberian Peninsula, France, UK, Southern Scandinavia and the Netherlands, and Northern Scandinavia. It was found that there is an increase in the vertically integrated horizontal water transport which led to an increase in the AR frequency, a result more visible in the high emission scenarios (RCP8.5) for the 2074-2099 period. Since ARs are associated with high impact weather, it is important to study their predictability. This assessment was performed with the ECMWF ensemble forecasts up to 10 days for winters 2013/14, 2014/15 and 2015/16 for events that made landfall in the Iberian Peninsula. We show the model's potential added value to detect upcoming ARs events, which is particularly useful to predict potential hydrometeorological extremes. AcknowledgementsThis work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [PTDC / ATPGEO / 1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012). The financial support for attending this workshop was also possible through FCT project UID/GEO/50019/2013 - Instituto Dom Luiz.

Undergraduate Research Experience in Ocean/Marine Science (URE-OMS) with African Student Component

DTIC Science & Technology

2008-01-01

Intergovernmental Panel on Climate Change (IPCC). RESULTS Temporal and Spatial Variations of Sea Surface Temperature and Chlorophyll a in Coastal Waters of...Duck, North Carolina [4] Climate change has affected the North Carolina coastal environments and coastal hazards have already taken place in the area...from geological materials (sands, dead and/or bleached corals ...etc) shifted by waves, tides, and currents moving sediments and eroding shorelines

The Role of Atmospheric Deposition on the Input of Trace Elements to the Surface Ocean: the Bermuda Wet and Dry Record

NASA Astrophysics Data System (ADS)

Church, T. M.; Sedwick, P. N.; Sholkovitz, E. R.

2011-12-01

Global surface temperature variations and changes result from intricate interplay of phenomena varying on scales ranging from fraction of seconds (turbulence) to thousands of years (e.g. glaciations). To complicate these issues further, the contribution of the anthropogenic forcing on the observed changes in surface temperatures varies over time and is spatially non-uniform. While evaluating all individual bands of this broad spectrum is virtually impossible, the availability of global daily datasets in the last few decades from reanalyses and Global Climate Models (GCMs) simulations allows estimating the contribution of phenomena varying on synoptic-to-interannual timescales. Previous studies using GCM simulations for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (IPCC AR4) have documented a consistent poleward shift in the storm tracks related to changes in baroclinicity resulting from global warming. However, our recent research (Cannon et al. 2013) indicated that the pattern of changes in the storm tracks observed in the last few decades is much more complex in both space and time. Complex terrain and the relative distribution of continents, oceans and icecaps play a significant role for changes in synoptic activity. Coupled modes such as the Northern and Southern annular modes, the El Nino-Southern Oscillation (ENSO) and respective teleconnections with changes in baroclinicity have been identified as relevant dynamical forcings for variations of the midlatitude storm tracks, increasing the uncertainties in future projections. Moreover, global warming has modified the amplitude of the annual cycles of temperature, moisture and circulation throughout the planet and there is strong indication that these changes have mostly affected the tropics and Polar Regions. The present study advances these findings by investigating the 'blue-shift' in the underlying dynamics causing surface temperature anomalies and investigates relationships with low and upper level circulation. This research uses two sources of data: global daily Climate Forecast System Reanalysis (CFSR) (1979- 2010) and the Geophysical Fluid Dynamics Laboratory (GFDL) global daily simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Two sets of simulations are investigated: the Historic and Pi-control runs. Here the term ';blue-shift' is used to indicate long-term increase in the amplitude of the synoptic scale relatively to the annual cycle amplitude derived from wavelet analysis as an analogy to the definition commonly used in physics (i.e., a shift toward shorter wavelengths of the spectral lines). It is shown that the blue-shift has been observed in midlatitudes of some continental areas of the Northern Hemisphere and North Pacific but in relatively higher latitudes in the Southern Hemisphere. Tropical areas and high latitudes of the Northern Hemisphere have experienced opposite trend (red-shift). Moreover, the pattern of the blue and red-shifts exhibits seasonal changes. References: Cannon, F., L. M. V. Carvalho, C. Jones, B. Bookhagen, 2013: Multi-Annual Variations in Winter Westerly Disturbance Activity Affecting the Himalaya. Submitted to Climate Dynamics

Measuring resilience to climate change: The benefits of forest conservation in the floodplain

Treesearch

Carolyn Kousky; Margaret Walls; Ziyan Chu

2014-01-01

The economic costs of flooding have increased in the United States over the last several decades, largely as a result of more people and property, and more valuable property, located in harm’s way (Pielke and Downton 2000). In addition, climate models predict increases in the intensity of precipitation events in many locations (Wuebbles and Hayhoe 2004; IPCC 2012). How...

Climatic trends over Ethiopia: regional signals and drivers

USGS Publications Warehouse

Jury, Mark R.; Funk, Christopher C.

2013-01-01

This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

PubMed

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

2012-09-01

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems. © 2012 Blackwell Publishing Ltd.

Linguistic analysis of IPCC summaries for policymakers and associated coverage

NASA Astrophysics Data System (ADS)

Barkemeyer, Ralf; Dessai, Suraje; Monge-Sanz, Beatriz; Renzi, Barbara Gabriella; Napolitano, Giulio

2016-03-01

The Intergovernmental Panel on Climate Change (IPCC) Summary for Policymakers (SPM) is the most widely read section of IPCC reports and the main springboard for the communication of its assessment reports. Previous studies have shown that communicating IPCC findings to a variety of scientific and non-scientific audiences presents significant challenges to both the IPCC and the mass media. Here, we employ widely established sentiment analysis tools and readability metrics to explore the extent to which information published by the IPCC differs from the presentation of respective findings in the popular and scientific media between 1990 and 2014. IPCC SPMs clearly stand out in terms of low readability, which has remained relatively constant despite the IPCC’s efforts to consolidate and readjust its communications policy. In contrast, scientific and quality newspaper coverage has become increasingly readable and emotive. Our findings reveal easy gains that could be achieved in making SPMs more accessible for non-scientific audiences.

Greenhouse gas emissions from municipal solid waste management in Indian mega-cities: a case study of Chennai landfill sites.

PubMed

Jha, Arvind K; Sharma, C; Singh, Nahar; Ramesh, R; Purvaja, R; Gupta, Prabhat K

2008-03-01

Municipal solid waste generation rate is over-riding the population growth rate in all mega-cities in India. Greenhouse gas emission inventory from landfills of Chennai has been generated by measuring the site specific emission factors in conjunction with relevant activity data as well as using the IPCC methodologies for CH4 inventory preparation. In Chennai, emission flux ranged from 1.0 to 23.5mg CH4m(-2)h(-1), 6 to 460microg N2Om(-2)h(-1) and 39 to 906mg CO2m(2)h(-1) at Kodungaiyur and 0.9 to 433mg CH4m(-2)h(-1), 2.7 to 1200microg N2Om(-2)h(-1) and 12.3 to 964.4mg CO2m(-2)h(-1) at Perungudi. CH4 emission estimates were found to be about 0.12Gg in Chennai from municipal solid waste management for the year 2000 which is lower than the value computed using IPCC, 1996 [IPCC, 1996. Report of the 12th session of the intergovernmental panel of climate change, Mexico City, 1996] methodologies.

Global Analysis of Climate Change Projection Effects on Atmospheric Rivers

NASA Astrophysics Data System (ADS)

Espinoza, Vicky; Waliser, Duane E.; Guan, Bin; Lavers, David A.; Ralph, F. Martin

2018-05-01

A uniform, global approach is used to quantify how atmospheric rivers (ARs) change between Coupled Model Intercomparison Project Phase 5 historical simulations and future projections under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 warming scenarios. The projections indicate that while there will be 10% fewer ARs in the future, the ARs will be 25% longer, 25% wider, and exhibit stronger integrated water vapor transports (IVTs) under RCP8.5. These changes result in pronounced increases in the frequency (IVT strength) of AR conditions under RCP8.5: 50% (25%) globally, 50% (20%) in the northern midlatitudes, and 60% (20%) in the southern midlatitudes. The models exhibit systematic low biases across the midlatitudes in replicating historical AR frequency ( 10%), zonal IVT ( 15%), and meridional IVT ( 25%), with sizable intermodel differences. A more detailed examination of six regions strongly impacted by ARs suggests that the western United States, northwestern Europe, and southwestern South America exhibit considerable intermodel differences in projected changes in ARs.

Assessing the Global Climate Response to Freshwater Forcing from the Antarctic Ice Sheet Under Future Climate Scenarios

NASA Astrophysics Data System (ADS)

Rogstad, S.; Condron, A.; DeConto, R.; Pollard, D.

2017-12-01

Observational evidence indicates that the West Antarctic Ice Sheet (WAIS) is losing mass at an accelerating rate. Impacts to global climate resulting from changing ocean circulation patterns due to increased freshwater runoff from Antarctica in the future could have significant implications for global heat transport, but to-date this topic has not been investigated using complex numerical models with realistic freshwater forcing. Here, we present results from a high resolution fully coupled ocean-atmosphere model (CESM 1.2) forced with runoff from Antarctica prescribed from a high resolution regional ice sheet-ice shelf model. Results from the regional simulations indicate a potential freshwater contribution from Antarctica of up to 1 m equivalent sea level rise by the end of the century under RCP 8.5 indicating that a substantial input of freshwater into the Southern Ocean is possible. Our high resolution global simulations were performed under IPCC future climate scenarios RCP 4.5 and 8.5. We will present results showing the impact of WAIS collapse on global ocean circulation, sea ice, air temperature, and salinity in order to assess the potential for abrupt climate change triggered by WAIS collapse.

Estimating Regional and National-Scale Greenhouse Gas Emissions in the Agriculture, Forestry, and Other Land Use (AFOLU) Sector using the `Agricultural and Land Use (ALU) Tool'

NASA Astrophysics Data System (ADS)

Spencer, S.; Ogle, S. M.; Wirth, T. C.; Sivakami, G.

2016-12-01

The Intergovernmental Panel on Climate Change (IPCC) provides methods and guidance for estimating anthropogenic greenhouse gas emissions for reporting to the United Nations Framework Convention on Climate Change. The methods are comprehensive and require extensive data compilation, management, aggregation, documentation and calculations of source and sink categories to achieve robust emissions estimates. IPCC Guidelines describe three estimation tiers that require increasing levels of country-specific data and method complexity. Use of higher tiers should improve overall accuracy and reduce uncertainty in estimates. The AFOLU sector represents a complex set of methods for estimating greenhouse gas emissions and carbon sinks. Major AFOLU emissions and sinks include carbon dioxide (CO2) from carbon stock change in biomass, dead organic matter and soils, urea or lime application to soils, and oxidation of carbon in drained organic soils; nitrous oxide (N2O) and methane (CH4) emissions from livestock management and biomass burning; N2O from organic amendments and fertilizer application to soils, and CH4 emissions from rice cultivation. To assist inventory compilers with calculating AFOLU-sector estimates, the Agriculture and Land Use Greenhouse Gas Inventory Tool (ALU) was designed to implement Tier 1 and 2 methods using IPCC Good Practice Guidance. It guides the compiler through activity data entry, emission factor assignment, and emissions calculations while carefully maintaining data integrity. ALU also provides IPCC defaults and can estimate uncertainty. ALU was designed to simplify the AFOLU inventory compilation process at regional or national scales, disaggregating the process into a series of steps reduces the potential for errors in the compilation process. An example application has been developed using ALU to estimate methane emissions from rice production in the United States.

Projected changes in rainfall and temperature over homogeneous regions of India

NASA Astrophysics Data System (ADS)

Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

2018-01-01

The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

Exploring the Multifaceted Topic of Climate Change in Our Changing Climate and Living With Our Changing Climate

NASA Astrophysics Data System (ADS)

Brey, J. A.; Kauffman, C.; Geer, I. W.; Mills, E. W.; Nugnes, K. A.; Stimach, A. E.

2015-12-01

As the effects of climate change become more profound, climate literacy becomes increasingly important. The American Meteorological Society (AMS) responds to this need through the publication of Our Changing Climate and Living With Our Changing Climate. Both publications incorporate the latest scientific understandings of Earth's climate system from reports such as IPCC AR5 and the USGCRP's Third National Climate Assessment. Topic In Depth sections appear throughout each chapter and lead to more extensive, multidisciplinary information related to various topics. Additionally, each chapter closes with a For Further Exploration essay, which addresses specific topics that complement a chapter concept. Web Resources, which encourage additional exploration of chapter content, and Scientific Literature, from which chapter content was derived can also be found at the conclusion of each chapter. Our Changing Climate covers a breadth of topics, including the scientific principles that govern Earth's climate system and basic statistics and geospatial tools used to investigate the system. Released in fall 2015, Living With Our Changing Climate takes a more narrow approach and investigates human and ecosystem vulnerabilities to climate change, the role of energy choices in affecting climate, actions humans can take through adaption, mitigation, and policy to lessen vulnerabilities, and psychological and financial reasons behind climate change denial. While Living With Our Changing Climate is intended for programs looking to add a climate element into their curriculum, Our Changing Climate is part of the AMS Climate Studies course. In a 2015 survey of California University of Pennsylvania undergraduate students using Our Changing Climate, 82% found it comfortable to read and utilized its interactive components and resources. Both ebooks illuminate the multidisciplinary aspect of climate change, providing the opportunity for a more sustainable future.

Assessment of climate change impacts on streamflow dynamics in the headwaters of the Amazon River basin

NASA Astrophysics Data System (ADS)

Yoon, Y.; Beighley, E.

2015-12-01

The Amazon River basin is the largest watershed in the world containing thousands of tributaries. Although the mainstream and its larger tributaries have been the focus on much research, there has been few studies focused on the hydrodynamics of smaller rivers in the foothills of the Andes Mountains. These smaller rivers are of particular importance for the fishery industry because fish migrate up these headwater rivers to spawn. During the rainy season, fish wait for storm event to increase water depths to a sufficient level for their passage. Understanding how streamflow dynamics will change in response to future conditions is vital for the sustainable management of the fishery industry. In this paper, we focus on improving the accuracy of river discharge estimates on relatively small-scale sub-catchments (100 ~ 40,000 km2) in the headwaters of the Amazon River basin. The Hillslope River Routing (HRR) hydrologic model and remotely sensed datasets are used. We provide annual runoff, seasonal patterns, and daily discharge characteristics for 81 known migration reaches. The model is calibrated for the period 2000-2014 and climate forecasts for the period 2070-2100 are used to assess future changes in streamflow dynamics. The forecasts for the 2070 to 2100 period were obtained by selecting 5 climate models from IPCC's Fifth Assessment Report (AR5) Coupled Model Intercomparison Project Phase 5 (CMIP5) based on their ability to represent the main aspects of recent (1970 to 2000) Amazon climate. The river network for the HRR model is developing using surface topography based on the SRTM digital elevation model. Key model forcings include precipitation (TRMM 3B42) and evapotranspiration (MODIS ET, MOD16). Model parameters for soil depth, hydraulic conductivity, runoff coefficients and lateral routing were initially approximated based on literature values and adjusted during calibration. Measurements from stream gauges located near the reaches of interest were used for calibration. Model calibration results and simulated changes in future streamflow dynamics for the 81 river reaches are presented.

Determining the Current and Future Health of Low-Latitude Andean Glaciers Using an Equilibrium Line Altitude Model and Hypsometric Data from the Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.; MacAyeal, D. R.

2015-12-01

Mountain glaciers have been described as the water towers of world, and for many populations in the low-latitude South American Andes, glacial runoff is vital for agricultural, industrial, and basic water needs. Previous studies of low-latitude Andean glaciers suggest a precarious future due to contemporary warming. These studies have looked at trends in freezing level heights or observations of contemporary retreat. However, regional-scale understanding of low-latitude glacial responses to present and future climate change is limited, in part due to incomplete information about the extent and elevation distribution of low-latitude glaciers. The recently published Randolph Glacier Inventory (RGI) (5.0) provides the necessary information about the size and elevation distribution of low-latitude glaciers to begin such studies. We determine the contemporary equilibrium line altitudes (ELAs) for low-latitude Andean glaciers in the RGI, using a numerical energy balance ablation model driven with reanalysis and gridded data products. Contemporary ELAs tend to fall around the peak of the elevation histogram, with an exception being the southern-most outer tropical glaciers whose modeled ELAs tend to be higher than the elevation histogram for that region (see below figure). Also, we use the linear tends in temperature and precipitation from the contemporary climatology to extrapolate 21stcentury climate forcings. Modeled ELAs by the middle on the century are universally predicted to rise, with outer tropical ELAs rising more than the inner tropical glaciers. These trends continue through the end of the century. Finally, we explore how climate variables and parameters in our numerical model may vary for different warming scenarios from United Nation's IPCC AR5 report. We quantify the impacts of these changes on ELAs for various climate change trajectories. These results support previous work on the precarious future of low latitude Andean glaciers, while providing a richer understanding of the glacial impacts of contemporary and future warming. Also, this work provides analysis of processes and feedbacks between different climate variables important to glacier mass balances in a warming world, improving predictions for the fate of low-latitude Andean glaciers.

A Software Prototype For Accessing Large Climate Simulation Data Through Digital Globe Interface

NASA Astrophysics Data System (ADS)

Chaudhuri, A.; Sorokine, A.

2010-12-01

The IPCC suite of global Earth system models produced terabytes of data for the CMIP3/AR4 archive and is expected to reach the petabyte scale by CMIP5/AR5. Dynamic downscaling of global models based on regional climate models can potentially lead to even larger data volumes. The model simulations for global or regional climate models like CCSM3 or WRF are typically run on supercomputers like the ORNL/DOE Jaguar and the results are stored on high performance storage systems. Access to these results from a user workstation is impeded by a number of factors such as enormous data size, limited bandwidth of standard office networks, data formats which are not fully supported by applications. So, a user-friendly interface for accessing and visualizing these results over standard Internet connection is required to facilitate collaborative work among geographically dispersed groups of scientists. To address this problem, we have developed a virtual globe based application which enables the scientists to query, visualize and analyze the results without the need of large data transfers to desktops and department-level servers. We have used open-source NASA WorldWind as a virtual globe platform and extended it with modules capable of visualizing model outputs stored in NetCDF format, while the data resides on the high-performance system. Based on the query placed by the scientist, our system initiates data processing routines on the high performance storage system to subset the data and reduce its size and then transfer it back to scientist's workstation through secure shell tunnel. The whole operation is kept totally transparent to the scientist and for the most part is controlled from a point-and-click GUI. The virtual globe also serves as a common platform for geospatial data, allowing smooth integration of the model simulation results with geographic data from other sources such as various web services or user-specific data in local files, if required. Also the system has the capability of building and updating a metadata catalog on the high performance storage that presents a simplified summary of the stored variables, hiding the low-level details such as physical location, size or format of the files from the user. Since data are often contributed to the system from multiple sources, the metadata catalog provides the user with a bird's eye view of the recent status of the database. As a next step, we plan on parallelizing the metadata updating and query-driven data selection routines to reduce the query response time. At current stage, the system can be immediately useful in making climate model simulation results available to a greater number of researchers who need simple and intuitive visualization of the simulation data or want to perform some analysis on it. The system's utility can reach beyond this particular application since it is generic enough to be ported to other high performance systems and to enable easy access to other types of geographic data.

How well do we understand the Earth's radiation budget and the role of clouds? Selected results of the GEWEX radiation flux assessment

NASA Astrophysics Data System (ADS)

Raschke, E.; Kinne, S.

2013-05-01

Multi-year average radiative flux maps of three satellite data-sets (CERES, ISSCP and GEWEX-SRB) are compared to each other and to typical values by global modeling (median values of results of 20 climate models of the 4th IPCC Assessment). Diversity assessments address radiative flux products and at the top of the atmosphere (TOA) and the surface, with particular attention to impacts by clouds. Involving both data from surface and TOA special attention is given to the vertical radiation flux divergence and on the infrared Greenhouse effect, which are rarely shown in literature.

An overview of results from the GEWEX radiation flux assessment

NASA Astrophysics Data System (ADS)

Raschke, E.; Stackhouse, P.; Kinne, S.; Contributors from Europe; the USA

2013-05-01

Multi-annual radiative flux averages of the International Cloud Climatology Project (ISCCP), of the GEWEX - Surface Radiation Budget Project (SRB) and of the Clouds and Earth Radiative Energy System (CERES) are compared and analyzed to characterize the Earth's radiative budget, assess differences and identify possible causes. These satellite based data-sets are also compared to results of a median model, which represents 20 climate models, that participated in the 4th IPCC assessment. Consistent distribution patterns and seasonal variations among the satellite data-sets demonstrate their scientific value, which would further increase if the datasets would be reanalyzed with more accurate and consistent ancillary data.

Regional temperature and precipitation changes under high-end (≥4°C) global warming.

PubMed

Sanderson, M G; Hemming, D L; Betts, R A

2011-01-13

Climate models vary widely in their projections of both global mean temperature rise and regional climate changes, but are there any systematic differences in regional changes associated with different levels of global climate sensitivity? This paper examines model projections of climate change over the twenty-first century from the Intergovernmental Panel on Climate Change Fourth Assessment Report which used the A2 scenario from the IPCC Special Report on Emissions Scenarios, assessing whether different regional responses can be seen in models categorized as 'high-end' (those projecting 4°C or more by the end of the twenty-first century relative to the preindustrial). It also identifies regions where the largest climate changes are projected under high-end warming. The mean spatial patterns of change, normalized against the global rate of warming, are generally similar in high-end and 'non-high-end' simulations. The exception is the higher latitudes, where land areas warm relatively faster in boreal summer in high-end models, but sea ice areas show varying differences in boreal winter. Many continental interiors warm approximately twice as fast as the global average, with this being particularly accentuated in boreal summer, and the winter-time Arctic Ocean temperatures rise more than three times faster than the global average. Large temperature increases and precipitation decreases are projected in some of the regions that currently experience water resource pressures, including Mediterranean fringe regions, indicating enhanced pressure on water resources in these areas.

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

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

Brunsell, Nathaniel; Mechem, David; Ma, Chunsheng

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive tomore » alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.« less

Impacts of episodic storms on coastal wetland processes in the Northeastern U.S.

EPA Science Inventory

Climate model simulations corresponding to IPCC emissions scenarios suggest that by 2100, increases in precipitation intensity, the number of heavy precipitation events, and the intensity of the wettest events are all expected to increase, while concurrently, one to three month d...

Evolution of the potential distribution area of french mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-02-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

General circulation model response to production-limited fossil fuel emission estimates.

NASA Astrophysics Data System (ADS)

Bowman, K. W.; Rutledge, D.; Miller, C.

2008-12-01

The differences in emissions scenarios used to drive IPCC climate projections are the largest sources of uncertainty in future temperature predictions. These estimates are critically dependent on oil, gas, and coal production where the extremal variations in fossil fuel production used in these scenarios is roughly 10:1 after 2100. The development of emission scenarios based on production-limited fossil fuel estimates, i.e., total fossil fuel reserves can be reliably predicted from cumulative production, offers the opportunity to significantly reduce this uncertainty. We present preliminary results of the response of the NASA GISS atmospheric general circulation model to input forcings constrained by production-limited cumulative future fossil-fuel CO2 emissions estimates that reach roughly 500 GtC by 2100, which is significantly lower than any of the IPCC emission scenarios. For climate projections performed from 1958 through 2400 and a climate sensitivity of 5C/2xCO2, the change in globally averaged annual mean temperature relative to fixed CO2 does not exceed 3C with most changes occurring at high latitudes. We find that from 2100-2400 other input forcings such as increased in N2O play an important role in maintaining increase surface temperatures.

Projected poleward shift of king penguins' (Aptenodytes patagonicus) foraging range at the Crozet Islands, southern Indian Ocean.

PubMed

Péron, Clara; Weimerskirch, Henri; Bost, Charles-André

2012-07-07

Seabird populations of the Southern Ocean have been responding to climate change for the last three decades and demographic models suggest that projected warming will cause dramatic population changes over the next century. Shift in species distribution is likely to be one of the major possible adaptations to changing environmental conditions. Habitat models based on a unique long-term tracking dataset of king penguin (Aptenodytes patagonicus) breeding on the Crozet Islands (southern Indian Ocean) revealed that despite a significant influence of primary productivity and mesoscale activity, sea surface temperature consistently drove penguins' foraging distribution. According to climate models of the Intergovernmental Panel on Climate Change (IPCC), the projected warming of surface waters would lead to a gradual southward shift of the more profitable foraging zones, ranging from 25 km per decade for the B1 IPCC scenario to 40 km per decade for the A1B and A2 scenarios. As a consequence, distances travelled by incubating and brooding birds to reach optimal foraging zones associated with the polar front would double by 2100. Such a shift is far beyond the usual foraging range of king penguins breeding and would negatively affect the Crozet population on the long term, unless penguins develop alternative foraging strategies.

Projected poleward shift of king penguins' (Aptenodytes patagonicus) foraging range at the Crozet Islands, southern Indian Ocean

PubMed Central

Péron, Clara; Weimerskirch, Henri; Bost, Charles-André

2012-01-01

Seabird populations of the Southern Ocean have been responding to climate change for the last three decades and demographic models suggest that projected warming will cause dramatic population changes over the next century. Shift in species distribution is likely to be one of the major possible adaptations to changing environmental conditions. Habitat models based on a unique long-term tracking dataset of king penguin (Aptenodytes patagonicus) breeding on the Crozet Islands (southern Indian Ocean) revealed that despite a significant influence of primary productivity and mesoscale activity, sea surface temperature consistently drove penguins' foraging distribution. According to climate models of the Intergovernmental Panel on Climate Change (IPCC), the projected warming of surface waters would lead to a gradual southward shift of the more profitable foraging zones, ranging from 25 km per decade for the B1 IPCC scenario to 40 km per decade for the A1B and A2 scenarios. As a consequence, distances travelled by incubating and brooding birds to reach optimal foraging zones associated with the polar front would double by 2100. Such a shift is far beyond the usual foraging range of king penguins breeding and would negatively affect the Crozet population on the long term, unless penguins develop alternative foraging strategies. PMID:22378808

Methane correction factors for estimating emissions from aerobic wastewater treatment facilities based on field data in Mexico and on literature review.

PubMed

Noyola, A; Paredes, M G; Güereca, L P; Molina, L T; Zavala, M

2018-10-15

Wastewater treatment (WWT) may be an important source of methane (CH 4 ), a greenhouse gas with significant global warming potential. Sources of CH 4 emissions from WWT facilities can be found in the water and in the sludge process lines. Among the methodologies for estimating CH 4 emissions inventories from WWT, the more adopted are the guidelines of the Intergovernmental Panel on Climate Change (IPCC), which recommends default emission factors (Tier 1) depending on WWT systems. Recent published results show that well managed treatment facilities may emit CH 4 , due to dissolved CH 4 in the influent wastewater; in addition, biological nutrient removal also will produce this gas in the anaerobic (or anoxic) steps. However, none of these elements is considered in the current IPCC guidelines. The aim of this work is to propose modified (and new) methane correction factors (MCF) regarding the current Tier 1 IPCC guidelines for CH 4 emissions from aerobic treatment systems, with and without anaerobic sludge digesters, focusing on intertropical countries. The modifications are supported on in situ assessment of fugitive CH 4 emissions in two facilities in Mexico and on relevant literature data. In the case of well-managed centralized aerobic treatment plant, a MCF of 0.06 (instead of the current 0.0) is proposed, considering that the assumption of a CH 4 -neutral treatment facility, as established in the IPCC methodology, is not supported. Similarly, a MCF of 0.08 is proposed for biological nutrient removal processes, being a new entry in the guidelines. Finally, a one-step straightforward calculation is proposed for centralized aerobic treatment plants with anaerobic digesters that avoids confusion when selecting the appropriate default MCF based on the Tier 1 IPCC guidelines. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Downscaling of sea level and fluxes in the Malacca and Singapore Straits using A2 scenario projections of AR4 GCMs

NASA Astrophysics Data System (ADS)

Tkalich, Pavel; Koshebutsky, Volodymyr; Maderich, Vladimir; Thompson, Bijoy

2013-04-01

IPCC-coordinated work has been completed within Fourth Assessment Report (AR4) to project climate and ocean variables for the 21st century using coupled atmospheric-ocean General Circulation Models (GCMs). Resolution of the GCMs is not sufficient to resolve local features of narrow Malacca and Singapore Straits, having complex coastal line and bathymetry; therefore, dynamical downscaling of ocean variables from the global grid to the regional scale is advisable using ocean models, such as Regional Ocean Modeling System (ROMS). ROMS is customized for the domain centered on the Singapore and Malacca Straits, extending from 98°E to 109°E and 6°S to 14°N. Following IPCC methodology, the modelling is done for the past reference period 1961-1990, and then for the 21st century projections; subsequently, established past and projected trends and variability of ocean parameters are inter-compared. Boundary conditions for the past reference period are extracted from Simple Ocean Data Assimilation (SODA), while the projections are made using A2 scenario runs of ECHAM5 and CCSM3 GCMs. Atmospheric forcing for ROMS is downscaled with WRF using ERA-40 dataset for the past period, and outputs of atmospheric variables of respective GCMs for the projections. ROMS-downscaled regional sea level change during 1961-1990, corrected for the global thermosteric effect, land-ice melting and Global Isostatic Adjustment (GIA) effect, corresponds to a mean total trend of 1.52 mm/year, which is higher than the global estimate 1.25 mm/year and observed global sea-level rise (1.44 mm/year) for the same period. Local linear trend in the Singapore Strait (0.9 mm/year) corresponds to the observed trend at Victoria Dock tide gauge (1.1 mm/year) for the past period. Mean discharges through the Karimata, Malacca and Singapore Straits are 0.9, 0.21 and 0.12 Sv, respectively, fall in the range of observations and recent model estimates. A2 scenario projections using ROMS-ECHAM5 and ROMS-CCSM3 for 2011-2099 suggest that linear trends of sea level rise in Singapore Strait are 5.4 and 6.1 mm/year, respectively. These values fall in the range of global estimates of 3.0-8.5 mm/year. Mean sea level rise is expected around 0.43 m (ROMS-ECHAM5) and 0.47 m (ROMS-CCSM3) in 2099 relative to mean sea level in 2011. These values are greater than median estimation of global sea rise 0.32 under scenario A2. Mean discharge through Singapore Strait for scenario A2 during 2011 to 2099 is projected to be 0.062 Sv for ROMS-ECHAM5 and 0.11 Sv for ROMS-CCSM3. These projections are comparable to the discharges during 1961-1990 (0.065 and 0.11 Sv, respectively). The linear trend in discharges for the period 2011-2099 is relatively small with statistical confidence level being less than 95%. An important feature computationally discovered is the transient reversal of flow in the Singapore Strait during southwest monsoon. In general, the reversals of flow in ROMS-ECHAM5 and ROMS-CCSM3 are observed respectively to occur 1/3 and 1/5 of the whole period.

Global Warming - Myth or Reality?, The Erring Ways of Climatology

NASA Astrophysics Data System (ADS)

Leroux, Marcel

In the global-warming debate, definitive answers to questions about ultimate causes and effects remain elusive. In Global Warming: Myth or Reality? Marcel Leroux seeks to separate fact from fiction in this critical debate from a climatological perspective. Beginning with a review of the dire hypotheses for climate trends, the author describes the history of the 1998 Intergovernmental Panel on Climate Change (IPCC) and many subsequent conferences. He discusses the main conclusions of the three IPCC reports and the predicted impact on global temperatures, rainfall, weather and climate, while highlighting the mounting confusion and sensationalism of reports in the media.

Probabilistic forecast of long-term climate changes under different RCP scenarios.

NASA Astrophysics Data System (ADS)

Sokolov, Andrei; Libardoni, Alex; Forest, Chris; Monier, Erwan

2014-05-01

Long-term response of the climate system to anthropogenic forcing was investigated with the MIT Earth System Model of intermediate complexity version 2.2 (MESM2.2). The MESM2.2 consists of a 2D (zonally averaged) atmospheric model coupled to an anomaly diffusing ocean model. Climate sensitivity of the MESM can be varied using a cloud adjustment technique and rate of oceanic heat uptake can be varied by changing effective diffusion coefficient. An ensemble of four hundred simulations was carried out for the period 1860-2005 using historical forcing. Values of climate sensitivity, rate of ocean heat uptake, and the strength of the aerosol forcing were drawn from the Libardoni and Forest (2013) distribution presented in the IPCC AR5. A 400-member ensemble was carried out for each of four different RCP scenarios from the year 2006 to the year 2500. By the end of the 21st century (2081-2100), the ensemble mean of surface air temperature increases, relative to 1986-2005 period, by 1.2, 1.8, 2.2 and 3.3oC for RCP26, RCP4.5, RCP6.0 and RCP8.5, respectively. Corresponding numbers for the ensemble of the CMPI5 models are 1.0, 1.8, 2.2 and 3.7oC. In spite of the forcing being fixed beyond year 2150 for RCP4.5 and RCP6.0 and beyond 2250 for RCP8.5, surface air temperature keeps rising until the end of 25th century under these scenarios. The upper bound of the 90% probability interval increases significantly more than the mean. For the RCP4.5 scenario, the mean value of possible SAT change increases by 1.6oC from the end of the 21st century to the end of the 25th century, while the value of the 95th percentile increases by 3.2oC. Corresponding numbers for RCP6.0 and RCP8.5 are 3.6 and 10.2oC for the medians and 7.0 and 14.5oC for the 95th percentiles, respectively. Such changes in the shape of probability distributions with time indicate an increase in the probability that surface warming will exceed a given value. For example, the probability of exceeding 3oC warming under the RCP4.5 scenario increases from 2.5% at the end of 21st century to 32% and 50% at the end of 23rd and 25th centuries, respectively. For the RCP2.6 scenario, in which radiative forcing peaks in the year 2070 before decreasing back to the 1990s level by the year 2300, the ensemble mean surface air temperature is still about 0.5oC above present at the end of the simulation. Obtained results show that in spite of large differences in radiative forcing between different RCP scenarios, uncertainties in the climate system characteristics defining climate system response make a significant contribution into overall uncertainty in possible climate change during the next few centuries. Comparison with simulations carried under SRES scenarios also will be presented.

Climate change and ecosystem services: The contribution of and impacts on federal public lands in the United States

Treesearch

Valerie Esposito; Spencer Phillips; Roelof Boumans; Azur Moulaert; Jennifer Boggs

2011-01-01

The Intergovernmental Panel on Climate Change (IPCC) (2007) reports a likely 2 °C to 4.5 °C temperature rise in the upcoming decades. This warming is likely to affect ecosystems and their ability to provide services that benefit human well-being. Ecosystem services valuation (ESV), meanwhile, has emerged as a way to recognize the economic value embodied in these...

Global Modeling and Projection of Short-Lived Climate Pollutants in an Earth System Model

NASA Astrophysics Data System (ADS)

Sudo, K.; Takemura, T.; Klimont, Z.; Kurokawa, J.; Akimoto, H.

2013-12-01

In predicting and mitigating future global warming, short-lived climate pollutants (SLCPs) such as tropospheric ozone (O3), black carbon (BC), and other related components including CH4/VOCs and aerosols play crucial roles as well as long-lived species like CO2 or N2O. Several recent studies suggests that reduction of heating SLCPs (i.e., O3 and black carbon) together with CH4 can decrease and delay the expected future warming, and can be an alternative to CO2 mitigation (Shindell et al., 2012). However it should be noted that there are still large uncertainties in simulating SLCPs and their climate impacts. For instance, present global models generally have a severe tendency to underestimate BC especially in remote areas like the polar regions as shown by the recent model intercomparison project under the IPCC (ACCMIP/AeroCOM). This problem in global BC modeling, basically coming from aging and removal processes of BC, causes still a large uncertainty in the estimate of BC's atmospheric heating and climate impacts (Bond et al., 2013; Kerr et al., 2013). This study attempted to improve global simulation of BC by developing a new scheme for simulating aging process of BC and re-evaluate radiative forcing of BC in the framework of a chemistry-aerosol coupled climate model (Earth system model) MIROC-ESM-CHEM. Our improved model with the new aging scheme appears to relatively well reproduce the observed BC concentrations and seasonality in the Arctic/Antarctic region. The new model estimates radiative forcing of BC to be 0.83 W m-2 which is about two times larger than the estimate by our original model with no aging scheme (0.41 W m-2), or the model ensemble mean in the IPCC report. Using this model, future projection of SLCPs and their climate impacts is conducted following the recent IIASA emission scenarios for the year 2030 (Klimont et al., 2006; Cofala et al., 2007). Our simulation suggests that heating SLCPs components (O3, BC, and CH4) are significantly reduced in the maximal feasible reduction (MFR) scenario, contributing to global mean temperature reduction by about -0.25 oC after 2030. This heating-SLCPs-induced warming mitigation in MFR is, however, largely cancelled out by the temperature increase due to decreases in cooling aerosols (SO42-, NO3-, and organics), resulting in temperature projection which is not quite different from the other scenarios like CLE (current legislation for air quality) or 450ppm climate stabilization (intermediate reduction) scenario. References Bond et al. (2013): Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res., 118, 5380-5552, doi:10.1002/jgrd.50171, 2013. Cofala et al. (2007): Scenarios of global anthropogenic emissions of air pollutants and methane until 2030, Atmos. Environ., 41, 8486-8499. Kerr et al. (2013): Soot is warming the world even more than thought, Science, 339, 382, doi: 10.1126/science.339.6118.382. Klimont, Z., Brink, C. (2006): Modelling of Emissions of Air Pollutants and Greenhouse Gases from Agricultural Sources in Europe. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria. Shindell et al. (2012): Simultaneously Mitigating Near-Term Climate Change and Improving Human Health and Food Security, Science, 335, 183-189, doi: 10.1126/science.1210026.

Hypsometric control on glacier mass balance sensitivity in Alaska

NASA Astrophysics Data System (ADS)

McGrath, D.; Sass, L.; Arendt, A. A.; O'Neel, S.; Kienholz, C.; Larsen, C.; Burgess, E. W.

2015-12-01

Mass loss from glaciers in Alaska is dominated by strongly negative surface balances, particularly on small, continental glaciers but can be highly variable from glacier to glacier. Glacier hypsometry can exert significant control on mass balance sensitivity, particularly if the equilibrium line altitude (ELA) is in a broad area of low surface slope. In this study, we explore the spatial variability in glacier response to future climate forcings on the basis of hypsometry. We first derive mass balance sensitivities (30-70 m ELA / 1° C and 40-90 m ELA / 50% decrease in snow accumulation) from the ~50-year USGS Benchmark glaciers mass balance record. We subsequently assess mean climate fields in 2090-2100 derived from the IPCC AR5/CMIP5 RCP 6.0 5-model mean. Over glaciers in Alaska, we find 2-4° C warming and 10-20% increase in precipitation relative to 2006-2015, but a corresponding 0-50% decrease in snow accumulation due to rising temperatures. We assess changes in accumulation area ratios (AAR) to a rising ELA using binned individual glacier hypsometries. For an ELA increase of 150 m, the mean statewide AAR drops by 0.45, representing a 70% reduction in accumulation area on an individual glacier basis. Small, interior glaciers are the primary drivers of this reduction and for nearly 25% of all glaciers, the new ELA exceeds the glacier's maximum elevation, portending eventual loss. The loss of small glaciers, particularly in the drier interior of Alaska will significantly modify streamflow properties (flashy hydrographs, earlier and reduced peak flows, increased interannual variability, warmer temperatures) with poorly understood downstream ecosystem and oceanographic impacts.

The uncertain climate footprint of wetlands under human pressure

PubMed Central

Petrescu, Ana Maria Roxana; Lohila, Annalea; Tuovinen, Juha-Pekka; Baldocchi, Dennis D.; Roulet, Nigel T.; Vesala, Timo; Dolman, Albertus Johannes; Oechel, Walter C.; Marcolla, Barbara; Friborg, Thomas; Rinne, Janne; Matthes, Jaclyn Hatala; Merbold, Lutz; Meijide, Ana; Kiely, Gerard; Sottocornola, Matteo; Sachs, Torsten; Zona, Donatella; Varlagin, Andrej; Lai, Derrick Y. F.; Veenendaal, Elmar; Parmentier, Frans-Jan W.; Skiba, Ute; Lund, Magnus; Hensen, Arjan; van Huissteden, Jacobus; Flanagan, Lawrence B.; Shurpali, Narasinha J.; Grünwald, Thomas; Humphreys, Elyn R.; Jackowicz-Korczyński, Marcin; Aurela, Mika A.; Laurila, Tuomas; Grüning, Carsten; Corradi, Chiara A. R.; Schrier-Uijl, Arina P.; Christensen, Torben R.; Tamstorf, Mikkel P.; Mastepanov, Mikhail; Martikainen, Pertti J.; Verma, Shashi B.; Bernhofer, Christian; Cescatti, Alessandro

2015-01-01

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange. PMID:25831506

The uncertain climate footprint of wetlands under human pressure.

PubMed

Petrescu, Ana Maria Roxana; Lohila, Annalea; Tuovinen, Juha-Pekka; Baldocchi, Dennis D; Desai, Ankur R; Roulet, Nigel T; Vesala, Timo; Dolman, Albertus Johannes; Oechel, Walter C; Marcolla, Barbara; Friborg, Thomas; Rinne, Janne; Matthes, Jaclyn Hatala; Merbold, Lutz; Meijide, Ana; Kiely, Gerard; Sottocornola, Matteo; Sachs, Torsten; Zona, Donatella; Varlagin, Andrej; Lai, Derrick Y F; Veenendaal, Elmar; Parmentier, Frans-Jan W; Skiba, Ute; Lund, Magnus; Hensen, Arjan; van Huissteden, Jacobus; Flanagan, Lawrence B; Shurpali, Narasinha J; Grünwald, Thomas; Humphreys, Elyn R; Jackowicz-Korczyński, Marcin; Aurela, Mika A; Laurila, Tuomas; Grüning, Carsten; Corradi, Chiara A R; Schrier-Uijl, Arina P; Christensen, Torben R; Tamstorf, Mikkel P; Mastepanov, Mikhail; Martikainen, Pertti J; Verma, Shashi B; Bernhofer, Christian; Cescatti, Alessandro

2015-04-14

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Modelling future changes to the stratospheric source gas injection of biogenic bromocarbons

NASA Astrophysics Data System (ADS)

Hossaini, R.; Chipperfield, M. P.; Dhomse, S.; Ordóñez, C.; Saiz-Lopez, A.; Abraham, N. L.; Archibald, A.; Braesicke, P.; Telford, P.; Warwick, N.; Yang, X.; Pyle, J.

2012-10-01

Simulations with a chemistry-climate model (CCM) show a future increase in the stratospheric source gas injection (SGI) of biogenic very short-lived substances (VSLS). For 2000, the modelled SGI of bromine from VSLS is ∼1.7 parts per trillion (pptv) and largest over the tropical West Pacific. For 2100, this increases to ∼2.0 and ∼2.7 pptv when the model is forced with Intergovernmental Panel on Climate Change (IPCC) representative concentration pathways (RCPs) 4.5 and 8.5. The increase is largely due to stronger tropical deep convection transporting more CHBr3 to the lower stratosphere. For CH2Br2, CHBr2Cl, CH2BrCl and CHBrCl2, changes to primary oxidant OH determines their SGI contribution. Under RCP 4.5 (moderate warming), OH increases in a warmer, more humid troposphere. Under RCP 8.5 (extreme warming) OH decreases significantly due to a large methane increase, allowing greater SGI of bromine from these VSLS. Potentially enhanced VSLS emissions in the future would further increase these estimates.

The rapid disintegration of projections: the West Antarctic Ice Sheet and the intergovernmental panel on climate change.

PubMed

O'Reilly, Jessica; Oreskes, Naomi; Oppenheimer, Michael

2012-10-01

How and why did the scientific consensus about sea level rise due to the disintegration of the West Antarctic Ice Sheet (WAIS), expressed in the third Intergovernmental Panel on Climate Change (IPCC) assessment, disintegrate on the road to the fourth? Using ethnographic interviews and analysis of IPCC documents, we trace the abrupt disintegration of the WAIS consensus. First, we provide a brief historical overview of scientific assessments of the WAIS. Second, we provide a detailed case study of the decision not to provide a WAIS prediction in the Fourth Assessment Report. Third, we discuss the implications of this outcome for the general issue of scientists and policymakers working in assessment organizations to make projections. IPCC authors were less certain about potential WAIS futures than in previous assessment reports in part because of new information, but also because of the outcome of cultural processes within the IPCC, including how people were selected for and worked together within their writing groups. It became too difficult for IPCC assessors to project the range of possible futures for WAIS due to shifts in scientific knowledge as well as in the institutions that facilitated the interpretations of this knowledge.

Next Generation Climate Change Experiments Needed to Advance Knowledge and for Assessment of CMIP6

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

Katzenberger, John; Arnott, James; Wright, Alyson

2014-10-30

The Aspen Global Change Institute hosted a technical science workshop entitled, “Next generation climate change experiments needed to advance knowledge and for assessment of CMIP6,” on August 4-9, 2013 in Aspen, CO. Jerry Meehl (NCAR), Richard Moss (PNNL), and Karl Taylor (LLNL) served as co-chairs for the workshop which included the participation of 32 scientists representing most of the major climate modeling centers for a total of 160 participant days. In August 2013, AGCI gathered a high level meeting of representatives from major climate modeling centers around the world to assess achievements and lessons learned from the most recent generationmore » of coordinated modeling experiments known as the Coupled Model Intercomparison Project – 5 (CMIP5) as well as to scope out the science questions and coordination structure desired for the next anticipated phase of modeling experiments called CMIP6. The workshop allowed for reflection on the coordination of the CMIP5 process as well as intercomparison of model results, such as were assessed in the most recent IPCC 5th Assessment Report, Working Group 1. For example, this slide from Masahiro Watanabe examines performance on a range of models capturing Atlantic Meridional Overturning Circulation (AMOC).« less

Preliminary forecasts of Pacific bigeye tuna population trends under the A2 IPCC scenario

NASA Astrophysics Data System (ADS)

Lehodey, P.; Senina, I.; Sibert, J.; Bopp, L.; Calmettes, B.; Hampton, J.; Murtugudde, R.

2010-07-01

An improved version of the spatial ecosystem and population dynamics model SEAPODYM was used to investigate the potential impacts of global warming on tuna populations. The model included an enhanced definition of habitat indices, movements, and accessibility of tuna predators to different vertically migrant and non-migrant micronekton functional groups. The simulations covered the Pacific basin (model domain) at a 2° × 2° geographic resolution. The structure of the model allows an evaluation from multiple data sources, and parameterization can be optimized by adjoint techniques and maximum likelihood using fishing data. A first such optimized parameterization was obtained for bigeye tuna ( Thunnus obesus) in the Pacific Ocean using historical catch data for the last 50 years and a hindcast from a coupled physical-biogeochemical model driven by the NCEP atmospheric reanalysis. The parameterization provided very plausible biological parameter values and a good fit to fishing data from the different fisheries, both within and outside the time period used for optimization. We then employed this model to forecast the future of bigeye tuna populations in the Pacific Ocean. The simulation was driven by the physical-biogeochemical fields predicted from a global marine biogeochemistry - climate simulation. This global simulation was performed with the IPSL climate model version 4 (IPSL-CM4) coupled to the oceanic biogeochemical model PISCES and forced by atmospheric CO 2, from historical records over 1860-2000, and under the SRES A2 IPCC scenario for the 21st century (i.e. atmospheric CO 2 concentration reaching 850 ppm in the year 2100). Potential future changes in distribution and abundance under the IPCC scenario are presented but without taking into account any fishing effort. The simulation showed an improvement in bigeye tuna spawning habitat both in subtropical latitudes and in the eastern tropical Pacific (ETP) where the surface temperature becomes optimal for bigeye tuna spawning. The adult feeding habitat also improved in the ETP due to the increase of dissolved oxygen concentration in the sub-surface allowing adults to access deeper forage. Conversely, in the Western Central Pacific the temperature becomes too warm for bigeye tuna spawning. The decrease in spawning is compensated by an increase of larvae biomass in subtropical regions. However, natural mortality of older stages increased due to lower habitat values (too warm surface temperatures, decreasing oxygen concentration in the sub-surface and less food). This increased mortality and the displacement of surviving fish to the eastern region led to stable then declining adult biomass at the end of the century.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

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

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

Determining the impacts of climate change and catchment development on future water availability in Tasmania, Australia

NASA Astrophysics Data System (ADS)

Post, David

2010-05-01

In a water-scarce country such as Australia, detailed, accurate and reliable assessments of current and future water availability are essential in order to adequately manage the limited water resource. This presentation describes a recently completed study which provided an assessment of current water availability in Tasmania, Australia, and also determined how this water availability would be impacted by climate change and proposed catchment development by the year 2030. The Tasmania Sustainable Yields Project (http://www.csiro.au/partnerships/TasSY.html) assessed current water availability through the application of rainfall-runoff models, river models, and recharge and groundwater models. These were calibrated to streamflow records and parameterised using estimates of current groundwater and surface water extractions and use. Having derived a credible estimate of current water availability, the impacts of future climate change on water availability were determined through deriving changes in rainfall and potential evapotranspiration from 15 IPCC AR4 global climate models. These changes in rainfall were then dynamically downscaled using the CSIRO-CCAM model over the relatively small study area (50,000 square km). A future climate sequence was derived by modifying the historical 84-year climate sequence based on these changes in rainfall and potential evapotranspiration. This future climate sequence was then run through the rainfall-runoff, river, recharge and groundwater models to give an estimate of water availability under future climate. To estimate the impacts of future catchment development on water availability, the models were modified and re-run to reflect projected increases in development. Specifically, outputs from the rainfall-runoff and recharge models were reduced over areas of projected future plantation forestry. Conversely, groundwater recharge was increased over areas of new irrigated agriculture and new extractions of water for irrigation were implemented in the groundwater and river models. Results indicate that historical average water availability across the project area was 21,815 GL/year. Of this, 636 GL/year of surface water and 38 GL/year of groundwater are currently extracted for use. By 2030, rainfall is projected to decrease by an average of 3% over the project area. This decrease in rainfall and concurrent increase in potential evapotranspiration leads to a decrease in water availability of 5% by 2030. As a result of lower streamflows, under current cease-to-take rules, currently licensed extractions are projected to decrease by 3% (19 GL/year). This however is offset by an additional 120 GL/year of extractions for proposed new irrigated agriculture. These new extractions, along with the increase in commercial forest plantations lead to a reduction in total surface water of 1% in addition to the 5% reduction due to climate change. Results from this study are being used by the Tasmanian and Australian governments to guide the development of a sustainable irrigated agriculture industry in Tasmania. In part, this is necessary to offset the loss of irrigated agriculture from the southern Murray-Darling Basin where climate change induced reductions in rainfall are projected to be far worse.

[Potential distribution of Panax ginseng and its predicted responses to climate change.

PubMed

Zhao, Ze Fang; Wei, Hai Yan; Guo, Yan Long; Gu, Wei

2016-11-18

This study utilized Panax ginseng as the research object. Based on BioMod2 platform, with species presence data and 22 climatic variables, the potential geographic distribution of P. ginseng under the current conditions in northeast China was simulated with ten species distribution model. And then with the receiver-operating characteristic curve (ROC) as weights, we build an ensemble model, which integrated the results of 10 models, using the ensemble model, the future distributions of P. ginseng were also projected for the periods 2050s and 2070s under the climate change scenarios of RCP 8.5, RCP 6, RCP 4.5 and RCP 2.6 emission scenarios described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that for the entire region of study area, under the present climatic conditions, 10.4% of the areas were identified as suitable habitats, which were mainly located in northeast Changbai Mountains area and the southeastern region of the Xiaoxing'an Mountains. The model simulations indicated that the suitable habitats would have a relatively significant change under the different climate change scenarios, and generally the range of suitable habitats would be a certain degree of decrease. Meanwhile, the goodness-of-fit, predicted ranges, and weights of explanatory variables was various for each model. And according to the goodness-of-fit, Maxent had the highest model performance, and GAM, RF and ANN were followed, while SRE had the lowest prediction accuracy. In this study we established an ensemble model, which could improve the accuracy of the existing species distribution models, and optimization of species distribution prediction results.

Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: a multi-model analysis with a new set of land-cover change scenarios

NASA Astrophysics Data System (ADS)

Guimberteau, Matthieu; Ciais, Philippe; Ducharne, Agnès; Boisier, Juan Pablo; Dutra Aguiar, Ana Paula; Biemans, Hester; De Deurwaerder, Hannes; Galbraith, David; Kruijt, Bart; Langerwisch, Fanny; Poveda, German; Rammig, Anja; Andres Rodriguez, Daniel; Tejada, Graciela; Thonicke, Kirsten; Von Randow, Celso; Von Randow, Rita C. S.; Zhang, Ke; Verbeeck, Hans

2017-03-01

Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3 °C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14 %, respectively. However, in south-east Amazonia, precipitation decreases by 10 % at the end of the dry season and the three LSMs produce a 6 % decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31 % in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34 % over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27 % in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.

Uncertainties in the projection of species distributions related to general circulation models

PubMed Central

Goberville, Eric; Beaugrand, Grégory; Hautekèete, Nina-Coralie; Piquot, Yves; Luczak, Christophe

2015-01-01

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM-based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi-GCM and multi-emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between-GCM variability was greater than the between-RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi-GCM and multi-RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between-GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties. PMID:25798227

Soil Organic Carbon and Nitrogen in the 21st Century: Projections of the Responses of an Old-Growth Douglas-Fir Forest in the Pacific Northwest under RCP 4.5 and RCP 8.5 Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Dong, Z.; Driscoll, C. T.; Hayhoe, K.; Pourmokhtarian, A.; Stoner, A. M. K.

2015-12-01

The biogeochemical model, PnET-BGC, was applied to Watershed 2 in H. J. Andrews Experimental Forest, Oregon, to project ecosystem carbon and nitrogen responses under different future climate change scenarios. Downscaled climate change inputs derived from two IPCC scenarios (RCP 4.5 and RCP 8.5) were interpreted by four Atmosphere-Ocean General Circulation Models (AOGCMs) at Andrews Forest. Model results showed decreases in foliar production under high temperature/CO2 scenarios due to increasing vapor pressure deficit. Projections by PnET-BGC suggest that under future climate changes in primary production coupled with an increasing rate of decomposition may result in decreases in litterfall carbon and nitrogen and soil organic carbon and nitrogen. Such changes in soil organic carbon and nitrogen may cause wide range of changes in ecosystem processing of nitrogen and carbon, such as nitrogen mineralization, plant NH4+ uptake, and stream NH4+ and dissolved organic carbon concentrations depending on climate change scenario considered. Under most high emission scenarios, net nitrogen mineralization and plant NH4+ uptake are projected to increase until the end of this century as result of increasing temperature and associated higher rates of decomposition. An accumulation of nitrogen in plant tissue due to decreasing litterfall decreases plant demand for nitrogen. Such changes in nitrogen mineralization and uptake will result in increase in stream NH4+ concentrations under high emission scenarios. Under low emission scenarios, net nitrogen mineralization and plant NH4+ uptake are projected to increase up to mid-century, then slightly decrease until the end of the century.

Upper Limit for Regional Sea Level Projections

NASA Astrophysics Data System (ADS)

Jevrejeva, Svetlana; Jackson, Luke; Riva, Riccardo; Grinsted, Aslak; Moore, John

2016-04-01

With more than 150 million people living within 1 m of high tide future sea level rise is one of the most damaging aspects of warming climate. The latest Intergovernmental Panel on Climate Change report (AR5 IPCC) noted that a 0.5 m rise in mean sea level will result in a dramatic increase the frequency of high water extremes - by an order of magnitude, or more in some regions. Thus the flood threat to the rapidly growing urban populations and associated infrastructure in coastal areas are major concerns for society. Hence, impact assessment, risk management, adaptation strategy and long-term decision making in coastal areas depend on projections of mean sea level and crucially its low probability, high impact, upper range. With probabilistic approach we produce regional sea level projections taking into account large uncertainties associated with Greenland and Antarctica ice sheets contribution. We calculate the upper limit (as 95%) for regional sea level projections by 2100 with RCP8.5 scenario, suggesting that for the most coastlines upper limit will exceed the global upper limit of 1.8 m.

Hydroclimatic projections for the Murray-Darling Basin based on an ensemble derived from Intergovernmental Panel on Climate Change AR4 climate models

NASA Astrophysics Data System (ADS)

Sun, Fubao; Roderick, Michael L.; Lim, Wee Ho; Farquhar, Graham D.

2011-12-01

We assess hydroclimatic projections for the Murray-Darling Basin (MDB) using an ensemble of 39 Intergovernmental Panel on Climate Change AR4 climate model runs based on the A1B emissions scenario. The raw model output for precipitation, P, was adjusted using a quantile-based bias correction approach. We found that the projected change, ΔP, between two 30 year periods (2070-2099 less 1970-1999) was little affected by bias correction. The range for ΔP among models was large (˜±150 mm yr-1) with all-model run and all-model ensemble averages (4.9 and -8.1 mm yr-1) near zero, against a background climatological P of ˜500 mm yr-1. We found that the time series of actually observed annual P over the MDB was indistinguishable from that generated by a purely random process. Importantly, nearly all the model runs showed similar behavior. We used these facts to develop a new approach to understanding variability in projections of ΔP. By plotting ΔP versus the variance of the time series, we could easily identify model runs with projections for ΔP that were beyond the bounds expected from purely random variations. For the MDB, we anticipate that a purely random process could lead to differences of ±57 mm yr-1 (95% confidence) between successive 30 year periods. This is equivalent to ±11% of the climatological P and translates into variations in runoff of around ±29%. This sets a baseline for gauging modeled and/or observed changes.

Estimating changes in carbon burial on the western US coastal shelf due to anthropogenic influences on river exports

NASA Astrophysics Data System (ADS)

Sauer, M.; Bergamaschi, B. A.; Smith, R. A.; Zhu, Z.; Shih, J.

2012-12-01

Flux of nutrients and sediments to the coastal zone varies in response to land-use modification, reservoir construction, management action and population change. It is anticipated that future changes in the flux of these components in response to climate and terrestrial processes will affect carbon (C) burial in the coastal ocean. Coastal oceans store appreciable amounts of C as a result of river inflows: coastal primary production is enhanced by inputs of terrestrially derived nutrients, and C burial is controlled by terrestrial sediment supply. Assessing the capacity and changes to coastal C preservation, therefore, requires estimation of (1) riverine nutrient and sediment delivery to the coastal ocean, and (2) the enhanced C production and sediment deposition in the coastal ocean. The United States Geological Survey (USGS) has embarked on a congressionally-mandated nationwide effort to assess the future effects of climate and land use and land cover change (LULC) on C storage. The USGS has developed alternative scenarios for changes in US LULC from 2006 to 2100 based on the Intergovernmental Panel on Climate Change (IPCC) climate, economic, and demographic scenarios (Sohl et al 2012). These spatially-detailed scenarios provide inputs to national-scale SPARROW watershed models of total nitrogen, total phosphorus, total organic C (TOC), and suspended sediment (Smith et al 1997; Schwarz et al, 2006). The watershed models, in turn, provide inputs of nutrients, TOC, and sediment to a coupled model of coastal transport, production, and sedimentation. This coastal modelling component includes particulate C sedimentation and burial estimated as functions of bathymetry and pycnocline depth (Armstrong, et al 2002; Dunne et al 2007). River borne fluxes of TOC to US Pacific coastal waters under baseline conditions (1992) were 1.59 TgC/yr. Projected future (2050) fluxes under a regionally-downscaled LULC scenario aligned with the IPCC A2 scenario were similar (1.61TgC/yr). C storage in coastal environments as influenced by terrestrial processes represents a significant sink for C in comparison to terrestrial biomass C sinks, and is significantly sensitive to changes in LULC and population. The estimated rate of storage in Pacific coastal waters was 2.0 TgC/yr under baseline conditions. Projection of land use and population changes through 2050 associated with the IPCC A2 scenario had a small effect on coastal C storage processes, reducing C storage by 4% over baseline conditions. Results of this modeling exercise indicate that the size of the C sink associated with terrestrial exports is substantial and sensitive to anthropogenic activity. Thus, future assessments of how terrestrial policy and management actions may alter C storage should include an evaluation of the effects prospective alterations in terrestrial processes have on coastal C storage.

Indirect effect of changing aerosol concentrations on methane and ozone radiative forcing

NASA Astrophysics Data System (ADS)

Rowlinson, Matthew; Rap, Alexandru; Arnold, Steve; Forster, Piers; Chipperfield, Martyn

2017-04-01

Atmospheric aerosols interact with climate in number of complex ways and quantifying the overall effect remains the dominant uncertainty in estimating anthropogenic climate forcing (IPCC, 2013). The radiative forcing (RF) caused by the direct effect of aerosol interacting with radiation is estimated at -0.35 (-0.85 to +0.15) Wm-2, while cloud-aerosol interactions are estimated at -0.45 (-1.2 to 0.0) Wm-2 (IPCC, 2013). The net impact is a cooling with an effective radiative forcing (ERF) of 0.9 (-1.9 to -0.1) Wm-2 (IPCC, 2013). One effect of aerosols which has not been well evaluated is their effect on atmospheric chemistry. Atmospheric aerosols provide a surface for homogeneous reactions to occur, altering reactions rates and the availability of oxidants, thereby influencing the removal/production of radiatively important species such as methane (CH4) and tropospheric ozone (O3). Oxidants such as the hydroxyl radical (OH) determine the atmospheric lifetime and hence burden of CH4, therefore changes to atmospheric aerosols which impact oxidation chemistry will also influence RF due to CH4. This effect could enhance or offset the negative RF of aerosols, depending on how the individual aerosol changes availability of oxidants. Quantifying the importance of this mechanism for RF is necessary to provide accurate estimates of the effect of aerosols, and assess relative effectiveness of measures to decrease aerosol emissions and precursors. Using a sophisticated aerosol micro-physics model (GLOMAP) coupled to the TOMCAT three-dimensional chemical transport model, we separately simulate changes in atmospheric composition resulting from a 50% decline in anthropogenic emissions of black carbon aerosol (BC), volatile organic compounds (VOCs) and anthropogenic precursors of sulphate and nitrate. The impact of changes to each aerosol on lifetime of CH4 is then calculated to establish the resulting impact on CH4 burden and RF. Cutting global anthropogenic SO2 emissions by 50% decreases atmospheric sulpate concentrations by 44% after 2 years, while increasing global OH concentrations by 0.9%. CH4 lifetime is reduced by approximately 50 days as a result, leading to a decrease in CH4 burden of 38ppb. NOx is anticipated to have a similar but much larger effect (Matsui and Koike 2016). The Edwards and Slingo offline radiation model is also used to calculate changes to direct and indirect aerosol forcing. Presented here is the net RF change following 50% emission decrease of each aerosol or precursors, accounting for the direct and indirect aerosol effect as well as indirect effects via oxidation chemistry on the RF due to CH4 and tropospheric O3.

Understanding extreme sea levels for coastal impact and adaptation analysis

NASA Astrophysics Data System (ADS)

Wahl, T.; Haigh, I. D.; Nicholls, R. J.; Arns, A.; Hinkel, J.; Dangendorf, S.; Slangen, A.

2016-12-01

Coastal impact and adaptation assessments require detailed knowledge on extreme sea levels, because increasing damage due to extreme events, such as storm surges and tropical cyclones, is one of the major consequences of sea level rise and climate change. In fact, the IPCC has highlighted in its AR4 report that "societal impacts of sea level change primarily occur via the extreme levels rather than as a direct consequence of mean sea level changes". Over the last few decades, substantial research efforts have been directed towards improved understanding of past and future mean sea level; different scenarios were developed with process-based or semi-empirical models and used for coastal impact assessments at various spatial scales to guide coastal management and adaptation efforts. The uncertainties in future sea level rise are typically accounted for by analyzing the impacts associated with a range of scenarios leading to a vertical displacement of the distribution of extreme sea-levels. And indeed most regional and global studies find little or no evidence for changes in storminess with climate change, although there is still low confidence in the results. However, and much more importantly, there is still a limited understanding of present-day extreme sea-levels which is largely ignored in most impact and adaptation analyses. The two key uncertainties stem from: (1) numerical models that are used to generate long time series of extreme sea-levels. The bias of these models varies spatially and can reach values much larger than the expected sea level rise; but it can be accounted for in most regions making use of in-situ measurements; (2) Statistical models used for determining present-day extreme sea-level exceedance probabilities. There is no universally accepted approach to obtain such values for flood risk assessments and while substantial research has explored inter-model uncertainties for mean sea level, we explore here, for the first time, inter-model uncertainties for extreme sea-levels at large spatial scales and compare them to the uncertainties in mean sea level projections.

Latest research related to climate change analysis with applications in impact studies over the territory of Serbia

NASA Astrophysics Data System (ADS)

Vukovic, Ana; Vujadinovic, Mirjam; Djurdjevic, Vladimir; Cvetkovic, Bojan; Djordjevic, Marija; Ruml, Mirjana; Rankovic-Vasic, Zorica; Przic, Zoran; Stojicic, Djurdja; Krzic, Aleksandra; Rajkovic, Borivoj

2015-04-01

Serbia is a country with relatively small scale terrain features with economy mostly based on local landowners' agricultural production. Climate change analysis must be downscaled accordingly, to recognize climatological features of the farmlands. Climate model simulations and impact studies significantly contribute to the future strategic planning in economic development and therefore impact analysis must be approached with high level of confidence. This paper includes research related to climate change and impacts in Serbia resulted from cooperative work of the modeling and user community. Dynamical downscaling of climate projections for the 21st century with multi-model approach and statistical bias correction are done in order to prepare model results for impact studies. Presented results are from simulations performed using regional EBU-POM model, which is forced with A1B and A2 SRES/IPCC (2007) with comparative analysis with other regional models and from the latest high resolution NMMB simulations forced with RCP8.5 IPCC scenario (2012). Application of bias correction of the model results is necessary when calculated indices are not linearly dependent on the model results and delta approach in presenting results with respect to present climate simulations is insufficient. This is most important during the summer over the north part of the country where model bias produce much higher temperatures and less precipitation, which is known as "summer drying problem" and is common in regional models' simulations over the Pannonian valley. Some of the results, which are already observed in present climate, like higher temperatures and disturbance in the precipitation pattern, lead to present and future advancement of the start of the vegetation period toward earlier dates, associated with an increased risk of the late spring frost, extended vegetation period, disturbed preparation for the rest period, increased duration and frequency of the draught periods, etc. Based on the projected climate changes an application is proposed of the ensemble seasonal forecasts for early preparation in case of upcoming unfavorable weather conditions. This paper was realized as a part of the projects "Studying climate change and its influence on the environment: impacts, adaptation and mitigation" (43007) and "Assessment of climate change impacts on water resources in Serbia" (37005) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011-2015.

Assessing the Vulnerability of Agriculture to Climate Change in Jordan

NASA Astrophysics Data System (ADS)

Khresat, Sa'eb; Shraidaeh, Fadi; Maddat, Amer

2015-04-01

Climate change represents one of the greatest environmental, social and economic threats facing Jordan. In particular, the combined effects of climate change and water scarcity threaten to affect food and water resources that are critical for livelihoods in Jordan. This is especially true for those communities who live in the dryland area in the country and who rely wholly on rain-fed agriculture. The exact nature and extent of the impact of climate change on temperature and precipitation distribution pattern remain uncertain and it is the poor and vulnerable who will be the most susceptible to climate change adverse effects. A vulnerability assessment of rain fed agriculture to climate change and variability in semi-arid parts of Jordan was conducted in 2014. The purpose of this study is to assess the vulnerability and resilience of the most vulnerable groups where rainfed and irrigated agriculture is practiced. Also, the study focused on quantifying the impacts on agricultural productivity in response to climate change. This will help policymakers and researchers better understand and anticipate the likely impacts of climate change on agriculture and on vulnerable communities in Jordan. Also, it will provide them with tools to identify and implement appropriate adaptation strategies. The data used includes; Representative Concentration Pathways (RCPs), RCP 4.5 and RCP 8.5 adopted by the IPCC for its fifth Assessment Report (AR5). Those pathways were used for climate modeling. A decision support system (DSSAT) for agricultural production was used to assess the impact of climate changes on agricultural production. This approach was used for the Identification of climate change risk and their impacts on Agriculture. Outputs from models are used to assess the vulnerability of farmers and crops to climate and socio-economic change by estimating their sensitivity and capacity to adapt to external factors as a means of identifying what causes the differences in their vulnerability. Based on the projection models for the area, average temperature in Jordan is projected to increase between 1.2 and 1.6°C by 2050. These upward temperature trends are projected to continue beyond 2050. Projections for precipitation trends are projected to decrease by 16% by the year 2050. Evaporation is likely to increase due to higher temperatures. This is likely to increase the incidence of drought potential since precipitation is projected to decrease. It is concluded that the Overall vulnerability of agriculture to climate change in Jordan is high, where impacts such as drought and increased temperatures and decreased precipitation will be more pronounced. Major implications on rain fed agriculture are possible shorter growing season, increasing moisture and heat stress to field and horticultural crops and eventually low income and food insecurity. There were different impacts among studied communities, which is related to the: economic capability, local knowledge, physical infrastructure, institutional capacity, modern technology used, age group of farmers and diversification of their income.

Investigating the Sensitivity of Streamflow and Water Quality to Climate Change and Urbanization in 20 U.S. Watersheds

NASA Astrophysics Data System (ADS)

Johnson, T. E.; Weaver, C. P.; Butcher, J.; Parker, A.

2011-12-01

Watershed modeling was conducted in 20 large (15,000-60,000 km2), U.S. watersheds to address gaps in our knowledge of the sensitivity of U.S. streamflow, nutrient (N and P) and sediment loading to potential future climate change, and methodological challenges associated with integrating existing tools (e.g., climate models, watershed models) and datasets to address these questions. Climate change scenarios are based on dynamically downscaled (50x50 km2) output from four of the GCMs used in the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report for the period 2041-2070 archived by the North American Regional Climate Change Assessment Program (NARCCAP). To explore the potential interaction of climate change and urbanization, model simulations also include urban and residential development scenarios for each of the 20 study watersheds. Urban and residential development scenarios were acquired from EPA's national-scale Integrated Climate and Land Use Scenarios (ICLUS) project. Watershed modeling was conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil and Water Assessment Tool (SWAT) models. Here we present a summary of results for 5 of the study watersheds; the Minnesota River, the Susquehanna River, the Apalachicola-Chattahoochee-Flint, the Salt/Verde/San Pedro, and the Willamette River Basins. This set of results provide an overview of the response to climate change in different regions of the U.S., the different sensitivities of different streamflow and water quality endpoints, and illustrate a number of methodological issues including the sensitivities and uncertainties associated with use of different watershed models, approaches for downscaling climate change projections, and interaction between climate change and other forcing factors, specifically urbanization and changes in atmospheric CO2 concentration.

Developing perturbations for Climate Change Impact Assessments

NASA Astrophysics Data System (ADS)

Hewitson, Bruce

Following the 2001 Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report [TAR; IPCC, 2001], and the paucity of climate change impact assessments from developing nations, there has been a significant growth in activities to redress this shortcoming. However, undertaking impact assessments (in relation to malaria, crop stress, regional water supply, etc.) is contingent on available climate-scale scenarios at time and space scales of relevance to the regional issues of importance. These scales are commonly far finer than even the native resolution of the Global Climate Models (GCMs) (the principal tools for climate change research), let alone the skillful resolution (scales of aggregation at which GCM observational error is acceptable for a given application) of GCMs.Consequently, there is a growing demand for regional-scale scenarios, which in turn are reliant on techniques to downscale from GCMs, such as empirical downscaling or nested Regional Climate Models (RCMs). These methods require significant skill, experiential knowledge, and computational infrastructure in order to derive credible regional-scale scenarios. In contrast, it is often the case that impact assessment researchers in developing nations have inadequate resources with limited access to scientists in the broader international scientific community who have the time and expertise to assist. However, where developing effective downscaled scenarios is problematic, it is possible that much useful information can still be obtained for impact assessments by examining the system sensitivity to largerscale climate perturbations. Consequently, one may argue that the early phase of assessing sensitivity and vulnerability should first be characterized by evaluation of the first-order impacts, rather than immediately addressing the finer, secondary factors that are dependant on scenarios derived through downscaling.

The Obama - Xi Accord: A Need for Further Action

NASA Astrophysics Data System (ADS)

Tribett, W. R.; Hope, A. P.; Canty, T. P.; Salawitch, R. J.

2015-12-01

Presidents Barrack Obama of the United States and Jinping Xi of China recently announced a bilateral framework to reduce the total carbon emissions of their respective countries. The U.S. agreed to reduce annual carbon emissions such that by 2025, emissions would be 27% below 2005 levels. China agreed to achieve peak carbon emissions around 2030 coupled with a best effort to peak early. Here we analyze the implications of the Obama-Xi accord for total global carbon emissions (GCE) out to year 2060, using projections of population, economic growth, and carbon intensity for the rest of the world as well as various assumptions regarding how emissions from the U.S. and China will evolve after the timeframe of the Obama-Xi accord. Our GCE projections will be compared to those of the four Representative Concentration Pathway (RCP) emission scenarios used in the IPCC Fifth Assessment Report (AR5). The Obama-Xi accord is shown to be a meaningful first step: if followed, the actual GCE will likely fall below RCP 8.5 between now and 2060. The U.S., China, and rest of the world presently emit 4.5, 2.0, and 1.1 tonne of carbon per person per year (tpy), respectively. We show that if the world's nations adopt a strategy of "Contraction and Convergence", such that per capita emission for each country reaches 1.0 tpy by 2060, actual GCE will approach that of RCP 4.5 by year 2060. Such action may be needed to reduce the risk of the most dire global warming forecasts within IPCC AR5.

Advanced Regional and Decadal Predictions of Coastal Inundation for the U.S. Atlantic and Gulf Coasts

NASA Astrophysics Data System (ADS)

Horton, B. P.; Donnelly, J. P.; Corbett, D. R.; Kemp, A.; Lindeman, K.; Mann, M. E.; Peltier, W. R.; Rahmstorf, S.

2012-12-01

Future inundation of the US Atlantic and Gulf coasts will depend upon both sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. In this proposal, we will employ new interdisciplinary approaches to bring about a step change in the reliability of predictions of such inundation. The rate of sea-level rise along the US Atlantic and Gulf coasts has increased throughout the 20th century. Whilst there is widespread agreement that it continue to accelerate during the 21st century, great uncertainty surrounds its magnitude and geographic distribution. Key uncertainties include the role of continental ice sheets, mountain glaciers and ocean density changes. Insufficient understanding of these complex physical processes precludes accurate prediction of sea-level rise. New approaches using semi-empirical models that relate instrumental records of climate and sea-level rise have projected up to 2 m of sea-level rise by AD 2100. But the time span of instrumental sea-level records is insufficient to adequately constrain the climate:sea-level relationship. Here, we produce new high resolution proxy data of sea-level and temperature to provide crucial additional constraints to such semi-empirical models. Our dataset will span the alternation between the "Medieval Climate Anomaly" and "Little Ice Age". Before the models can provide appropriate data for coastal management and planning, they must be complemented with regional estimates of sea-level rise. Therefore, the proxy sea-level data has been collected from six study areas (Massachusetts, New Jersey, North Carolina, Georgia and Atlantic and Gulf coasts of Florida) to accommodate the required extent of regional variability. In the case of inundation arising from tropical cyclones, the historical and observational records are insufficient for predicting their nature and recurrence, because they are such extreme and rare events. Moreover, in the future, the resultant storm surges will be superimposed on background sea-level rise. To overcome these problems, we couple regional sea-level rise projections with hurricane simulations and storm surge models to map coastal inundation for the current climate and the best and worst case climate scenarios of the IPCC AR4. The products of this proposal will raise the bar for the scientific prediction of region-specific inundation probabilities in terms of coordinated semi-empirical proxy data, hindcast- and forecast-driven sea-level modeling and tropical cyclone forecasting. To optimize transfer of this often complex information for effective adaptive decision-making by managers and planners, we will systematically review >800 adaptation reports and consult early and often with primary endusers to identify their exact needs. We will produce high penetration print and web products for diverse audiences, specific to each region.

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

NASA Astrophysics Data System (ADS)

Vavrus, S. J.

2012-12-01

Although impending Arctic climate change is widely recognized, a wild card in its expression is how extreme weather events in this region will respond to greenhouse warming. Intense polar cyclones represent one type of high-latitude phenomena falling into this category, including very deep synoptic-scale cyclones and mesoscale polar lows. These systems inflict damage through high winds, heavy precipitation, and wave action along coastlines, and their impact is expected to expand in the future, when reduced sea ice cover allows enhanced wave energy. The loss of a buffering ice pack could greatly increase the rate of coastal erosion, which has already been increasing in the Arctic. These and related threats may amplify if extreme Arctic cyclones become more frequent and/or intense in a warming climate with much more open water to fuel them. This possibility has merit on the basis of GCM experiments, which project that greenhouse forcing causes lower mean sea level pressure (SLP) in the Arctic and a strengthening of the deepest storms over boreal high latitudes. In this study, the latest Coupled Model Intercomparison Project (CMIP5) climate model output is used to investigate the following questions: (1) What are the spatial and seasonal characteristics of extreme Arctic cyclones? (2) How well do GCMs simulate these phenomena? (3) Are Arctic cyclones already showing the expected response to greenhouse warming in climate models? To address these questions, a retrospective analysis is conducted of the transient 20th century simulations among the CMIP5 GCMs (spanning years 1850-2005). The results demonstrate that GCMs are able to reasonably represent extreme Arctic cyclones and that the simulated characteristics do not depend significantly on model resolution. Consistent with observational evidence, climate models generate these storms primarily during winter and within the climatological Aleutian and Icelandic Low regions. Occasionally the cyclones remain very intense over the Arctic Ocean. The historical tendency in Arctic SLP varies considerably among the GCMs, but the intermodel average trend exhibits a lowering of mean-annual pressure over the Arctic during the past 150 years and an increase in extreme cyclones in the vicinity of the Aleutian and Icelandic Lows. However, only weak trends in extreme cyclones are simulated through 2005 over the Arctic Ocean, where simulations of future climate change produce the largest SLP falls.

Sea level rise from the Greenland Ice Sheet during the Eemian interglacial: Review of previous work with focus on the surface mass balance

NASA Astrophysics Data System (ADS)

Plach, Andreas; Hestnes Nisancioglu, Kerim

2016-04-01

The contribution from the Greenland Ice Sheet (GIS) to the global sea level rise during the Eemian interglacial (about 125,000 year ago) was the focus of many studies in the past. A main reason for the interest in this period is the considerable warmer climate during the Eemian which is often seen as an equivalent for possible future climate conditions. Simulated sea level rise during the Eemian can therefore be used to better understand a possible future sea level rise. The most recent assessment report of the Intergovernmental Panel on Climate Change (IPCC AR5) gives an overview of several studies and discusses the possible implications for a future sea level rise. The report also reveals the big differences between these studies in terms of simulated GIS extent and corresponding sea level rise. The present study gives a more exhaustive review of previous work discussing sea level rise from the GIS during the Eemian interglacial. The smallest extents of the GIS simulated by various authors are shown and summarized. A focus is thereby given to the methods used to calculate the surface mass balance. A hypothesis of the present work is that the varying results of the previous studies can largely be explained due to the various methods used to calculate the surface mass balance. In addition, as a first step for future work, the surface mass balance of the GIS for a proxy-data derived forcing ("index method") and a direct forcing with a General Circulation Model (GCM) are shown and discussed.

The Change of First-flowering Date over South Korea Projected from Downscaled IPCC AR5 Simulation: Peach and Pear

NASA Astrophysics Data System (ADS)

Ahn, J. B.; Hur, J.

2014-12-01

The variations in the first-flowering date (FFD) of peach (Prunus persica) and pear (Pyrus pyrifolia) under future climate change in South Korea are investigated using simulations obtained from five models of the fifth Coupled Model Intercomparison Project. For the study, daily temperature simulations with Historical (1986-2005), and RCP (2071-2090) 4.5 and 8.5 scenarios are statistically downscaled to 50 peach and pear FFD (FFDpeach and FFDpear, respectively) observation sites over South Korea. The number of days transformed to standard temperature (DTS) method is selected as the phenological model and applied to simulations for estimating FFDpeach and FFDpear over South Korea, due to its superior performance on the target plants and region compared to the growing degree days (GDD) and chill days (CD) methods. In the analysis, mean temperatures for early spring (February to April) over South Korea in 2090 under RCP4.5 and 8.5 scenarios are expected to have increased by 1.9K and 3.3K, respectively. Among the early spring months of February to April, February shows the largest temperature increase of 2.1K and 3.7K for RCP4.5 and 8.5 scenarios, respectively. The increased temperature during February and March accelerates the plant growth rate and thereby advances FFDpeach by 7.0 and 12.7 days and FFDpear by 6.1 and 10.7 days, respectively. These results imply that the present flowering of peach and pear in the middle of April will have advanced to late March or early April by the end of this century. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953, Republic of Korea.

End-of-century projections of North American atmospheric river events in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Warner, M.; Mass, C.; Salathe, E. P., Jr.

2013-12-01

Most extreme precipitation events that occur along the North American west coast are associated with narrow plumes of above-average water vapor concentration that stretch from the tropics or subtropics to the West Coast. These events generally occur during the wet season (October-March) and are referred to as atmospheric rivers (AR). ARs can cause major river management problems, damage from flooding or landslides, and loss of life. It is expected that anthropogenic global warming could lead to changes in the general circulation of the atmosphere, such as Hadley Cell expansion and jet stream and storm track shifts. Since AR events are associated with cyclonic activity that originates near and propagates along the jet stream, the jet stream configuration influences the frequency and location of AR landfall along the North American west coast. Therefore, it is probable that any changes in the general circulation of the atmosphere will result in changes in the frequency, orientation, and location of AR landfalls. Generally, along the West Coast, CMIP5 models predict increases in integrated water vapor and precipitation, and little change in low-level wind associated with AR events. In this study, CMIP5 RCP 8.5 climate models and high resolution regional climate models are used to analyze predicted changes in frequency and location of AR events impacting the West Coast from the contemporary period (1970-1999) to the end of this century (2070-2099).

Climate change impact on the management of water resources in the Seine River basin, France

NASA Astrophysics Data System (ADS)

Dorchies, David; Thirel, Guillaume; Chauveau, Mathilde; Jay-Allemand, Maxime; Perrin, Charles; Dehay, Florine

2013-04-01

It is today commonly accepted that adaptation strategies will be needed to cope with the hydrological consequences of projected climate change. The main objective of the IWRM-Net Climaware project is to design adaptation strategies for various socio-economic sectors and evaluate their relevance at the European scale. Within the project, the Seine case study focuses on dam management. The Seine River basin at Paris (43800km²) shows major socio-economic stakes in France. Due to its important and growing demography, the number of industries depending on water resources or located on the river sides, and the developed agricultural sector, the consequences of droughts and floods may be dramatic. To mitigate the extreme hydrological events, a system of four large multi-purpose reservoirs was built in the upstream part of the basin between 1949 and 1990. The IPCC reports indicate modifications of the climate conditions in northern France in the future. An increase of mean temperature is very likely, and the rainfall patterns could be modified: the uncertainty on future trends is still high, but summer periods could experience lower quantities of rainfall. Anticipating these changes are crucial: will the present reservoirs system be adapted to these conditions? Here we propose to evaluate the capacity of the Seine River reservoirs to withstand future projected climate conditions using the current management rules. For this study a modeling chain was designed. We used two hydrological models: GR4J, a lumped model used as a benchmark, and TGR, a semi-distributed model. TGR was tuned to explicitly account for reservoir management rules. Seven climatic models forced by the moderate A1B IPCC scenario and downscaled using a weather-type method (DSCLIM, Pagé et al., 2009), were used. A quantile-quantile type method was applied to correct bias in climate simulations. A model to mimic the way reservoirs are managed was also developed. The evolution of low flows, high flows and annual flows were assessed under natural condition (i.e. without the inclusion of the reservoirs in the models). Then, the impact of reservoirs and their management were accounted for in the modeling chain. Results will be discussed relatively to future hydro-climatic conditions and current mitigation objectives within the basin. Reference: Pagé, C., L. Terray et J. Boé, 2009: dsclim: A software package to downscale climate scenarios at regional scale using a weather-typing based statistical methodology. Technical Report TR/CMGC/09/21, SUC au CERFACS, URA CERFACS/CNRS No1875, Toulouse, France. Link : http://www.cerfacs.fr/~page/dsclim/dsclim_doc-latest.pdf

Projections of atmospheric mercury levels and their effect on air quality in the United States

NASA Astrophysics Data System (ADS)

Lei, H.; Wuebbles, D. J.; Liang, X.-Z.; Tao, Z.; Olsen, S.; Artz, R.; Ren, X.; Cohen, M.

2013-08-01

The individual and combined effects of global climate change and emissions changes from 2000 to 2050 on atmospheric mercury levels in the US are investigated by using the global climate-chemistry model, CAM-chem, coupled with a mercury chemistry-physics mechanism (CAM-Chem/Hg). Three future pathways from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) are considered, with the A1FI, A1B and B1 scenarios representing the upper, middle and lower bounds of potential climate warming, respectively. The anthropogenic and biomass burning emissions of mercury are projected from the energy use assumptions in the IPCC SRES report. Natural emissions from both land and ocean sources are projected using dynamic schemes. The zonal mean surface total gaseous mercury (TGM) concentrations in the tropics and mid-latitudes of the Southern Hemisphere are projected to increase by 0.5-1.2 ng m-3 in 2050. TGM concentration increases are greater in the low latitudes than they are in the high latitudes, indicative of a larger meridional gradient than in the present day. In the A1FI scenario, TGM concentrations in 2050 are projected to increase by 2.1-4.0 ng m-3 for the eastern US and 1.4-3.0 ng m-3 for the western US. This pattern corresponds to potential increases in wet deposition of 10-14 μg m-2 for the eastern US and 2-4 μg m-2 for the western US. The increase in Hg(II) emissions tends to enhance wet deposition and hence increase the risk of higher mercury entering the hydrological cycle and ecosystems. In the B1 scenario, mercury concentrations in 2050 are similar to present level concentrations; this indicates that the domestic reduction in mercury emissions is essentially counteracted by the effects of climate warming and emissions increases in other regions. The sensitivity analyses presented show that anthropogenic emissions changes contribute 32-53% of projected mercury air concentration changes, while the independent contribution by climate change accounts for 47-68%. In summary, global climate change could have a comparable effect on mercury pollution in the US to that caused by global emissions changes.

Why Hasn't Earth Warmed as Much as Expected?

NASA Technical Reports Server (NTRS)

Schwartz, Stephen E.; Charlson, Robert J.; Kahn, Ralph A.; Ogren, John A.; Rodhe, Henning

2010-01-01

The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15 %. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth's climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

a Process-Based Drought Early Warning Indicator for Supporting State Drought Mitigation Decision

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, D. N.; Pu, B.

2014-12-01

Drought prone states such as Texas requires creditable and actionable drought early warning ranging from seasonal to multi-decadal scales. Such information cannot be simply extracted from the available climate prediction and projections because of their large uncertainties at regional scales and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA national multi-models ensemble experiment (NMME) and the IPCC AR5 (CMIP5) models, are much more reliable for winter and spring than for the summer season for the US Southern Plains. They also show little connection between the droughts in winter/spring and those in summer, in contrast to the observed dry memory from spring to summer over that region. To mitigate the weakness of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies. Based on these key processes and related fields, we have developed a multivariate principle component statistical model to provide a probabilistic summer drought early warning indicator, using the observed or predicted climate conditions in winter and spring on seasonal scale and climate projection for the mid-21stcentury. The summer drought early warning indicator is constructed in a similar way to the NOAA probabilistic predictions that are familiar to water resource managers. The indicator skill is assessed using the standard NOAA climate prediction assessment tools, i.e., the two alternative forced choice (2AFC) and the Receiver Operating Characteristic (ROC). Comparison with long-term observations suggest that this summer drought early warning indicator is able to capture nearly all the strong summer droughts and outperform the dynamic prediction in this regard over the US Southern Plains. This early warning indicator has been used by the state water agency in May 2014 in briefing the state drought preparedness council and will be provided to stake holders through the website of the Texas state water planning agency. We will also present the results of our ongoing work on using NASA satellite based soil moisture and vegetation stress measurements to further improve the reliability of the summer drought early warning indicator.

Verifying the UK agricultural N2O emission inventory with tall tower measurements

NASA Astrophysics Data System (ADS)

Carnell, E. J.; Meneguz, E.; Skiba, U. M.; Misselbrook, T. H.; Cardenas, L. M.; Arnold, T.; Manning, A.; Dragosits, U.

2016-12-01

Nitrous oxide (N2O) is a key greenhouse gas (GHG), with a global warming potential 300 times greater than that of CO2. N2O is emitted from a variety of sources, predominantly from agriculture. Annual UK emission estimates are reported, to comply with government commitments under the United Nations Framework Convention on Climate Change (UNFCCC). The UK N2O inventory follows internationally agreed protocols and emission estimates are derived by applying emission factors to estimates of (anthropogenic) emission sources. This approach is useful for comparing anthropogenic emissions from different countries, but does not capture regional differences and inter-annual variability associated with environmental factors (such as climate and soils) and agricultural management. In recent years, the UK inventory approach has been refined to include regional information into its emissions estimates, in an attempt to reduce uncertainty. This study attempts to assess the difference between current published inventory methodology (default IPCC methodology) and an alternative approach, which incorporates the latest thinking, using data from recent work. For 2013, emission estimates made using the alternative approach were 30 % lower than those made using default IPCC methodology, due to the use of lower emission factors suggested by recent projects (Defra projects: AC0116, AC0213 and MinNO). The 2013 emissions estimates were disaggregated on a monthly basis using agricultural management (e.g. sowing dates), climate data and soil properties. The temporally disaggregated emission maps were used as input to the Met Office atmospheric dispersion model NAME, for comparison with measured N2O concentrations, at three observation stations (Tacolneston, E. England; Ridge Hill, W. England; Mace Head, W. Ireland) in the UK DECC network (Deriving Emissions linked to Climate Change). The Mace Head site, situated on the west coast of Ireland, was used to establish baseline concentrations. The trends in the modelled data were found to correspond with the observational data trends, with concentration peaks coinciding with periods of land spreading of manures and fertiliser application. The model run using the default IPCC methodology was found to correspond with the observed data more closely than the alternative approach.

Net radiative forcing responses to regional CO and NMVOC reductions

NASA Astrophysics Data System (ADS)

Fry, M. M.; Schwarzkopf, M. D.; Adelman, Z.; Naik, V.; West, J.

2012-12-01

Recent studies suggest that short-lived pollutants and their precursors be considered in near-term climate mitigation strategies, in addition to national air quality programs, but their associated forcings vary based on the region of emissions. Here we quantify the net radiative forcing (RF) impacts of regional anthropogenic carbon monoxide (CO) and non-methane volatile organic compound (NMVOC) emissions due to changes in the tropospheric concentrations of ozone (O3), methane (CH4), and aerosols (carbonaceous and sulfate), to inform future coordinated actions addressing air quality and climate forcing. We present the RF from CO and NMVOC emission reductions from 10 regions (North America, South America, Europe, Former Soviet Union, Southern Africa, India, East Asia, Southeast Asia, Australia and New Zealand, and Middle East and Northern Africa). The global chemical transport model MOZART-4 is used to simulate tropospheric concentration changes, using the IPCC AR5 Representative Concentration Pathway 8.5 (RCP 8.5) emissions inventory for 2005 and global meteorology from the Goddard Earth Observing System Model, version 5 (GEOS-5) for the years 2004-2005. We utilize the NOAA Geophysical Fluid Dynamics Laboratory standalone radiative transfer model to calculate the stratospheric-adjusted net RF for each regional CO and NMVOC reduction, relative to the base. We find that global annual net RF per unit change in emissions ranges from -0.115 to -0.131 mW m-2 / Tg CO for CO reductions, and -0.0035 to -0.436 mW m-2 / Tg C for NMVOC reductions, with the regions in the tropics providing the greatest improvements (Middle East, Southeast Asia, and India CO reductions, and Middle East, Africa, and India NMVOC reductions). The net RF distributions for the CO and NMVOC reductions show widespread cooling across the northern and southern hemispheres corresponding to the patterns of O3 and CH4 decreases, and localized positive and negative net RFs due to increases and decreases in aerosols. The strongest annual net RF impacts occur within the tropics (28 S - 28 N) followed by the northern mid-latitudes (28 N - 60 N), independent of reduction region for CO, and for many of the NMVOC regional reductions. The small variation in RF per unit emissions for CO, among world regions (coefficient of variation = 0.045), suggests that the error would be small in using a uniform global warming potential (GWP), and in possibly including CO in international climate agreements. In contrast, NMVOCs show greater variability among the reduction regions (coefficient of variation = 0.48), suggesting that regionally-specific GWPs may be more appropriate for NMVOCs.

GLOBAL CHANGE RESEARCH NEWS #3: IPCC SPECIAL REPORT ON "LAND USE, LAND USE CHANGE, AND FORESTRY"

EPA Science Inventory

ORD is participating in the development of an Intergovernmental Panel on Climate Change (IPCC) Special Report on "Land Use, Land Use Change and Forestry." Preparation of the Special Report was requested by the Conference of the Parties(COP) to the United Nations Framework Conve...

A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

NASA Astrophysics Data System (ADS)

Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

2013-04-01

Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at 110 coastal locations along the French coast. The model, based on the BAJ parameterization of the source terms (Bidlot et al, 2007) was calibrated against ten years of GlobWave altimeter observations (2000-2009) and validated through deep and shallow water buoy observations. The dynamical downscaling method has been performed with the same numerical wave model TOMAWAC used for building ANEMOC-2. Forecast simulations are forced by the 10m wind fields of ARPEGE-CLIMAT (A1B, A2, B1) from 2010 to 2100. The model covers the Atlantic Ocean and uses a spatial resolution along the French and European coast of 10 and 20 km respectively. The results of the model are stored with a time resolution of one hour. References: Benoit M., Marcos F., and F. Becq, (1996). Development of a third generation shallow-water wave model with unstructured spatial meshing. Proc. 25th Int. Conf. on Coastal Eng., (ICCE'1996), Orlando (Florida, USA), pp 465-478. Bidlot J-R, Janssen P. and Adballa S., (2007). A revised formulation of ocean wave dissipation and its model impact, technical memorandum ECMWF n°509. Menendez, M., Mendez, F.J., Izaguirre,C., Camus, P., Espejo, A., Canovas, V., Minguez, R., Losada, I.J., Medina, R. (2011). Statistical Downscaling of Multivariate Wave Climate Using a Weather Type Approach, 12th International Workshop on Wave Hindcasting and Forecasting and 3rd Coastal Hazard Symposium, Kona (Hawaii).

Holistic view to integrated climate change assessment and extreme weather adaptation in the Lake Victoria Basin East Africa

NASA Astrophysics Data System (ADS)

Mutua, F.; Koike, T.

2013-12-01

Extreme weather events have been the leading cause of disasters and damage all over the world.The primary ingredient to these disasters especially floods is rainfall which over the years, despite advances in modeling, computing power and use of new data and technologies, has proven to be difficult to predict. Also, recent climate projections showed a pattern consistent with increase in the intensity and frequency of extreme events in the East African region.We propose a holistic integrated approach to climate change assessment and extreme event adaptation through coupling of analysis techniques, tools and data. The Lake Victoria Basin (LVB) in East Africa supports over three million livelihoods and is a valuable resource to five East African countries as a source of water and means of transport. However, with a Mesoscale weather regime driven by land and lake dynamics,extreme Mesoscale events have been prevalent and the region has been on the receiving end during anomalously wet years in the region. This has resulted in loss of lives, displacements, and food insecurity. In the LVB, the effects of climate change are increasingly being recognized as a significant contributor to poverty, by its linkage to agriculture, food security and water resources. Of particular importance are the likely impacts of climate change in frequency and intensity of extreme events. To tackle this aspect, this study adopted an integrated regional, mesoscale and basin scale approach to climate change assessment. We investigated the projected changes in mean climate over East Africa, diagnosed the signals of climate change in the atmosphere, and transferred this understanding to mesoscale and basin scale. Changes in rainfall were analyzed and similar to the IPCC AR4 report; the selected three General Circulation Models (GCMs) project a wetter East Africa with intermittent dry periods in June-August. Extreme events in the region are projected to increase; with the number of wet days exceeding the 90% percentile of 1981-2000 likely to increase by 20-40% in the whole region. We also focused on short-term weather forecasting as a step towards adapting to a changing climate. This involved dynamic downscaling of global weather forecasts to high resolution with a special focus on extreme events. By utilizing complex model dynamics, the system was able to reproduce the Mesoscale dynamics well, simulated the land/lake breeze and diurnal pattern but was inadequate in some aspects. The quantitative prediction of rainfall was inaccurate with overestimation and misplacement but with reasonable occurrence. To address these shortcomings we investigated the value added by assimilating Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature during the event. By assimilating 23GHz (sensitive to water) and 89GHz (sensitive to cloud) frequency brightness temperature; the predictability of an extreme rain weather event was investigated. The assimilation through a Cloud Microphysics Data Assimilation (CMDAS) into the weather prediction model considerably improved the spatial distribution of this event.

Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 Intergovernmental Panel on Climate Change Guidelines

NASA Astrophysics Data System (ADS)

Yan, Xiaoyuan; Akiyama, Hiroko; Yagi, Kazuyuki; Akimoto, Hajime

2009-06-01

The Intergovernmental Panel on Climate Change (IPCC) regularly publishes guidelines for national greenhouse gas inventories and methane emission (CH4) from rice paddies has been an important component of these guidelines. While there have been many estimates of global CH4 emissions from rice fields, none of them have been obtained using the IPCC guidelines. Therefore, we used the Tier 1 method described in the 2006 IPCC guidelines to estimate the global CH4 emissions from rice fields. To accomplish this, we used country-specific statistical data regarding rice harvest areas and expert estimates of relevant agricultural activities. The estimated global emission for 2000 was 25.6 Tg a-1, which is at the lower end of earlier estimates and close to the total emission summarized by individual national communications. Monte Carlo simulation revealed a 95% uncertainty range of 14.8-41.7 Tg a-1; however, the estimation uncertainty was found to depend on the reliability of the information available regarding the amount of organic amendments and the area of rice fields that were under continuous flooding. We estimated that if all of the continuously flooded rice fields were drained at least once during the growing season, the CH4 emissions would be reduced by 4.1 Tg a-1. Furthermore, we estimated that applying rice straw off season wherever and whenever possible would result in a further reduction in emissions of 4.1 Tg a-1 globally. Finally, if both of these mitigation options were adopted, the global CH4 emission from rice paddies could be reduced by 7.6 Tg a-1. Although draining continuously flooded rice fields may lead to an increase in nitrous oxide (N2O) emission, the global warming potential resulting from this increase is negligible when compared to the reduction in global warming potential that would result from the CH4 reduction associated with draining the fields.

Synergistic impacts of deforestation, climate change and fire on the future biomes distribution in Amazonia

NASA Astrophysics Data System (ADS)

Sampaio, G.; Cardoso, M. F.; Nobre, C. A.; Salazar, L. F.

2013-05-01

Several studies indicate future increase of environmental risks for the ecosystems in the Amazon region as a result of climate and land-use change, and their synergistic interactions. Modeling studies (e.g. Oyama and Nobre 2004, Salazar et al. 2007, Malhi et al. 2008) project rapid and irreversible replacement of forests by savannas with large-scale losses of biodiversity and livelihoods for people in the region. This process is referred to as the Amazon Dieback, where accelerated plant mortality due to environmental changes lead to forest collapse and savannas expansion after "tipping points" in climate and land surface changes are achieved. In this study we performed new analyses to quantify how deforestation, climate change and fire may combine to affect the distribution of major biomes in Amazonia. Changes in land use consider deforestation scenarios of 0%, 20%, 40%, and 50% (Sampaio et al., 2007), with and without fires (Cardoso et al., 2008), under the two greenhouse gases scenarios B1 and A2 and three "representative concentration pathways" (RCPs): 2.6, 4.5 and 8.5, for years 2015-2034 and 2040-2059 ("2025" and "2050" time-slices), from IPCC AR4 and CMIP5. The results show that the area affected in scenarios A2 and RCP 8.5 is larger than in the climate scenario B1 and RCP 2.6, and in both cases the effect is progressively higher in time. Most important changes occur in the East and South of the Amazon, with replacement of tropical forest by seasonal forest and savanna. The effect of fire in this region is important in all scenarios. The Northwest Amazon presents the smallest changes in the area of tropical forest, indicating that even for substantial land-use modifications and global climate change, the resulting atmospheric conditions would still support tropical forest in the region. In summary, we conclude that the synergistic combination of deforestation, climate change resulting from global warming, and the potential for higher fire occurrence may lead to important impacts that add considerably to the vulnerability of tropical forest ecosystems in the study region. REFERENCES Cardoso, M. F. ; Nobre, C. A. ; Sampaio, G. ; Hirota, M. ; Valeriano, D. ; Câmara, G. Long-term potential for tropical-forest degradation due to deforestation and fires in the Brazilian Amazon. Biologia (Bratislava), v. 64, p. 433-437, 2009. Malhi Y, et al. (2008) Climate change, deforestation, and the fate of the Amazon. Science 319:169-172. Oyama, M.D. and C.A. Nobre (2004), A simple potencial vegetation model for coupling with the Simple Biosphere Model (SIB). Revista Brasileira de Meteorologia, v. 19, n. 2, p. 203-216, 2004. Salazar, L. F., C. A. Nobre, and M. D. Oyama (2007), Climate change consequences on the biome distribution in tropical South America, Geophys. Res. Lett., 34, L09708, doi:10.1029/2007GL029695 Sampaio, G., C. A. Nobre, M. H. Costa, P. Satyamurty, B. S. Soares-Filho and, M. Cardoso (2007), Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophys. Res. Lett., 34, L17709, doi:10.1029/2007GL030612.

Risk Assessment of Hurricane Storm Surge for Tampa Bay

NASA Astrophysics Data System (ADS)

Lin, N.; Emanuel, K.

2011-12-01

Hurricane storm surge presents a major hazard for the United States and many other coastal areas around the world. Risk assessment of current and future hurricane storm surge provides the basis for risk mitigation and related decision making. This study investigates the hurricane surge risk for Tampa Bay, located on the central west coast of Florida. Although fewer storms have made landfall in the central west Florida than in regions farther west in the Gulf of Mexico and the east coast of U.S., Tampa Bay is highly vulnerable to storm surge due to its geophysical features. It is surrounded by low-lying lands, much of which may be inundated by a storm tide of 6 m. Also, edge waves trapped on the west Florida shelf can propagate along the coastline and affect the sea level outside the area of a forced storm surge; Tampa Bay may be affected by storms traversing some distance outside the Bay. Moreover, when the propagation speed of the edge wave is close to that of a storm moving parallel to the coast, resonance may occur and the water elevation in the Bay may be greatly enhanced. Therefore, Tampa Bay is vulnerable to storms with a broad spectrum of characteristics. We apply a model-based risk assessment method to carry out the investigation. To estimate the current surge risk, we apply a statistical/deterministic hurricane model to generate a set of 1500 storms for the Tampa area, under the observed current climate (represented by 1981-2000 statistics) estimated from the NCAR/NCEP reanalysis. To study the effect of climate change, we use four climate models, CNRM-CM3, ECHAM, GFDL-CM2.0, and MIROC3.2, respectively, to drive the hurricane model to generate four sets of 1500 Tampa storms under current climate conditions (represented by 1981-2000 statistics) and another four under future climate conditions of the IPCC-AR4 A1B emission scenario (represented by 2081-2100 statistics). Then, we apply two hydrodynamic models, the Advanced Circulation (ADCIRC) model and the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model with grids of various resolutions to simulate the surges induced by the synthetic storms. The surge risk under each of the climate scenarios is depicted by a surge return level curve (exceedance probability curve). For the city of Tampa, the heights of the 100-year, 500-year, and 1000-year surges under the current climate are estimated to be 3.85, 5.66, and 6.31 m, respectively. Two of the four climate models predict that surge return periods will be significantly shortened in the future climates due to the change of storm climatology; the current 100-year surge may happen every 50 years or less, the 500-year surge every 200 years or less, and the 1000-year surge every 300 years or less. The other two climate models predict that the surge return periods will become moderately shorter or remain almost unchanged in the future climates. Extreme surges up to 12 m at Tampa appear in our simulations. Although occurring with very small probabilities, these extreme surges would have a devastating impact on the Tampa Bay area. By examining the generated synthetic surge database, we study the characteristics of the extreme storms at Tampa Bay, especially for the storms that may interact with edge waves along the Florida west coast.

Bridging the climate-induced water gap in the twenty-first century: adaptation support based on water supply, demand, adaptation and financing.

NASA Astrophysics Data System (ADS)

Straatsma, Menno; Droogers, Peter; Brandsma, Jaïrus; Buytaert, Wouter; Karssenberg, Derek; Van Beek, Rens; Wada, Yoshihide; Sutanudjaja, Edwin; Vitolo, Claudia; Schmitz, Oliver; Meijer, Karen; Van Aalst, Maaike; Bierkens, Marc

2014-05-01

Water scarcity affects large parts of the world. Over the course of the twenty-first century, water demand is likely to increase due to population growth and associated food production, and increased economic activity, while water supply is projected to decrease in many regions due to climate change. Despite recent studies that analyze the effect of climate change on water scarcity, e.g. using climate projections under representative concentration pathways (RCP) of the fifth assessment report of the IPCC (AR5), decision support for closing the water gap between now and 2100 does not exist at a meaningful scale and with a global coverage. In this study, we aimed (i) to assess the joint impact of climatic and socio-economic change on water scarcity, (ii) to integrate impact and potential adaptation in one workflow, (iii) to prioritize adaptation options to counteract water scarcity based on their financial, regional socio-economic and environmental implications, and (iv) to deliver all this information in an integrated user-friendly web-based service. To enable the combination of global coverage with local relevance, we aggregated all results for 1604 water provinces (food producing units) delineated in this study, which is five times smaller than previous food producing units. Water supply was computed using the PCR-GLOBWB hydrological and water resources model, parameterized at 5 arcminutes for the whole globe, excluding Antarctica and Greenland. We ran PCR-GLOBWB with a daily forcing derived from five different GCM models from the CMIP5 (GFDL-ESM2M, Hadgem2-ES, IPSL-CMA5-LR, MIROC-ESM-CHEM, NorESM1-M) that were bias corrected using observation-based WATCH data between 1960-1999. For each of the models all four RCPs (RCP 2.6, 4.5, 6.0, and 8.5) were run, producing the ensemble of 20 future projections. The blue water supply was aggregated per month and per water province. Industrial, domestic and irrigation water demands were computed for a limited number of realistic combinations of a shared socio-economic pathways (SSPs) and RCPs. Our Water And Climate Adaptation Model (WatCAM) was used to compute the water gap based on reservoir capacity, water supply, and water demand. WatCam is based on the existing ModSim (Labadie, 2010) water allocation model, and facilitated the evaluation of nine technological and infrastructural adaptation measures to assess the investments needed to bridge the future water gap. Regional environmental and socio-economic effects of these investments, such as environmental flows or downstream effects, were evaluated. A scheme was developed to evaluate the strategies on robustness and flexibility under climate change and scenario uncertainty, and each measure was linked to possibilities for investment and financing mechanisms. The WatCAM is available as a web modeling service from www.water2invest.com, and enables user specified adaptation measures and the creation of an ensemble of water gap forecasts.

Spatial-temporal analysis of climate variations in mid-17th through 19th centuries in East China and the possible relationships with Monsoon climate

NASA Astrophysics Data System (ADS)

Lin, K. H. E.; Wang, P. K.; Liao, Y. C.; Lee, S. Y.; Tan, P.

2016-12-01

IPCC AR5 has revealed more frequent extreme climate events and higher climate variability in the near future. Regardless of all the improvements, East Asia monsoon climate is still less understood and/or poorly projected due partly to insufficient records. Most areas of the Asian region lack sufficient observational records to draw conclusions about trends in annual precipitation over the past century (i.e. WGIAR5 Chapter 2). Precipitation trends, including extremes, are characterized by strong variability, with both increasing and decreasing observed in different parts and seasons of Asia. Understanding the variations of the monsoon climate in historical time may bring significant insights to reveal its spatial and temporal patterns embedded in the atmospheric dynamics at different decadal or centennial scales. This study presents some preliminary research results of high resolution climate reconstruction, in both time and space coverage, in east China, by using RCEC historical climate dataset that is developed under interdisciplinary collaboration led by Research Center for Environmental Changes at Academia Sinica, Taiwan. The present research results are derived from chronological meteorological records in the RCEC dataset in Qing dynasty labeling mid-17th to 19th centuries. In total, the dataset comprises more than 1,300 cities/counties in China that has had more than sixty thousands meteorological records in the period. The analysis comprises three parts. Firstly, the frequency of extreme temperature, precipitation, drought, and flood in every recorded cities/counties were computed to depicting climate variabilities in northeast, central-east and southeast China. Secondly, the multivariate regression model was conducted to estimate the coefficients among the climatic index (temperature, precipitation, and drought). It is found that the temperature and wet-dry characteristics have great seasonal and yearly variations; northeast China compared with central-east or southeast tends to have higher variability. Thirdly, those data was used to conduct empirical orthogonal function (EOF) analysis to decompose possible mechanisms that might have cause changes in East Asia monsoon regime during the time period. The reconstructed data were also compared against paleoclimate simulation.

Ranking GCM Estimates of Twentieth Century Precipitation Seasonality in the Western U.S. and its Influence on Floristic Provinces.

NASA Astrophysics Data System (ADS)

Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Ironside, K.; Cobb, N. S.

2008-12-01

Floristic provinces of the western United States (west of 100W) can be segregated into three regions defined by significant seasonal precipitation during the months of: 1) November-March (Mediterranean); 2) July- September (Monsoonal); or, 3) May-June (Rocky Mountain). This third region is best defined by the absence of the late spring-early summer drought that affects regions 1 and 2. Each of these precipitation regimes is characterized by distinct vegetation types and fire seasonality adapted to that particular cycle of seasonal moisture availability and deficit. Further, areas where these regions blend from one to another can support even more complex seasonal patterns and resulting distinctive vegetation types. As a result, modeling the effects of climates on these ecosystems requires confidence that GCMs can at least approximate these sub- continental seasonal precipitation patterns. We evaluated the late Twentieth Century (1950-1999 AD) estimates of annual precipitation seasonality produced by 22 GCMs contained within the IPCC Fourth Assessment (AR4). These modeled estimates were compared to values from the PRISM dataset, extrapolated from station data, over the same historical period for the 3 seasonal periods defined above. The correlations between GCM estimates and PRISM values were ranked using 4 measures: 1) A map pattern relationship based on the correlation coefficient, 2) A map pattern relationship based on the congruence coefficient, 3) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation amounts, and, 4) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation percentages of the annual total. For each of the four metrics, the rank order of models was very similar. The ranked order of the performance of the different models quantified aspects of the model performance visible in the mapped results. While some models represented the seasonal patterns very well, others showed little correspondence with the regional patterns, especially for the summer monsoon period. These sub-continental patterns were especially well simulated over this period by the UKMO-HadGEM1, ECHAM5/MPI-OM, and the MRI-CGCM2 model runs.

Advancing Methods for Estimating Soil Nitrous Oxide Emissions by Incorporating Freeze-Thaw Cycles into a Tier 3 Model-Based Assessment

NASA Astrophysics Data System (ADS)

Ogle, S. M.; DelGrosso, S.; Parton, W. J.

2017-12-01

Soil nitrous oxide emissions from agricultural management are a key source of greenhouse gas emissions in many countries due to the widespread use of nitrogen fertilizers, manure amendments from livestock production, planting legumes and other practices that affect N dynamics in soils. In the United States, soil nitrous oxide emissions have ranged from 250 to 280 Tg CO2 equivalent from 1990 to 2015, with uncertainties around 20-30 percent. A Tier 3 method has been used to estimate the emissions with the DayCent ecosystem model. While the Tier 3 approach is considerably more accurate than IPCC Tier 1 methods, there is still the possibility of biases in emission estimates if there are processes and drivers that are not represented in the modeling framework. Furthermore, a key principle of IPCC guidance is that inventory compilers estimate emissions as accurately as possible. Freeze-thaw cycles and associated hot moments of nitrous oxide emissions are one of key drivers influencing emissions in colder climates, such as the cold temperate climates of the upper Midwest and New England regions of the United States. Freeze-thaw activity interacts with management practices that are increasing N availability in the plant-soil system, leading to greater nitrous oxide emissions during transition periods from winter to spring. Given the importance of this driver, the DayCent model has been revised to incorproate freeze-thaw cycles, and the results suggests that including this driver can significantly modify the emissions estimates in cold temperate climate regions. Consequently, future methodological development to improve estimation of nitrous oxide emissions from soils would benefit from incorporating freeze-thaw cycles into the modeling framework for national territories with a cold climate.

Atmospheric Rivers in VR-CESM: Historical Comparison and Future Projections

NASA Astrophysics Data System (ADS)

McClenny, E. E.; Ullrich, P. A.

2016-12-01

Atmospheric rivers (ARs) are responsible for most of the horizontal vapor transport from the tropics, and bring upwards of half the annual precipitation to midlatitude west coasts. The difference between a drought year and a wet year can come down to 1-2 ARs. Such few events transform an otherwise arid region into one which supports remarkable biodiversity, productive agriculture, and booming human populations. It follows that such a sensitive hydroclimate feature would demand priority in evaluating end-of-century climate runs, and indeed, the AR subfield has grown significantly over the last decade. However, results tend to vary wildly from study to study, raising questions about how to best approach ARs in models. The disparity may result from any number of issues, including the ability for a model to properly resolve a precipitating AR, to the formulation and application of an AR detection algorithm. ARs pose a unique problem in global climate models (GCMs) computationally and physically, because the GCM horizontal grid must be fine enough to resolve coastal mountain range topography and force orographic precipitation. Thus far, most end-of-century projections on ARs have been performed on models whose grids are too coarse to resolve mountain ranges, causing authors to draw conclusions on AR intensity from water vapor content or transport alone. The use of localized grid refinement in the Variable Resolution version of NCAR's Community Earth System Model (VR-CESM) has succeeded in resolving AR landfall. This study applies an integrated water vapor AR detection algorithm to historical and future projections from VR-CESM, with historical ARs validated against NASA's Modern Era Retrospective-Analysis for Research and Applications. Results on end-of-century precipitating AR frequency, intensity, and landfall location will be discussed.

Climatic change impacts on water balance of the Upper Jordan River

NASA Astrophysics Data System (ADS)

Heckl, A.; Kunstmann, H.

2009-04-01

The Eastern Mediterranean and Near East (EM/NE) is an extremely water scarce environment. It is expected that problems will increase due to climate change and population growth. The impact of climate change on water availability in EM/NE and in particular the Jordan River catchment is investigated in this study. Focus is set on the Upper Jordan River catchment (UJC) as it provides 1/3rd of freshwater resources in Israel and Palestine. It is a hydro-geologically extremely complex region with karstic groundwater flow and an orography with steep gradients. The methods used are high resolution coupled regional climate - hydrology simulations. Two IPCC scenarios (A2 and B2) of the global climate model ECHAM4 have been dynamically downscaled using the non-hydrostatic meteorological model MM5 in two nesting steps with resolutions of 54x54 km2 and 18x18 km2 for the period 1961-2099, whereby the time slice 1961-1989 represents the current climate. The meteorological fields are used to drive the physically based hydrological model WaSiM applied to the UJC. The hydrological model computes in detail the surface and subsurface water flow and water balance in a horizontal resolution of 450 x 450 m2 and dynamically couples to a 2-dim numerical groundwater model. Parameters like surface runoff, groundwater recharge, soil moisture and evapotranspiration can be extracted. Results show in both scenarios increasing yearly mean temperatures up to 4-5 K until 2099 and decreasing yearly precipitation amounts up to 25% (scenario A2). The effect on the water balance of the UJC are reduced discharge and groundwater recharge, increased evaporation and reduction of snow cover in the mountains which usually serves as an important freshwater reservoir for the summer discharge.

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

Geographic Inventory Framework (GiF) for estimating N2O and CH4 emissions from agriculture in the province of Alberta, Canada

NASA Astrophysics Data System (ADS)

Dimitrov, D. D.; Wang, J.

2016-12-01

A Geographic Information Framework (GiF) has been created to estimate and map agricultural N2O and CH4 emissions of the province of Alberta, Canada. The GiF consists of a modelling component, a GIS component, and application software to communicate between the model, database and census data. For compatibility, GiF follows the IPCC Tier 1 method and contains census data for animal populations, crop areas, and farms for the main IPCC animal and plant types (dairy cows, cattle cows, pigs, sheep, poultry, other animals, grasses, legumes, other crops), and estimated N2O and CH4 emissions from manure management, enteric fermentation, direct soil emissions (with applied manure, synthetic fertilizer, crop residue degradation, biological fixation) and indirect soil emissions (with atmospheric deposition and leaching). Methane emissions from enteric fermentation (609.24 Gg) prevailed over those from manure (44.99 Gg), and nitrous oxide emission from manure (22.01 Gg) prevailed over those from soil (17.73 Gg), with cattle cows emitting most N2O and CH4, followed by plant N2O emissions, and pigs and dairy cows CH4 emissions. The GIS maps showed discernible pattern of N2O and CH4 emissions increasing from North and West to the central Alberta and then slightly declining to South and East, which could be useful to address various mitigation strategies. The framework allows easy replacement of Tier 1 emission factors by Tire 2 or 3 ones from process-based models. Future applying of the latter will allow accounting for CO2 source/sink strength of agricultural ecosystems, hence their complete GHG balance affected by soil, water, and climate.

Characterization of extreme precipitation within atmospheric river events over California

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

Jeon, S.; Prabhat,; Byna, S.

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Characterization of extreme precipitation within atmospheric river events over California

DOE PAGES

Jeon, S.; Prabhat,; Byna, S.; ...

2015-11-17

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Solar cycle length hypothesis appears to support the ipcc on global warming

NASA Astrophysics Data System (ADS)

Laut, P.; Gundermann, J.

1998-12-01

Since the discovery of a striking correlation between 1-2-2-2-1 filtered solar cycle lengths and the 11-year running average of northern hemisphere land air temperatures, there have been widespread speculations as to whether these findings would rule out any significant contributions to global warming from the enhanced concentrations of greenhouse gases. The solar hypothesis (as we shall term this assumption) claims that solar activity causes a significant component of the global mean temperature to vary in phase opposite to the filtered solar cycle lengths. In an earlier article we have demonstrated that for data covering the period 1860-1980 the solar hypothesis does not rule out any significant contribution from man-made greenhouse gases and sulphate aerosols. The present analysis goes a step further. We analyse the period 1579-1987 and find that the solar hypothesis-instead of contradicting-appears to support the assumption of a significant warming due to human activities. We have tentatively corrected the historical northern hemisphere land air temperature anomalies by removing the assumed effects of human activities. These are represented by northern hemisphere land air temperature anomalies calculated as the contributions from man-made greenhouse gases and sulphate aerosols by using an upwelling diffusion-energy balance model similar to the model of [Wigley and Raper, 1993] employed in the Second Assessment Report of The Intergovernmental Panel on Climate Change (IPCC). It turns out that the agreement of the filtered solar cycle lengths with the corrected temperature anomalies is substantially better than with the historical anomalies, with the mean square deviation reduced by 36% for a climate sensitivity of 2.5°C, the central value of the IPCC assessment, and by 43% for the best-fit value of 1.7°C. Therefore our findings support a total reversal of the common assumption that a verification of the solar hypothesis would challenge the IPCC assessment of man-made global warming.

Changes of the potential distribution area of French Mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-11-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growth with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20th and 21st centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5 K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak respectively) at the end of the 21st century. While both species have different growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21st century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Advancing the adaptive capacity of social-ecological systems to absorb climate extremes

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja

2017-04-01

The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.