Constraining cloud responses to CO2 and warming in climate models: physical and statistical approaches

NASA Astrophysics Data System (ADS)

Sherwood, S. C.; Fuchs, D.; Bony, S.; Jean-Louis, D.

2014-12-01

Earth's climate sensitivity has been the subject of heated debate for decades, and recently spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of the most likely range of climate sensitivities. Here, we present an observation-based study based on the time period 1964 to 2010, which is unique in that it does not rely on global climate models (GCMs) in any way. The study uses surface observations of temperature and incoming solar radiation from approximately 1300 surface sites, along with observations of the equivalent CO2 concentration (CO2,eq) in the atmosphere, to produce a new best estimate for the transient climate sensitivity of 1.9K (95% confidence interval 1.2K - 2.7K). This is higher than other recent observation-based estimates, and is better aligned with the estimate of 1.8K and range (1.1K - 2.5K) derived from the latest generation of GCMs. The new estimate is produced by incorporating the observations in an energy balance framework, and by applying statistical methods that are standard in the field of Econometrics, but less common in climate studies. The study further suggests that about a third of the continental warming due to increasing CO2,eq was masked by aerosol cooling during the time period studied.

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

Vallis, Geoffrey K.

The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability.more » The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.« less

Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko

2017-06-01

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.

Geobiological constraints on Earth system sensitivity to CO₂ during the Cretaceous and Cenozoic.

PubMed

Royer, D L; Pagani, M; Beerling, D J

2012-07-01

Earth system climate sensitivity (ESS) is the long-term (>10³ year) response of global surface temperature to doubled CO₂ that integrates fast and slow climate feedbacks. ESS has energy policy implications because global temperatures are not expected to decline appreciably for at least 10³ year, even if anthropogenic greenhouse gas emissions drop to zero. We report provisional ESS estimates of 3 °C or higher for some of the Cretaceous and Cenozoic based on paleo-reconstructions of CO₂ and temperature. These estimates are generally higher than climate sensitivities simulated from global climate models for the same ancient periods (approximately 3 °C). Climate models probably do not capture the full suite of positive climate feedbacks that amplify global temperatures during some globally warm periods, as well as other characteristic features of warm climates such as low meridional temperature gradients. These absent feedbacks may be related to clouds, trace greenhouse gases (GHGs), seasonal snow cover, and/or vegetation, especially in polar regions. Better characterization and quantification of these feedbacks is a priority given the current accumulation of atmospheric GHGs. © 2012 Blackwell Publishing Ltd.

How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Zaehle, Sönke; Keeling, Ralph; Heimann, Martin

2018-04-01

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as inter-annual climate sensitivity. We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical inter-annual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

A sensitive slope: estimating landscape patterns of forest resilience in a changing climate

Treesearch

Jill F. Johnstone; Eliot J.B. McIntire; Eric J. Pedersen; Gregory King; Michael J.F. Pisaric

2010-01-01

Changes in Earth's environment are expected to stimulate changes in the composition and structure of ecosystems, but it is still unclear how the dynamics of these responses will play out over time. In long-lived forest systems, communities of established individuals may be resistant to respond to directional climate change, but may be highly sensitive to climate...

Earth system sensitivity inferred from Pliocene modelling and data

USGS Publications Warehouse

Lunt, D.J.; Haywood, A.M.; Schmidt, G.A.; Salzmann, U.; Valdes, P.J.; Dowsett, H.J.

2010-01-01

Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earths climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere-ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30-50% greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. ?? 2010 Macmillan Publishers Limited. All rights reserved.

A revised energy-balance framework for the Earth

NASA Astrophysics Data System (ADS)

Dessler, A. E.

2017-12-01

Some of the most important conclusions of climate science are based on energy balance calculations, in which solar energy absorbed by the Earth system is set equal to infrared energy radiated to space. Traditionally, energy radiated to space is assumed to be proportional to surface temperature. We show here problems with this framework, including potential biases in estimates of climate sensitivity based on the 20th-century historical record. This could potentially explain why estimates of equilibrium climate sensitivity (ECS) using observations over the 20th century yield values lower than other estimates. We then present a modified version of the energy balance framework in which energy radiated to space is assumed to be proportional to tropical atmospheric temperature. We use this new framework to estimate ECS and obtain an estimate of 3°C, with a likely range (66% confidence interval) of 2.2-4.1°C.

CLIMATE CHANGE IN THAILAND AND ITS POTENTIAL IMPACT ON RICE YIELD

EPA Science Inventory

Because of the uncertainties surrounding prediction of climate change, it is common to employ climate scenarios to estimate its impacts on a system. Climate scenarios are sets of climatic perturbations used with models to test system sensitivity to projected changes. In this stud...

Improving Constraints on Climate System Properties withAdditional Data and New Statistical and Sampling Methods

NASA Astrophysics Data System (ADS)

Forest, C. E.; Libardoni, A. G.; Sokolov, A. P.; Monier, E.

2017-12-01

We use the updated MIT Earth System Model (MESM) to derive the joint probability distribution function for Equilibrium Climate sensitivity (S), an effective heat diffusivity (Kv), and the net aerosol forcing (Faer). Using a new 1800-member ensemble of MESM runs, we derive PDFs by comparing model outputs against historical observations of surface temperature and global mean ocean heat content. We focus on how changes in (i) the MESM model, (ii) recent surface temperature and ocean heat content observations, and (iii) estimates of internal climate variability will all contribute to uncertainties. We show that estimates of S increase and Faer is less negative. These shifts result partly from new model forcing inputs but also from including recent temperature records that lead to higher values of S and Kv. We show that the parameter distributions are sensitive to the internal variability in the climate system. When considering these factors, we derive our best estimate for the joint probability distribution for the climate system properties. We estimate the 90-percent confidence intervals for climate sensitivity as 2.7-5.4 oC with a mode of 3.5 oC, for Kv as 1.9-23.0 cm2 s-1 with a mode of 4.41 cm2 s-1, and for Faer as -0.4 - -0.04 Wm-2 with a mode of -0.25 Wm-2. Lastly, we estimate TCR to be between 1.4 and 2.1 oC with a mode of 1.8 oC.

Observational constraints on mixed-phase clouds imply higher climate sensitivity

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

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D.

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO 2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here, in this paper, we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. Finally, wemore » point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.« less

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

NASA Technical Reports Server (NTRS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-01-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

NASA Astrophysics Data System (ADS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-02-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Observational constraints on mixed-phase clouds imply higher climate sensitivity

DOE PAGES

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D.

2016-04-08

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO 2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here, in this paper, we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. Finally, wemore » point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.« less

Observational constraints on mixed-phase clouds imply higher climate sensitivity.

PubMed

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D

2016-04-08

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. We point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback. Copyright © 2016, American Association for the Advancement of Science.

A lower and more constrained estimate of climate sensitivity using updated observations and detailed radiative forcing time series

NASA Astrophysics Data System (ADS)

Skeie, R. B.; Berntsen, T.; Aldrin, M.; Holden, M.; Myhre, G.

2012-04-01

A key question in climate science is to quantify the sensitivity of the climate system to perturbation in the radiative forcing (RF). This sensitivity is often represented by the equilibrium climate sensitivity, but this quantity is poorly constrained with significant probabilities for high values. In this work the equilibrium climate sensitivity (ECS) is estimated based on observed near-surface temperature change from the instrumental record, changes in ocean heat content and detailed RF time series. RF time series from pre-industrial times to 2010 for all main anthropogenic and natural forcing mechanisms are estimated and the cloud lifetime effect and the semi-direct effect, which are not RF mechanisms in a strict sense, are included in the analysis. The RF time series are linked to the observations of ocean heat content and temperature change through an energy balance model and a stochastic model, using a Bayesian approach to estimate the ECS from the data. The posterior mean of the ECS is 1.9˚C with 90% credible interval (C.I.) ranging from 1.2 to 2.9˚C, which is tighter than previously published estimates. Observational data up to and including year 2010 are used in this study. This is at least ten additional years compared to the majority of previously published studies that have used the instrumental record in attempts to constrain the ECS. We show that the additional 10 years of data, and especially 10 years of additional ocean heat content data, have significantly narrowed the probability density function of the ECS. If only data up to and including year 2000 are used in the analysis, the 90% C.I. is 1.4 to 10.6˚C with a pronounced heavy tail in line with previous estimates of ECS constrained by observations in the 20th century. Also the transient climate response (TCR) is estimated in this study. Using observational data up to and including year 2010 gives a 90% C.I. of 1.0 to 2.1˚C, while the 90% C.I. is significantly broader ranging from 1.1 to 3.4 ˚C if only data up to and including year 2000 is used.

Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Hill, D.J.; Dolan, A. M.; Otto-Bliesner, B. L.; Bragg, F.; Chan, W.-L.; Chandler, M. A.; Contoux, C.; Dowsett, H. J.; Jost, A.;

Effects of model spatial resolution on ecohydrologic predictions and their sensitivity to inter-annual climate variability

Treesearch

Kyongho Son; Christina Tague; Carolyn Hunsaker

2016-01-01

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates...

Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531

An early warning system for high climate sensitivity? (Invited)

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.

2010-12-01

The scientific case for the clear and present danger of global warming has been unassailable at least since the release of the Charney Report more than thirty years ago, if not longer. While prompt action to begin decarbonizing energy systems could still head off much of the potential warming, it is distinctly possible that emissions will continue unabated in the coming decades, leading to a doubling or more of pre-industrial carbon dioxide concentrations. At present, we are in the unenviable position of not even knowing how bad things will get if this scenario comes to pass, because of the uncertainty in climate sensitivity. If climate sensitivity is high, then the consequences will be dire, perhaps even catastrophic. As the world continues to warm in response to continued carbon dioxide emissions, will we at least be able to monitor the climate and provide an early warning that the planet is on a high-sensitivity track, if such turns out to be the case? At what point will we actually know the climate sensitivity? It has long been recognized that the prime contributor to uncertainty in climate sensitivity is uncertainty in cloud feedbacks. Study of paleoclimate and climate of the past century has not been able to resolve which models do cloud feedback most correctly, because of uncertainties in radiative forcing. In this talk, I will discuss monitoring requirements, and analysis techniques, that might have the potential to determine which climate models most faithfully represent climate feedbacks, and thus determine which models provide the best estimate of climate sensitivity. The endeavor is complicated by the distinction between transient climate response and equilibrium climate sensitivity. I will discuss the particular challenges posed by this issue, particularly in light of recent indications that the pattern of ocean heat storage may lead to different cloud feedbacks in the transient warming stage than apply once the system has reached equilibrium. Apart from this problem, the transient nature of climate response driven by increasing CO2 requires careful monitoring of ocean heat storage as well as top-of-atmosphere radiative budgets, if climate sensitivity is to be estimated. Water vapor feedback is not considered as uncertain as cloud feedback, but there is still a considerable potential for surprises. I will discuss microwave monitoring requirements for tracking water vapor feedback. At the other extreme, the longer term feedbacks that contribute to Earth System Sensitivity are even more uncertain than cloud feedbacks, particularly with regard to the terrestrial carbon cycle. Prospects for obtaining an early warning of a PETM-type organic carbon release seem bleak. Finally, I will discuss the particular challenge of obtaining an early warning of high climate sensitivity in the case that the climate system has a bifurcation.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections.

PubMed

Caballero, Rodrigo; Huber, Matthew

2013-08-27

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow "Earth system" feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or "Charney" climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections

PubMed Central

Caballero, Rodrigo; Huber, Matthew

2013-01-01

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow “Earth system” feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or “Charney” climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature. PMID:23918397

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.

Evaluation of uncertainties in the CRCM-simulated North American climate

NASA Astrophysics Data System (ADS)

de Elía, Ramón; Caya, Daniel; Côté, Hélène; Frigon, Anne; Biner, Sébastien; Giguère, Michel; Paquin, Dominique; Harvey, Richard; Plummer, David

2008-02-01

This work is a first step in the analysis of uncertainty sources in the RCM-simulated climate over North America. Three main sets of sensitivity studies were carried out: the first estimates the magnitude of internal variability, which is needed to evaluate the significance of changes in the simulated climate induced by any model modification. The second is devoted to the role of CRCM configuration as a source of uncertainty, in particular the sensitivity to nesting technique, domain size, and driving reanalysis. The third study aims to assess the relative importance of the previously estimated sensitivities by performing two additional sensitivity experiments: one, in which the reanalysis driving data is replaced by data generated by the second generation Coupled Global Climate Model (CGCM2), and another, in which a different CRCM version is used. Results show that the internal variability, triggered by differences in initial conditions, is much smaller than the sensitivity to any other source. Results also show that levels of uncertainty originating from liberty of choices in the definition of configuration parameters are comparable among themselves and are smaller than those due to the choice of CGCM or CRCM version used. These results suggest that uncertainty originated by the CRCM configuration latitude (freedom of choice among domain sizes, nesting techniques and reanalysis dataset), although important, does not seem to be a major obstacle to climate downscaling. Finally, with the aim of evaluating the combined effect of the different uncertainties, the ensemble spread is estimated for a subset of the analysed simulations. Results show that downscaled surface temperature is in general more uncertain in the northern regions, while precipitation is more uncertain in the central and eastern US.

Carbon and water flux responses to physiology by environment interactions: a sensitivity analysis of variation in climate on photosynthetic and stomatal parameters

NASA Astrophysics Data System (ADS)

Bauerle, William L.; Daniels, Alex B.; Barnard, David M.

2014-05-01

Sensitivity of carbon uptake and water use estimates to changes in physiology was determined with a coupled photosynthesis and stomatal conductance ( g s) model, linked to canopy microclimate with a spatially explicit scheme (MAESTRA). The sensitivity analyses were conducted over the range of intraspecific physiology parameter variation observed for Acer rubrum L. and temperate hardwood C3 (C3) vegetation across the following climate conditions: carbon dioxide concentration 200-700 ppm, photosynthetically active radiation 50-2,000 μmol m-2 s-1, air temperature 5-40 °C, relative humidity 5-95 %, and wind speed at the top of the canopy 1-10 m s-1. Five key physiological inputs [quantum yield of electron transport ( α), minimum stomatal conductance ( g 0), stomatal sensitivity to the marginal water cost of carbon gain ( g 1), maximum rate of electron transport ( J max), and maximum carboxylation rate of Rubisco ( V cmax)] changed carbon and water flux estimates ≥15 % in response to climate gradients; variation in α, J max, and V cmax input resulted in up to ~50 and 82 % intraspecific and C3 photosynthesis estimate output differences respectively. Transpiration estimates were affected up to ~46 and 147 % by differences in intraspecific and C3 g 1 and g 0 values—two parameters previously overlooked in modeling land-atmosphere carbon and water exchange. We show that a variable environment, within a canopy or along a climate gradient, changes the spatial parameter effects of g 0, g 1, α, J max, and V cmax in photosynthesis- g s models. Since variation in physiology parameter input effects are dependent on climate, this approach can be used to assess the geographical importance of key physiology model inputs when estimating large scale carbon and water exchange.

Predicting potential global distributions of two Miscanthus grasses: implications for horticulture, biofuel production, and biological invasions.

PubMed

Hager, Heather A; Sinasac, Sarah E; Gedalof, Ze'ev; Newman, Jonathan A

2014-01-01

In many regions, large proportions of the naturalized and invasive non-native floras were originally introduced deliberately by humans. Pest risk assessments are now used in many jurisdictions to regulate the importation of species and usually include an estimation of the potential distribution in the import area. Two species of Asian grass (Miscanthus sacchariflorus and M. sinensis) that were originally introduced to North America as ornamental plants have since escaped cultivation. These species and their hybrid offspring are now receiving attention for large-scale production as biofuel crops in North America and elsewhere. We evaluated their potential global climate suitability for cultivation and potential invasion using the niche model CLIMEX and evaluated the models' sensitivity to the parameter values. We then compared the sensitivity of projections of future climatically suitable area under two climate models and two emissions scenarios. The models indicate that the species have been introduced to most of the potential global climatically suitable areas in the northern but not the southern hemisphere. The more narrowly distributed species (M. sacchariflorus) is more sensitive to changes in model parameters, which could have implications for modelling species of conservation concern. Climate projections indicate likely contractions in potential range in the south, but expansions in the north, particularly in introduced areas where biomass production trials are under way. Climate sensitivity analysis shows that projections differ more between the selected climate change models than between the selected emissions scenarios. Local-scale assessments are required to overlay suitable habitat with climate projections to estimate areas of cultivation potential and invasion risk.

Climate sensitivity derived from orbital-scale, δ11B-based pCO2 estimates in the early Pleistocene, ~1.5 Ma

NASA Astrophysics Data System (ADS)

Dyez, K. A.; Hoenisch, B.

2015-12-01

Atmospheric CO2 concentrations in the late Pleistocene have been characterized from ancient air bubbles trapped within polar ice sheets. Ice-core records clearly demonstrate the glacial-interglacial relationship between the global carbon cycle and climate, but they are so far limited to the last 800 ky, when glacial cycles occurred approximately every 100-ky. Boron isotope ratios (δ11B) recorded in the tests of fossil planktic foraminifera offer an opportunity to extend the atmospheric pCO2 record into the early Pleistocene, when glacial cycles instead occurred approximately every 41-ky. We present a new high-resolution record of planktic foraminiferal d11B, Mg/Ca (a sea surface temperature proxy) and salinity estimates from the deconvolution of δ18O and Mg/Ca. Combined with reasonable assumptions of ocean alkalinity, these data allow us to estimate pCO2 over three of the 41-ky climate cycles at ~1.5 Ma. Our results confirm the hypothesis that climate and atmospheric pCO2 were coupled beyond ice core records and provide new constraints for studies of long-term CO2 storage and release, regional controls on the early Pleistocene carbon cycle, and estimating climate sensitivity before the mid-Pleistocene transition.

Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

NASA Astrophysics Data System (ADS)

Errickson, F. C.; Anthoff, D.; Keller, K.

2016-12-01

Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

NASA Astrophysics Data System (ADS)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.

How does the sensitivity of climate affect stratospheric solar radiation management?

NASA Astrophysics Data System (ADS)

Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.

2011-12-01

If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best-estimate models, and so near-median climate sensitivity, may be ignoring important contingencies associated with implementing SRM in reality. A primary motivation for studying SRM via the injection of aerosols in the stratosphere is to evaluate its potential effectiveness as "insurance" in the case of higher-than-expected climate response to global warming. We find that this is precisely when SRM appears to be least effective in returning regional climates to their baseline states and reducing regional rates of precipitation change. On the other hand, given the very high regional temperature anomalies associated with rising greenhouse gas concentrations in high sensitivity models, it is also where SRM is most effective in reducing rates of change relative to a no SRM alternative.

Climate Change and Future Pollen Allergy in Europe.

PubMed

Lake, Iain R; Jones, Natalia R; Agnew, Maureen; Goodess, Clare M; Giorgi, Filippo; Hamaoui-Laguel, Lynda; Semenov, Mikhail A; Solomon, Fabien; Storkey, Jonathan; Vautard, Robert; Epstein, Michelle M

2017-03-01

Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans. We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed ( Ambrosia artemisiifolia ) in Europe. A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios. Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results. Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR, Jones NR, Agnew M, Goodess CM, Giorgi F, Hamaoui-Laguel L, Semenov MA, Solomon F, Storkey J, Vautard R, Epstein MM. 2017. Climate change and future pollen allergy in Europe. Environ Health Perspect 125:385-391; http://dx.doi.org/10.1289/EHP173.

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE PAGES

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; ...

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake sincemore » 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

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

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

DOE PAGES

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra; ...

2017-11-20

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

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

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China.

PubMed

Hou, Lan-Gong; Zou, Song-Bing; Xiao, Hong-Lang; Yang, Yong-Gang

2013-01-01

The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

Updated estimates of the climate response to emissions and their policy implications (Invited)

NASA Astrophysics Data System (ADS)

Allen, M. R.; Otto, A.; Stocker, T. F.; Frame, D. J.

2013-12-01

We review the implications of observations of the global energy budget over recent decades, particularly the 'warming hiatus' period over the 2000s, for key climate system properties including equilibrium climate sensitivity (ECS), transient climate response (TCR) and transient climate response to cumulative carbon emissions (TCRE). We show how estimates of the upper bound of ECS remain, as ever, sensitive to prior assumptions and also how ECS, even if it were better constrained, would provide much less information about the social cost of carbon than TCR or TCRE. Hence the excitement over recent, apparently conflicting, estimates of ECS, is almost entirely misplaced. Of greater potential policy significance is the fact that recent observations imply a modest (of order 25%) downward revision in the upper bound and most likely values of TCR and TCRE, as compared to some, but not all, of the estimates published in the mid-2000s. This is partly due to the recent reduced rate of warming, and partly due to revisions in estimates of total anthropogenic forcing to date. Both of these developments may turn out to be short-lived, so the policy implications of this modest revision in TCR/TCRE should not be over-sold: nevertheless, it is interesting to explore what they are. The implications for climate change adaptation of a 25% downward revision in TCR and TCRE are minimal, being overshadowed by uncertainty due to internal variability and non-CO2 climate forcings over typical timescales for adaptation planning. We introduce a simple framework for assessing the implications for mitigation in terms of timing of peak emissions average rates of emission reduction required to avoid specific levels of peak warming. We show that, as long as emissions continue to increase approximately exponentially, the implications for mitigation of any revisions in the climate response are surprisingly small.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Overview of the Special Issue: A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

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

Waldhoff, Stephanie T.; Martinich, Jeremy; Sarofim, Marcus

2015-07-01

The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets ofmore » 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potential benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less

Climate impacts on agricultural land use in the USA: the role of socio-economic scenarios

USGS Publications Warehouse

Mu, Jianhong E.; Sleeter, Benjamin M.; Abatzoglou, John T.; Antle, John M.

2017-01-01

We examine the impacts of climate on net returns from crop and livestock production and the resulting impact on land-use change across the contiguous USA. We first estimate an econometric model to project effects of weather fluctuations on crop and livestock net returns and then use a semi-reduced form land-use share model to study agricultural land-use changes under future climate and socio-economic scenarios. Estimation results show that crop net returns are more sensitive to thermal and less sensitive to moisture variability than livestock net returns; other agricultural land uses substitute cropland use when 30-year averaged degree-days or precipitation are not beneficial for crop production. Under future climate and socio-economic scenarios, we project that crop and livestock net returns are both increasing, but with crop net returns increasing at a higher rate; cropland increases with declines of marginal and pastureland by the end of the twenty-first century. Projections also show that impacts of future climate on agricultural land uses are substantially different and a larger variation of land-use change is evident when socio-economic scenarios are incorporated into the climate impact analysis.

Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007

USGS Publications Warehouse

Johnson, Adam G.; Engott, John A.; Bassiouni, Maoya; Rotzoll, Kolja

2014-12-14

Demand for freshwater on the Island of Maui is expected to grow. To evaluate the availability of fresh groundwater, estimates of groundwater recharge are needed. A water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Maui for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Maui is about 1,309 million gallons per day, or about 44 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 39 percent of total water inflow consisting of precipitation, irrigation, septic leachate, and seepage from reservoirs and cesspools. Most recharge occurs on the wet, windward slopes of Haleakalā and on the wet, uplands of West Maui Mountain. Dry, coastal areas generally have low recharge. In the dry isthmus, however, irrigated fields have greater recharge than nearby unirrigated areas. For drought conditions, mean annual recharge for Maui is about 1,010 million gallons per day, which is 23 percent less than recharge for average climate conditions. For individual aquifer-system areas used for groundwater management, recharge for drought conditions is about 8 to 51 percent less than recharge for average climate conditions. The spatial distribution of rainfall is the primary factor determining spatially distributed recharge estimates for most areas on Maui. In wet areas, recharge estimates are also sensitive to water-budget parameters that are related to runoff, fog interception, and forest-canopy evaporation. In dry areas, recharge estimates are most sensitive to irrigated crop areas and parameters related to evapotranspiration.

Estimating option values of solar radiation management assuming that climate sensitivity is uncertain.

PubMed

Arino, Yosuke; Akimoto, Keigo; Sano, Fuminori; Homma, Takashi; Oda, Junichiro; Tomoda, Toshimasa

2016-05-24

Although solar radiation management (SRM) might play a role as an emergency geoengineering measure, its potential risks remain uncertain, and hence there are ethical and governance issues in the face of SRM's actual deployment. By using an integrated assessment model, we first present one possible methodology for evaluating the value arising from retaining an SRM option given the uncertainty of climate sensitivity, and also examine sensitivities of the option value to SRM's side effects (damages). Reflecting the governance challenges on immediate SRM deployment, we assume scenarios in which SRM could only be deployed with a limited degree of cooling (0.5 °C) only after 2050, when climate sensitivity uncertainty is assumed to be resolved and only when the sensitivity is found to be high (T2x = 4 °C). We conduct a cost-effectiveness analysis with constraining temperature rise as the objective. The SRM option value is originated from its rapid cooling capability that would alleviate the mitigation requirement under climate sensitivity uncertainty and thereby reduce mitigation costs. According to our estimates, the option value during 1990-2049 for a +2.4 °C target (the lowest temperature target level for which there were feasible solutions in this model study) relative to preindustrial levels were in the range between $2.5 and $5.9 trillion, taking into account the maximum level of side effects shown in the existing literature. The result indicates that lower limits of the option values for temperature targets below +2.4 °C would be greater than $2.5 trillion.

Estimating option values of solar radiation management assuming that climate sensitivity is uncertain

PubMed Central

Arino, Yosuke; Akimoto, Keigo; Sano, Fuminori; Homma, Takashi; Oda, Junichiro; Tomoda, Toshimasa

2016-01-01

Although solar radiation management (SRM) might play a role as an emergency geoengineering measure, its potential risks remain uncertain, and hence there are ethical and governance issues in the face of SRM’s actual deployment. By using an integrated assessment model, we first present one possible methodology for evaluating the value arising from retaining an SRM option given the uncertainty of climate sensitivity, and also examine sensitivities of the option value to SRM’s side effects (damages). Reflecting the governance challenges on immediate SRM deployment, we assume scenarios in which SRM could only be deployed with a limited degree of cooling (0.5 °C) only after 2050, when climate sensitivity uncertainty is assumed to be resolved and only when the sensitivity is found to be high (T2x = 4 °C). We conduct a cost-effectiveness analysis with constraining temperature rise as the objective. The SRM option value is originated from its rapid cooling capability that would alleviate the mitigation requirement under climate sensitivity uncertainty and thereby reduce mitigation costs. According to our estimates, the option value during 1990–2049 for a +2.4 °C target (the lowest temperature target level for which there were feasible solutions in this model study) relative to preindustrial levels were in the range between $2.5 and $5.9 trillion, taking into account the maximum level of side effects shown in the existing literature. The result indicates that lower limits of the option values for temperature targets below +2.4 °C would be greater than $2.5 trillion. PMID:27162346

Carbon Climate Feedbacks and Climate Sensitivity (Invited)

NASA Astrophysics Data System (ADS)

Fung, I.

2009-12-01

The Charney report (22 pages including bibliography and appendices) was written when atmospheric CO2 was 334 ppmv (1979). It estimates a climate sensitivity of 3 +/- 1.5C for a doubling of CO2, and points out the warming delay due to the slow penetration of heat into intermediate depths in the oceans and the decreasing capacity of the oceans to serve a CO2 sink. “We may not be given a warning until the CO2 loading is such that an appreciable climate change is inevitable. The equilibrium warming will eventually occur; it will merely have been postponed.” CO2 exceeded 385 ppmv in 2008, and the warning signs are now abundantly evident. One of the “slow” feedbacks not included in the Charney Report involves the interaction between the land carbon cycle and climate change. The carbon cycle on land is coupled to the water and energy cycles. This paper reviews positive and negative carbon-climate feedbacks associated with changes in the function and distribution of land ecosystems. These feedbacks, once in gear, will magnify climate sensitivity and accelerate global warming.

Water resource sensitivity from a Mediterranean perspective

NASA Astrophysics Data System (ADS)

Lyon, S. W.; Klein, J.; Archibald, J. A.; Walter, T.

2012-12-01

The water cycle in semiarid environments is intimately connected to plant-water interactions making these regions sensitive to both future climatic changes and landuse alterations. This study explores the sensitivity of water resource availability from a Mediterranean perspective using the Navarino Environmental Observatory (NEO) in Costa Navarino, Greece as a large-scale laboratory for developing and testing the potential resource impacts of various landuse/climatic trajectories. Direct measurements of evapotranspiration were combined with Penman-Monteith estimates to compare water vapor flux variability across the gradient of current management conditions found within the NEO landscape. These range from native, non-managed vegetation to historic, traditionally managed agriculture to modern, actively managed recreational lands. These management conditions greatly impact the vertical flux of water vapor in this semiarid landscape. Our evapotranspiration estimates were placed into a process-based modeling framework to characterize the current state of regional water resource availability and simulate future trajectories (and the associated uncertainties) in response to landuse/climatic changes. This region is quite sensitive with regards to water cycle modifications due to the anthropogenic redistribution of water within and across the landscape. Such sensitivity typifies that expected for much of the Mediterranean region, highlighting the NEO as a potential key location for future observation and investigation.

Pleistocene tropical Pacific temperature sensitivity to radiative greenhouse gas forcing

NASA Astrophysics Data System (ADS)

Dyck, K. A.; Ravelo, A. C.

2011-12-01

How high will Earth's global average surface temperature ultimately rise as greenhouse gas concentrations increase in the future? One way to tackle this question is to compare contemporaneous temperature and greenhouse gas concentration data from paleoclimate records, while considering that other radiative forcing mechanisms (e.g. changes in the amount and distribution of incoming solar radiation associated with changes in the Earth's orbital configuration) also contribute to surface temperature change. Since the sensitivity of surface temperature varies with location and latitude, here we choose a central location representative of the west Pacific warm pool, far from upwelling regions or surface temperature gradients in order to minimize climate feedbacks associated with high-latitude regions or oceanic dynamics. The 'steady-state' or long-term temperature change associated with greenhouse gas radiative forcing is often labeled as equilibrium (or 'Earth system') climate sensitivity to the doubling of atmospheric greenhouse gas concentration. Climate models suggest that Earth system sensitivity does not change dramatically over times when CO2 was lower or higher than the modern atmospheric value. Thus, in our investigation of the changes in tropical SST, from the glacial to interglacial states when greenhouse gas forcing nearly doubled, we use Late Pleistocene paleoclimate records to constrain earth system sensitivity for the tropics. Here we use Mg/Ca-paleothermometry using the foraminifera G. ruber from ODP Site 871 from the past 500 kyr in the western Pacific warm pool to estimate tropical Pacific equilibrium climate sensitivity to a doubling of greenhouse gas concentrations to be ~4°C. This tropical SST sensitivity to greenhouse gas forcing is ~1-2°C higher than that predicted by climate models of past glacial periods or future warming for the tropical Pacific. Equatorial Pacific SST sensitivity may be higher than predicted by models for a number of reasons. First, models may not be adequately representing long-term deep ocean feedbacks. Second, models may incorrectly parameterize tropical cloud (or other short-term) feedback processes. Lastly, either paleo-temperature or radiative forcing may have been incorrectly estimated (e.g. through calibration of paleoclimate evidence for temperature change). Since theory suggests that surface temperature in the high latitudes is more sensitive to radiative forcing changes than surface temperature in the tropics, the results of this study also imply that globally averaged Earth system sensitivity to greenhouse gas concentrations may be higher than most climate models predict.

Using fuzzy logic to determine the vulnerability of marine species to climate change.

PubMed

Jones, Miranda C; Cheung, William W L

2018-02-01

Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species-specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species' traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the 'business-as-usual' greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large-bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information. © 2017 John Wiley & Sons Ltd.

Estimating daily climatologies for climate indices derived from climate model data and observations

PubMed Central

Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

2015-01-01

Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

Applying a simple water-energy balance framework to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-12-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There are coherent spatial patterns with basins of increasing catchment efficiency being dominant in the western and central parts of the US. A hot spot of decreasing efficiency is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as the observed change signal. However, we find that both, the CCUW hypothesis and the approaches using the Budyko hypothesis, show minimal deviations between observed and predicted changes in streamflow for basins where a dominance of climatic changes and low influences of basin changes have been found. Thus, climate sensitivity methods can be regarded as valid tools if we expect climate changes only and neglect any direct anthropogenic influences.

Estimating climate sensitivity from paleo-data.

NASA Astrophysics Data System (ADS)

Crowley, T. J.; Hegerl, G. C.

2003-12-01

For twenty years estimates of climate sensitivity from the instrumental record have neen between about 1.5-4.5° C for a doubling of CO2. Various efforts, most notably by J. Hansen, and M. Hoffert and C. Covey. have been made to test this range against paleo-data for the ice age and Cretaceous, yielding approximately the same range with a "best guess" sensitivity of about 2.0-3.0° C. Here we re-examine this issue with new paleo-data and also include information for the time period 1000-present. For this latter interval formal pdfs can for the first time be calculated for paleo data. Regardless of the time interval examined we generally find that paleo-sensitivities still fall within the range of about 1.5-4.5° C. The primary impediments to more precise determinations involve not only uncertainties in forcings but also the paleo reconstructions. Barring a dramatic breakthrough in reconciliation of some long-standing differences in the magnitude of paleotemperature estimates for different proxies, the range of paleo-sensitivities will continue to have this uncertainty. This range can be considered either unsatisfactory or satisfactory. It is unsatisfactory because some may consider it insufficiently precise. It is satisfactory in the sense that the range is both robust and entirely consistent with the range independently estimated from the instrumental record.

Robust Emergent Climate Phenomena Associated with the High-Sensitivity Tail

NASA Astrophysics Data System (ADS)

Boslough, M.; Levy, M.; Backus, G.

2010-12-01

Because the potential effects of climate change are more severe than had previously been thought, increasing focus on uncertainty quantification is required for risk assessment needed by policy makers. Current scientific efforts focus almost exclusively on establishing best estimates of future climate change. However, the greatest consequences occur in the extreme tail of the probability density functions for climate sensitivity (the “high-sensitivity tail”). To this end, we are exploring the impacts of newly postulated, highly uncertain, but high-consequence physical mechanisms to better establish the climate change risk. We define consequence in terms of dramatic change in physical conditions and in the resulting socioeconomic impact (hence, risk) on populations. Although we are developing generally applicable risk assessment methods, we have focused our initial efforts on uncertainty and risk analyses for the Arctic region. Instead of focusing on best estimates, requiring many years of model parameterization development and evaluation, we are focusing on robust emergent phenomena (those that are not necessarily intuitive and are insensitive to assumptions, subgrid-parameterizations, and tunings). For many physical systems, under-resolved models fail to generate such phenomena, which only develop when model resolution is sufficiently high. Our ultimate goal is to discover the patterns of emergent climate precursors (those that cannot be predicted with lower-resolution models) that can be used as a "sensitivity fingerprint" and make recommendations for a climate early warning system that would use satellites and sensor arrays to look for the various predicted high-sensitivity signatures. Our initial simulations are focused on the Arctic region, where underpredicted phenomena such as rapid loss of sea ice are already emerging, and because of major geopolitical implications associated with increasing Arctic accessibility to natural resources, shipping routes, and strategic locations. We anticipate that regional climate will be strongly influenced by feedbacks associated with a seasonally ice-free Arctic, but with unknown emergent phenomena. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

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

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

DOE PAGES

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.; ...

2015-12-21

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Projecting Global Decadal Change in Water Supply for Strategic Planning: Window Size Sensitivity in CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Luck, M.; Landis, M.; Gassert, F.; Luo, T.; Reig, P.

2013-12-01

Climate adaptation and strategic planning by states, corporations, and long-term investors require reliable information on the range of possible climatic changes. However, most decision makers are incapable of planning over the century-scale time horizons for which global climate models (GCMs) are developed. Even the most forward-looking actors rarely consider scenarios more than several decades into the future. The mismatch in model design and practical demands poses a challenge in extracting useful information on the decadal scale from global climate change models. Here, we explore options and limitations in generating decadal water supply change projections, as evaluated for the World Resources Institute's Aqueduct project's estimates of future change in water stress. Our approach uses an ensemble of six CMIP5 GCMs, selected to represent a broad lineage of models that best reproduce the mean and standard deviation of recent streamflow records in 18 large river basins, bias corrected to GLDAS-2.0 runoff. We examine sensitivity of point estimates of climate normal supply and water supply variability (interannual and seasonal) at the years 2020, 2030, and 2040, with a focus on using temporal windows of different lengths (11-, 21-, and 31-years) to generate the point estimates. With the aim of creating practical information for non-expert audiences, we will discuss the persistent question of 'how can we balance uncertainty and usability in designing scientific data products?'

Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

Treesearch

E. Garcia; C.L. Tague; J. Choate

2013-01-01

Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

Delays reducing waterborne and water-related infectious diseases in China under climate change

PubMed Central

Hodges, Maggie; Belle, Jessica H.; Carlton, Elizabeth J.; Liang, Song; Li, Huazhong; Luo, Wei; Freeman, Matthew C.; Liu, Yang; Gao, Yang; Hess, Jeremy J.; Remais, Justin V.

2014-01-01

Despite China’s rapid progress improving water, sanitation and hygiene (WSH) access, in 2011, 471 million people lacked access to improved sanitation and 401 million to household piped water. Because certain infectious diseases are sensitive to changes in both climate and WSH conditions, we projected impacts of climate change on WSH-attributable diseases in China in 2020 and 2030 by coupling estimates of the temperature sensitivity of diarrheal diseases and three vector-borne diseases, temperature projections from global climate models, WSH-infrastructure development scenarios, and projected demographic changes. By 2030, climate change is projected to delay China’s rapid progress toward reducing WSH-attributable infectious disease burden by 8–85 months. This development delay summarizes the adverse impact of climate change on WSH-attributable infectious diseases in China, and can be used in other settings where a significant health burden may accompany future changes in climate even as the total burden of disease falls due to non-climate reasons. PMID:25530812

Delays in reducing waterborne and water-related infectious diseases in China under climate change

NASA Astrophysics Data System (ADS)

Hodges, Maggie; Belle, Jessica H.; Carlton, Elizabeth J.; Liang, Song; Li, Huazhong; Luo, Wei; Freeman, Matthew C.; Liu, Yang; Gao, Yang; Hess, Jeremy J.; Remais, Justin V.

2014-12-01

Despite China's rapid progress in improving water, sanitation and hygiene (WSH) access, in 2011, 471 million people lacked access to improved sanitation and 401 million to household piped water. As certain infectious diseases are sensitive to changes in both climate and WSH conditions, we projected impacts of climate change on WSH-attributable diseases in China in 2020 and 2030 by coupling estimates of the temperature sensitivity of diarrhoeal diseases and three vector-borne diseases, temperature projections from global climate models, WSH-infrastructure development scenarios, and projected demographic changes. By 2030, climate change is projected to delay China's rapid progress towards reducing WSH-attributable infectious disease burden by 8-85 months. This development delay summarizes the adverse impact of climate change on WSH-attributable infectious diseases in China, and can be used in other settings where a significant health burden may accompany future changes in climate even as the total burden of disease falls owing to non-climate reasons.

Delays reducing waterborne and water-related infectious diseases in China under climate change.

PubMed

Hodges, Maggie; Belle, Jessica H; Carlton, Elizabeth J; Liang, Song; Li, Huazhong; Luo, Wei; Freeman, Matthew C; Liu, Yang; Gao, Yang; Hess, Jeremy J; Remais, Justin V

2014-12-01

Despite China's rapid progress improving water, sanitation and hygiene (WSH) access, in 2011, 471 million people lacked access to improved sanitation and 401 million to household piped water. Because certain infectious diseases are sensitive to changes in both climate and WSH conditions, we projected impacts of climate change on WSH-attributable diseases in China in 2020 and 2030 by coupling estimates of the temperature sensitivity of diarrheal diseases and three vector-borne diseases, temperature projections from global climate models, WSH-infrastructure development scenarios, and projected demographic changes. By 2030, climate change is projected to delay China's rapid progress toward reducing WSH-attributable infectious disease burden by 8-85 months. This development delay summarizes the adverse impact of climate change on WSH-attributable infectious diseases in China, and can be used in other settings where a significant health burden may accompany future changes in climate even as the total burden of disease falls due to non-climate reasons.

Climate Sensitivity of the Community Climate System Model, Version 4

DOE PAGES

Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...

2012-05-01

Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less

Excessive heat and respiratory hospitalizations in New York State: estimating current and future public health burden related to climate change.

PubMed

Lin, Shao; Hsu, Wan-Hsiang; Van Zutphen, Alissa R; Saha, Shubhayu; Luber, George; Hwang, Syni-An

2012-11-01

Although many climate-sensitive environmental exposures are related to mortality and morbidity, there is a paucity of estimates of the public health burden attributable to climate change. We estimated the excess current and future public health impacts related to respiratory hospitalizations attributable to extreme heat in summer in New York State (NYS) overall, its geographic regions, and across different demographic strata. On the basis of threshold temperature and percent risk changes identified from our study in NYS, we estimated recent and future attributable risks related to extreme heat due to climate change using the global climate model with various climate scenarios. We estimated effects of extreme high apparent temperature in summer on respiratory admissions, days hospitalized, direct hospitalization costs, and lost productivity from days hospitalized after adjusting for inflation. The estimated respiratory disease burden attributable to extreme heat at baseline (1991-2004) in NYS was 100 hospital admissions, US$644,069 in direct hospitalization costs, and 616 days of hospitalization per year. Projections for 2080-2099 based on three different climate scenarios ranged from 206-607 excess hospital admissions, US$26-$76 million in hospitalization costs, and 1,299-3,744 days of hospitalization per year. Estimated impacts varied by geographic region and population demographics. We estimated that excess respiratory admissions in NYS due to excessive heat would be 2 to 6 times higher in 2080-2099 than in 1991-2004. When combined with other heat-associated diseases and mortality, the potential public health burden associated with global warming could be substantial.

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Influence of watershed topographic and socio-economic attributes on the climate sensitivity of global river water quality

NASA Astrophysics Data System (ADS)

Khan, Afed U.; Jiang, Jiping; Wang, Peng; Zheng, Yi

2017-10-01

Surface waters exhibit regionalization due to various climatic conditions and anthropogenic activities. Here we assess the impact of topographic and socio-economic factors on the climate sensitivity of surface water quality, estimated using an elasticity approach (climate elasticity of water quality (CEWQ)), and identify potential risks of instability in different regions and climatic conditions. Large global datasets were used for 12 main water quality parameters from 43 water quality monitoring stations located at large major rivers. The results demonstrated that precipitation elasticity shows higher sensitivity to topographic and socio-economic determinants as compared to temperature elasticity. In tropical climate class (A), gross domestic product (GDP) played an important role in stabilizing the CEWQ. In temperate climate class (C), GDP played the same role in stability, while the runoff coefficient, slope, and population density fuelled the risk of instability. The results implied that watersheds with lower runoff coefficient, thick population density, over fertilization and manure application face a higher risk of instability. We discuss the socio-economic and topographic factors that cause instability of CEWQ parameters and conclude with some suggestions for watershed managers to bring sustainability in freshwater bodies.

Nonlinear climate sensitivity and its implications for future greenhouse warming.

PubMed

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-11-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing-referred to as specific equilibrium climate sensitivity ( S )-is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth's future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.

Nonlinear climate sensitivity and its implications for future greenhouse warming

PubMed Central

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-01-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections. PMID:28861462

Sphagnum-dwelling testate amoebae in subarctic bogs are more sensitive to soil warming in the growing season than in winter: the results of eight-year field climate manipulations.

PubMed

Tsyganov, Andrey N; Aerts, Rien; Nijs, Ivan; Cornelissen, Johannes H C; Beyens, Louis

2012-05-01

Sphagnum-dwelling testate amoebae are widely used in paleoclimate reconstructions as a proxy for climate-induced changes in bogs. However, the sensitivity of proxies to seasonal climate components is an important issue when interpreting proxy records. Here, we studied the effects of summer warming, winter snow addition solely and winter snow addition together with spring warming on testate amoeba assemblages after eight years of experimental field climate manipulations. All manipulations were accomplished using open top chambers in a dry blanket bog located in the sub-Arctic (Abisko, Sweden). We estimated sensitivity of abundance, diversity and assemblage structure of living and empty shell assemblages of testate amoebae in the living and decaying layers of Sphagnum. Our results show that, in a sub-arctic climate, testate amoebae are more sensitive to climate changes in the growing season than in winter. Summer warming reduced species richness and shifted assemblage composition towards predominance of xerophilous species for the living and empty shell assemblages in both layers. The higher soil temperatures during the growing season also decreased abundance of empty shells in both layers hinting at a possible increase in their decomposition rates. Thus, although possible effects of climate changes on preservation of empty shells should always be taken into account, species diversity and structure of testate amoeba assemblages in dry subarctic bogs are sensitive proxies for climatic changes during the growing season. Copyright © 2011 Elsevier GmbH. All rights reserved.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

PubMed

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

PubMed Central

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. PMID:26901763

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

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

Strzepek, K.; Neumann, Jim; Smith, Joel

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

DOE PAGES

Strzepek, K.; Neumann, Jim; Smith, Joel; ...

2014-11-29

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

microclim: Global estimates of hourly microclimate based on long-term monthly climate averages

PubMed Central

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms. PMID:25977764

Microclim: Global estimates of hourly microclimate based on long-term monthly climate averages.

PubMed

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms.

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

PubMed Central

Selmants, Paul C.; Moreno, Alvaro; Running, Steve W.; Giardina, Christian P.

2017-01-01

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales. PMID:28886187

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

USGS Publications Warehouse

Kimball, Heather L.; Selmants, Paul; Moreno, Alvaro; Running Steve W,; Giardina, Christian P.

2017-01-01

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems.

PubMed

Kimball, Heather L; Selmants, Paul C; Moreno, Alvaro; Running, Steve W; Giardina, Christian P

2017-01-01

Gross primary production (GPP) is the Earth's largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.

Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two GFDL Climate Models

NASA Astrophysics Data System (ADS)

Paynter, D.; Frölicher, T. L.; Horowitz, L. W.; Silvers, L. G.

2018-02-01

Equilibrium climate sensitivity (ECS), defined as the long-term change in global mean surface air temperature in response to doubling atmospheric CO2, is usually computed from short atmospheric simulations over a mixed layer ocean, or inferred using a linear regression over a short-time period of adjustment. We report the actual ECS from multimillenial simulations of two Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models (GCMs), ESM2M, and CM3 of 3.3 K and 4.8 K, respectively. Both values are 1 K higher than estimates for the same models reported in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change obtained by regressing the Earth's energy imbalance against temperature. This underestimate is mainly due to changes in the climate feedback parameter (-α) within the first century after atmospheric CO2 has stabilized. For both GCMs it is possible to estimate ECS with linear regression to within 0.3 K by increasing CO2 at 1% per year to doubling and using years 51-350 after CO2 is constant. We show that changes in -α differ between the two GCMs and are strongly tied to the changes in both vertical velocity at 500 hPa (ω500) and estimated inversion strength that the GCMs experience during the progression toward the equilibrium. This suggests that while cloud physics parametrizations are important for determining the strength of -α, the substantially different atmospheric state resulting from a changed sea surface temperature pattern may be of equal importance.

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

NASA Astrophysics Data System (ADS)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

Delays in Reducing Waterborne and Water-related Infectious Diseases in China under Climate Change

DOE PAGES

Hodges, Maggie; Belle, Jessica; Carlton, Elizabeth; ...

2014-11-02

Despite China’s rapid progress improving water, sanitation and hygiene (WSH) infrastructure and access, in 2011, 471 million people lacked access to improved sanitation, and 401 million people lacked access to household piped water. Infectious diseases are sensitive to changes in climate, particularly temperature, and WSH conditions. To explore possible impacts of climate change on these diseases in China in 2020 and 2030, we coupled estimates of the temperature sensitivity of diarrheal disease and three vector-borne diseases, temperature projections from global climate models using four emissions pathways, WSH-infrastructure development scenarios and projected demographic changes. By 2030, the projected impacts would delaymore » China’s historically rapid progress toward reducing the burden of WSH-attributable infectious disease by 8-85 months. This developmental delay provides a key summary measure of the impact of climate change in China, and in other societies undergoing rapid social, economic, and environmental change.« less

Delays in Reducing Waterborne and Water-related Infectious Diseases in China under Climate Change

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

Hodges, Maggie; Belle, Jessica; Carlton, Elizabeth

Despite China’s rapid progress improving water, sanitation and hygiene (WSH) infrastructure and access, in 2011, 471 million people lacked access to improved sanitation, and 401 million people lacked access to household piped water. Infectious diseases are sensitive to changes in climate, particularly temperature, and WSH conditions. To explore possible impacts of climate change on these diseases in China in 2020 and 2030, we coupled estimates of the temperature sensitivity of diarrheal disease and three vector-borne diseases, temperature projections from global climate models using four emissions pathways, WSH-infrastructure development scenarios and projected demographic changes. By 2030, the projected impacts would delaymore » China’s historically rapid progress toward reducing the burden of WSH-attributable infectious disease by 8-85 months. This developmental delay provides a key summary measure of the impact of climate change in China, and in other societies undergoing rapid social, economic, and environmental change.« less

Excessive Heat and Respiratory Hospitalizations in New York State: Estimating Current and Future Public Health Burden Related to Climate Change

PubMed Central

Hsu, Wan-Hsiang; Van Zutphen, Alissa R.; Saha, Shubhayu; Luber, George; Hwang, Syni-An

2012-01-01

Background: Although many climate-sensitive environmental exposures are related to mortality and morbidity, there is a paucity of estimates of the public health burden attributable to climate change. Objective: We estimated the excess current and future public health impacts related to respiratory hospitalizations attributable to extreme heat in summer in New York State (NYS) overall, its geographic regions, and across different demographic strata. Methods: On the basis of threshold temperature and percent risk changes identified from our study in NYS, we estimated recent and future attributable risks related to extreme heat due to climate change using the global climate model with various climate scenarios. We estimated effects of extreme high apparent temperature in summer on respiratory admissions, days hospitalized, direct hospitalization costs, and lost productivity from days hospitalized after adjusting for inflation. Results: The estimated respiratory disease burden attributable to extreme heat at baseline (1991–2004) in NYS was 100 hospital admissions, US$644,069 in direct hospitalization costs, and 616 days of hospitalization per year. Projections for 2080–2099 based on three different climate scenarios ranged from 206–607 excess hospital admissions, US$26–$76 million in hospitalization costs, and 1,299–3,744 days of hospitalization per year. Estimated impacts varied by geographic region and population demographics. Conclusions: We estimated that excess respiratory admissions in NYS due to excessive heat would be 2 to 6 times higher in 2080–2099 than in 1991–2004. When combined with other heat-associated diseases and mortality, the potential public health burden associated with global warming could be substantial. PMID:22922791

What drives uncertainty in model diagnoses of carbon dynamics in southern US forests: climate, vegetation, disturbance, or model parameters?

NASA Astrophysics Data System (ADS)

Zhou, Y.; Gu, H.; Williams, C. A.

2017-12-01

Results from terrestrial carbon cycle models have multiple sources of uncertainty, each with its behavior and range. Their relative importance and how they combine has received little attention. This study investigates how various sources of uncertainty propagate, temporally and spatially, in CASA-Disturbance (CASA-D). CASA-D simulates the impact of climatic forcing and disturbance legacies on forest carbon dynamics with the following steps. Firstly, we infer annual growth and mortality rates from measured biomass stocks (FIA) over time and disturbance (e.g., fire, harvest, bark beetle) to represent annual post-disturbance carbon fluxes trajectories across forest types and site productivity settings. Then, annual carbon fluxes are estimated from these trajectories by using time since disturbance which is inferred from biomass (NBCD 2000) and disturbance maps (NAFD, MTBS and ADS). Finally, we apply monthly climatic scalars derived from default CASA to temporally distribute annual carbon fluxes to each month. This study assesses carbon flux uncertainty from two sources: driving data including climatic and forest biomass inputs, and three most sensitive parameters in CASA-D including maximum light use efficiency, temperature sensitivity of soil respiration (Q10) and optimum temperature identified by using EFAST (Extended Fourier Amplitude Sensitivity Testing). We quantify model uncertainties from each, and report their relative importance in estimating forest carbon sink/source in southeast United States from 2003 to 2010.

Seasonal hydrologic responses to climate change in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Vano, Julie A.; Nijssen, Bart; Lettenmaier, Dennis P.

2015-04-01

Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land-surface hydrology model applied at 1/16° latitude-longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC-8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin-specific transfer functions to estimate future changes in long-term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first-order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations.

Tropical Ocean Evaporation/SST Sensitivity and It's Link to Water and Energy Budget Variations During ENSO

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Marshall, Susan; Oglesby, Robert; Roads, John; Sohn, Byung-Ju; Arnold, James E. (Technical Monitor)

2001-01-01

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system - changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus primarily on interannual variations of ocean evaporative fluxes and their significance for coupled water and energy cycles within the tropical climate system. In particular, we use both the da Silva estimates of surface fluxes (based on the Comprehensive Ocean Atmosphere Data Set, COADS) and numerical simulations from several global climate models to examine evaporation sensitivity to perturbations in SST associated with warm and cold ENSO events. The specific questions we address are as follows: (1) What recurring patterns of surface wind and humidity anomalies are present during ENSO and how do they combine to yield systematic evaporation anomalies?, (2) What is the resulting tropical ocean mean evaporation-SST sensitivity associated with this climate perturbation?, and (3) What role does this evaporation play in tropical heat and water balance over tropical oceanic regions? We use the da Silva ocean flux data to identify composite structure of departures of latent heat flux from climatology. We also show how these patterns arise out of associated wind and humidity anomaly distributions. Our preliminary work shows that evaporation sensitivity estimates from the da Silva / COADS data, computed for the tropical oceans (30 degrees N/S) are in the neighborhood of 5 to 6 W/square m K. Model estimates are also quite close to this figure. This rate is only slightly less than a rate corresponding to constant relative humidity; however, substantial regional departures from constant relative humidity are present. These patterns are robust and we relate the associated wind and humidity fluctuations noted in previous investigations to the derived evaporation anomalies. Finally, these results are interpreted with other data from the Earth radiation Budget Experiment (ERBE), Global Precipitation Climatology Project (GPCP) and NASA's Surface Radiation Budget (SRB) data set to characterize the tropical energetics of ENSO-related climate variability.

The role of climate in the global patterns of ecosystem carbon turnover rates - contrasts between data and models

NASA Astrophysics Data System (ADS)

Carvalhais, N.; Forkel, M.; Khomik, M.; Bellarby, J.; Migliavacca, M.; Thurner, M.; Beer, C.; Jung, M.; Mu, M.; Randerson, J. T.; Saatchi, S. S.; Santoro, M.; Reichstein, M.

2012-12-01

The turnover rates of carbon in terrestrial ecosystems and their sensitivity to climate are instrumental properties for diagnosing the interannual variability and forecasting trends of biogeochemical processes and carbon-cycle-climate feedbacks. We propose to globally look at the spatial distribution of turnover rates of carbon to explore the association between bioclimatic regimes and the rates at which carbon cycles in terrestrial ecosystems. Based on data-driven approaches of ecosystem carbon fluxes and data-based estimates of ecosystem carbon stocks it is possible to build fully observationally supported diagnostics. These data driven diagnostics support the benchmarking of CMIP5 model outputs (Coupled Model Intercomparison Project Phase 5) with observationally based estimates. The models' performance is addressed by confronting spatial patterns of carbon fluxes and stocks with data, as well as the global and regional sensitivities of turnover rates to climate. Our results show strong latitudinal gradients globally, mostly controlled by temperature, which are not always paralleled by CMIP5 simulations. In northern colder regions is also where the largest difference in temperature sensitivity between models and data occurs. Interestingly, there seem to be two different statistical populations in the data (some with high, others with low apparent temperature sensitivity of carbon turnover rates), where the different models only seem to describe either one or the other population. Additionally, the comparisons within bioclimatic classes can even show opposite patterns between turnover rates and temperature in water limited regions. Overall, our analysis emphasizes the role of finding patterns and intrinsic properties instead of plain magnitudes of fluxes for diagnosing the sensitivities of terrestrial biogeochemical cycles to climate. Further, our regional analysis suggests a significant gap in addressing the partial influence of water in the ecosystem carbon turnover rates especially in very cold or water limited regions.

Empirically Estimating the Potential for Farm-Level Adaptation to Climate Change in Western European Agriculture

NASA Astrophysics Data System (ADS)

Moore, F. C.; Lobell, D. B.

2013-12-01

Agriculture is one of the economic sectors most exposed to climate change and estimating the sensitivity of food production to these changes is critical for determining the severity of climate change impacts and for informing both adaptation and mitigation policy. While climate change might have adverse effects in many areas, it has long been recognized that farmers have a suite of adaptation options at their disposal including, inter alia, changing planting date, varieties, crops, or the mix and quantity of inputs applied. These adaptations may significantly reduce the adverse impacts of climate change but the potential effectiveness of these options and the speed with which farmers will adopt them remain uncertain. We estimate the sensitivity of crop yields and farm profits in western Europe to climate change with and without the adoption of on-farm adaptations. We use cross-sectional variation across farms to define the long-run response function that includes adaptation and inter-annual variation within farms to define the short-run response function without adaptation. The difference between these can be interpreted as the potential for adaptation. We find that future warming will have a large adverse impact on wheat and barley yields and that adaptation will only be able to mitigate a small fraction of this. Maize, oilseed and sugarbeet yields are more modestly affected and adaptation is more effective for these crops. Farm profits could increase slightly under moderate amounts of warming if adaptations are adopted but will decline in the absence of adaptation. A decomposition of variance gives the relative importance of different sources of uncertainty in projections of climate change impacts. We find that in most cases uncertainty over future adaptation pathways (whether farmers will or will not adopt beneficial adaptations) is the most important source of uncertainty in projecting the effect of temperature changes on crop yields and farm profits. This source of uncertainty dominates both uncertainty over temperature projections (climate uncertainty) and uncertainty over how sensitive crops or profits are to changes in temperature (response uncertainty). Therefore, constraining how quickly farmers are likely to adapt will be essential for improving our understanding of how climate change will affect food production over the next few decades.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

PubMed

Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-08-16

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska.

PubMed

Genet, Hélène; He, Yujie; Lyu, Zhou; McGuire, A David; Zhuang, Qianlai; Clein, Joy; D'Amore, David; Bennett, Alec; Breen, Amy; Biles, Frances; Euskirchen, Eugénie S; Johnson, Kristofer; Kurkowski, Tom; Kushch Schroder, Svetlana; Pastick, Neal; Rupp, T Scott; Wylie, Bruce; Zhang, Yujin; Zhou, Xiaoping; Zhu, Zhiliang

2018-01-01

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km 2 ), are influencing and will influence state-wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO 2 ), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950-2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (-6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010-2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO 2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO 2 , we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO 2 increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO 2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO 2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional. © 2017 by the Ecological Society of America.

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska

USGS Publications Warehouse

Genet, Hélène; He, Yujie; Lyu, Zhou; McGuire, A. David; Zhuang, Qianlai; Clein, Joy S.; D'Amore, David; Bennett, Alec; Breen, Amy; Biles, Frances; Euskirchen, Eugénie S.; Johnson, Kristofer; Kurkowski, Tom; Schroder, Svetlana (Kushch); Pastick, Neal J.; Rupp, T. Scott; Wylie, Bruce K.; Zhang, Yujin; Zhou, Xiaoping; Zhu, Zhiliang

2018-01-01

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km2), are influencing and will influence state‐wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO2), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950–2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (−6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010–2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO2, we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO2increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.

On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect

NASA Astrophysics Data System (ADS)

Rothenberg, Daniel; Avramov, Alexander; Wang, Chien

2018-06-01

Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m-2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology.

Temperature impacts on economic growth warrant stringent mitigation policy

NASA Astrophysics Data System (ADS)

Moore, Frances C.; Diaz, Delavane B.

2015-02-01

Integrated assessment models compare the costs of greenhouse gas mitigation with damages from climate change to evaluate the social welfare implications of climate policy proposals and inform optimal emissions reduction trajectories. However, these models have been criticized for lacking a strong empirical basis for their damage functions, which do little to alter assumptions of sustained gross domestic product (GDP) growth, even under extreme temperature scenarios. We implement empirical estimates of temperature effects on GDP growth rates in the DICE model through two pathways, total factor productivity growth and capital depreciation. This damage specification, even under optimistic adaptation assumptions, substantially slows GDP growth in poor regions but has more modest effects in rich countries. Optimal climate policy in this model stabilizes global temperature change below 2 °C by eliminating emissions in the near future and implies a social cost of carbon several times larger than previous estimates. A sensitivity analysis shows that the magnitude of climate change impacts on economic growth, the rate of adaptation, and the dynamic interaction between damages and GDP are three critical uncertainties requiring further research. In particular, optimal mitigation rates are much lower if countries become less sensitive to climate change impacts as they develop, making this a major source of uncertainty and an important subject for future research.

Climate simulations and projections with a super-parameterized climate model

DOE PAGES

Stan, Cristiana; Xu, Li

2014-07-01

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less

Probabilistic estimates of drought impacts on agricultural production

NASA Astrophysics Data System (ADS)

Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

2017-08-01

Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

High-resolution pCO2 reconstruction across the early Cenozoic greenhouse and late Cenozoic icehouse climates

NASA Astrophysics Data System (ADS)

Cui, Y.; Schubert, B.

2016-12-01

Historical data and ice core records provide the best-constrained data on global temperatures and atmospheric carbon dioxide concentrations (pCO2), which can be used to calculate short-term estimates of climate sensitivity. These data, however, may not be representative of longer timescales and represent a period of Earth history when pCO2 and global temperatures were relatively low; recent work suggests that climate sensitivity may change under different climate states and timescales. Here we present a new high-resolution pCO2 reconstruction for the early (65 to 50 Ma) and late (30 to 0 Ma) Cenozoic using a proxy based on changes in carbon isotope fractionation in C3 land plants. This work uses widely available carbon isotope data from various terrestrial organic substrates to produce a nearly continuous record of pCO2. This record identifies both large-scale trends (e.g., the early Cenozoic is characterized by higher pCO2 than the late Cenozoic), as well as transient, highly elevated pCO2 during the early Eocene hyperthermals. We discuss the uncertainties associated with this new pCO2 reconstruction, which include the effects of precipitation, plant community shifts, and source effects on the δ13C record. Additionally, uncertainty associated with the correlation in time between δ13C estimates of atmospheric CO2 and the terrestrial δ13C of organic matter is included in the error propagation. Comparison of the new pCO2 record to existing global average temperature records based on the δ18O value of well-preserved marine foraminifera can yield new insight into Earth system climate sensitivity across a wide range of climate states and timescales.

Applying simple water-energy balance frameworks to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2012-08-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2012) introduced the climate change impact hypothesis (CCUW), which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (the Budyko approach of Roderick and Farquhar, 2011, and the CCUW) with data of more than 400 basins distributed over the continental United States. We first estimate the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949 to 2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect to changes in climate. Next, we test the ability of both approaches to predict climate impacts on streamflow by splitting the data into two periods. We (i) analyse the long-term average changes in hydro-climatology and (ii) derive a statistical classification of potential climate and basin change impacts based on the significance of observed changes in runoff, precipitation and potential evapotranspiration. Then we (iii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iv) evaluate the predictions by (v) using the statistical classification scheme and (vi) a conceptual approach to separate the impacts of changes in climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to assess the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow of the majority of basins in the US is dominated by an increase in precipitation. It is further evident that impacts of changes in basin characteristics appear simultaneously with climate changes. There are coherent spatial patterns with catchments where basin changes compensate for climatic changes being dominant in the western and central parts of the US. A hot spot of basin changes leading to excessive runoff is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as much as the observed change signal. Although the CCUW and the Budyko approach yield similar predictions for most basins, the data of water-limited basins support the Budyko framework rather than the CCUW approach, which is known to be invalid under limiting climatic conditions.

Commensurate comparisons of models with energy budget observations reveal consistent climate sensitivities

NASA Astrophysics Data System (ADS)

Armour, K.

2017-12-01

Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are consistently in good agreement with values of ICS inferred from global energy budget constraints. This suggests that the current generation of coupled climate models are not overly sensitive. However, since global energy budget observations do not constrain ECS, it is less certain whether model ECS values are realistic.

Burden of climate change on malaria mortality.

PubMed

Dasgupta, Shouro

2018-06-01

In 2016, an estimated 445,000 deaths and 216 million cases of malaria occurred worldwide, while 70% of the deaths occurred in children under five years old. Changes in climatic exposures such as temperature and precipitation make malaria one of the most climate sensitive outcomes. Using a global malaria mortality dataset for 105 countries between 1980 and 2010, we find a non-linear relationship between temperature and malaria mortality and estimate that the global optimal temperature threshold beyond which all-age malaria mortality increases is 20.8 °C, while in the case of child mortality; a significantly lower optimum temperature of 19.3° is estimated. Our results also suggest that this optimal temperature is 28.4 °C and 26.3 °C in Africa and Asia, respectively - the continents where malaria is most prevalent. Furthermore, we estimate that child mortality (ages 0-4) is likely to increase by up to 20% in some areas due to climate change by the end of the 21st century. Copyright © 2018 Elsevier GmbH. All rights reserved.

An Estimation of the Climatic Effects of Stratospheric Ozone Losses during the 1980s. Appendix K

NASA Technical Reports Server (NTRS)

MacKay, Robert M.; Ko, Malcolm K. W.; Shia, Run-Lie; Yang, Yajaing; Zhou, Shuntai; Molnar, Gyula

1997-01-01

In order to study the potential climatic effects of the ozone hole more directly and to assess the validity of previous lower resolution model results, the latest high spatial resolution version of the Atmospheric and Environmental Research, Inc., seasonal radiative dynamical climate model is used to simulate the climatic effects of ozone changes relative to the other greenhouse gases. The steady-state climatic effect of a sustained decrease in lower stratospheric ozone, similar in magnitude to the observed 1979-90 decrease, is estimated by comparing three steady-state climate simulations: 1) 1979 greenhouse gas concentrations and 1979 ozone, II) 1990 greenhouse gas concentrations with 1979 ozone, and III) 1990 greenhouse gas concentrations with 1990 ozone. The simulated increase in surface air temperature resulting from nonozone greenhouse gases is 0.272 K. When changes in lower stratospheric ozone are included, the greenhouse warming is 0.165 K, which is approximately 39% lower than when ozone is fixed at the 1979 concentrations. Ozone perturbations at high latitudes result in a cooling of the surface-troposphere system that is greater (by a factor of 2.8) than that estimated from the change in radiative forcing resulting from ozone depiction and the model's 2 x CO, climate sensitivity. The results suggest that changes in meridional heat transport from low to high latitudes combined with the decrease in the infrared opacity of the lower stratosphere are very important in determining the steady-state response to high latitude ozone losses. The 39% compensation in greenhouse warming resulting from lower stratospheric ozone losses is also larger than the 28% compensation simulated previously by the lower resolution model. The higher resolution model is able to resolve the high latitude features of the assumed ozone perturbation, which are important in determining the overall climate sensitivity to these perturbations.

Using Impact-Relevant Sensitivities to Efficiently Evaluate and Select Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Vano, J. A.; Kim, J. B.; Rupp, D. E.; Mote, P.

2014-12-01

We outline an efficient approach to help researchers and natural resource managers more effectively use global climate model information in their long-term planning. The approach provides an estimate of the magnitude of change of a particular impact (e.g., summertime streamflow) from a large ensemble of climate change projections prior to detailed analysis. These estimates provide both qualitative information as an end unto itself (e.g., the distribution of future changes between emissions scenarios for the specific impact) and a judicious, defensible evaluation structure that can be used to qualitatively select a sub-set of climate models for further analysis. More specifically, the evaluation identifies global climate model scenarios that both (1) span the range of possible futures for the variable/s most important to the impact under investigation, and (2) come from global climate models that adequately simulate historical climate, providing plausible results for the future climate in the region of interest. To identify how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an impact variable (e.g., streamflow magnitude, vegetation carbon) responds locally to projected regional temperature and precipitation changes. We demonstrate our technique over the Pacific Northwest, focusing on two types of impacts each in three distinct geographic settings: (a) changes in streamflow magnitudes in critical seasons for water management in the Willamette, Yakima, and Upper Columbia River basins; and (b) changes in annual vegetation carbon in the Oregon and Washington Coast Ranges, Western Cascades, and Columbia Basin ecoregions.

Climate Change Vulnerability Assessment for Idaho National Laboratory

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

Christopher P. Ischay; Ernest L. Fossum; Polly C. Buotte

2014-10-01

The University of Idaho (UI) was asked to participate in the development of a climate change vulnerability assessment for Idaho National Laboratory (INL). This report describes the outcome of that assessment. The climate change happening now, due in large part to human activities, is expected to continue in the future. UI and INL used a common framework for assessing vulnerability that considers exposure (future climate change), sensitivity (system or component responses to climate), impact (exposure combined with sensitivity), and adaptive capacity (capability of INL to modify operations to minimize climate change impacts) to assess vulnerability. Analyses of climate change (exposure)more » revealed that warming that is ongoing at INL will continue in the coming decades, with increased warming in later decades and under scenarios of greater greenhouse gas emissions. Projections of precipitation are more uncertain, with multi model means exhibiting somewhat wetter conditions and more wet days per year. Additional impacts relevant to INL include estimates of more burned area and increased evaporation and transpiration, leading to reduced soil moisture and plant growth.« less

Biotic and Climatic Velocity Identify Contrasting Areas of Vulnerability to Climate Change.

PubMed

Carroll, Carlos; Lawler, Joshua J; Roberts, David R; Hamann, Andreas

2015-01-01

Metrics that synthesize the complex effects of climate change are essential tools for mapping future threats to biodiversity and predicting which species are likely to adapt in place to new climatic conditions, disperse and establish in areas with newly suitable climate, or face the prospect of extirpation. The most commonly used of such metrics is the velocity of climate change, which estimates the speed at which species must migrate over the earth's surface to maintain constant climatic conditions. However, "analog-based" velocities, which represent the actual distance to where analogous climates will be found in the future, may provide contrasting results to the more common form of velocity based on local climate gradients. Additionally, whereas climatic velocity reflects the exposure of organisms to climate change, resultant biotic effects are dependent on the sensitivity of individual species as reflected in part by their climatic niche width. This has motivated development of biotic velocity, a metric which uses data on projected species range shifts to estimate the velocity at which species must move to track their climatic niche. We calculated climatic and biotic velocity for the Western Hemisphere for 1961-2100, and applied the results to example ecological and conservation planning questions, to demonstrate the potential of such analog-based metrics to provide information on broad-scale patterns of exposure and sensitivity. Geographic patterns of biotic velocity for 2954 species of birds, mammals, and amphibians differed from climatic velocity in north temperate and boreal regions. However, both biotic and climatic velocities were greatest at low latitudes, implying that threats to equatorial species arise from both the future magnitude of climatic velocities and the narrow climatic tolerances of species in these regions, which currently experience low seasonal and interannual climatic variability. Biotic and climatic velocity, by approximating lower and upper bounds on migration rates, can inform conservation of species and locally-adapted populations, respectively, and in combination with backward velocity, a function of distance to a source of colonizers adapted to a site's future climate, can facilitate conservation of diversity at multiple scales in the face of climate change.

Biotic and Climatic Velocity Identify Contrasting Areas of Vulnerability to Climate Change

PubMed Central

Carroll, Carlos; Lawler, Joshua J.; Roberts, David R.; Hamann, Andreas

2015-01-01

Metrics that synthesize the complex effects of climate change are essential tools for mapping future threats to biodiversity and predicting which species are likely to adapt in place to new climatic conditions, disperse and establish in areas with newly suitable climate, or face the prospect of extirpation. The most commonly used of such metrics is the velocity of climate change, which estimates the speed at which species must migrate over the earth’s surface to maintain constant climatic conditions. However, “analog-based” velocities, which represent the actual distance to where analogous climates will be found in the future, may provide contrasting results to the more common form of velocity based on local climate gradients. Additionally, whereas climatic velocity reflects the exposure of organisms to climate change, resultant biotic effects are dependent on the sensitivity of individual species as reflected in part by their climatic niche width. This has motivated development of biotic velocity, a metric which uses data on projected species range shifts to estimate the velocity at which species must move to track their climatic niche. We calculated climatic and biotic velocity for the Western Hemisphere for 1961–2100, and applied the results to example ecological and conservation planning questions, to demonstrate the potential of such analog-based metrics to provide information on broad-scale patterns of exposure and sensitivity. Geographic patterns of biotic velocity for 2954 species of birds, mammals, and amphibians differed from climatic velocity in north temperate and boreal regions. However, both biotic and climatic velocities were greatest at low latitudes, implying that threats to equatorial species arise from both the future magnitude of climatic velocities and the narrow climatic tolerances of species in these regions, which currently experience low seasonal and interannual climatic variability. Biotic and climatic velocity, by approximating lower and upper bounds on migration rates, can inform conservation of species and locally-adapted populations, respectively, and in combination with backward velocity, a function of distance to a source of colonizers adapted to a site’s future climate, can facilitate conservation of diversity at multiple scales in the face of climate change. PMID:26466364

Quantifying global warming from the retreat of glaciers.

PubMed

Oerlemans, J

1994-04-08

Records of glacier fluctuations compiled by the World Glacier Monitoring Service can be used to derive an independent estimate of global warming during the last 100 years. Records of different glaciers are made comparable by a two-step scaling procedure: one allowing for differences in glacier geometry, the other for differences in climate sensitivity. The retreat of glaciers during the last 100 years appears to be coherent over the globe. On the basis of modeling of the climate sensitivity of glaciers, the observed glacier retreat can be explained by a linear warming trend of 0.66 kelvin per century.

Climatic vulnerability of the world’s freshwater and marine fishes

NASA Astrophysics Data System (ADS)

Comte, Lise; Olden, Julian D.

2017-10-01

Climate change is a mounting threat to biological diversity, compromising ecosystem structure and function, and undermining the delivery of essential services worldwide. As the magnitude and speed of climate change accelerates, greater understanding of the taxonomy and geography of climatic vulnerability is critical to guide effective conservation action. However, many uncertainties remain regarding the degree and variability of climatic risk within entire clades and across vast ecosystem boundaries. Here we integrate physiological estimates of thermal sensitivity for 2,960 ray-finned fishes with future climatic exposure, and demonstrate that global patterns of vulnerability differ substantially between freshwater and marine realms. Our results suggest that climatic vulnerability for freshwater faunas will be predominantly determined by elevated levels of climatic exposure predicted for the Northern Hemisphere, whereas marine faunas in the tropics will be the most at risk, reflecting their higher intrinsic sensitivity. Spatial overlap between areas of high physiological risk and high human impacts, together with evidence of low past rates of evolution in upper thermal tolerance, highlights the urgency of global conservation actions and policy initiatives if harmful climate effects on the world’s fishes are to be mitigated in the future.

Potential effect of climate change on malaria transmission in Africa.

PubMed

Tanser, Frank C; Sharp, Brian; le Sueur, David

2003-11-29

Climate change is likely to affect transmission of vector-borne diseases such as malaria. We quantitatively estimated current malaria exposure and assessed the potential effect of projected climate scenarios on malaria transmission. We produced a spatiotemporally validated (against 3791 parasite surveys) model of Plasmodium falciparum malaria transmission in Africa. Using different climate scenarios from the Hadley Centre global climate model (HAD CM3) climate experiments, we projected the potential effect of climate change on transmission patterns. Our model showed sensitivity and specificity of 63% and 96%, respectively (within 1 month temporal accuracy), when compared with the parasite surveys. We estimate that on average there are 3.1 billion person-months of exposure (445 million people exposed) in Africa per year. The projected scenarios would estimate a 5-7% potential increase (mainly altitudinal) in malaria distribution with surprisingly little increase in the latitudinal extents of the disease by 2100. Of the overall potential increase (although transmission will decrease in some countries) of 16-28% in person-months of exposure (assuming a constant population), a large proportion will be seen in areas of existing transmission. The effect of projected climate change indicates that a prolonged transmission season is as important as geographical expansion in correct assessment of the effect of changes in transmission patterns. Our model constitutes a valid baseline against which climate scenarios can be assessed and interventions planned.

Estimation of root zone storage capacity at the catchment scale using improved Mass Curve Technique

NASA Astrophysics Data System (ADS)

Zhao, Jie; Xu, Zongxue; Singh, Vijay P.

2016-09-01

The root zone storage capacity (Sr) greatly influences runoff generation, soil water movement, and vegetation growth and is hence an important variable for ecological and hydrological modelling. However, due to the great heterogeneity in soil texture and structure, there seems to be no effective approach to monitor or estimate Sr at the catchment scale presently. To fill the gap, in this study the Mass Curve Technique (MCT) was improved by incorporating a snowmelt module for the estimation of Sr at the catchment scale in different climatic regions. The "range of perturbation" method was also used to generate different scenarios for determining the sensitivity of the improved MCT-derived Sr to its influencing factors after the evaluation of plausibility of Sr derived from the improved MCT. Results can be showed as: (i) Sr estimates of different catchments varied greatly from ∼10 mm to ∼200 mm with the changes of climatic conditions and underlying surface characteristics. (ii) The improved MCT is a simple but powerful tool for the Sr estimation in different climatic regions of China, and incorporation of more catchments into Sr comparisons can further improve our knowledge on the variability of Sr. (iii) Variation of Sr values is an integrated consequence of variations in rainfall, snowmelt water and evapotranspiration. Sr values are most sensitive to variations in evapotranspiration of ecosystems. Besides, Sr values with a longer return period are more stable than those with a shorter return period when affected by fluctuations in its influencing factors.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Rural Nevada and climate change: vulnerability, beliefs, and risk perception.

PubMed

Safi, Ahmad Saleh; Smith, William James; Liu, Zhnongwei

2012-06-01

In this article, we present the results of a study investigating the influence of vulnerability to climate change as a function of physical vulnerability, sensitivity, and adaptive capacity on climate change risk perception. In 2008/2009, we surveyed Nevada ranchers and farmers to assess their climate change-related beliefs, and risk perceptions, political orientations, and socioeconomic characteristics. Ranchers' and farmers' sensitivity to climate change was measured through estimating the proportion of their household income originating from highly scarce water-dependent agriculture to the total income. Adaptive capacity was measured as a combination of the Social Status Index and the Poverty Index. Utilizing water availability and use, and population distribution GIS databases; we assessed water resource vulnerability in Nevada by zip code as an indicator of physical vulnerability to climate change. We performed correlation tests and multiple regression analyses to examine the impact of vulnerability and its three distinct components on risk perception. We find that vulnerability is not a significant determinant of risk perception. Physical vulnerability alone also does not impact risk perception. Both sensitivity and adaptive capacity increase risk perception. While age is not a significant determinant of it, gender plays an important role in shaping risk perception. Yet, general beliefs such as political orientations and climate change-specific beliefs such as believing in the anthropogenic causes of climate change and connecting the locally observed impacts (in this case drought) to climate change are the most prominent determinants of risk perception. © 2012 Society for Risk Analysis.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

PubMed Central

Hondula, David M.; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-01-01

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634 PMID:28885979

Comparative risk assessment of the burden of disease from climate change.

PubMed

Campbell-Lendrum, Diarmid; Woodruff, Rosalie

2006-12-01

The World Health Organization has developed standardized comparative risk assessment methods for estimating aggregate disease burdens attributable to different risk factors. These have been applied to existing and new models for a range of climate-sensitive diseases in order to estimate the effect of global climate change on current disease burdens and likely proportional changes in the future. The comparative risk assessment approach has been used to assess the health consequences of climate change worldwide, to inform decisions on mitigating greenhouse gas emissions, and in a regional assessment of the Oceania region in the Pacific Ocean to provide more location-specific information relevant to local mitigation and adaptation decisions. The approach places climate change within the same criteria for epidemiologic assessment as other health risks and accounts for the size of the burden of climate-sensitive diseases rather than just proportional change, which highlights the importance of small proportional changes in diseases such as diarrhea and malnutrition that cause a large burden. These exercises help clarify important knowledge gaps such as a relatively poor understanding of the role of nonclimatic factors (socioeconomic and other) that may modify future climatic influences and a lack of empiric evidence and methods for quantifying more complex climate-health relationships, which consequently are often excluded from consideration. These exercises highlight the need for risk assessment frameworks that make the best use of traditional epidemiologic methods and that also fully consider the specific characteristics of climate change. These include the longterm and uncertain nature of the exposure and the effects on multiple physical and biotic systems that have the potential for diverse and widespread effects, including high-impact events.

Sensitivity of the global submarine hydrate inventory to scenarios of future climate change

NASA Astrophysics Data System (ADS)

Hunter, S. J.; Goldobin, D. S.; Haywood, A. M.; Ridgwell, A.; Rees, J. G.

2013-04-01

The global submarine inventory of methane hydrate is thought to be considerable. The stability of marine hydrates is sensitive to changes in temperature and pressure and once destabilised, hydrates release methane into sediments and ocean and potentially into the atmosphere, creating a positive feedback with climate change. Here we present results from a multi-model study investigating how the methane hydrate inventory dynamically responds to different scenarios of future climate and sea level change. The results indicate that a warming-induced reduction is dominant even when assuming rather extreme rates of sea level rise (up to 20 mm yr-1) under moderate warming scenarios (RCP 4.5). Over the next century modelled hydrate dissociation is focussed in the top ˜100m of Arctic and Subarctic sediments beneath <500m water depth. Predicted dissociation rates are particularly sensitive to the modelled vertical hydrate distribution within sediments. Under the worst case business-as-usual scenario (RCP 8.5), upper estimates of resulting global sea-floor methane fluxes could exceed estimates of natural global fluxes by 2100 (>30-50TgCH4yr-1), although subsequent oxidation in the water column could reduce peak atmospheric release rates to 0.75-1.4 Tg CH4 yr-1.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

Surface temperatures of the Mid-Pliocene North Atlantic Ocean: Implications for future climate

USGS Publications Warehouse

Dowsett, Harry J.; Chandler, Mark A.; Robinson, Marci M.

2009-01-01

The Mid-Pliocene is the most recent interval in the Earth's history to have experienced warming of the magnitude predicted for the second half of the twenty-first century and is, therefore, a possible analogue for future climate conditions. With continents basically in their current positions and atmospheric CO2 similar to early twenty-first century values, the cause of Mid-Pliocene warmth remains elusive. Understanding the behaviour of the North Atlantic Ocean during the Mid-Pliocene is integral to evaluating future climate scenarios owing to its role in deep water formation and its sensitivity to climate change. Under the framework of the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) sea surface reconstruction, we synthesize Mid-Pliocene North Atlantic studies by PRISM members and others, describing each region of the North Atlantic in terms of palaeoceanography. We then relate Mid-Pliocene sea surface conditions to expectations of future warming. The results of the data and climate model comparisons suggest that the North Atlantic is more sensitive to climate change than is suggested by climate model simulations, raising the concern that estimates of future climate change are conservative.

Climate and health impacts of clean cookstove implementation programs in Africa

NASA Astrophysics Data System (ADS)

Lacey, F.; Marais, E. A.; Wiedinmyer, C.; Coffey, E.; Muvandimwe, D.; Hannigan, M.; Henze, D. K.

2016-12-01

In Africa, 77% of the population (646 million people in 2010) use solid fuels as the main cooking source. These cooking methods are often inefficient and result in significant burdens to both climate and human health, particularly for women and children. In order to fully understand the impacts of clean cookstove implementation programs, a better understanding of the background concentrations of aerosols, aerosol precursors, and ozone precursors are needed, along with improved information on the changes in emissions from transitions to newer technologies. Through the use of the GEOS-Chem adjoint model, we have calculated species-specific climate and health sensitivities using a range of African emissions estimates including EDGAR-HTAP and a more recent improved emissions inventory, DICE-Africa. These sensitivities account for the spatial heterogeneity of emissions with respect to their impacts and allow for efficient estimation of the impacts of various clean cookstove implementation emissions scenarios that are based on laboratory and field measurements of emissions factors, along with realistic adoption and usage rates from field surveys. The resulting estimates of premature deaths and global surface temperature change are then aggregated to the national scale in order to provide policy makers with improved information regarding the implementation of clean cookstoves throughout continental Africa.

Economic Value of Narrowing the Uncertainty in Climate Sensitivity: Decadal Change in Shortwave Cloud Radiative Forcing and Low Cloud Feedback

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R. M.; Golub, A. A.; Mlynczak, M. G.; Young, D. F.; Baize, R. R.

2016-12-01

Several previous studies have been published on the economic value of narrowing the uncertainty in climate sensitivity (Cooke et al. 2015, Cooke et al. 2016, Hope, 2015). All three of these studies estimated roughly 10 Trillion U.S. dollars for the Net Present Value and Real Option Value at a discount rate of 3%. This discount rate is the nominal discount rate used in the U.S. Social Cost of Carbon Memo (2010). The Cooke et al studies approached this problem by examining advances in accuracy of global temperature measurements, while the Hope 2015 study did not address the type of observations required. While temperature change is related to climate sensitivity, large uncertainties of a factor of 3 in current anthropogenic radiative forcing (IPCC, 2013) would need to be solved for advanced decadal temperature change observations to assist the challenge of narrowing climate sensitivity. The present study takes a new approach by extending the Cooke et al. 2015,2016 papers to replace observations of temperature change to observations of decadal change in the effects of changing clouds on the Earths radiative energy balance, a measurement known as Cloud Radiative Forcing, or Cloud Radiative Effect. Decadal change in this observation is direclty related to the largest uncertainty in climate sensitivity which is cloud feedback from changing amount of low clouds, primarily low clouds over the world's oceans. As a result, decadal changes in shortwave cloud radiative forcing are more directly related to cloud feedback uncertainty which is the dominant uncertainty in climate sensitivity. This paper will show results for the new approach, and allow an examination of the sensitivity of economic value results to different observations used as a constraint on uncertainty in climate sensitivity. The analysis suggests roughly a doubling of economic value to 20 Trillion Net Present Value or Real Option Value at 3% discount rate. The higher economic value results from two changes: a larger increase in accuracy for SW cloud radiative forcing vs temperature, and from a lower confounding noise from natural variability in the cloud radiative forcing variable compared to temperature. In particular, global average temperature is much more sensitive to the climate noise of ENSO cycles.

Estimation of ozone dry deposition over Europe for the period 2071-2100

NASA Astrophysics Data System (ADS)

Komjáthy, Eszter; Gelybó, Györgyi; László Lagzi, István.; Mészáros, Róbert

2010-05-01

Ozone in the lower troposphere is a phytotoxic air pollutant which can cause injury to plant tissues, causing reduction in plant growth and productivity. In the last decades, several investigations have been carried out for the purpose to estimate ozone load over different surface types. At the same time, the changes of atmospheric variables as well as surface/vegetation parameters due to the global climate change could also strongly modify both temporal and spatial variations of ozone load over Europe. In this study, the possible effects of climate change on ozone deposition are analyzed. Using a sophisticated deposition model, ozone deposition was estimated on a regular grid over Europe for the period 2071-2100. Our aim is to determine the uncertainties and the possible degree of change in ozone deposition velocity as an important predictor of total ozone load using climate data from multiple climate models and runs. For these model calculations, results of the PRUDENCE (Predicting of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects) climate prediction project were used. As a first step, seasonal variations of ozone deposition over different vegetation types in case of different climate scenarios are presented in this study. Besides model calculations, in the frame of a sensitivity analyses, the effects of surface/vegetation parameters (e.g. leaf area index or stomatal resistance) on ozone deposition under a modified climate regime have also been analyzed.

An Oceanographic Perspective on the Charney Report

NASA Astrophysics Data System (ADS)

Wunsch, C. I.

2009-12-01

The Charney report (“Carbon Dioxide and Climate: A Scientific Assessment”, NRC 1979) was produced early in the discussions of oncoming climate change. Despite the somewhat crude understanding in 1979, its climate sensitivity estimates have proven remarkably stable over the past three decades. From the perspective of an oceanographic member of the Committee, the deliberations made it clear how primitive knowledge was of the ocean circulation at that time. The inability to say very much about how rapidly the ocean would take up carbon and heat led to the formulation and conduct of the World Ocean Circulation Experiment (WOCE) and associated programs such as the Joint Global Ocean Flux Study (JGOFS). Thus one less-obvious outcome of the Report was the various initiatives that brought a revolution in understanding of the ocean circulation and its climate impacts. That the range of uncertainty has not been reduced from its 1979 estimate is in part a consequence of the discovery of many elements influencing climate sensitivities which were only marginally perceived by the Committee. The climate system is far better understood today, but as the scientific cliché has it, we now know much more about what we don’t know.. One unexpected result of the Report was the insistence---by the G. W. Bush Administration---that since the uncertainty range had not diminished, the US global change research program had been a waste of money. The inference was dealt with in yet another, much longer, NRC report, “Thinking Strategically: The Appropriate Use of Metrics for the Climate Change Science Program.”

A multi-paradigm framework to assess the impacts of climate change on end-use energy demand.

PubMed

Nateghi, Roshanak; Mukherjee, Sayanti

2017-01-01

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.

A multi-paradigm framework to assess the impacts of climate change on end-use energy demand

PubMed Central

Nateghi, Roshanak

2017-01-01

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months. PMID:29155862

Comparing estimates of climate change impacts from process-based and statistical crop models

NASA Astrophysics Data System (ADS)

Lobell, David B.; Asseng, Senthold

2017-01-01

The potential impacts of climate change on crop productivity are of widespread interest to those concerned with addressing climate change and improving global food security. Two common approaches to assess these impacts are process-based simulation models, which attempt to represent key dynamic processes affecting crop yields, and statistical models, which estimate functional relationships between historical observations of weather and yields. Examples of both approaches are increasingly found in the scientific literature, although often published in different disciplinary journals. Here we compare published sensitivities to changes in temperature, precipitation, carbon dioxide (CO2), and ozone from each approach for the subset of crops, locations, and climate scenarios for which both have been applied. Despite a common perception that statistical models are more pessimistic, we find no systematic differences between the predicted sensitivities to warming from process-based and statistical models up to +2 °C, with limited evidence at higher levels of warming. For precipitation, there are many reasons why estimates could be expected to differ, but few estimates exist to develop robust comparisons, and precipitation changes are rarely the dominant factor for predicting impacts given the prominent role of temperature, CO2, and ozone changes. A common difference between process-based and statistical studies is that the former tend to include the effects of CO2 increases that accompany warming, whereas statistical models typically do not. Major needs moving forward include incorporating CO2 effects into statistical studies, improving both approaches’ treatment of ozone, and increasing the use of both methods within the same study. At the same time, those who fund or use crop model projections should understand that in the short-term, both approaches when done well are likely to provide similar estimates of warming impacts, with statistical models generally requiring fewer resources to produce robust estimates, especially when applied to crops beyond the major grains.

Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

PubMed

Cox, Peter M; Pearson, David; Booth, Ben B; Friedlingstein, Pierre; Huntingford, Chris; Jones, Chris D; Luke, Catherine M

2013-02-21

The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.

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

Waldhoff, Stephanie T.; Anthoff, David; Rose, Steven K.

We use FUND 3.8 to estimate the social cost of four greenhouse gases: carbon dioxide, methane, nitrous oxide, and sulphur hexafluoride emissions. The damage potential for each gas—the ratio of the social cost of the non-carbon dioxide greenhouse gas to the social cost of carbon dioxide—is also estimated. The damage potentials are compared to several metrics, focusing in particular on the global warming potentials, which are frequently used to measure the trade-off between gases in the form of carbon dioxide equivalents. We find that damage potentials could be significantly higher than global warming potentials. This finding implies that previous papersmore » have underestimated the relative importance of reducing non-carbon dioxide greenhouse gas emissions from an economic damage perspective. We show results for a range of sensitivity analyses: carbon dioxide fertilization on agriculture productivity, terrestrial feedbacks, climate sensitivity, discounting, equity weighting, and socioeconomic and emissions scenarios. The sensitivity of the results to carbon dioxide fertilization is a primary focus as it is an important element of climate change that has not been considered in much of the previous literature. We estimate that carbon dioxide fertilization has a large positive impact that reduces the social cost of carbon dioxide with a much smaller effect on the other greenhouse gases. As a result, our estimates of the damage potentials of methane and nitrous oxide are much higher compared to estimates that ignore carbon dioxide fertilization. As a result, our base estimates of the damage potential for methane and nitrous oxide that include carbon dioxide fertilization are twice their respective global warming potentials. Our base estimate of the damage potential of sulphur hexafluoride is similar to the one previous estimate, both almost three times the global warming potential.« less

Methods for estimating water consumption for thermoelectric power plants in the United States

USGS Publications Warehouse

Diehl, Timothy H.; Harris, Melissa; Murphy, Jennifer C.; Hutson, Susan S.; Ladd, David E.

2013-01-01

Heat budgets were constructed for the first four generation-type categories; data at solar thermal plants were insufficient for heat budgets. These heat budgets yielded estimates of the amount of heat transferred to the condenser. The ratio of evaporation to the heat discharged through the condenser was estimated using existing heat balance models that are sensitive to environmental data; this feature allows estimation of consumption under different climatic conditions. These two estimates were multiplied to yield an estimate of consumption at each power plant.

Snowmelt Pattern and Lake Ice Phenology around Tibetan Plateau Estimated from Enhanced Resolution Passive Microwave Data

NASA Astrophysics Data System (ADS)

Xiong, C.; Shi, J.; Wang, T.

2017-12-01

Snow and ice is very sensitive to the climate change. Rising air temperature will cause the snowmelt time change. In contrast, the change in snow state will have feedback on climate through snow albedo. The snow melt timing is also correlated with the associated runoff. Ice phenology describes the seasonal cycle of lake ice cover and includes freeze-up and breakup periods and ice cover duration, which is an important weather and climate indicator. It is also important for lake-atmosphere interactions and hydrological and ecological processes. The enhanced resolution (up to 3.125 km) passive microwave data is used to estimate the snowmelt pattern and lake ice phenology on and around Tibetan Plateau. The enhanced resolution makes the estimation of snowmelt and lake ice phenology in more spatial detail compared to previous 25 km gridded passive microwave data. New algorithm based on smooth filters and change point detection was developed to estimate the snowmelt and lake ice freeze-up and break-up timing. Spatial and temporal pattern of snowmelt and lake ice phonology are estimated. This study provides an objective evidence of climate change impact on the cryospheric system on Tibetan Plateau. The results show significant earlier snowmelt and lake ice break-up in some regions.

Climate catastrophes

NASA Astrophysics Data System (ADS)

Budyko, Mikhail

1999-05-01

Climate catastrophes, which many times occurred in the geological past, caused the extinction of large or small populations of animals and plants. Changes in the terrestrial and marine biota caused by the catastrophic climate changes undoubtedly resulted in considerable fluctuations in global carbon cycle and atmospheric gas composition. Primarily, carbon dioxide and other greenhouse gas contents were affected. The study of these catastrophes allows a conclusion that climate system is very sensitive to relatively small changes in climate-forcing factors (transparency of the atmosphere, changes in large glaciations, etc.). It is important to take this conclusion into account while estimating the possible consequences of now occurring anthropogenic warming caused by the increase in greenhouse gas concentration in the atmosphere.

Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits.

PubMed

Pawar, Samraat; Dell, Anthony I; Savage, Van M; Knies, Jennifer L

2016-02-01

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.

Economic Evidence on the Health Impacts of Climate Change in Europe

PubMed Central

Hutton, Guy; Menne, Bettina

2014-01-01

BACKGROUND In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. METHODS The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). RESULTS A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. CONCLUSIONS Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe. PMID:25452694

Economic evidence on the health impacts of climate change in europe.

PubMed

Hutton, Guy; Menne, Bettina

2014-01-01

In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe.

Opportunities for understanding of aerosol cloud interactions in the context of Marine Cloud Brightening Experiments

NASA Astrophysics Data System (ADS)

Rasch, Philip J.; Wood, Robert; Ackerman, Thomas P.

2017-04-01

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in radiative forcing of climate, confounding estimates of climate sensitivity to increases in greenhouse gases. Projections of future warming are also thus strongly dependent on estimates of aerosol effects on clouds. I will discuss the opportunities for improving estimates of aerosol effects on clouds from controlled field experiments where aerosol with well understood size, composition, amount, and injection altitude could be introduced to deliberately change cloud properties. This would allow scientific investigation to be performed in a manner much closer to a lab environment, and facilitate the use of models to predict cloud responses ahead of time, testing our understanding of aerosol cloud interactions.

Are landscapes buffered to high-frequency climate change? A comparison of sediment fluxes and depositional volumes in the Corinth rift, central Greece, over the past 130 kyrs

NASA Astrophysics Data System (ADS)

Watkins, Stephen E.; Whittaker, Alexander C.; Bell, Rebecca E.; McNeill, Lisa C.; Gawthope, Robert L.

2017-04-01

Sediment supply is a fundamental control on the stratigraphic record. However, a key question is the extent to which tectonics and climate affect sediment fluxes in time and space. To address this question, estimates of sediment fluxes must be compared with measured sediment volumes within a closed basin, for which the tectonic and climatic boundary conditions are constrained. The Corinth rift, Greece is one of the most actively extending basins on Earth, with modern day extension rates of up to 15 mm/yr. The Gulf of Corinth is a closed system and has periodically become a lake during marine lowstands over the late Pleistocene. We estimated suspended sediment fluxes through time for rivers draining into the Gulf of Corinth using an empirically-derived BQART method. WorldClim climate data, palaeoclimate models and palaeoclimate proxies were used to estimate discharges and temperatures over the last 130 ky. We used high-resolution 2D seismic surveys to interpret three seismic units over this period and we used this data to derive independent time series of basin sedimentary volumes to compare with our sediment input flux estimates. Our results predict total Holocene sediment fluxes into the Corinth Gulf of 20 km3, within a factor of 2 of the measured sediment volume in the central depocentres over this timescale. Sediment fluxes vary spatially around the Gulf, but imply catchment-averaged erosion rates of 0.2 to 0.4 mm/yr. Moreover, BQART predicted sediment fluxes and sedimentation rate measurements both indicate a 25% reduction during the last glacial period compared to the Holocene. At the last glacial maximum mean annual temperatures were lower by 5 degrees, although precipitation was similar, or lower, than present. Consequently, our results demonstrate that sediment export to the basin is sensitive to glacial-interglacial cycles. However, precipitation constraints alone are insufficient to understand sediment flux sensitivity to climate change.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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