Models of Solar Irradiance Variability and the Instrumental Temperature Record

NASA Technical Reports Server (NTRS)

Marcus, S. L.; Ghil, M.; Ide, K.

1998-01-01

The effects of decade-to-century (Dec-Cen) variations in total solar irradiance (TSI) on global mean surface temperature Ts during the pre-Pinatubo instrumental era (1854-1991) are studied by using two different proxies for TSI and a simplified version of the IPCC climate model.

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

Willner, Sven N.; Hartin, Corinne; Gieseke, Robert

Here, pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary productionmore » and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system. The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2.« less

New flux based dose-response relationships for ozone for European forest tree species.

PubMed

Büker, P; Feng, Z; Uddling, J; Briolat, A; Alonso, R; Braun, S; Elvira, S; Gerosa, G; Karlsson, P E; Le Thiec, D; Marzuoli, R; Mills, G; Oksanen, E; Wieser, G; Wilkinson, M; Emberson, L D

2015-11-01

To derive O3 dose-response relationships (DRR) for five European forest trees species and broadleaf deciduous and needleleaf tree plant functional types (PFTs), phytotoxic O3 doses (PODy) were related to biomass reductions. PODy was calculated using a stomatal flux model with a range of cut-off thresholds (y) indicative of varying detoxification capacities. Linear regression analysis showed that DRR for PFT and individual tree species differed in their robustness. A simplified parameterisation of the flux model was tested and showed that for most non-Mediterranean tree species, this simplified model led to similarly robust DRR as compared to a species- and climate region-specific parameterisation. Experimentally induced soil water stress was not found to substantially reduce PODy, mainly due to the short duration of soil water stress periods. This study validates the stomatal O3 flux concept and represents a step forward in predicting O3 damage to forests in a spatially and temporally varying climate. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

iClimate: a climate data and analysis portal

NASA Astrophysics Data System (ADS)

Goodman, P. J.; Russell, J. L.; Merchant, N.; Miller, S. J.; Juneja, A.

2015-12-01

We will describe a new climate data and analysis portal called iClimate that facilitates direct comparisons between available climate observations and climate simulations. Modeled after the successful iPlant Collaborative Discovery Environment (www.iplantcollaborative.org) that allows plant scientists to trade and share environmental, physiological and genetic data and analyses, iClimate provides an easy-to-use platform for large-scale climate research, including the storage, sharing, automated preprocessing, analysis and high-end visualization of large and often disparate observational and model datasets. iClimate will promote data exploration and scientific discovery by providing: efficient and high-speed transfer of data from nodes around the globe (e.g. PCMDI and NASA); standardized and customized data/model metrics; efficient subsampling of datasets based on temporal period, geographical region or variable; and collaboration tools for sharing data, workflows, analysis results, and data visualizations with collaborators or with the community at large. We will present iClimate's capabilities, and demonstrate how it will simplify and enhance the ability to do basic or cutting-edge climate research by professionals, laypeople and students.

Practical modeling approaches for geological storage of carbon dioxide.

PubMed

Celia, Michael A; Nordbotten, Jan M

2009-01-01

The relentless increase of anthropogenic carbon dioxide emissions and the associated concerns about climate change have motivated new ideas about carbon-constrained energy production. One technological approach to control carbon dioxide emissions is carbon capture and storage, or CCS. The underlying idea of CCS is to capture the carbon before it emitted to the atmosphere and store it somewhere other than the atmosphere. Currently, the most attractive option for large-scale storage is in deep geological formations, including deep saline aquifers. Many physical and chemical processes can affect the fate of the injected CO2, with the overall mathematical description of the complete system becoming very complex. Our approach to the problem has been to reduce complexity as much as possible, so that we can focus on the few truly important questions about the injected CO2, most of which involve leakage out of the injection formation. Toward this end, we have established a set of simplifying assumptions that allow us to derive simplified models, which can be solved numerically or, for the most simplified cases, analytically. These simplified models allow calculation of solutions to large-scale injection and leakage problems in ways that traditional multicomponent multiphase simulators cannot. Such simplified models provide important tools for system analysis, screening calculations, and overall risk-assessment calculations. We believe this is a practical and important approach to model geological storage of carbon dioxide. It also serves as an example of how complex systems can be simplified while retaining the essential physics of the problem.

Modeling Reef Island Morphodynamics in Profile and Plan View

NASA Astrophysics Data System (ADS)

Ashton, A. D.; Ortiz, A. C.; Lorenzo-Trueba, J.

2016-12-01

Reef islands are carbonate detrital landforms perched atop shallow reef flats of atolls and barrier reef systems. Often comprising the only subaerial, inhabitable land of many island chains and island nations, these low-lying, geomorphically active landforms face considerable hazards from climate change. While there hazards include wave overtopping and groundwater salinization, sea-level rise and wave climate change will affect sediment transport and shoreline dynamics, including the possibility for wholesale reorganization of the islands themselves. Here we present a simplified morphodynamic model that can spatially quantify the potential impacts of climate change on reef islands. Using parameterizations of sediment transport pathways and feedbacks from previously presented XBeach modeling results, we investigate how sea-level rise, change in storminess, and different carbonate production rates can affect the profile evolution of reef islands, including feedbacks with the shallow reef flat that bounds the islands offshore (and lagoonward). Model results demonstrate that during rising sea levels, the reef flat can serve as a sediment trap, starving reef islands of detrital sediment that could otherwise fortify the shore against sea-level-rise-driven erosion. On the other hand, if reef flats are currently shallow (likely due to geologic inheritance or biologic cementation processes) such that sea-level rise does not result in sediment accumulation on the flat, reef island shorelines may be more resilient to rising seas. We extend the model in plan view to examine how long-term (decadal) changes in wave approach direction could affect reef island shoreline orientation. We compare model results to historical and geologic change for different case studies on the Marshall Islands. This simplified modeling approach, focusing on boundary dynamics and mass fluxes, provides a quantitative tool to predict the response of reef island environments to climate change.

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

2000-01-01

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

A climate model with cryodynamics and geodynamics

NASA Technical Reports Server (NTRS)

Ghil, M.; Le Treut, H.

1981-01-01

A simplified, zero-dimensional model of the climatic system is presented which attempts to incorporate mechanisms important on the time scale of glaciation cycles: 10,000 to 100,000 years. The ocean-atmosphere radiation balance, continental ice sheet plastic flow, and upper mantle viscous flow are taken into account, with stress on the interaction between the ice sheets and the upper mantle. The model exhibits free, self-sustained oscillations of an amplitude and period comparable to those found in the paleoclimatic record of glaciations, offering mild support for the idea that unforced oscillations can actually exist in the real climatic system itself. The careful study of the interplay between internal mechanisms and external forcing is held to represent an interesting challenge to the theory of ice ages.

Quantifying the economic risks of climate change

NASA Astrophysics Data System (ADS)

Diaz, Delavane; Moore, Frances

2017-11-01

Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work.

Optical properties of light absorbing carbon aggregates mixed with sulfate: assessment of different model geometries for climate forcing calculations.

PubMed

Kahnert, Michael; Nousiainen, Timo; Lindqvist, Hannakaisa; Ebert, Martin

2012-04-23

Light scattering by light absorbing carbon (LAC) aggregates encapsulated into sulfate shells is computed by use of the discrete dipole method. Computations are performed for a UV, visible, and IR wavelength, different particle sizes, and volume fractions. Reference computations are compared to three classes of simplified model particles that have been proposed for climate modeling purposes. Neither model matches the reference results sufficiently well. Remarkably, more realistic core-shell geometries fall behind homogeneous mixture models. An extended model based on a core-shell-shell geometry is proposed and tested. Good agreement is found for total optical cross sections and the asymmetry parameter. © 2012 Optical Society of America

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.

PubMed

Koven, C D; Schuur, E A G; Schädel, C; Bohn, T J; Burke, E J; Chen, G; Chen, X; Ciais, P; Grosse, G; Harden, J W; Hayes, D J; Hugelius, G; Jafarov, E E; Krinner, G; Kuhry, P; Lawrence, D M; MacDougall, A H; Marchenko, S S; McGuire, A D; Natali, S M; Nicolsky, D J; Olefeldt, D; Peng, S; Romanovsky, V E; Schaefer, K M; Strauss, J; Treat, C C; Turetsky, M

2015-11-13

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming. © 2015 The Authors.

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

PubMed Central

Koven, C. D.; Schuur, E. A. G.; Schädel, C.; Bohn, T. J.; Burke, E. J.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J. W.; Hayes, D. J.; Hugelius, G.; Jafarov, E. E.; Krinner, G.; Kuhry, P.; Lawrence, D. M.; MacDougall, A. H.; Marchenko, S. S.; McGuire, A. D.; Natali, S. M.; Nicolsky, D. J.; Olefeldt, D.; Peng, S.; Romanovsky, V. E.; Schaefer, K. M.; Strauss, J.; Treat, C. C.; Turetsky, M.

2015-01-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming. PMID:26438276

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

DOE PAGES

Koven, C. D.; Schuur, E. A. G.; Schadel, C.; ...

2015-10-05

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soilmore » temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of –14 to –19 Pg C °C–1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. In conclusion, the simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.« less

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

USGS Publications Warehouse

Koven, C.D.; Schuur, E.A.G.; Schädel, C.; Bohn, T. J.; Burke, E. J.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J.W.; Hayes, D.J.; Hugelius, G.; Jafarov, Elchin E.; Krinner, G.; Kuhry, P.; Lawrence, D.M.; MacDougall, A. H.; Marchenko, Sergey S.; McGuire, A. David; Natali, Susan M.; Nicolsky, D.J.; Olefeldt, David; Peng, S.; Romanovsky, V.E.; Schaefer, Kevin M.; Strauss, J.; Treat, C.C.; Turetsky, M.

2015-01-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator.

EPA Science Inventory

The U.S. Environmental Protection Agency National Stormwater Calculator (NSWC) simplifies the task of estimating runoff through a straightforward simulation process based on the EPA Stormwater Management Model. The NSWC accesses localized climate and soil hydrology data, and opti...

High-Latitude Stratospheric Sensitivity to QBO Width in a Chemistry-Climate Model with Parameterized Ozone Chemistry

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

In a pair of idealized simulations with a simplified chemistry-climate model, the sensitivity of the wintertime Arctic stratosphere to variability in the width of the quasi-biennial oscillation (QBO) is assessed. The width of the QBO appears to have equal influence on the Arctic stratosphere as does the phase (i.e. the Holton-Tan mechanism). In the model, a wider QBO acts like a preferential shift toward the easterly phase of the QBO, where zonal winds at 60 N tend to be relatively weaker, while 50 hPa geopotential heights and polar ozone values tend to be higher.

A Simplified Biosphere Model for Global Climate Studies.

NASA Astrophysics Data System (ADS)

Xue, Y.; Sellers, P. J.; Kinter, J. L.; Shukla, J.

1991-03-01

The Simple Biosphere Model (SiB) as described in Sellers et al. is a bio-physically based model of land surface-atmosphere interaction. For some general circulation model (GCM) climate studies, further simplifications are desirable to have greater computation efficiency, and more important, to consolidate the parametric representation. Three major reductions in the complexity of SiB have been achieved in the present study.The diurnal variation of surface albedo is computed in SiB by means of a comprehensive yet complex calculation. Since the diurnal cycle is quite regular for each vegetation type, this calculation can be simplified considerably. The effect of root zone soil moisture on stomatal resistance is substantial, but the computation in SiB is complicated and expensive. We have developed approximations, which simulate the effects of reduced soil moisture more simply, keeping the essence of the biophysical concepts used in SiB.The surface stress and the fluxes of heat and moisture between the top of the vegetation canopy and an atmospheric reference level have been parameterized in an off-line version of SiB based upon the studies by Businger et al. and Paulson. We have developed a linear relationship between Richardson number and aero-dynamic resistance. Finally, the second vegetation layer of the original model does not appear explicitly after simplification. Compared to the model of Sellers et al., we have reduced the number of input parameters from 44 to 21. A comparison of results using the reduced parameter biosphere with those from the original formulation in a GCM and a zero-dimensional model shows the simplified version to reproduce the original results quite closely. After simplification, the computational requirement of SiB was reduced by about 55%.

Three-dimensional hydrogeological modeling to assess the elevated-water-table technique for controlling acid generation from an abandoned tailings site in Quebec, Canada

NASA Astrophysics Data System (ADS)

Ethier, Marie-Pier; Bussière, Bruno; Broda, Stefan; Aubertin, Michel

2018-01-01

The Manitou Mine sulphidic-tailings storage facility No. 2, near Val D'Or, Canada, was reclaimed in 2009 by elevating the water table and applying a monolayer cover made of tailings from nearby Goldex Mine. Previous studies showed that production of acid mine drainage can be controlled by lowering the oxygen flux through Manitou tailings with a water table maintained at the interface between the cover and reactive tailings. Simulations of different scenarios were performed using numerical hydrogeological modeling to evaluate the capacity of the reclamation works to maintain the phreatic surface at this interface. A large-scale numerical model was constructed and calibrated using 3 years of field measurements. This model reproduced the field measurements, including the existence of a western zone on the site where the phreatic level targeted is not always met during the summer. A sensitivity analysis was performed to assess the response of the model to varying saturated hydraulic conductivities, porosities, and grain-size distributions. Higher variations of the hydraulic heads, with respect to the calibrated scenario results, were observed when simulating a looser or coarser cover material. Long-term responses were simulated using: the normal climatic data, data for a normal climate with a 2-month dry spell, and a simplified climate-change case. Environmental quality targets were reached less frequently during summer for the dry spell simulation as well as for the simplified climate-change scenario. This study illustrates how numerical simulations can be used as a key tool to assess the eventual performance of various mine-site reclamation scenarios.

Three-dimensional hydrogeological modeling to assess the elevated-water-table technique for controlling acid generation from an abandoned tailings site in Quebec, Canada

NASA Astrophysics Data System (ADS)

Ethier, Marie-Pier; Bussière, Bruno; Broda, Stefan; Aubertin, Michel

2018-06-01

The Manitou Mine sulphidic-tailings storage facility No. 2, near Val D'Or, Canada, was reclaimed in 2009 by elevating the water table and applying a monolayer cover made of tailings from nearby Goldex Mine. Previous studies showed that production of acid mine drainage can be controlled by lowering the oxygen flux through Manitou tailings with a water table maintained at the interface between the cover and reactive tailings. Simulations of different scenarios were performed using numerical hydrogeological modeling to evaluate the capacity of the reclamation works to maintain the phreatic surface at this interface. A large-scale numerical model was constructed and calibrated using 3 years of field measurements. This model reproduced the field measurements, including the existence of a western zone on the site where the phreatic level targeted is not always met during the summer. A sensitivity analysis was performed to assess the response of the model to varying saturated hydraulic conductivities, porosities, and grain-size distributions. Higher variations of the hydraulic heads, with respect to the calibrated scenario results, were observed when simulating a looser or coarser cover material. Long-term responses were simulated using: the normal climatic data, data for a normal climate with a 2-month dry spell, and a simplified climate-change case. Environmental quality targets were reached less frequently during summer for the dry spell simulation as well as for the simplified climate-change scenario. This study illustrates how numerical simulations can be used as a key tool to assess the eventual performance of various mine-site reclamation scenarios.

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

A toy model linking atmospheric thermal radiation and sea ice growth

NASA Technical Reports Server (NTRS)

Thorndike, A. S.

1992-01-01

A simplified analytical model of sea ice growth is presented where the atmosphere is in thermal radiative equilibrium with the ice. This makes the downwelling longwave radiation reaching the ice surface an internal variable rather than a specified forcing. Analytical results demonstrate how the ice state depends on properties of the ice and on the externally specified climate.

A large ozone-circulation feedback and its implications for global warming assessments.

PubMed

Nowack, Peer J; Abraham, N Luke; Maycock, Amanda C; Braesicke, Peter; Gregory, Jonathan M; Joshi, Manoj M; Osprey, Annette; Pyle, John A

2015-01-01

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever 1 . Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations 1,2 . Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO 2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies 1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks 3-5 .

Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report

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

Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee

The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics throughmore » atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the ocean’s thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.« less

Modeling climate change impact in hospitality sector, using building resources consumption signature

NASA Astrophysics Data System (ADS)

Pinto, Armando; Bernardino, Mariana; Silva Santos, António; Pimpão Silva, Álvaro; Espírito Santo, Fátima

2016-04-01

Hotels are one of building types that consumes more energy and water per person and are vulnerable to climate change because in the occurrence of extreme events (heat waves, water stress) same failures could compromise the hotel services (comfort) and increase energy cost or compromise the landscape and amenities due to water use restrictions. Climate impact assessments and the development of adaptation strategies require the knowledge about critical climatic variables and also the behaviour of building. To study the risk and vulnerability of buildings and hotels to climate change regarding resources consumption (energy and water), previous studies used building energy modelling simulation (BEMS) tools to study the variation in energy and water consumption. In general, the climate change impact in building is evaluated studying the energy and water demand of the building for future climate scenarios. But, hotels are complex buildings, quite different from each other and assumption done in simplified BEMS aren't calibrated and usually neglect some important hotel features leading to projected estimates that do not usually match hotel sector understanding and practice. Taking account all uncertainties, the use of building signature (statistical method) could be helpful to assess, in a more clear way, the impact of Climate Change in the hospitality sector and using a broad sample. Statistical analysis of the global energy consumption obtained from bills shows that the energy consumption may be predicted within 90% confidence interval only with the outdoor temperature. In this article a simplified methodology is presented and applied to identify the climate change impact in hospitality sector using the building energy and water signature. This methodology is applied to sixteen hotels (nine in Lisbon and seven in Algarve) with four and five stars rating. The results show that is expect an increase in water and electricity consumption (manly due to the increase in cooling) and a decrease in gas consumption (for heating). The hotels in Algarve are more vulnerable than Lisbon hotels.

Studying Weather and Climate Using Atmospheric Retrospective Analyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.

2014-12-01

Over the last 35 years, tremendous amounts of satellite observations of the Earth's atmosphere have been collected along side the much longer and diverse record of in situ measurements. The satellite data records have disparate qualities, structure and uncertainty which make comparing weather from the 80s and 2000s a challenging prospect. Likewise, in-situ data records lack complete coverage of the earth in both space and time. Atmospheric reanalyses use the observations with numerical models and data assimilation to produce continuous and consistent weather data records for periods longer than decades. The result is a simplified data format with a relatively straightforward learning curve that includes many more variables available (through the modeling component of the system), but driven by a full suite of observational data. The simplified data format allows introduction into weather and climate data analysis. Some examples are provided from undergraduate meteorology program internship projects. We will present the students progression through the projects from their initial understanding and competencies to some final results and the skills learned along the way. Reanalyses are a leading research tool in weather and climate, but can also provide an introductory experience as well, allowing students to develop an understanding of the physical system while learning basic programming and analysis skills.

Edge states in the climate system: exploring global instabilities and critical transitions

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Bódai, Tamás

2017-07-01

Multistability is a ubiquitous feature in systems of geophysical relevance and provides key challenges for our ability to predict a system’s response to perturbations. Near critical transitions small causes can lead to large effects and—for all practical purposes—irreversible changes in the properties of the system. As is well known, the Earth climate is multistable: present astronomical and astrophysical conditions support two stable regimes, the warm climate we live in, and a snowball climate characterized by global glaciation. We first provide an overview of methods and ideas relevant for studying the climate response to forcings and focus on the properties of critical transitions in the context of both stochastic and deterministic dynamics, and assess strengths and weaknesses of simplified approaches to the problem. Following an idea developed by Eckhardt and collaborators for the investigation of multistable turbulent fluid dynamical systems, we study the global instability giving rise to the snowball/warm multistability in the climate system by identifying the climatic edge state, a saddle embedded in the boundary between the two basins of attraction of the stable climates. The edge state attracts initial conditions belonging to such a boundary and, while being defined by the deterministic dynamics, is the gate facilitating noise-induced transitions between competing attractors. We use a simplified yet Earth-like intermediate complexity climate model constructed by coupling a primitive equations model of the atmosphere with a simple diffusive ocean. We refer to the climatic edge states as Melancholia states and provide an extensive analysis of their features. We study their dynamics, their symmetry properties, and we follow a complex set of bifurcations. We find situations where the Melancholia state has chaotic dynamics. In these cases, we have that the basin boundary between the two basins of attraction is a strange geometric set with a nearly zero codimension, and relate this feature to the time scale separation between instabilities occurring on weather and climatic time scales. We also discover a new stable climatic state that is similar to a Melancholia state and is characterized by non-trivial symmetry properties.

Climate Change, Nutrition, and Bottom-Up and Top-Down Food Web Processes.

PubMed

Rosenblatt, Adam E; Schmitz, Oswald J

2016-12-01

Climate change ecology has focused on climate effects on trophic interactions through the lenses of temperature effects on organismal physiology and phenological asynchronies. Trophic interactions are also affected by the nutrient content of resources, but this topic has received less attention. Using concepts from nutritional ecology, we propose a conceptual framework for understanding how climate affects food webs through top-down and bottom-up processes impacted by co-occurring environmental drivers. The framework integrates climate effects on consumer physiology and feeding behavior with effects on resource nutrient content. It illustrates how studying responses of simplified food webs to simplified climate change might produce erroneous predictions. We encourage greater integrative complexity of climate change research on trophic interactions to resolve patterns and enhance predictive capacities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Connectivity planning to address climate change.

PubMed

Nuñez, Tristan A; Lawler, Joshua J; McRae, Brad H; Pierce, D John; Krosby, Meade B; Kavanagh, Darren M; Singleton, Peter H; Tewksbury, Joshua J

2013-04-01

As the climate changes, human land use may impede species from tracking areas with suitable climates. Maintaining connectivity between areas of different temperatures could allow organisms to move along temperature gradients and allow species to continue to occupy the same temperature space as the climate warms. We used a coarse-filter approach to identify broad corridors for movement between areas where human influence is low while simultaneously routing the corridors along present-day spatial gradients of temperature. We modified a cost-distance algorithm to model these corridors and tested the model with data on current land-use and climate patterns in the Pacific Northwest of the United States. The resulting maps identified a network of patches and corridors across which species may move as climates change. The corridors are likely to be robust to uncertainty in the magnitude and direction of future climate change because they are derived from gradients and land-use patterns. The assumptions we applied in our model simplified the stability of temperature gradients and species responses to climate change and land use, but the model is flexible enough to be tailored to specific regions by incorporating other climate variables or movement costs. When used at appropriate resolutions, our approach may be of value to local, regional, and continental conservation initiatives seeking to promote species movements in a changing climate. Planificación de Conectividad para Atender el Cambio Climático. © 2013 Society for Conservation Biology.

Does Climate Care about Land?

NASA Astrophysics Data System (ADS)

Dawson, E.; Lague, M. M.; Swann, A. L. S.

2017-12-01

Everyone knows that plants are influenced by the climate they live in. However, the reverse is also true: plants can influence climate both locally and globally by changing atmospheric circulation. Uncovering the role that plants play in climate has been challenging—the interactions are complex and vary greatly in different regions of the world. We lack a systematic understanding of the role of vegetation in the climate system. Using a new simplified land model coupled to a modern Earth System Model (ESM), we are able to separate the individual influences of the land system in the context of modern ESMs. For example, with our model we are able to test how the capacity of the land to hold water influences the atmosphere. If less water is able to evaporate, this could lead to substantial warming, and could even influence clouds. Understanding specifically where and how the atmosphere is influenced by the land surface improves our understanding of how future changes in the land surface will in turn feedback on climate, and how that will impact people. This improved understanding also advances our knowledge of the key role biology plays in driving the global climate system.

Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

The interactions between vegetation and climate seasonality, topography on different time scales under the Budyko framework: case study in China's Loess Plateau

NASA Astrophysics Data System (ADS)

Liu, W.; Ning, T.; Shen, H.; Li, Z.

2017-12-01

Vegetation, climate seasonality and topography are the main impact factors controlling the water and heat balance over a catchment, and they are usually empirically formulated into the controlling parameter in Budyko model. However, their interactions on different time scales have not been fully addressed. Taking 30 catchments in China's Loess Plateau as an example, on annual scale, vegetation coverage was found poorly correlated with climate seasonality index; therefore, they could be both parameterized into the Budyko model. On the long-term scale, vegetation coverage tended to have close relationships with topographic conditions and climate seasonality, which was confirmed by the multi-collinearity problems; in that sense, vegetation information could fit the controlling parameter exclusively. Identifying the dominant controlling factors over different time scales, this study simplified the empirical parameterization of the Budyko formula. Though the above relationships further investigation over the other regions/catchments.

Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate

DOE PAGES

Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; ...

2017-04-28

A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less

Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate

NASA Astrophysics Data System (ADS)

Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevâg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D. O.; Bertram, A. K.; Zuend, A.; Virtanen, A.; Riipinen, I.

2017-05-01

A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.

Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate.

PubMed

Rastak, N; Pajunoja, A; Acosta Navarro, J C; Ma, J; Song, M; Partridge, D G; Kirkevåg, A; Leong, Y; Hu, W W; Taylor, N F; Lambe, A; Cerully, K; Bougiatioti, A; Liu, P; Krejci, R; Petäjä, T; Percival, C; Davidovits, P; Worsnop, D R; Ekman, A M L; Nenes, A; Martin, S; Jimenez, J L; Collins, D R; Topping, D O; Bertram, A K; Zuend, A; Virtanen, A; Riipinen, I

2017-05-28

A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.

Microphysical explanation of the RH‐dependent water affinity of biogenic organic aerosol and its importance for climate

PubMed Central

Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevåg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D.O.; Bertram, A. K.; Zuend, A.; Virtanen, A.

2017-01-01

Abstract A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH‐dependent SOA water‐uptake with solubility and phase separation; (2) show that laboratory data on IP‐ and MT‐SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single‐parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. PMID:28781391

Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate

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

Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.

A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less

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

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2013-10-01

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

The impact of global warming on river runoff

NASA Technical Reports Server (NTRS)

Miller, James R.; Russell, Gary L.

1992-01-01

A global atmospheric model is used to calculate the annual river runoff for 33 of the world's major rivers for the present climate and for a doubled CO2 climate. The model has a horizontal resolution of 4 x 5 deg, but the runoff from each model grid box is quartered and added to the appropriate river drainage basin on a 2 x 2.5 deg resolution. The computed runoff depends on the model's precipitation, evapotranspiration, and soil moisture storage. For the doubled CO2 climate, the runoff increased for 25 of the 33 rivers, and in most cases the increases coincide with increased rainfall within the drainage basins. There were runoff increases in all rivers in high northern latitudes, with a maximum increase of 47 percent. At low latitudes there were both increases and decreases ranging from a 96 increase to a 43 percent decrease. The effect of the simplified model assumptions of land-atmosphere interactions on the results is discussed.

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

A toy model of sea ice growth

NASA Technical Reports Server (NTRS)

Thorndike, Alan S.

1992-01-01

My purpose here is to present a simplified treatment of the growth of sea ice. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the sea ice cover will respond to climate change. Three models are discussed. The first deals with the growth of sea ice during the cold season. The second describes the cycle of growth and melting for perennial ice. The third model extends the second to account for the possibility that the ice melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what ice properties determine the ice behavior, and to which climate variables the system is most sensitive.

Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2010-12-01

EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.

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.

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

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

Notz, Dirk; Jahn, Alexandra; Holland, Marika

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

DOE PAGES

Notz, Dirk; Jahn, Alexandra; Holland, Marika; ...

2016-09-23

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

Tinkering With AGCMs To Investigate Atmospheric Behavior

NASA Astrophysics Data System (ADS)

Bitz, C. M.

2014-12-01

My experience teaching a course in global climate modeling has proven that students (and instructors) with wide-ranging backgrounds in earth-science learn effectively about the complexity of climate by tinker with model components. As an example, I will present a series of experiments in an AGCM with highly simplified geometries for ocean and land to test the response of the atmosphere to variations in basic parameters. The figure below shows an example of how the zonal wind changes with surface roughness and orography. The pinnacle of experiments explored in my course was the outcome of a homework assignment where students reduced the cloud droplet radius by 40% over ocean, and the results surprised students and instructor alike.

X-DRAIN and XDS: a simplified road erosion prediction method

Treesearch

William J. Elliot; David E. Hall; S. R. Graves

1998-01-01

To develop a simple road sediment delivery tool, the WEPP program modeled sedimentation from forest roads for more than 50,000 combinations of distance between cross drains, road gradient, soil texture, distance from stream, steepness of the buffer between the road and the stream, and climate. The sediment yield prediction from each of these runs was stored in a data...

Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.

Seasonal changes in the atmospheric heat balance simulated by the GISS general circulation model

NASA Technical Reports Server (NTRS)

Stone, P. H.; Chow, S.; Helfand, H. M.; Quirk, W. J.; Somerville, R. C. J.

1975-01-01

Tests of the ability of numerical general circulation models to simulate the atmosphere have focussed so far on simulations of the January climatology. These models generally present boundary conditions such as sea surface temperature, but this does not prevent testing their ability to simulate seasonal changes in atmospheric processes that accompany presented seasonal changes in boundary conditions. Experiments to simulate changes in the zonally averaged heat balance are discussed since many simplified models of climatic processes are based solely on this balance.

Extensions and applications of a second-order landsurface parameterization

NASA Technical Reports Server (NTRS)

Andreou, S. A.; Eagleson, P. S.

1983-01-01

Extensions and applications of a second order land surface parameterization, proposed by Andreou and Eagleson are developed. Procedures for evaluating the near surface storage depth used in one cell land surface parameterizations are suggested and tested by using the model. Sensitivity analysis to the key soil parameters is performed. A case study involving comparison with an "exact" numerical model and another simplified parameterization, under very dry climatic conditions and for two different soil types, is also incorporated.

Model confirmation in climate economics

PubMed Central

Millner, Antony; McDermott, Thomas K. J.

2016-01-01

Benefit–cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth—one of its most important economic components—had questionable predictive power over the 20th century. PMID:27432964

Altitude dependency of future snow cover changes over Central Japan evaluated by a regional climate model

NASA Astrophysics Data System (ADS)

Kawase, Hiroaki; Hara, Masayuki; Yoshikane, Takao; Ishizaki, Noriko N.; Uno, Fumichika; Hatsushika, Hiroaki; Kimura, Fujio

2013-11-01

Sea of Japan side of Central Japan is one of the heaviest snowfall areas in the world. We investigate near-future snow cover changes on the Sea of Japan side using a regional climate model. We perform the pseudo global warming (PGW) downscaling based on the five global climate models (GCMs). The changes in snow cover strongly depend on the elevation; decrease in the ratios of snow cover is larger in the lower elevations. The decrease ratios of the maximum accumulated snowfall in the short term, such as 1 day, are smaller than those in the long term, such as 1 week. We conduct the PGW experiments focusing on specific periods when a 2 K warming at 850 hPa is projected by the individual GCMs (PGW-2K85). The PGW-2K85 experiments show different changes in precipitation, resulting in snow cover changes in spite of similar warming conditions. Simplified sensitivity experiments that assume homogenous warming of the atmosphere (2 K) and the sea surface show that the altitude dependency of snow cover changes is similar to that in the PGW-2K85 experiments, while the uncertainty of changes in the sea surface temperature influences the snow cover changes both in the lower and higher elevations. The decrease in snowfall is, however, underestimated in the simplified sensitivity experiments as compared with the PGW experiments. Most GCMs project an increase in dry static stability and some GCMs project an anticyclonic anomaly over Central Japan, indicating the inhibition of precipitation, including snowfall, in the PGW experiments.

On evolutionary climate tracks in deep mantle volatile cycle computed from numerical mantle convection simulations and its impact on the habitability of the Earth-like planets

NASA Astrophysics Data System (ADS)

Nakagawa, T.; Tajika, E.; Kadoya, S.

2017-12-01

Discussing an impact of evolution and dynamics in the Earth's deep interior on the surface climate change for the last few decades (see review by Ehlmann et al., 2016), the mantle volatile (particularly carbon) degassing in the mid-oceanic ridges seems to play a key role in understanding the evolutionary climate track for Earth-like planets (e.g. Kadoya and Tajika, 2015). However, since the mantle degassing occurs not only in the mid-oceanic ridges but also in the wedge mantle (island arc volcanism) and hotspots, to incorporate more accurate estimate of mantle degassing flux into the climate evolution framework, we developed a coupled model of surface climate-deep Earth evolution in numerical mantle convection simulations, including more accurate deep water and carbon cycle (e.g. Nakagawa and Spiegelman, 2017) with an energy balance theory of climate change. Modeling results suggest that the evolution of planetary climate computed from a developed model is basically consistent with an evolutionary climate track in simplified mantle degassing model (Kadoya and Tajika, 2015), but an occurrence timing of global (snowball) glaciation is strongly dependent on mantle degassing rate occurred with activities of surface plate motions. With this implication, the surface plate motion driven by deep mantle dynamics would play an important role in the planetary habitability of such as the Earth and Earth-like planets over geologic time-scale.

A Unified Approach to Quantifying Feedbacks in Earth System Models

NASA Astrophysics Data System (ADS)

Taylor, K. E.

2008-12-01

In order to speed progress in reducing uncertainty in climate projections, the processes that most strongly influence those projections must be identified. It is of some importance, therefore, to assess the relative strengths of various climate feedbacks and to determine the degree to which various earth system models (ESMs) agree in their simulations of these processes. Climate feedbacks have been traditionally quantified in terms of their impact on the radiative balance of the planet, whereas carbon cycle responses have been assessed in terms of the size of the perturbations to the surface fluxes of carbon dioxide. In this study we introduce a diagnostic strategy for unifying the two approaches, which allows us to directly compare the strength of carbon-climate feedbacks with other conventional climate feedbacks associated with atmospheric and surface changes. Applying this strategy to a highly simplified model of the carbon-climate system demonstrates the viability of the approach. In the simple model we find that even if the strength of the carbon-climate feedbacks is very large, the uncertainty associated with the overall response of the climate system is likely to be dominated by uncertainties in the much larger feedbacks associated with clouds. This does not imply that the carbon cycle itself is unimportant, only that changes in the carbon cycle that are associated with climate change have a relatively small impact on global temperatures. This new, unified diagnostic approach is suitable for assessing feedbacks in even the most sophisticated earth system models. It will be interesting to see whether our preliminary conclusions are confirmed when output from the more realistic models is analyzed. This work was carried out at the University of California Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.

Data in support of energy performance of double-glazed windows.

PubMed

Shakouri, Mahmoud; Banihashemi, Saeed

2016-06-01

This paper provides the data used in a research project to propose a new simplified windows rating system based on saved annual energy ("Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network" (Shakouri Hassanabadi and Banihashemi Namini, 2012) [1], "Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates" (Banihashemi et al., 2015) [2]). A full factorial simulation study was conducted to evaluate the performance of 26 different types of windows in a four-story residential building. In order to generalize the results, the selected windows were tested in four climates of cold, tropical, temperate, and hot and arid; and four different main orientations of North, West, South and East. The accompanied datasets include the annual saved cooling and heating energy in different climates and orientations by using the selected windows. Moreover, a complete dataset is provided that includes the specifications of 26 windows, climate data, month, and orientation of the window. This dataset can be used to make predictive models for energy efficiency assessment of double glazed windows.

Generalised and Fractional Langevin Equations-Implications for Energy Balance Models

NASA Astrophysics Data System (ADS)

Watkins, N. W.; Chapman, S. C.; Chechkin, A.; Ford, I.; Klages, R.; Stainforth, D. A.

2017-12-01

Energy Balance Models (EBMs) have a long heritage in climate science, including their use in modelling anomalies in global mean temperature. Many types of EBM have now been studied, and this presentation concerns the stochastic EBMs, which allow direct treatment of climate fluctuations and noise. Some recent stochastic EBMs (e.g. [1]) map on to Langevin's original form of his equation, with temperature anomaly replacing velocity, and other corresponding replacements being made. Considerable sophistication has now been reached in the application of multivariate stochastic Langevin modelling in many areas of climate. Our work is complementary in intent and investigates the Mori-Kubo "Generalised Langevin Equation" (GLE) which incorporates non-Markovian noise and response in a univariate framework, as a tool for modelling GMT [2]. We show how, if it is present, long memory simplifies the GLE to a fractional Langevin equation (FLE). Evidence for long range memory in global temperature, and the success of fractional Gaussian noise in its prediction [5] has already motivated investigation of a power law response model [3,4,5]. We go beyond this work to ask whether an EBM of FLE-type exists, and what its solutions would be. [l] Padilla et al, J. Climate (2011); [2] Watkins, GRL (2013); [3] Rypdal, JGR (2012); [4] Rypdal and Rypdal, J. Climate (2014); [5] Lovejoy et al, ESDD (2015).

Strategic reasoning and bargaining in catastrophic climate change games

NASA Astrophysics Data System (ADS)

Verendel, Vilhelm; Johansson, Daniel J. A.; Lindgren, Kristian

2016-03-01

Two decades of international negotiations show that agreeing on emission levels for climate change mitigation is a hard challenge. However, if early warning signals were to show an upcoming tipping point with catastrophic damage, theory and experiments suggest this could simplify collective action to reduce greenhouse gas emissions. At the actual threshold, no country would have a free-ride incentive to increase emissions over the tipping point, but it remains for countries to negotiate their emission levels to reach these agreements. We model agents bargaining for emission levels using strategic reasoning to predict emission bids by others and ask how this affects the possibility of reaching agreements that avoid catastrophic damage. It is known that policy elites often use a higher degree of strategic reasoning, and in our model this increases the risk for climate catastrophe. Moreover, some forms of higher strategic reasoning make agreements to reduce greenhouse gases unstable. We use empirically informed levels of strategic reasoning when simulating the model.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

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

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; M{ü}ller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2012-11-01

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

A Statistical Bias Correction Tool for Generating Climate Change Scenarios in Indonesia based on CMIP5 Datasets

NASA Astrophysics Data System (ADS)

Faqih, A.

2017-03-01

Providing information regarding future climate scenarios is very important in climate change study. The climate scenario can be used as basic information to support adaptation and mitigation studies. In order to deliver future climate scenarios over specific region, baseline and projection data from the outputs of global climate models (GCM) is needed. However, due to its coarse resolution, the data have to be downscaled and bias corrected in order to get scenario data with better spatial resolution that match the characteristics of the observed data. Generating this downscaled data is mostly difficult for scientist who do not have specific background, experience and skill in dealing with the complex data from the GCM outputs. In this regards, it is necessary to develop a tool that can be used to simplify the downscaling processes in order to help scientist, especially in Indonesia, for generating future climate scenario data that can be used for their climate change-related studies. In this paper, we introduce a tool called as “Statistical Bias Correction for Climate Scenarios (SiBiaS)”. The tool is specially designed to facilitate the use of CMIP5 GCM data outputs and process their statistical bias corrections relative to the reference data from observations. It is prepared for supporting capacity building in climate modeling in Indonesia as part of the Indonesia 3rd National Communication (TNC) project activities.

Modeling black-footed ferret energetics: Are southern release sites better?

USGS Publications Warehouse

Harrington, Lauren A.; Biggins, Dean E.; Alldredge, A. William

2006-01-01

Several models have been developed to estimate prey requirements and to assess habitat suitability of release sites for the black-footed ferret (Mustela nigripes) (e.g., Stromberg and others, 1983; Powell and others, 1985; Biggins and others, 1993). None of these models, however, addressed possible differences in energetic requirements between sites due to climatic differences within the ferret’s historical range. We used a simplified energetics model to examine the effect of variation in environmental conditions on ferret energetic requirements. The aim of the study was to determine whether the ferret might be more successful in one area than another.

Simulating climate change with interactive stratospheric ozone

NASA Astrophysics Data System (ADS)

Lin, P.; Ming, Y.

2017-12-01

We compare the simulated climate changes with and without interactive ozone in GFDL AM4. We also compare the simulations with a fully interactive stratospheric chemistry scheme versus those with a simplified scheme in which ozone is treated as a passive tracer. Despite its simplicity, the ozone tracer is sufficient to represent the ozone changes in response to changes in the stratospheric circulation as well as the zonally asymmetric distribution of ozone concentration. With interactive ozone, the model simulates a stronger cooling in the tropical lower stratosphere and less stratospheric moistening in response to surface warming. We further investigate how the different stratospheric response translate into different responses in the tropospheric circulations.

Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

NASA Technical Reports Server (NTRS)

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Paleodust variability since the Last Glacial Maximum and implications for iron inputs to the ocean

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Murphy, L. N.; Raiswell, R.; Moore, J. K.; Anderson, R. F.; McGee, D.; Bradtmiller, L. I.; Delmonte, B.; Hesse, P. P.; Mayewski, P. A.

2016-04-01

Changing climate conditions affect dust emissions and the global dust cycle, which in turn affects climate and biogeochemistry. In this study we use observationally constrained model reconstructions of the global dust cycle since the Last Glacial Maximum, combined with different simplified assumptions of atmospheric and sea ice processing of dust-borne iron, to provide estimates of soluble iron deposition to the oceans. For different climate conditions, we discuss uncertainties in model-based estimates of atmospheric processing and dust deposition to key oceanic regions, highlighting the large degree of uncertainty of this important variable for ocean biogeochemistry and the global carbon cycle. We also show the role of sea ice acting as a time buffer and processing agent, which results in a delayed and pulse-like soluble iron release into the ocean during the melting season, with monthly peaks up to ~17 Gg/month released into the Southern Oceans during the Last Glacial Maximum (LGM).

The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

DOE PAGES

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

2016-11-16

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

NASA Technical Reports Server (NTRS)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.;

Simple Climate Model Evaluation Using Impulse Response Tests

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Comparing different methods to model scenarios of future glacier change for the entire Swiss Alps

NASA Astrophysics Data System (ADS)

Linsbauer, A.; Paul, F.; Haeberli, W.

2012-04-01

There is general agreement that observed climate change already has strong impacts on the cryosphere. The rapid shrinkage of glaciers during the past two decades as observed in many mountain ranges globally and in particular in the Alps, are impressive confirmations of a changed climate. With the expected future temperature increase glacier shrinkage will likely further accelerate and their role as an important water resource more and more diminish. To determine the future contribution of glaciers to run-off with hydrological models, the change in glacier area and/or volume must be considered. As these models operate at regional scales, simplified approaches to model the future development of all glaciers in a mountain range need to be applied. In this study we have compared different simplified approaches to model the area and volume evolution of all glaciers in the Swiss Alps over the 21st century according to given climate change scenarios. One approach is based on an upward shift of the ELA (by 150 m per degree temperature increase) and the assumption that the glacier extent will shrink until the smaller accumulation area covers again 60% of the total glacier area. A second approach is based on observed elevation changes between 1985 and 2000 as derived from DEM differencing for all glaciers in Switzerland. With a related elevation-dependent parameterization of glacier thickness change and a modelled glacier thickness distribution, the 15-year trends in observed thickness loss are extrapolated into the future with glacier area loss taking place when thickness becomes zero. The models show an overall glacier area reduction between 60-80% until 2100 with some ice remaining at the highest elevations. However, compared to the ongoing temperature increase and considering that several reinforcement feedbacks (albedo lowering, lake formation) are not accounted for, the real area loss might even be stronger. Uncertainties in the modelled glacier thickness have only a small influence on the final area loss, but influence the temporal evolution of the loss. In particular the largest valley glaciers will suffer from a strong volume loss, as large parts of their beds have a small inclination and are thus located at low elevations.

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

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

Contrasting model complexity under a changing climate in a headwaters catchment.

NASA Astrophysics Data System (ADS)

Foster, L.; Williams, K. H.; Maxwell, R. M.

2017-12-01

Alpine, snowmelt-dominated catchments are the source of water for more than 1/6th of the world's population. These catchments are topographically complex, leading to steep weather gradients and nonlinear relationships between water and energy fluxes. Recent evidence suggests that alpine systems are more sensitive to climate warming, but these regions are vastly simplified in climate models and operational water management tools due to computational limitations. Simultaneously, point-scale observations are often extrapolated to larger regions where feedbacks can both exacerbate or mitigate locally observed changes. It is critical to determine whether projected climate impacts are robust to different methodologies, including model complexity. Using high performance computing and an integrated model of a representative headwater catchment we determined the hydrologic response from 30 projected climate changes to precipitation, temperature and vegetation for the Rocky Mountains. Simulations were run with 100m and 1km resolution, and with and without lateral subsurface flow in order to vary model complexity. We found that model complexity alters nonlinear relationships between water and energy fluxes. Higher-resolution models predicted larger changes per degree of temperature increase than lower resolution models, suggesting that reductions to snowpack, surface water, and groundwater due to warming may be underestimated in simple models. Increases in temperature were found to have a larger impact on water fluxes and stores than changes in precipitation, corroborating previous research showing that mountain systems are significantly more sensitive to temperature changes than to precipitation changes and that increases in winter precipitation are unlikely to compensate for increased evapotranspiration in a higher energy environment. These numerical experiments help to (1) bracket the range of uncertainty in published literature of climate change impacts on headwater hydrology; (2) characterize the role of precipitation and temperature changes on water supply for snowmelt-dominated downstream basins; and (3) identify which climate impacts depend on the scale of simulation.

Climatic impact of Amazon deforestation - a mechanistic model study

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

Ning Zeng; Dickinson, R.E.; Xubin Zeng

1996-04-01

Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less

Climate sensitivity, sea level and atmospheric carbon dioxide

PubMed Central

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1°C for a 4 W m−2 CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3–4°C for a 4 W m−2 CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change. PMID:24043864

Climate sensitivity, sea level and atmospheric carbon dioxide.

PubMed

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-10-28

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1(°)C for a 4 W m(-2) CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4(°)C for a 4 W m(-2) CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Diversity, Adaptability and Ecosystem Resilience

NASA Astrophysics Data System (ADS)

Keribin, Rozenn; Friend, Andrew

2013-04-01

Our ability to predict climate change and anticipate its impacts depends on Earth System Models (ESMs) and their ability to account for the high number of interacting components of the Earth System and to gauge both their influence on the climate and the feedbacks they induce. The land carbon cycle is a component of ESMs that is still poorly constrained. Since the 1990s dynamic global vegetation models (DGVMs) have become the main tool through which we understand the interactions between plant ecosystems and the climate. While DGVMs have made it clear the impacts of climate change on vegetation could be dramatic, predicting the dieback of rainforests and massive carbon losses from various ecosystems, they are highly variable both in their composition and their predictions. Their treatment of plant diversity and competition in particular vary widely and are based on highly-simplified relationships that do not account for the multiple levels of diversity and adaptability found in real plant ecosystems. The aim of this GREENCYCLES II project is to extend an individual-based DGVM to treat the diversity of physiologies found in plant communities and evaluate their effect if any on the ecosystem's transient dynamics and resilience. In the context of the InterSectoral Impacts Model Intercomparison Project (ISI-MIP), an initiative coordinated by a team at the Potsdam Institute for Climate Impact Research (PIK) that aims to provide fast-track global impact assessments for the IPCC's Fifth Assessment Report, we compare 6 vegetation models including 4 DGVMs under different climate change scenarios and analyse how the very different treatments of plant diversity and interactions from one model to the next affect the models' results. We then investigate a new, more mechanistic method of incorporating plant diversity into the DGVM "Hybrid" based on ecological tradeoffs mediated by plant traits and individual-based competition for light.

Landscape units of Puerto Rico: influence of climate, substrate, and topography

Treesearch

William A. Gould; Michael E. Jimenez; Gary Potts; Maya Quinones

2008-01-01

The landscape units map of Puerto Rico represents climatic, substrate, and topographic variation by integrating six climatic zones (Ewel and Whitmore 1973), six distinct substrates (Bawiec 2001, USGS 2005), five topographic positions or landforms (Martinuzzi et al. 2007), and prominent lakes and rivers (USGS 2005). Substrates were a simplified set of Bawiec’s (2001)...

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Development of a global aerosol model using a two-dimensional sectional method: 1. Model design

NASA Astrophysics Data System (ADS)

Matsui, H.

2017-08-01

This study develops an aerosol module, the Aerosol Two-dimensional bin module for foRmation and Aging Simulation version 2 (ATRAS2), and implements the module into a global climate model, Community Atmosphere Model. The ATRAS2 module uses a two-dimensional (2-D) sectional representation with 12 size bins for particles from 1 nm to 10 μm in dry diameter and 8 black carbon (BC) mixing state bins. The module can explicitly calculate the enhancement of absorption and cloud condensation nuclei activity of BC-containing particles by aging processes. The ATRAS2 module is an extension of a 2-D sectional aerosol module ATRAS used in our previous studies within a framework of a regional three-dimensional model. Compared with ATRAS, the computational cost of the aerosol module is reduced by more than a factor of 10 by simplifying the treatment of aerosol processes and 2-D sectional representation, while maintaining good accuracy of aerosol parameters in the simulations. Aerosol processes are simplified for condensation of sulfate, ammonium, and nitrate, organic aerosol formation, coagulation, and new particle formation processes, and box model simulations show that these simplifications do not substantially change the predicted aerosol number and mass concentrations and their mixing states. The 2-D sectional representation is simplified (the number of advected species is reduced) primarily by the treatment of chemical compositions using two interactive bin representations. The simplifications do not change the accuracy of global aerosol simulations. In part 2, comparisons with measurements and the results focused on aerosol processes such as BC aging processes are shown.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

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

Intraseasonal and Interannual Variability of Mars Present Climate

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1996-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to investigate the nature of intraseasonal and interannual variability of Mars'present climate. We have applied a three-dimensional climate model based on the full hydrostatic primitive equations to determine the spatial, but primarily, the temporal structures of the planet's large-scale circulation as it evolves during a given seasonal advance, and, over multi-annual cycles. The particular climate model applies simplified physical parameterizations and is computationally efficient. It could thus easily be integrated in a perpetual season or advancing season configuration, as well as over many Mars years. We have assessed both high and low-frequency components of the circulation (i.e., motions having periods of Omicron(2-10 days) or greater than Omicron(10 days), respectively). Results from this investigation have explored the basic issue whether Mars' climate system is naturally 'chaotic' associated with nonlinear interactions of the large-scale circulation-regardless of any allowance for year-to-year variations in external forcing mechanisms. Titles of papers presented at scientific conferences and a manuscript to be submitted to the scientific literature are provided. An overview of a areas for further investigation is also presented.

Tailored scenarios for streamflow climate change impacts based on the perturbation of precipitation and evapotranspiration

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel

2015-04-01

It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.

Development of a simplified urban water balance model (WABILA).

PubMed

Henrichs, M; Langner, J; Uhl, M

2016-01-01

During the last decade, water sensitive urban design (WSUD) has become more and more accepted. However, there is not any simple tool or option available to evaluate the influence of these measures on the local water balance. To counteract the impact of new settlements, planners focus on mitigating increases in runoff through installation of infiltration systems. This leads to an increasing non-natural groundwater recharge and decreased evapotranspiration. Simple software tools which evaluate or simulate the effect of WSUD on the local water balance are still needed. The authors developed a tool named WABILA (Wasserbilanz) that could support planners for optimal WSUD. WABILA is an easy-to-use planning tool that is based on simplified regression functions for established measures and land covers. Results show that WSUD has to be site-specific, based on climate conditions and the natural water balance.

Paleodynamics of large closed lakes as a standard for climate modeling data verification

NASA Astrophysics Data System (ADS)

Kislov, Alexander

2015-04-01

Observed and reconstructed variations of large lakes can serve as a standard for assessing the quality of the model run off simulated by climate models. It provides the opportunity to assess whether models designed for future scenarios are skillful in 'out-of sample' climate change experiments. Based on general ideas about the laws of temporal dynamics relating to massive inertial objects, slow changes of the lake level under the semi-steady climate state can be represented as resulting from the accumulation of small anomalies in the water regime; it appears like a kind of "self-developing" system. To test this hypothesis, the water balance model of the Caspian Sea (CS) was used. Time scale for the CS is estimated as ~20 years. Model is interpreted as stochastic, and from this perspective, it is a Langevin equation that incorporates the action of precipitation and evaporation like random white noise, so that the whole can be thought of as an analogue of Brownian motion. Under these conditions, the CS palaeostages during the Holocene is represented by a system undergoing random walk. It should be emphasized that modeling results are interpreted from the probabilistic point of view, despite the fact that the model is deterministically based on the physical law of conservation of water mass. Despite the CS, another candidate to be as a potential evaluation tool for climate model simulations is the Black Sea (BS) until its merger with the Mediterranean. Therefore, although the image of the CS, BS and other lakes within the climate models is very simplified (or absent), changes in the levels could be used to assess the ability of climate models to reproduce the water budget over the catchment areas. For the CS or the BS, they are the large parts of the East European Plane and can be as indicators of climate model quality. However, the use of reconstructed data of other closed lakes is problematic. It is due to its water budget components cannot be simulated with needed accuracy because they are either too small (the size of the largest closed Siberian lake (the Chany) is less than the typical grid box of climate model) or they are located in mountain region (like the Issyk-Kul Lake, located in the northern Tian Shan mountains) where the lake variability is determined by badly reproduced glacier melting.

Organic condensation: a vital link connecting aerosol formation to cloud condensation nuclei (CCN) concentrations

NASA Astrophysics Data System (ADS)

Riipinen, I.; Pierce, J. R.; Yli-Juuti, T.; Nieminen, T.; Häkkinen, S.; Ehn, M.; Junninen, H.; Lehtipalo, K.; Petäjä, T.; Slowik, J.; Chang, R.; Shantz, N. C.; Abbatt, J.; Leaitch, W. R.; Kerminen, V.-M.; Worsnop, D. R.; Pandis, S. N.; Donahue, N. M.; Kulmala, M.

2011-04-01

Atmospheric aerosol particles influence global climate as well as impair air quality through their effects on atmospheric visibility and human health. Ultrafine (<100 nm) particles often dominate aerosol numbers, and nucleation of atmospheric vapors is an important source of these particles. To have climatic relevance, however, the freshly nucleated particles need to grow in size. We combine observations from two continental sites (Egbert, Canada and Hyytiälä, Finland) to show that condensation of organic vapors is a crucial factor governing the lifetimes and climatic importance of the smallest atmospheric particles. We model the observed ultrafine aerosol growth with a simplified scheme approximating the condensing species as a mixture of effectively non-volatile and semi-volatile species, demonstrate that state-of-the-art organic gas-particle partitioning models fail to reproduce the observations, and propose a modeling approach that is consistent with the measurements. We find that roughly half of the mass of the condensing mass needs to be distributed proportional to the aerosol surface area (thus implying that the condensation is governed by gas-phase concentration rather than the equilibrium vapour pressure) to explain the observed aerosol growth. We demonstrate the large sensitivity of predicted number concentrations of cloud condensation nuclei (CCN) to these interactions between organic vapors and the smallest atmospheric nanoparticles - highlighting the need for representing this process in global climate models.

Climate Model Ensemble Methodology: Rationale and Challenges

NASA Astrophysics Data System (ADS)

Vezer, M. A.; Myrvold, W.

2012-12-01

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

Modeling the evolution of channel shape: Balancing computational efficiency with hydraulic fidelity

USGS Publications Warehouse

Wobus, C.W.; Kean, J.W.; Tucker, G.E.; Anderson, R. Scott

2008-01-01

The cross-sectional shape of a natural river channel controls the capacity of the system to carry water off a landscape, to convey sediment derived from hillslopes, and to erode its bed and banks. Numerical models that describe the response of a landscape to changes in climate or tectonics therefore require formulations that can accommodate evolution of channel cross-sectional geometry. However, fully two-dimensional (2-D) flow models are too computationally expensive to implement in large-scale landscape evolution models, while available simple empirical relationships between width and discharge do not adequately capture the dynamics of channel adjustment. We have developed a simplified 2-D numerical model of channel evolution in a cohesive, detachment-limited substrate subject to steady, unidirectional flow. Erosion is assumed to be proportional to boundary shear stress, which is calculated using an approximation of the flow field in which log-velocity profiles are assumed to apply along vectors that are perpendicular to the local channel bed. Model predictions of the velocity structure, peak boundary shear stress, and equilibrium channel shape compare well with predictions of a more sophisticated but more computationally demanding ray-isovel model. For example, the mean velocities computed by the two models are consistent to within ???3%, and the predicted peak shear stress is consistent to within ???7%. Furthermore, the shear stress distributions predicted by our model compare favorably with available laboratory measurements for prescribed channel shapes. A modification to our simplified code in which the flow includes a high-velocity core allows the model to be extended to estimate shear stress distributions in channels with large width-to-depth ratios. Our model is efficient enough to incorporate into large-scale landscape evolution codes and can be used to examine how channels adjust both cross-sectional shape and slope in response to tectonic and climatic forcing. Copyright 2008 by the American Geophysical Union.

The role of building models in the evaluation of heat-related risks

NASA Astrophysics Data System (ADS)

Buchin, Oliver; Jänicke, Britta; Meier, Fred; Scherer, Dieter; Ziegler, Felix

2016-04-01

Hazard-risk relationships in epidemiological studies are generally based on the outdoor climate, despite the fact that most of humans' lifetime is spent indoors. By coupling indoor and outdoor climates with a building model, the risk concept developed can still be based on the outdoor conditions but also includes exposure to the indoor climate. The influence of non-linear building physics and the impact of air conditioning on heat-related risks can be assessed in a plausible manner using this risk concept. For proof of concept, the proposed risk concept is compared to a traditional risk analysis. As an example, daily and city-wide mortality data of the age group 65 and older in Berlin, Germany, for the years 2001-2010 are used. Four building models with differing complexity are applied in a time-series regression analysis. This study shows that indoor hazard better explains the variability in the risk data compared to outdoor hazard, depending on the kind of building model. Simplified parameter models include the main non-linear effects and are proposed for the time-series analysis. The concept shows that the definitions of heat events, lag days, and acclimatization in a traditional hazard-risk relationship are influenced by the characteristics of the prevailing building stock.

Models for integrated and differential scattering optical properties of encapsulated light absorbing carbon aggregates.

PubMed

Kahnert, Michael; Nousiainen, Timo; Lindqvist, Hannakaisa

2013-04-08

Optical properties of light absorbing carbon (LAC) aggregates encapsulated in a shell of sulfate are computed for realistic model geometries based on field measurements. Computations are performed for wavelengths from the UV-C to the mid-IR. Both climate- and remote sensing-relevant optical properties are considered. The results are compared to commonly used simplified model geometries, none of which gives a realistic representation of the distribution of the LAC mass within the host material and, as a consequence, fail to predict the optical properties accurately. A new core-gray shell model is introduced, which accurately reproduces the size- and wavelength dependence of the integrated and differential optical properties.

Test of a simplified modeling approach for nitrogen transfer in agricultural subsurface-drained catchments

NASA Astrophysics Data System (ADS)

Henine, Hocine; Julien, Tournebize; Jaan, Pärn; Ülo, Mander

2017-04-01

In agricultural areas, nitrogen (N) pollution load to surface waters depends on land use, agricultural practices, harvested N output, as well as the hydrology and climate of the catchment. Most of N transfer models need to use large complex data sets, which are generally difficult to collect at larger scale (>km2). The main objective of this study is to carry out a hydrological and a geochemistry modeling by using a simplified data set (land use/crop, fertilizer input, N losses from plots). The modelling approach was tested in the subsurface-drained Orgeval catchment (Paris Basin, France) based on following assumptions: Subsurface tile drains are considered as a giant lysimeter system. N concentration in drain outlets is representative for agricultural practices upstream. Analysis of observed N load (90% of total N) shows 62% of export during the winter. We considered prewinter nitrate (NO3) pool (PWNP) in soils at the beginning of hydrological drainage season as a driving factor for N losses. PWNP results from the part of NO3 not used by crops or the mineralization part of organic matter during the preceding summer and autumn. Considering these assumptions, we used PWNP as simplified input data for the modelling of N transport. Thus, NO3 losses are mainly influenced by the denitrification capacity of soils and stream water. The well-known HYPE model was used to perform water and N losses modelling. The hydrological simulation was calibrated with the observation data at different sub-catchments. We performed a hydrograph separation validated on the thermal and isotopic tracer studies and the general knowledge of the behavior of Orgeval catchment. Our results show a good correlation between the model and the observations (a Nash-Sutcliffe coefficient of 0.75 for water discharge and 0.7 for N flux). Likewise, comparison of calibrated PWNP values with the results from a field survey (annual PWNP campaign) showed significant positive correlation. One can conclude that the simplified modeling approach using PWNP as a driving factor for the evaluation of N losses from drained agricultural catchments gave satisfactory results and we can propose this approach for a wider use.

Integrated Research on the Development of Global Climate Risk Management Strategies - Framework and Initial Results of the Research Project ICA-RUS

NASA Astrophysics Data System (ADS)

Emori, Seita; Takahashi, Kiyoshi; Yamagata, Yoshiki; Oki, Taikan; Mori, Shunsuke; Fujigaki, Yuko

2013-04-01

With the aim of proposing strategies of global climate risk management, we have launched a five-year research project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). In this project with the phrase "risk management" in its title, we aspire for a comprehensive assessment of climate change risks, explicit consideration of uncertainties, utilization of best available information, and consideration of every possible conditions and options. We also regard the problem as one of decision-making at the human level, which involves social value judgments and adapts to future changes in circumstances. The ICA-RUS project consists of the following five themes: 1) Synthesis of global climate risk management strategies, 2) Optimization of land, water and ecosystem uses for climate risk management, 3) Identification and analysis of critical climate risks, 4) Evaluation of climate risk management options under technological, social and economic uncertainties and 5) Interactions between scientific and social rationalities in climate risk management (see also: http://www.nies.go.jp/ica-rus/en/). For the integration of quantitative knowledge of climate change risks and responses, we apply a tool named AIM/Impact [Policy], which consists of an energy-economic model, a simplified climate model and impact projection modules. At the same time, in order to make use of qualitative knowledge as well, we hold monthly project meetings for the discussion of risk management strategies and publish annual reports based on the quantitative and qualitative information. To enhance the comprehensiveness of the analyses, we maintain an inventory of risks and risk management options. The inventory is revised iteratively through interactive meetings with stakeholders such as policymakers, government officials and industrial representatives.

What scaling means in wind engineering: Complementary role of the reduced scale approach in a BLWT and the full scale testing in a large climatic wind tunnel

NASA Astrophysics Data System (ADS)

Flamand, Olivier

2017-12-01

Wind engineering problems are commonly studied by wind tunnel experiments at a reduced scale. This introduces several limitations and calls for a careful planning of the tests and the interpretation of the experimental results. The talk first revisits the similitude laws and discusses how they are actually applied in wind engineering. It will also remind readers why different scaling laws govern in different wind engineering problems. Secondly, the paper focuses on the ways to simplify a detailed structure (bridge, building, platform) when fabricating the downscaled models for the tests. This will be illustrated by several examples from recent engineering projects. Finally, under the most severe weather conditions, manmade structures and equipment should remain operational. What “recreating the climate” means and aims to achieve will be illustrated through common practice in climatic wind tunnel modelling.

Interannual Variability of Martian Global Dust Storms: Simulations with a Low-Order Model of the General Circulation

NASA Technical Reports Server (NTRS)

Pankine, A. A.; Ingersoll, Andrew P.

2002-01-01

We present simulations of the interannual variability of martian global dust storms (GDSs) with a simplified low-order model (LOM) of the general circulation. The simplified model allows one to conduct computationally fast long-term simulations of the martian climate system. The LOM is constructed by Galerkin projection of a 2D (zonally averaged) general circulation model (GCM) onto a truncated set of basis functions. The resulting LOM consists of 12 coupled nonlinear ordinary differential equations describing atmospheric dynamics and dust transport within the Hadley cell. The forcing of the model is described by simplified physics based on Newtonian cooling and Rayleigh friction. The atmosphere and surface are coupled: atmospheric heating depends on the dustiness of the atmosphere, and the surface dust source depends on the strength of the atmospheric winds. Parameters of the model are tuned to fit the output of the NASA AMES GCM and the fit is generally very good. Interannual variability of GDSs is possible in the IBM, but only when stochastic forcing is added to the model. The stochastic forcing could be provided by transient weather systems or some surface process such as redistribution of the sand particles in storm generating zones on the surface. The results are sensitive to the value of the saltation threshold, which hints at a possible feedback between saltation threshold and dust storm activity. According to this hypothesis, erodable material builds up its a result of a local process, whose effect is to lower the saltation threshold until a GDS occurs. The saltation threshold adjusts its value so that dust storms are barely able to occur.

Quantifying Uncertainty in the Greenland Surface Mass Balance Elevation Feedback

NASA Astrophysics Data System (ADS)

Edwards, T.

2015-12-01

As the shape of the Greenland ice sheet responds to changes in surface mass balance (SMB) and dynamics, it affects the surface mass balance through the atmospheric lapse rate and by altering atmospheric circulation patterns. Positive degree day models include simplified representations of this feedback, but it is difficult to simulate with state-of-the-art models because it requires coupling of regional climate models with dynamical ice sheet models, which is technically challenging. This difficulty, along with the high computational expense of regional climate models, also drastically limits opportunities for exploring the impact of modelling uncertainties on sea level projections. We present a parameterisation of the SMB-elevation feedback in the MAR regional climate model that provides a far easier and quicker estimate than atmosphere-ice sheet model coupling, which can be used with any ice sheet model. This allows us to use ensembles of different parameter values and ice sheet models to assess the effect of uncertainty in the feedback and ice sheet model structure on future sea level projections. We take a Bayesian approach to uncertainty in the feedback parameterisation, scoring the results from multiple possible "SMB lapse rates" according to how well they reproduce a MAR simulation with altered ice sheet topography. We test the impact of the resulting parameterisation on sea level projections using five ice sheet models forced by MAR (in turned forced by two different global climate models) under the emissions scenario A1B. The estimated additional sea level contribution due to the SMB-elevation feedback is 4.3% at 2100 (95% credibility interval 1.8-6.9%), and 9.6% at 2200 (3.6-16.0%).

Response of Sierra Nevada forests to projected climate-wildfire interactions.

PubMed

Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy

2017-05-01

Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.

Constructing a framework for risk analyses of climate change effects on the water budget of differently sloped vineyards with a numeric simulation using the Monte Carlo method coupled to a water balance model

PubMed Central

Hofmann, Marco; Lux, Robert; Schultz, Hans R.

2014-01-01

Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively, green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over 2 years. The results showed good agreement of modeled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity (SWC) and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in SWC. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes. PMID:25540646

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

Beyond Wiki to Judgewiki for Transparent Climate Change Decisions

NASA Astrophysics Data System (ADS)

Capron, M. E.

2008-12-01

Climate Change is like the prisoner's dilemma, a zero-sum game, or cheating in sports. Everyone and every country is tempted to selfishly maintain or advance their standard of living. The tremendous difference between standards of living amplifies the desire to opt out of Climate Change solutions adverse to economic competitiveness. Climate Change is also exceedingly complex. No one person, one organization, one country, or partial collection of countries has the capacity and the global support needed to make decisions on Climate Change solutions. There are thousands of potential actions, tens of thousands of known and unknown environmental and economic impacts. Some actions are belatedly found to be unsustainable beyond token volumes, corn ethanol or soy-biodiesel for example. Mankind can address human nature and complexity with a globally transparent information and decision process available to all 7 billion of us. We need a process that builds trust and simplifies complexity. Fortunately, we have the Internet for trust building communication and computers to simplify complexity. Mankind can produce new software tailored to the challenge. We would combine group information collection software (a wiki) with a decision-matrix (a judge), market forecasting, and video games to produce the tool mankind needs for trust building transparent decisions on Climate Change actions. The resulting software would be a judgewiki.

Ice Cores Dating With a New Inverse Method Taking Account of the Flow Modeling Errors

NASA Astrophysics Data System (ADS)

Lemieux-Dudon, B.; Parrenin, F.; Blayo, E.

2007-12-01

Deep ice cores extracted from Antarctica or Greenland recorded a wide range of past climatic events. In order to contribute to the Quaternary climate system understanding, the calculation of an accurate depth-age relationship is a crucial point. Up to now ice chronologies for deep ice cores estimated with inverse approaches are based on quite simplified ice-flow models that fail to reproduce flow irregularities and consequently to respect all available set of age markers. We describe in this paper, a new inverse method that takes into account the model uncertainty in order to circumvent the restrictions linked to the use of simplified flow models. This method uses first guesses on two flow physical entities, the ice thinning function and the accumulation rate and then identifies correction functions on both flow entities. We highlight two major benefits brought by this new method: first of all the ability to respect large set of observations and as a consequence, the feasibility to estimate a synchronized common ice chronology for several cores at the same time. This inverse approach relies on a bayesian framework. To respect the positive constraint on the searched correction functions, we assume lognormal probability distribution on one hand for the background errors, but also for one particular set of the observation errors. We test this new inversion method on three cores simultaneously (the two EPICA cores : DC and DML and the Vostok core) and we assimilate more than 150 observations (e.g.: age markers, stratigraphic links,...). We analyze the sensitivity of the solution with respect to the background information, especially the prior error covariance matrix. The confidence intervals based on the posterior covariance matrix calculation, are estimated on the correction functions and for the first time on the overall output chronologies.

A model for the sustainable selection of building envelope assemblies

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

Huedo, Patricia, E-mail: huedo@uji.es; Mulet, Elena, E-mail: emulet@uji.es; López-Mesa, Belinda, E-mail: belinda@unizar.es

2016-02-15

The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies. To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate themore » impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model. - Highlights: • Method to assess the envelope impacts based on a simplified LCA • To be used at an earlier phase than the existing methods in a simple way. • It assigns a score by means of known sustainability indicators. • It estimates data about the embodied and operating environmental impacts. • It compares the investment costs with the costs of the consumed energy.« less

Evaluation on penetration rate of cloud for incoming solar radiation using geostationary satellite data

NASA Astrophysics Data System (ADS)

Yeom, Jong-Min; Han, Kyung-Soo; Kim, Jae-Jin

2012-05-01

Solar surface insolation (SSI) represents how much solar radiance reaches the Earth's surface in a specified area and is an important parameter in various fields such as surface energy research, meteorology, and climate change. This study calculates insolation using Multi-functional Transport Satellite (MTSAT-1R) data with a simplified cloud factor over Northeast Asia. For SSI retrieval from the geostationary satellite data, the physical model of Kawamura is modified to improve insolation estimation by considering various atmospheric constituents, such as Rayleigh scattering, water vapor, ozone, aerosols, and clouds. For more accurate atmospheric parameterization, satellite-based atmospheric constituents are used instead of constant values when estimating insolation. Cloud effects are a key problem in insolation estimation because of their complicated optical characteristics and high temporal and spatial variation. The accuracy of insolation data from satellites depends on how well cloud attenuation as a function of geostationary channels and angle can be inferred. This study uses a simplified cloud factor that depends on the reflectance and solar zenith angle. Empirical criteria to select reference data for fitting to the ground station data are applied to suggest simplified cloud factor methods. Insolation estimated using the cloud factor is compared with results of the unmodified physical model and with observations by ground-based pyranometers located in the Korean peninsula. The modified model results show far better agreement with ground truth data compared to estimates using the conventional method under overcast conditions.

Insensitivity of evapotranspiration to seasonal rainfall distribution directs climate change impacts at water yield

NASA Astrophysics Data System (ADS)

Montaldo, N.; Oren, R.

2017-12-01

Over the past century, climate change is affecting precipitation regimes across the world. In the Mediterranean regions there is a persistent trend of precipitation and runoff decreases, generating a desertification process. Given the past winter precipitation shifts, the impacts on evapotranspiration (ET) need to be carefully evaluated, and the compelling question is what will be the impact of future climate change scenarios (predicting changes of precipitation and vapor pressure deficit, VPD) on evapotranspiration and water yield? Looking for the key elements of the climate change that are impacting annual ET, we investigate main climate conditions (e.g. precipitation and VPD) and basin physiographic properties contributing to annual ET. We propose a simplified model for annual ET predictions that accounts for the strong meteo seasonality typical of Mediterranean climates, using the steady state assumption of the basin water balance at mean annual scale. We investigate the Sardinia case study because the position of the island of Sardinia in the center of the western Mediterranean Sea basin and its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. Sardinian runoff decreased drastically over the 1975-2010 period, with mean yearly runoff reduced by more than 40% compared to the previous 1922-1974 period, and most yearly runoff in the Sardinian basins (70% on average) is produced by winter precipitation due to the seasonality typical of the Mediterranean climate regime. The use of our proposed model allows to predict future ET and water yield using future climate scenarios. We use the future climate scenarios predicted by Global climate models (GCM) in the Fifth Assessment report of the Intergovernmental Panel on Climate Change (IPCC), and we select most reliable models testing the past GCM predictions with historical data. Contrasting shifts of precipitation (both positive and negative) are predicted in the future scenarios by GCMs but these changes will produce significant changes (level of significance > 90%) only in runoff and not in ET. Surprisingly, we show that ET is insensitive to intra-annual rainfall distribution changes, and is insensitive to VPD scenario changes.

Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Qiang; Zhang, Yongqiang; Chen, Xi; Li, Jianfeng; Aryal, Santosh K.

2017-10-01

Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four-parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980-2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.

Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model. M.S. Thesis

NASA Technical Reports Server (NTRS)

Brubaker, Kaye L.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates.

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kerns, B. K.; Halofsky, J.

2014-12-01

GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest point demonstrates the importance of using model out as a forum for discussion along with other information, rather than using model output in an inappropriately predictive sense. These lessons are being applied currently to other national forests in the Pacific Northwest to contribute in vulnerability assessments.

Development of a system emulating the global carbon cycle in Earth system models

NASA Astrophysics Data System (ADS)

Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.

2010-08-01

Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

Improving the complementary methods to estimate evapotranspiration under diverse climatic and physical conditions

NASA Astrophysics Data System (ADS)

Anayah, F. M.; Kaluarachchi, J. J.

2014-06-01

Reliable estimation of evapotranspiration (ET) is important for the purpose of water resources planning and management. Complementary methods, including complementary relationship areal evapotranspiration (CRAE), advection aridity (AA) and Granger and Gray (GG), have been used to estimate ET because these methods are simple and practical in estimating regional ET using meteorological data only. However, prior studies have found limitations in these methods especially in contrasting climates. This study aims to develop a calibration-free universal method using the complementary relationships to compute regional ET in contrasting climatic and physical conditions with meteorological data only. The proposed methodology consists of a systematic sensitivity analysis using the existing complementary methods. This work used 34 global FLUXNET sites where eddy covariance (EC) fluxes of ET are available for validation. A total of 33 alternative model variations from the original complementary methods were proposed. Further analysis using statistical methods and simplified climatic class definitions produced one distinctly improved GG-model-based alternative. The proposed model produced a single-step ET formulation with results equal to or better than the recent studies using data-intensive, classical methods. Average root mean square error (RMSE), mean absolute bias (BIAS) and R2 (coefficient of determination) across 34 global sites were 20.57 mm month-1, 10.55 mm month-1 and 0.64, respectively. The proposed model showed a step forward toward predicting ET in large river basins with limited data and requiring no calibration.

Changes in crop yields and their variability at different levels of global warming

NASA Astrophysics Data System (ADS)

Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, Katja

2018-05-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.

A Markov Environment-dependent Hurricane Intensity Model and Its Comparison with Multiple Dynamic Models

NASA Astrophysics Data System (ADS)

Jing, R.; Lin, N.; Emanuel, K.; Vecchi, G. A.; Knutson, T. R.

2017-12-01

A Markov environment-dependent hurricane intensity model (MeHiM) is developed to simulate the climatology of hurricane intensity given the surrounding large-scale environment. The model considers three unobserved discrete states representing respectively storm's slow, moderate, and rapid intensification (and deintensification). Each state is associated with a probability distribution of intensity change. The storm's movement from one state to another, regarded as a Markov chain, is described by a transition probability matrix. The initial state is estimated with a Bayesian approach. All three model components (initial intensity, state transition, and intensity change) are dependent on environmental variables including potential intensity, vertical wind shear, midlevel relative humidity, and ocean mixing characteristics. This dependent Markov model of hurricane intensity shows a significant improvement over previous statistical models (e.g., linear, nonlinear, and finite mixture models) in estimating the distributions of 6-h and 24-h intensity change, lifetime maximum intensity, and landfall intensity, etc. Here we compare MeHiM with various dynamical models, including a global climate model [High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR)], a regional hurricane model (Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model), and a simplified hurricane dynamic model [Coupled Hurricane Intensity Prediction System (CHIPS)] and its newly developed fast simulator. The MeHiM developed based on the reanalysis data is applied to estimate the intensity of simulated storms to compare with the dynamical-model predictions under the current climate. The dependences of hurricanes on the environment under current and future projected climates in the various models will also be compared statistically.

Lysimetric evaluation of simplified surface energy balance approach in the Texas high plains

USGS Publications Warehouse

Gowda, P.H.; Senay, G.B.; Howell, T.A.; Marek, T.H.

2009-01-01

Numerous energy balance (EB) algorithms have been developed to make use of remote sensing data to estimate evapotranspiration (ET) regionally. However, most EB models are complex to use and efforts are being made to simplify procedures mainly through the scaling of reference ET. The Simplified Surface Energy Balance (SSEB) is one such method. This approach has never been evaluated using measured ET data. In this study, the SSEB approach was applied to 14 Landsat TM images covering a major portion of the Southern High Plains that were acquired during 2006 and 2007 cropping seasons. Performance of the SSEB was evaluated by comparing estimated ET with measured daily ET from four large monolithic lysimeters at the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas. Statistical evaluation of results indicated that the SSEB accounted for 84% of the variability in the measured ET values with a slope and intercept of 0.75 and 1.1 mm d-1, respectively. Considering the minimal amount of ancillary data required and excellent performance in predicting daily ET, the SSEB approach is a promising tool for mapping ET in the semiarid Texas High Plains and in other parts of the world with similar hydro-climatic conditions.

Lysimetric Evaluation of Simplified Surface Energy Balance Approach in the Texas High Plains

USGS Publications Warehouse

Senay, Gabriel B.; Gowda, P.H.; Howell, T.A.; Marek, T.H.

2009-01-01

Numerous energy balance (EB) algorithms have been developed to make use of remote sensing data to estimate evapotranspiration (ET) regionally. However, most EB models are complex to use and efforts are being made to simplify procedures mainly through the scaling of reference ET. The Simplified Surface Energy Balance (SSEB) is one such method. This approach has never been evaluated using measured ET data. In this study, the SSEB approach was applied to fourteen Landsat TM images covering a major portion of the Southern High Plains that were acquired during 2006 and 2007 cropping seasons. Performance of the SSEB was evaluated by comparing estimated ET with measured daily ET from four large monolithic lysimeters at the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas. Statistical evaluation of results indicated that the SSEB accounted for 84% of the variability in the measured ET values with a slope and intercept of 0.75 and 1.1 mm d-1, respectively. Considering the minimal amount of ancillary data required and excellent performance in predicting daily ET, the SSEB approach is a promising tool for mapping ET in the semiarid Texas High Plains and in other parts of the world with similar hydro-climatic conditions.

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.

2003-01-01

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.

1997-01-01

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Evaluating Secondary Inorganic Aerosols in Three Dimensions

NASA Technical Reports Server (NTRS)

Mezuman, Keren; Bauer, Susanne E.; Tsigaridis, Kostas

2016-01-01

The spatial distribution of aerosols and their chemical composition dictates whether aerosols have a cooling or a warming effect on the climate system. Hence, properly modeling the three-dimensional distribution of aerosols is a crucial step for coherent climate simulations. Since surface measurement networks only give 2-D data, and most satellites supply integrated column information, it is thus important to integrate aircraft measurements in climate model evaluations. In this study, the vertical distribution of secondary inorganic aerosol (i.e., sulfate, ammonium, and nitrate) is evaluated against a collection of 14 AMS flight campaigns and surface measurements from 2000 to 2010 in the USA and Europe. GISS ModelE2 is used with multiple aerosol microphysics (MATRIX, OMA) and thermodynamic (ISORROPIA II, EQSAM) configurations. Our results show that the MATRIX microphysical scheme improves the model performance for sulfate, but that there is a systematic underestimation of ammonium and nitrate over the USA and Europe in all model configurations. In terms of gaseous precursors, nitric acid concentrations are largely underestimated at the surface while overestimated in the higher levels of the model. Heterogeneous reactions on dust surfaces are an important sink for nitric acid, even high in the troposphere. At high altitudes, nitrate formation is calculated to be ammonia limited. The underestimation of ammonium and nitrate in polluted regions is most likely caused by a too simplified treatment of the NH3/NH4(+) partitioning which affects the HNO3/NO3(-) partitioning.

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

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

Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana

The recent International Panel on Climate change (IPCC) report identifies significant co-benefits from climate policies on near-term ambient air pollution and related human health outcomes [1]. This is increasingly relevant for policy making as the health impacts of air pollution are a major global concern- the Global Burden of Disease (GBD) study identifies outdoor air pollution as the sixth major cause of death globally [2]. Integrated assessment models (IAMs) are an effective tool to evaluate future air pollution outcomes across a wide range of assumptions on socio-economic development and policy regimes. The Representative Concentration Pathways (RCPs) [3] were the firstmore » set of long-term global scenarios developed across multiple integrated assessment models that provided detailed estimates of a number of air pollutants until 2100. However these scenarios were primarily designed to cover a defined range of radiative forcing outcomes and thus did not specifically focus on the interactions of long-term climate goals on near-term air pollution impacts. More recently, [4] used the RCP4.5 scenario to evaluate the co-benefits of global GHG reductions on air quality and human health in 2030. [5-7] have further examined the interactions of more diverse pollution control regimes with climate policies. This paper extends the listed studies in a number of ways. Firstly it uses multiple IAMs to look into the co-benefits of a global climate policy for ambient air pollution under harmonized assumptions on near-term air pollution control. Multi-model frameworks have been extensively used in the analysis of climate change mitigation pathways, and the structural uncertainties regarding the underlying mechanisms (see for example [8-10]. This is to our knowledge the first time that a multi-model evaluation has been specifically designed and applied to analyze the co-benefits of climate change policy on ambient air quality, thus enabling a better understanding of at a detailed sector and region level. A second methodological advancement is a quantification of the co-benefits in terms of the associated atmospheric concentrations of fine particulate matter (PM2.5) and consequent mortality related outcomes across different models. This is made possible by the use of state-of the art simplified atmospheric model that allows for the first time a computationally feasible multi-model evaluation of such outcomes.« less

Climate change on the Colorado River: a method to search for robust management strategies

NASA Astrophysics Data System (ADS)

Keefe, R.; Fischbach, J. R.

2010-12-01

The Colorado River is a principal source of water for the seven Basin States, providing approximately 16.5 maf per year to users in the southwestern United States and Mexico. Though the dynamics of the river ensure Upper Basin users a reliable supply of water, the three Lower Basin states (California, Nevada, and Arizona) are in danger of delivery interruptions as Upper Basin demand increases and climate change threatens to reduce future streamflows. In light of the recent drought and uncertain effects of climate change on Colorado River flows, we evaluate the performance of a suite of policies modeled after the shortage sharing agreement adopted in December 2007 by the Department of the Interior. We build on the current literature by using a simplified model of the Lower Colorado River to consider future streamflow scenarios given climate change uncertainty. We also generate different scenarios of parametric consumptive use growth in the Upper Basin and evaluate alternate management strategies in light of these uncertainties. Uncertainty associated with climate change is represented with a multi-model ensemble from the literature, using a nearest neighbor perturbation to increase the size of the ensemble. We use Robust Decision Making to compare near-term or long-term management strategies across an ensemble of plausible future scenarios with the goal of identifying one or more approaches that are robust to alternate assumptions about the future. This method entails using search algorithms to quantitatively identify vulnerabilities that may threaten a given strategy (including the current operating policy) and characterize key tradeoffs between strategies under different scenarios.

Primary production sensitivity to phytoplankton light attenuation parameter increases with transient forcing

NASA Astrophysics Data System (ADS)

Kvale, Karin F.; Meissner, Katrin J.

2017-10-01

Treatment of the underwater light field in ocean biogeochemical models has been attracting increasing interest, with some models moving towards more complex parameterisations. We conduct a simple sensitivity study of a typical, highly simplified parameterisation. In our study, we vary the phytoplankton light attenuation parameter over a range constrained by data during both pre-industrial equilibrated and future climate scenario RCP8.5. In equilibrium, lower light attenuation parameters (weaker self-shading) shift net primary production (NPP) towards the high latitudes, while higher values of light attenuation (stronger shelf-shading) shift NPP towards the low latitudes. Climate forcing magnifies this relationship through changes in the distribution of nutrients both within and between ocean regions. Where and how NPP responds to climate forcing can determine the magnitude and sign of global NPP trends in this high CO2 future scenario. Ocean oxygen is particularly sensitive to parameter choice. Under higher CO2 concentrations, two simulations establish a strong biogeochemical feedback between the Southern Ocean and low-latitude Pacific that highlights the potential for regional teleconnection. Our simulations serve as a reminder that shifts in fundamental properties (e.g. light attenuation by phytoplankton) over deep time have the potential to alter global biogeochemistry.

A Reusable Framework for Regional Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and utilizing large volumes of observational data for model evaluation research. We feel that the RCMES is particularly appealing in that it represents a principled, reusable architectural approach rather than a one-off technological implementation. In fact, early RCMES prototypes have already utilized a variety of implementation technologies in an effort to address different performance and scalability concerns. This has been greatly facilitated by the fact that, at the architectural level, the RCMES is fundamentally domain agnostic. Strictly separating the data model from the implementation has enabled us to create a reusable architecture that we believe can be modified and configured to suit the demands of researchers in other domains.

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.