Sample records for hadley climate model

  1. Narrowing of the Upwelling Branch of the Brewer-Dobson Circulation and Hadley Cell in Chemistry-Climate Model Simulations of the 21st Century

    NASA Technical Reports Server (NTRS)

    Li, Feng; Stolarski, Richard S.; Pawson, Steven; Newman, Paul A.; Waugh, Darryn

    2010-01-01

    Changes in the width of the upwelling branch of the Brewer-Dobson circulation and Hadley cell in the 21st Century are investigated using simulations from a coupled chemistry-climate model. In these model simulations the tropical upwelling region narrows in the troposphere and lower stratosphere. The narrowing of the Brewer-Dobson circulation is caused by an equatorward shift of Rossby wave critical latitudes and Eliassen-Palm flux convergence in the subtropical lower stratosphere. In the troposphere, the model projects an expansion of the Hadley cell's poleward boundary, but a narrowing of the Hadley rising branch. Model results suggest that the narrowing of the Hadley cell ascent is also eddy-driven.

  2. The Dynamics of Hadley Circulation Variability and Change

    NASA Astrophysics Data System (ADS)

    Davis, Nicholas Alexander

    The Hadley circulation exerts a dominant control on the surface climate of earth's tropical belt. Its converging surface winds fuel the tropical rains, while subsidence in the subtropics dries and stabilizes the atmosphere, creating deserts on land and stratocumulus decks over the oceans. Because of the strong meridional gradients in temperature and precipitation in the subtropics, any shift in the Hadley circulation edge could project as major changes in surface climate. While climate model simulations predict an expansion of the Hadley cells in response to greenhouse gas forcings, the mechanisms remain elusive. An analysis of the climatology, variability, and response of the Hadley circulation to radiative forcings in climate models and reanalyses illuminates the broader landscape in which Hadley cell expansion is realized. The expansion is a fundamental response of the atmosphere to increasing greenhouse gas concentrations as it scales with other key climate system changes, including polar amplification, increasing static stability, stratospheric cooling, and increasing global-mean surface temperatures. Multiple measures of the Hadley circulation edge latitudes co-vary with the latitudes of the eddy-driven jets on all timescales, and both exhibit a robust poleward shift in response to forcings. Further, across models there is a robust coupling between the eddy-driving on the Hadley cells and their width. On the other hand, the subtropical jet and tropopause break latitudes, two common observational proxies for the tropical belt edges, lack a strong statistical relationship with the Hadley cell edges and have no coherent response to forcings. This undermines theories for the Hadley cell width predicated on angular momentum conservation and calls for a new framework for understanding Hadley cell expansion. A numerical framework is developed within an idealized general circulation model to isolate the mean flow and eddy responses of the global atmosphere to

  3. Temperature influence on Hadley cell dynamics

    NASA Astrophysics Data System (ADS)

    Molnos, S.

    2016-12-01

    Over the last decades, satellite observations indicate that the Hadley cells have widened and possibly also intensified [1,2]. This might lead to a shift of fertile habitats with implications for biodiversity and agriculture [3]. Causes for these observed changes are uncertain and the possible role of global warming is debated. To better understand the key dynamical forcings involved, we investigate Hadley cell dynamics with an idealized atmosphere model [4,5] and compare its results with reanalysis data. This statistical-dynamical atmosphere model (SDAM) is based on time-averaged equations, and therefore much faster than the more widely used Atmospheric general circulations models (AGCMs).With SDAMS it is possible to perform climate simulations up to multi-millennia timescales. Here, we employ it to study the dominant processes related to the observed strengthening and widening of the Hadley cell using a very large ensemble sensitivity experiment testing the following possible underlying drivers: meridional temperature gradient, temperature anomaly and global mean temperature GMT. Interestingly, whereas the width of the Hadley cell depends nonlinearly on the temperature gradient, while its Intensification is nearly independent on temperature gradient. In contrast, a larger GMT always leads to an intensified Hadley cell. References: [1] Mitas, C. M.: Has the Hadley cell been strengthening in recent decades?, Geophys. Res. Lett., 32(3), 2005. [2] Seidel, D., Fu, Q., Randel, W. and Reichler, T.: Widening of the tropical belt in a changing climate, Nat. Geosci., 1(1), 21-248, 2008. [3] Heffernan, O.: The Mystery of Expanding Tropics, Nature, 530, 20-22, 2016. [4] Coumou, D., Petoukhov, V. and Eliseev, A. V.: Three-dimensional parameterizations of the synoptic scale kinetic energy and momentum flux in the Earth's atmosphere, Nonlinear Process. Geophys., 18(6), 807-827, 2011. [5] Eliseev, A. V., Coumou, D., Chernokulsky, A. V., Petoukhov, V. and Petri, S.: Scheme for

  4. CMIP5 models' shortwave cloud radiative response and climate sensitivity linked to the climatological Hadley cell extent

    NASA Astrophysics Data System (ADS)

    Lipat, Bernard R.; Tselioudis, George; Grise, Kevin M.; Polvani, Lorenzo M.

    2017-06-01

    This study analyzes Coupled Model Intercomparison Project phase 5 (CMIP5) model output to examine the covariability of interannual Southern Hemisphere Hadley cell (HC) edge latitude shifts and shortwave cloud radiative effect (SWCRE). In control climate runs, during years when the HC edge is anomalously poleward, most models substantially reduce the shortwave radiation reflected by clouds in the lower midlatitude region (LML; ˜28°S-˜48°S), although no such reduction is seen in observations. These biases in HC-SWCRE covariability are linked to biases in the climatological HC extent. Notably, models with excessively equatorward climatological HC extents have weaker climatological LML subsidence and exhibit larger increases in LML subsidence with poleward HC edge expansion. This behavior, based on control climate interannual variability, has important implications for the CO2-forced model response. In 4×CO2-forced runs, models with excessively equatorward climatological HC extents produce stronger SW cloud radiative warming in the LML region and tend to have larger climate sensitivity values than models with more realistic climatological HC extents.

  5. Observational Evidence of the "Tightening of Hadley Ascent"

    NASA Astrophysics Data System (ADS)

    Su, H.; Wu, L.; Jiang, J. H.

    2017-12-01

    Recent studies show that the Hadley Circulation undergoes complicated structure changes under global warming (e.g., Su et al., 2014; Lau and Kim 2015; Byrne and Schneider 2016; Su et al., 2017)). Accompanied by the widening of the descent zone, a narrowing of the ascending branch of the Hadley Circulation is simulated in most climate models. The magnitude of the tightening of Hadley ascent (THA) in the models is found to be highly correlated with the decrease of tropical high cloud fraction, which is a major contributor to the inter-model spread of the longwave radiative cooling rate and the global-mean precipitation change per degree of surface warming (Su et al. 2017). While the THA is a common feature in the models, its observational evidence is limited. We have examined a number of reanalyses and satellite datasets to identify the indicators of the THA in terms of large-scale winds, water vapor, cloud and precipitation changes in the past decades. The robustness of the THA in the observations and the differences between various datasets will be presented.

  6. Climate Variability over India and Bangladesh from the Perturbed UK Met Office Hadley Model: Impacts on Flow and Nutrient Fluxes in the Ganges Delta System

    NASA Astrophysics Data System (ADS)

    Whitehead, P. G.; Caesar, J.; Crossman, J.; Barbour, E.; Ledesma, J.; Futter, M. N.

    2015-12-01

    A semi-distributed flow and water quality model (INCA- Integrated Catchments Model) has been set up for the whole of the Ganges- Brahmaputra- Meghna (GBM) River system in India and Bangladesh. These massive rivers transport large fluxes of water and nutrients into the Bay of Bengal via the GBM Delta system in Bangladesh. Future climate change will impact these fluxes with changing rainfall, temperature, evapotranspiration and soil moisture deficits being altered in the catchment systems. In this study the INCA model has been used to assess potential impacts of climate change using the UK Met Office Hadley Centre GCM model linked to a regionally coupled model of South East Asia, covering India and Bangladesh. The Hadley Centre model has been pururbed by varying the parameters in the model to generate 17 realisations of future climates. Some of these reflect expected change but others capture the more extreme potential behaviour of future climate conditions. The 17 realisations have been used to drive the INCA Flow and Nitrogen model inorder to generate downstream times series of hydrology and nitrate- nitrogen. The variability of the climates on these fluxes are investigated and and their likley impact on the Bay of Begal Delta considered. Results indicate a slight shift in the monsoon season with increased wet season flows and increased temperatures which alter nutrient fluxes. Societal Importance to Stakeholders The GBM Delta supports one of the most densely populated regions of people living in poverty, who rely on ecosystem services provided by the Delta for survival. These ecosystem services are dependent upon fluxes of water and nutrients. Freshwater for urban, agriculture, and aquaculture requirements are essential to livelihoods. Nutrient loads stimulate estuarine ecosystems, supporting fishing stocks, which contribute significantly the economy of Bangladesh. Thus the societal importance of upstream climate driven change change in Bangladesh are very

  7. Possible Role of Hadley Circulation Strengthening in Interdecadal Intensification of Snowfalls Over Northeastern China Under Climate Change

    NASA Astrophysics Data System (ADS)

    Zhou, Botao; Wang, Zunya; Shi, Ying

    2017-11-01

    This article revealed that strengthening of winter Hadley circulation in the context of climate change may partially contribute to interdecadal increasing of snowfall intensity over northeastern China in recent decades. This hypothesis is well supported by the process-based linkage between Hadley circulation and atmospheric circulations over the Asian-Pacific region on the interdecadal time scale. The strengthening of winter Hadley circulation corresponds to a weakening of the Siberian high, an eastward shifting of the Aleutian low, a reduction of the East Asian trough, and anomalous southwesterly prevailing over northeastern China. These atmospheric situations weaken the East Asian winter monsoon and lead to an increase of air temperature over northeastern China. Increased local evaporation due to the increase of air temperature, concurrent with more water vapor transported from the Pacific Ocean, can significantly enhance atmospheric water vapor content in the target region. Meanwhile, the ascending of airflows is also strengthened over northeastern China. All of these provide favorable interdecadal backgrounds for the occurrence of intense snowfalls, and thus, snowfall intensity is intensified over northeastern China after the 1980s. Further analysis suggests that the circum-Pacific-like teleconnection pattern may play an important role in connecting Hadley circulation strengthening signal and atmospheric circulation anomalies favoring interdecadal intensification of snowfalls over northeastern China.

  8. Hadley circulation extent and strength in a wide range of simulated climates

    NASA Astrophysics Data System (ADS)

    D'Agostino, Roberta; Adam, Ori; Lionello, Piero; Schneider, Tapio

    2017-04-01

    Understanding the Hadley circulation (HC) dynamics is crucial because its changes affect the seasonal migration of the ITCZ, the extent of subtropical arid regions and the strength of the monsoons. Despite decades of study, the factors controlling its strength and extent have remained unclear. Here we analyse how HC strength and extent change over a wide range of climate conditions from the Last Glacial Maximum to future projections. The large climate change between paleoclimate simulations and future scenarios offers the chance to analyse robust HC changes and their link to large-scale factors. The HC shrinks and strengthens in the coldest simulation relative to the warmest. A progressive poleward shift of its edges is evident as the climate warms (at a rate of 0.35°lat./K in each hemisphere). The HC extent and strength both depend on the isentropic slope, which in turn is related to the meridional temperature gradient, subtropical static stability and tropopause height. In multiple robust regression analysis using these as predictors, we find that the tropical tropopause height does not add relevant information to the model beyond surface temperature. Therefore, primarily the static stability and secondarily the meridional temperature contrast together account for the bulk of the almost the total HC variance. However, the regressions leave some of the northern HC edge and southern HC strength variance unexplained. The effectiveness of this analysis is limited by the correlation among the predictors and their relationship with mean temperature. In fact, for all simulations, the tropical temperature explains well the variations of HC except its southern hemisphere intensity. Hence, it can be used as the sole predictor to diagnose the HC response to greenhouse-induced global warming. How to account for the evolution of the southern HC strength remains unclear, because of the large inter-model spread in this quantity.

  9. The Interplay of Internal and Forced Modes of Hadley Cell Expansion: Lessons from the Global Warming Hiatus

    NASA Astrophysics Data System (ADS)

    Amaya, D. J.; Siler, N.; Xie, S. P.; Miller, A. J.

    2017-12-01

    The poleward branches of the Hadley Cells show a robust shift poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe's subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we us a joint EOF method to identify two distinct modes of Hadley Cell variability: (i) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (ii) an internal mode, which identify using a 1000-year pre-industrial control simulation with a global climate model. The forced mode is found to be closely related to the TOA radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is found to be essentially indistinguishable from the El Niño Southern Oscillation (ENSO). Together these two modes explain an average of 70% of the interannual variability seen in model "edge indices" over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the "hiatus"). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere (SH), but not in the Northern Hemisphere (NH), with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of Hadley Cell width change and improve our understanding of the interannual variability and long-term trend seen in observations.

  10. The dynamics of the Snowball Earth Hadley circulation for off-equatorial and seasonally varying insolation

    NASA Astrophysics Data System (ADS)

    Voigt, A.

    2013-11-01

    I study the Hadley circulation of a completely ice-covered Snowball Earth through simulations with a comprehensive atmosphere general circulation model. Because the Snowball Earth atmosphere is an example of a dry atmosphere, these simulations allow me to test to what extent dry theories and idealized models capture the dynamics of realistic dry Hadley circulations. Perpetual off-equatorial as well as seasonally varying insolation is used, extending a previous study for perpetual on-equatorial (equinox) insolation. Vertical diffusion of momentum, representing the momentum transport of dry convection, is fundamental to the momentum budgets of both the winter and summer cells. In the zonal budget, it is the primary process balancing the Coriolis force. In the meridional budget, it mixes meridional momentum between the upper and the lower branch and thereby decelerates the circulation. Because of the latter, the circulation intensifies by a factor of three when vertical diffusion of momentum is suppressed. For seasonally varying insolation, the circulation undergoes rapid transitions from the weak summer into the strong winter regime. Consistent with previous studies in idealized models, these transitions result from a mean-flow feedback, because of which they are insensitive to the treatment of vertical diffusion of momentum. Overall, the results corroborate previous findings for perpetual on-equatorial insolation. They demonstrate that descriptions of realistic dry Hadley circulations, in particular their strength, need to incorporate the vertical momentum transport by dry convection, a process that is neglected in most dry theories and idealized models. An improved estimate of the strength of the Snowball Earth Hadley circulation will also help to better constrain the climate of a possible Neoproterozoic Snowball Earth and its deglaciation threshold.

  11. The dynamics of the Snowball Earth Hadley circulation for off-equatorial and seasonally-varying insolation

    NASA Astrophysics Data System (ADS)

    Voigt, A.

    2013-08-01

    I study the Hadley circulation of a completely ice-covered Snowball Earth through simulations with a comprehensive atmosphere general circulation model. Because the Snowball Earth atmosphere is an example of a dry atmosphere, these simulations allow me to test to what extent dry theories and idealized models capture the dynamics of dry Hadley circulations. Perpetual off-equatorial as well as seasonally-varying insolation is used, extending a previous study for perpetual on-equatorial (equinox) insolation. Vertical diffusion of momentum, representing the momentum transport of dry convection, is fundamental to the momentum budgets of both the winter and summer cells. In the zonal budget, it is the primary process balancing the Coriolis force. In the meridional budget, it mixes meridional momentum between the upper and the lower branch and thereby decelerates the circulation. Because of the latter, the circulation intensifies by a factor of three when vertical diffusion of momentum is suppressed. For seasonally-varying insolation, the circulation undergoes rapid transitions from the weak summer into the strong winter regime. Consistent with previous studies in idealized models, these transitions result from a mean-flow feedback, because of which they are insensitive to the treatment of vertical diffusion of momentum. Overall, the results corroborate previous findings for perpetual on-equatorial insolation. They demonstrate that an appropriate description of dry Hadley circulations, in particular their strength, needs to incorporate the vertical momentum transport by dry convection, a process that is neglected in most dry theories and idealized models. An improved estimate of the strength of the Snowball Earth Hadley circulation will also help to better constrain the climate of a possible Neoproterozoic Snowball Earth and its deglaciation threshold.

  12. Hadley cell dynamics of a cold and virtually dry Snowball Earth atmosphere

    NASA Astrophysics Data System (ADS)

    Voigt, Aiko; Held, Isaac; Marotzke, Jochem

    2010-05-01

    We use the full-physics atmospheric general circulation model ECHAM5 to investigate a cold and virtually dry Snowball Earth atmosphere that results from specifying sea ice as the surface boundary condition everywhere, corresponding to a frozen aquaplanet, while keeping total solar irradiance at its present-day value of 1365 Wm-2. The aim of this study is the investigation of the zonal-mean circulation of a Snowball Earth atmosphere, which, due to missing moisture, might constitute an ideal though yet unexplored testbed for theories of atmospheric dynamics. To ease comparison with theories, incoming solar insolation follows permanent equinox conditions with disabled diurnal cycle. The meridional circulation consists of a thermally direct cell extending from the equator to 45 N/S with ascent in the equatorial region, and a weak thermally indirect cell with descent between 45 and 65 N/S and ascent in the polar region. The former cell corresponds to the present-day Earth's Hadley cell, while the latter can be viewed as an eddy-driven Ferrell cell; the present-day Earth's direct polar cell is missing. The Hadley cell itself is subdivided into a vigorous cell confined to the troposphere and a weak deep cell reaching well into the stratosphere. The dynamics of the vigorous Snowball Earth Hadley cell differ substantially from the dynamics of the present-day Hadley cell. The zonal momentum balance shows that in the poleward branch of the vigorous Hadley cell, mean flow meridional advection of absolute vorticity is not only balanced by eddy momentum flux convergence but also by vertical diffusion. Inside the poleward branch, eddies are more important in the upper part and vertical diffusion is more important in the lower part. Vertical diffusion also contributes to the meridional momentum balance as it decelerates the vigorous Hadley cell by downgradient momentum mixing between its poleward and equatorward branch. Zonal winds, therefore, are not in thermal wind balance in

  13. Evidence for Interannual to Decadal Variations in Hadley and Walker Circulations and Links to Water and Energy Fluxes

    NASA Technical Reports Server (NTRS)

    Robertson, Franklin; Bosilovich, Michael; Miller, Timothy

    2007-01-01

    Mass and energy transports associated with the Hadley and Walker circulations are important components of the earth s climate system and are strongly linked to hydrologic processes. Interannual to decadal variation in these flows likely signify a combination of natural climate noise as well as a response to anthropgenic forcing. There remains considerable uncertainty in quantifying variations in these flows. Evidence in the surface pressure record supports a weakening of the Walker circulation over the Pacific in recent decades. Conversely the NCEP / NCAR and ERA 40 reanalyses indicate that the Hadley circulation has increased in strength over the last two decades, though these analyses depict significantly different mass circulation changes. Interestingly, the NCEP - II / DOE reanalysis contains essentially no Hadley circulation changes. Most climate model integrations anticipate a weakening of both tropical circulations associated with stronger static stability. Clearly there is much uncertainty not only with the mass transports, but also how they are linked to water and energy balance of the planet through variations in turbulent heat and radiative fluxes and horizontal exports / imports of energy. Here we examine heat and water budget variations from a number of reanalysis products and focus on the linear and nonlinear response of ENSO warm and cold events as opportunities to study budget variations over the past 15-20 years. Our analysis addresses such questions as To what extent do Hadley and Walker Cell variations compensate each other on mass and energy transport? Do static stability adjustments appear to constrain fractional precipitation response vs. fractional water vapor response? We appeal to constraints offered by GPCP precipitation, SSWI ocean evaporation estimates, and ISCCP-FD radiative fluxes, and other satellite data sets to interpret and confirm reanalysis-based diagnostics. Using our findings we also attempt to place in context the recent

  14. Hadley circulation strength and width in a wide range of simulated climates

    NASA Astrophysics Data System (ADS)

    D'Agostino, R.; Adam, O.; Lionello, P.; Schneider, T.

    2016-12-01

    Understanding how the Hadley circulation (HC) responds to global warming is crucial because it determines climatic features such as the seasonal migration of the ITCZ, the extent of subtropical arid regions and the strength of the monsoons. Here we analyse changes in the HC strength and width in the set of PMIP3 and CMIP5 simulations, spanning a wide range of climate conditions from Last Glacial Maximum to future RCP projections. The large climate change signal emerging from comparing paleoclimate simulations to future scenarios offers the possibility to analyse the corresponding HC change and to investigate its response to large variations of the factors controlling it. The results confirm that the HC generally expands and weakens as the global mean temperature increases, consistent with results from other studies. Furthermore, we find an asymmetric HC response between the northern and southern hemisphere in the rate at which the HC edges shift poleward with global warming. The mid-latitude static stability and meridional temperature gradients affect the HC edges to different degrees in the two hemispheres. In the southern hemisphere the increase in the mid-latitude static stability is associated with a poleward shift of the southern HC edge, while in the northern hemisphere, the reduction in the meridional temperature gradient plays the dominant role in the poleward shift of the northern HC edge. The two hemispheres also exhibit very different changes of HC strength. The HC weakening with global warming occurs primarily in the northern hemisphere, while there is no change, or even a slighter weakening in the southern hemisphere. The HC changes also have pronounced seasonal signatures. The maximum poleward shift of the northern HC edge occurs one month later (from August to September) in future global warming scenarios than when comparing pre-industrial simulations with the Last Glacial Maximum.

  15. Analysis of bullwhip effect on supply chain with Q model using Hadley-Within approach

    NASA Astrophysics Data System (ADS)

    Siregar, I.; Nasution, A. A.; Matondang, N.; Persada, M. R.; Syahputri, K.

    2018-02-01

    This research held on a tapioca flour industry company that uses cassava as raw material to produce tapioca starch product. Problems that occur in this company is inaccurate planning, consequently there is a shortage of variation between the number of requests with the total supply is met, so it is necessary to do research with the formulation of the problem that is how to analyze the Bullwhip Effect on the supply chain using Q model through Hadley-Within approach so as not to disturb the product distribution system at the company. Product distribution system at the company, obtained by the number of requests. The 2015 forecast result is lower than actual demand for distributors and manufactures in 2016 with average percentage difference for Supermarket A distributor, Supermarket B and manufacturing respectively 38.24%, 89.57% and 43.11%. The occurrence of information distortion to the demand of this product can identify the existence of bullwhip effect on the supply chain. The proposed improvement to overcome the bullwhip effect is by doing inventory control policy with Q model using Hadley-Within approach.

  16. A transient stochastic weather generator incorporating climate model uncertainty

    NASA Astrophysics Data System (ADS)

    Glenis, Vassilis; Pinamonti, Valentina; Hall, Jim W.; Kilsby, Chris G.

    2015-11-01

    Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called 'perturbed physics ensembles' (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.

  17. Trends and variability in the Hadley circulation over the Last Millennium from the proxy record

    NASA Astrophysics Data System (ADS)

    Horlick, K. A.; Noone, D.; Hakim, G. J.; Tardif, R.; Anderson, D. M.; Perkins, W. A.; Erb, M. P.; Steig, E. J.

    2017-12-01

    The Hadley circulation (HC) is the dominant atmospheric overturning circulation controlling variability in precipitation distribution in the tropics and subtropics, affecting agricultural production and water resource allocation, among other human civilizational dependencies. A lack of pre-instrumental data-model synthesis has been cited as the barrier to diagnostic analyses of the variability in width, position, and intensity of the HC and its response to anthropogenic forcing. We analyze the HC, and its rising limb associated with the Intertropical Convergence Zone (ITCZ), over the past 1000 years using the Last Millennium Reanalysis (LMR) (Hakim et al. 2016). The LMR systematically blends the dynamical constraints of climate models with a proxy network of coral, tree ring, and ice core records. It allows for a spatiotemporal analysis with robust uncertainty measures. A three dimensional analysis of LMR wind fields shows an centennial-scale circulatory trend over the last 200 years resembling that which might be expected from an ENSO and PDO-like structure. An observed aridification of both the central equatorial Pacific and the southwest United States, a strengthening of the east-west sea surface temperature and sea level pressure gradient in the equatorial Pacific, and a strengthening of the Walker overturning circulation suggest a more "La Niña-like" mean state. This is compared to our statistical description of the centennial-scale mean circulation and variability of the previous millennia. Similarly, precipitation and relative humidity trends suggest expansion and asymmetric meridional movement of the Hadley circulation as a result of asymmetric shifts in mean ITCZ position and intensity. These observations are then compared to free running model simulations, other instrumental reanalysis products, and late-Holocene aerosol, solar, and greenhouse forcings. This LMR reconstruction improves upon previous work by enabling a proxy-consistent, quantitative

  18. The 1997/98 El Nino: A Test for Climate Models

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

    Lu, R; Dong, B; Cess, R D

    Version 3 of the Hadley Centre Atmospheric Model (HadAM3) has been used to demonstrate one means of comparing a general circulation model with observations for a specific climate perturbation, namely the strong 1997/98 El Nino. This event was characterized by the collapse of the tropical Pacific's Walker circulation, caused by the lack of a zonal sea surface temperature gradient during the El Nino. Relative to normal years, cloud altitudes were lower in the western portion of the Pacific and higher in the eastern portion. HadAM3 likewise produced the observed collapse of the Walker circulation, and it did a reasonable jobmore » of reproducing the west/east cloud structure changes. This illustrates that the 1997/98 El Nino serves as a useful means of testing cloud-climate interactions in climate models.« less

  19. A Robust Response of the Hadley Circulation to Global Warming

    NASA Technical Reports Server (NTRS)

    Lau, William K M.; Kim, Kyu-Myong

    2014-01-01

    Tropical rainfall is expected to increase in a warmer climate. Yet, recent studies have inferred that the Hadley Circulation (HC), which is primarily driven by latent heating from tropical rainfall, is weakened under global warming. Here, we show evidence of a robust intensification of the HC from analyses of 33 CMIP5 model projections under a scenario of 1 per year CO2 emission increase. The intensification is manifested in a deep-tropics squeeze, characterized by a pronounced increase in the zonal mean ascending motion in the mid and upper troposphere, a deepening and narrowing of the convective zone and enhanced rainfall in the deep tropics. These changes occur in conjunction with a rise in the region of maximum outflow of the HC, with accelerated meridional mass outflow in the uppermost branch of the HC away from the equator, coupled to a weakened inflow in the return branches of the HC in the lower troposphere.

  20. Apollo 15 at Hadley Base.

    ERIC Educational Resources Information Center

    National Aeronautics and Space Administration, Washington, DC.

    This publication highlights the mission of Apollo 15 and includes many detailed black and white and color photographs taken near the lunar Apennine Mountains and the mile-wide, meandering Hadley Rille. Some of the photographs are full page (9 by 12 inch) reproductions. (Author/PR)

  1. The Hadley circulation: assessing NCEP/NCAR reanalysis and sparse in-situ estimates

    NASA Astrophysics Data System (ADS)

    Waliser, D. E.; Shi, Zhixiong; Lanzante, J. R.; Oort, A. H.

    We present a comparison of the zonal mean meridional circulations derived from monthly in situ data (i.e. radiosondes and ship reports) and from the NCEP/NCAR reanalysis product. To facilitate the interpretation of the results, a third estimate of the mean meridional circulation is produced by subsampling the reanalysis at the locations where radiosonde and surface ship data are available for the in situ calculation. This third estimate, known as the subsampled estimate, is compared to the complete reanalysis estimate to assess biases in conventional, in situ estimates of the Hadley circulation associated with the sparseness of the data sources (i.e., radiosonde network). The subsampled estimate is also compared to the in situ estimate to assess the biases introduced into the reanalysis product by the numerical model, initialization process and/or indirect data sources such as satellite retrievals. The comparisons suggest that a number of qualitative differences between the in situ and reanalysis estimates are mainly associated with the sparse sampling and simplified interpolation schemes associated with in situ estimates. These differences include: (1) a southern Hadley cell that consistently extends up to 200 hPa in the reanalysis, whereas the bulk of the circulation for the in situ and subsampled estimates tends to be confined to the lower half of the troposphere, (2) more well-defined and consistent poleward limits of the Hadley cells in the reanalysis compared to the in-situ and subsampled estimates, and (3) considerably less variability in magnitude and latitudinal extent of the Ferrel cells and southern polar cell exhibited in the reanalysis estimate compared to the in situ and subsampled estimates. Quantitative comparison shows that the subsampled estimate, relative to the reanalysis estimate, produces a stronger northern Hadley cell ( 20%), a weaker southern Hadley cell ( 20-60%), and weaker Ferrel cells in both hemispheres. These differences stem from

  2. Predictions of extreme precipitation and sea-level rise under climate change.

    PubMed

    Senior, C A; Jones, R G; Lowe, J A; Durman, C F; Hudson, D

    2002-07-15

    Two aspects of global climate change are particularly relevant to river and coastal flooding: changes in extreme precipitation and changes in sea level. In this paper we summarize the relevant findings of the IPCC Third Assessment Report and illustrate some of the common results found by the current generation of coupled atmosphere-ocean general circulation models (AOGCMs), using the Hadley Centre models. Projections of changes in extreme precipitation, sea-level rise and storm surges affecting the UK will be shown from the Hadley Centre regional models and the Proudman Oceanographic Laboratory storm-surge model. A common finding from AOGCMs is that in a warmer climate the intensity of precipitation will increase due to a more intense hydrological cycle. This leads to reduced return periods (i.e. more frequent occurrences) of extreme precipitation in many locations. The Hadley Centre regional model simulates reduced return periods of extreme precipitation in a number of flood-sensitive areas of the UK. In addition, simulated changes in storminess and a rise in average sea level around the UK lead to reduced return periods of extreme high coastal water events. The confidence in all these results is limited by poor spatial resolution in global coupled models and by uncertainties in the physical processes in both global and regional models, and is specific to the climate change scenario used.

  3. View of Mount Hadley as photographed by Apollo 15 during EVA

    NASA Image and Video Library

    1971-07-31

    AS15-87-11849 (31 July-2 Aug. 1971) --- An excellent view of Mount Hadley, fully lighted, showing abundant linear features, as photographed during the Apollo 15 lunar surface extravehicular activity (EVA). This view is looking north from the Apollo Lunar Surface Experiments Package (ALSEP) site. Mount Hadley rises about 4,500 meters (approximately 14,765 feet) above the plain. While astronauts David R. Scott, commander, and James B. Irwin, lunar module pilot, descended in the Apollo 15 Lunar Module (LM) "Falcon" to explore the Hadley-Apennine area of the moon, astronaut Alfred M. Worden, command module pilot, remained with the Command and Service Modules (CSM) in lunar orbit.

  4. Artist's concept of Hadley-Apennine landing site with alternate traverses

    NASA Image and Video Library

    1971-06-01

    S71-33432 (1 July 1971) --- These alternative traverses can be carried out on foot. They will be used if the Lunar Roving Vehicle (LRV) becomes inoperative. This artist's concept showing part of the Hadley Rille and several of the Apennine Mountains was excerpted from "On the Moon with Apollo 15: A Guidebook to the Hadley-Apennine Region," by Gene Simmons. Artwork by Jerry Elmore.

  5. The morphology and origin of Hadley Rille, the moon

    NASA Technical Reports Server (NTRS)

    Brewer, T.

    1976-01-01

    Hadley Rille is directly related to the emplacement of mare basalts in Palus Putredinis. Existing hypotheses of sinuous rille origin are in discord with the cooling behavior of deep lava flows and the strength of materials. It is proposed that Hadley Rille is a channel which returned lava to the southern vent from which it initially extruded and that the channel persisted through many episodes of volcanism. This view is supported by available topographic information obtained by the lunar orbiter photography and the Apollo 15 mission.

  6. Socioeconomic impacts of climate change on U.S. water supplies

    USGS Publications Warehouse

    Frederick, K.D.; Schwarz, G.E.

    1999-01-01

    A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.

  7. Potential effects of climate change on ground water in Lansing, Michigan

    USGS Publications Warehouse

    Croley, T.E.; Luukkonen, C.L.

    2003-01-01

    Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri-County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.

  8. The interplay of internal and forced modes of Hadley Cell expansion: lessons from the global warming hiatus

    NASA Astrophysics Data System (ADS)

    Amaya, Dillon J.; Siler, Nicholas; Xie, Shang-Ping; Miller, Arthur J.

    2017-09-01

    The poleward branches of the Hadley Cells and the edge of the tropics show a robust poleward shift during the satellite era, leading to concerns over the possible encroachment of the globe's subtropical dry zones into currently temperate climates. The extent to which this trend is caused by anthropogenic forcing versus internal variability remains the subject of considerable debate. In this study, we use a Joint EOF method to identify two distinct modes of tropical width variability: (1) an anthropogenically-forced mode, which we identify using a 20-member simulation of the historical climate, and (2) an internal mode, which we identify using a 1000-year pre-industrial control simulation. The forced mode is found to be closely related to the top of the atmosphere radiative imbalance and exhibits a long-term trend since 1860, while the internal mode is essentially indistinguishable from the El Niño Southern Oscillation. Together these two modes explain an average of 70% of the interannual variability seen in model "edge indices" over the historical period. Since 1980, the superposition of forced and internal modes has resulted in a period of accelerated Hadley Cell expansion and decelerated global warming (i.e., the "hiatus"). A comparison of the change in these modes since 1980 indicates that by 2013 the signal has emerged above the noise of internal variability in the Southern Hemisphere, but not in the Northern Hemisphere, with the latter also exhibiting strong zonal asymmetry, particularly in the North Atlantic. Our results highlight the important interplay of internal and forced modes of tropical width change and improve our understanding of the interannual variability and long-term trend seen in observations.

  9. Water Vapor Feedbacks to Climate Change

    NASA Technical Reports Server (NTRS)

    Rind, David

    1999-01-01

    The response of water vapor to climate change is investigated through a series of model studies with varying latitudinal temperature gradients, mean temperatures, and ultimately, actual climate change configurations. Questions to be addressed include: what role does varying convection have in water vapor feedback; do Hadley Circulation differences result in differences in water vapor in the upper troposphere; and, does increased eddy energy result in greater eddy vertical transport of water vapor in varying climate regimes?

  10. Mediterranean summer climate and the monsoon regimes

    NASA Astrophysics Data System (ADS)

    Baldi, M.; Crisci, A.; Dalu, G. A.; Maracchi, G.; Meneguzzo, F.; Pasqui, M.

    2003-04-01

    The Authors examine the general features of climate of the Mediterranean Region, i.e. its variability and trends in the last 40 years, and the teleconnections between Mediterranean climate and the global climate, using zonal and global indices. In particular they focus the attention on the analysis of the summer Mediterranean climate, and its variability and connection with the summer monsoon regimes. Several subregions can be distinguished in the Mediterranean for each season, and the occurrence of Mediterranean Oscillation is evident between West and East sub-basins. Precipitation and SLP fields in the Eastern basin are shown to be correlated with Mediterranean Oscillation. A total decrease of precipitation has been detected in last few years, although there are some very intense. During winter a fundamental role is played by NAO index, which, influencing the storm tracks coming from the Atlantic and passing over the Mediterranean and North Europe, it has a major role in the precipitation patterns over the Region. Moreover, temperature analysis over the last 40 years in the Mediterranean shows a distinct warming, in agreement with the pattern over North Emisphere and NAO index fluctuations. During summer the Hadley cell extend further northwards, influencing the Mediterranean climate, and there is evidence of a possible teleconnection with the Asian Monsoon, and the Sahel precipitation (and related Hadley cell): the SLP field in the Eastern Mediterranean is inversely correlated with those two precipitation indices, while it is positively correlated with the pressure in the Western Mediterranean. Leading mechanisms of interaction between Mediterranean summer rainfall and SLP patterns and precipitation indices associated with monsoon regimes are stressed out and investigated, as well as the influence of the position and strength of the Hadley cell, by means of both statistical and dynamical analytical arguments. A modeling study has been carried out in order to

  11. View of Hadley-Apennine area, looking north, photographed by Apollo 15

    NASA Technical Reports Server (NTRS)

    1971-01-01

    An oblique view of the Hadley-Apennine area, looking north, as photographed by the Fairchild metric camera in the SIM bay of the Apollo 15 Command/Service Module in lunar orbit. Hadley Rille meanders through the lower center of the picture. The Apennine Mountains are at lower right. The Apollo 15 Lunar Module touchdown point is on the east side of the 'chicken beak' of Hadley Rille. The Caucasus Mountains are at upper right. The dark mare area at the extreme upper right is a portion of the Sea of Serenity. The Marsh of Decay is at lower left. The large crater near the horizon is Aristillus, which is about 55 kilometers (34.18 statute miles) in diameter. The crater just to the south of Aristillus is Autolycus, which is about 40 kilometers (35 statute miles) in diameter. The crater Cassini is barely visible on the horizon at upper right.

  12. Volcano and ship tracks indicate excessive aerosol-induced cloud water increases in a climate model.

    PubMed

    Toll, Velle; Christensen, Matthew; Gassó, Santiago; Bellouin, Nicolas

    2017-12-28

    Aerosol-cloud interaction is the most uncertain mechanism of anthropogenic radiative forcing of Earth's climate, and aerosol-induced cloud water changes are particularly poorly constrained in climate models. By combining satellite retrievals of volcano and ship tracks in stratocumulus clouds, we compile a unique observational dataset and confirm that liquid water path (LWP) responses to aerosols are bidirectional, and on average the increases in LWP are closely compensated by the decreases. Moreover, the meteorological parameters controlling the LWP responses are strikingly similar between the volcano and ship tracks. In stark contrast to observations, there are substantial unidirectional increases in LWP in the Hadley Centre climate model, because the model accounts only for the decreased precipitation efficiency and not for the enhanced entrainment drying. If the LWP increases in the model were compensated by the decreases as the observations suggest, its indirect aerosol radiative forcing in stratocumulus regions would decrease by 45%.

  13. Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

    NASA Technical Reports Server (NTRS)

    Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

    2014-01-01

    The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

  14. An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

    NASA Astrophysics Data System (ADS)

    Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

    2003-12-01

    Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

  15. Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

    NASA Astrophysics Data System (ADS)

    Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

    2018-01-01

    This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

  16. Artist's concept of Hadley-Apennine landing site with LRV traverses outlined

    NASA Image and Video Library

    1971-06-01

    S71-33433 (1 July 1971) --- An artist's concept of the Hadley-Apennine landing site, depicting the traverses planned on the Apollo 15 lunar landing mission using the Lunar Roving Vehicle (LRV). The Roman numerals indicate the three periods of extravehicular activity (EVA). The Arabic numbers represent the station stops. This artist's concept was excerpted from "On the Moon with Apollo 15: A Guidebook to Hadley Rille and the Apennine Mountains," by Gene Simmons. The station stops indicated here are keyed to information given in the publication. Artwork by Jerry Elmore.

  17. Volcano and Ship Tracks Indicate Excessive Aerosol-Induced Cloud Water Increases in a Climate Model

    NASA Astrophysics Data System (ADS)

    Toll, Velle; Christensen, Matthew; Gassó, Santiago; Bellouin, Nicolas

    2017-12-01

    Aerosol-cloud interaction is the most uncertain mechanism of anthropogenic radiative forcing of Earth's climate, and aerosol-induced cloud water changes are particularly poorly constrained in climate models. By combining satellite retrievals of volcano and ship tracks in stratocumulus clouds, we compile a unique observational data set and confirm that liquid water path (LWP) responses to aerosols are bidirectional, and on average the increases in LWP are closely compensated by the decreases. Moreover, the meteorological parameters controlling the LWP responses are strikingly similar between the volcano and ship tracks. In stark contrast to observations, there are substantial unidirectional increases in LWP in the Hadley Centre climate model, because the model accounts only for the decreased precipitation efficiency and not for the enhanced entrainment drying. If the LWP increases in the model were compensated by the decreases as the observations suggest, its indirect aerosol radiative forcing in stratocumulus regions would decrease by 45%.

  18. Geoengineering by stratospheric SO2 injection: results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE

    NASA Astrophysics Data System (ADS)

    Jones, A.; Haywood, J.; Boucher, O.; Kravitz, B.; Robock, A.

    2010-03-01

    We examine the response of the Met Office Hadley Centre's HadGEM2-AO climate model to simulated geoengineering by continuous injection of SO2 into the lower stratosphere, and compare the results with those from the Goddard Institute for Space Studies ModelE. The HadGEM2 simulations suggest that the SO2 injection rate considered here (5 Tg[SO2] yr-1) could defer the amount of global warming predicted under the Intergovernmental Panel on Climate Change's A1B scenario by approximately 30-35 years, although both models indicate rapid warming if geoengineering is not sustained. We find a broadly similar geographic distribution of the response to geoengineering in both models in terms of near-surface air temperature and mean June-August precipitation. The simulations also suggest that significant changes in regional climate would be experienced even if geoengineering was successful in maintaining global-mean temperature near current values.

  19. 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

  20. View of Hadley-Apennine area, looking north, photographed by Apollo 15

    NASA Image and Video Library

    1971-08-25

    S71-44667 (31 July-2 Aug. 1971) --- An oblique view of the Hadley-Apennine area, looking north, as photographed by the Fairchild metric camera in the Scientific Instrumentation Module (SIM) bay of the Apollo 15 Command and Service Modules (CSM) in lunar orbit. Hadley Rille meanders through the lower center of the picture. The Apennine Mountains are at lower right. The Apollo 15 Lunar Module (LM) touchdown point is on the east side of the "chicken beak" of Hadley Rille. The Caucasus Mountains are at upper right. The dark mare area at the extreme upper right is a portion of the Sea of Serenity. The Marsh of Decay is at lower left. The large crater near the horizon is Aristillus, which is about 55 kilometers (34.18 statute miles) in diameter. The crater just to the south of Aristillus is Autolycus, which is about 40 kilometers (25 statute miles) in diameter. The crater Cassini is barely visible on the horizon at upper right. The three-inch mapping camera was one of eight lunar orbital science experiments mounted in the SIM bay.

  1. The formation of Hadley Rille and implications for the geology of the Apollo 15 region

    NASA Technical Reports Server (NTRS)

    Spudis, Paul D.; Swann, Gordon A.; Greeley, Ronald

    1988-01-01

    The results of studies of terrestrial lava tube systems and the regional and detailed site geology of the Apollo 15 area have been combined to develop a model for the formation of Hadley Rille. The regional geology of the Apennine bench formation and its relation to Mozart and Hadley Rilles is discussed. It is shown that the total thickness of mare basalt at the Apollo landing site is on the order of a few tens of meters, mostly less than 50 m. It is suggested that the role of thermal erosion in the development of sinuous rilles on the moon may be less important than previously assumed and that the assimilation of refractory highland rock types into mare basaltic magma is a minor lunar process.

  2. View of Hadley Delta from top hatch of Apollo 15 Lunar Module after landing

    NASA Image and Video Library

    1971-07-31

    AS15-87-11748 (31 July 1971) --- A view of Hadley Delta, looking southeasterly, as photographed from the top hatch of the Apollo 15 Lunar Module (LM) by astronaut David R. Scott, commander, during his stand-up extravehicular activity (EVA) just after the LM "Falcon" touched down at the Hadley-Apennine landing site. The prominent feature on the horizon in the center of the picture was called Silver Spur by the Apollo 15 crew men. Hadley Delta Mountain rises approximately 4,000 meters (about 13,124 feet) above the plain. While astronauts Scott and James B. Irwin, lunar module pilot, descended in the LM to explore the moon, astronaut Alfred M. Worden, command module pilot, remained with the Command and Service Module's (CSM) in lunar orbit.

  3. Variability of the extent of the Hadley circulation in the southern hemisphere: a regional perspective

    NASA Astrophysics Data System (ADS)

    Nguyen, H.; Hendon, H. H.; Lim, E.-P.; Boschat, G.; Maloney, E.; Timbal, B.

    2018-01-01

    In order to understand the regional impacts of variations in the extent of the Hadley circulation in the Southern Hemisphere, regional Hadley circulations are defined in three sectors centered on the main tropical heat sources over Africa, Asia-Pacific (Maritime Continent) and the Americas. These regional circulations are defined by computing a streamfunction from the divergent component of the meridional wind. A major finding from this study is that year-to-year variability in the extent of the hemispheric Hadley circulation in the Southern Hemisphere is primarily governed by variations of the extent of the Hadley circulation in the Asia-Pacific sector, especially during austral spring and summer when there is little co-variability with the African sector, and the American sector exhibits an out of phase behavior. An expanded Hadley circulation in the Southern Hemisphere (both hemispherically and in the Asia-Pacific sector) is associated with La Niña conditions and a poleward expansion of the tropical wet zone in the Asia-Pacific sector. While La Niña also promotes expansion in the American and African sectors during austral winter, these tropical conditions tend to promote contraction in the two sectors during austral summer as a result of compensating convergence over the Americas and Africa sectors: a process driven by variations in the Walker circulation and Rossby wave trains emanating from the tropical Indian Ocean.

  4. Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

    NASA Astrophysics Data System (ADS)

    Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

    2016-02-01

    In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

  5. Potential impacts of climate change on rainfall erosivity and water availability in China in the next 100 years

    Treesearch

    Ge Sun; Steven G. McNulty; Jennifer Moore; Corey Bunch; Jian Ni

    2002-01-01

    Soil erosion and water shortages threaten China’s social and economic development in the 21st century. This paper examines how projected climate change could affect soil erosion and water availability across China. We used both historical climate data (1961-1980) and the UKMO Hadley3 climate scenario (1960-2099) to drive regional hydrology and soil erosivity models....

  6. A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

    NASA Technical Reports Server (NTRS)

    Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.; hide

    2013-01-01

    For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

  7. 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

  8. Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models

    NASA Astrophysics Data System (ADS)

    Son, Seok-Woo; Han, Bo-Reum; Garfinkel, Chaim I.; Kim, Seo-Yeon; Park, Rokjin; Abraham, N. Luke; Akiyoshi, Hideharu; Archibald, Alexander T.; Butchart, N.; Chipperfield, Martyn P.; Dameris, Martin; Deushi, Makoto; Dhomse, Sandip S.; Hardiman, Steven C.; Jöckel, Patrick; Kinnison, Douglas; Michou, Martine; Morgenstern, Olaf; O’Connor, Fiona M.; Oman, Luke D.; Plummer, David A.; Pozzer, Andrea; Revell, Laura E.; Rozanov, Eugene; Stenke, Andrea; Stone, Kane; Tilmes, Simone; Yamashita, Yousuke; Zeng, Guang

    2018-05-01

    The Southern Hemisphere (SH) zonal-mean circulation change in response to Antarctic ozone depletion is re-visited by examining a set of the latest model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project. All models reasonably well reproduce Antarctic ozone depletion in the late 20th century. The related SH-summer circulation changes, such as a poleward intensification of westerly jet and a poleward expansion of the Hadley cell, are also well captured. All experiments exhibit quantitatively the same multi-model mean trend, irrespective of whether the ocean is coupled or prescribed. Results are also quantitatively similar to those derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) high-top model simulations in which the stratospheric ozone is mostly prescribed with monthly- and zonally-averaged values. These results suggest that the ozone-hole-induced SH-summer circulation changes are robust across the models irrespective of the specific chemistry-atmosphere-ocean coupling.

  9. View of Hadley Delta from top hatch of Apollo 15 Lunar Module after landing

    NASA Technical Reports Server (NTRS)

    1971-01-01

    A view of Hadley Delta, looking southeasterly, as photographed from the top hatch of the Apollo 15 Lunar Module by Astronaut David R. Scott during his stand-up extravehicular activity just after the Lunar Module 'Falcon' touched down at the Hadly Apennine landing site. The prominent feature on the horizon in the center of the picture was called Silver Spur by the Apollo 15 crewmen. Hadley Delta mountain rises approximately 4,000 meters (about 13,124 feet) above the plain.

  10. High resolution global climate modelling; the UPSCALE project, a large simulation campaign

    NASA Astrophysics Data System (ADS)

    Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

    2014-01-01

    The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

  11. High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign

    NASA Astrophysics Data System (ADS)

    Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

    2014-08-01

    The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

  12. Amazon collapse in the next century: exploring the sensitivity to climate and model formulation uncertainties

    NASA Astrophysics Data System (ADS)

    Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.

    2007-12-01

    A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.

  13. Midlatitude Cloud Shifts, Their Primary Link to the Hadley Cell, and Their Diverse Radiative Effects

    NASA Technical Reports Server (NTRS)

    Tselioudis, George; Lipat, Bernard R.; Konsta, Dimitra; Grise, Kevin M.; Polvani, Lorenzo M.

    2016-01-01

    We investigate the interannual relationship among clouds, their radiative effects, and two key indices of the atmospheric circulation: the latitudinal positions of the Hadley cell edge and the midlatitude jet. From reanalysis data and satellite observations, we find a clear and consistent relationship between the width of the Hadley cell and the high cloud field, statistically significant in nearly all regions and seasons. In contrast, shifts of the midlatitude jet correlate significantly with high cloud shifts only in the North Atlantic region during the winter season. While in that region and season poleward high cloud shifts are associated with shortwave radiative warming, over the Southern Oceans during all seasons they are associated with shortwave radiative cooling. Finally, a trend analysis reveals that poleward high cloud shifts observed over the 1983-2009 period are more likely related to Hadley cell expansion, rather than poleward shifts of the midlatitude jets.

  14. Decadal-timescale changes of the Atlantic overturning circulation and climate in a coupled climate model with a hybrid-coordinate ocean component

    NASA Astrophysics Data System (ADS)

    Persechino, A.; Marsh, R.; Sinha, B.; Megann, A. P.; Blaker, A. T.; New, A. L.

    2012-08-01

    A wide range of statistical tools is used to investigate the decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) and associated key variables in a climate model (CHIME, Coupled Hadley-Isopycnic Model Experiment), which features a novel ocean component. CHIME is as similar as possible to the 3rd Hadley Centre Coupled Model (HadCM3) with the important exception that its ocean component is based on a hybrid vertical coordinate. Power spectral analysis reveals enhanced AMOC variability for periods in the range 15-30 years. Strong AMOC conditions are associated with: (1) a Sea Surface Temperature (SST) anomaly pattern reminiscent of the Atlantic Multi-decadal Oscillation (AMO) response, but associated with variations in a northern tropical-subtropical gradient; (2) a Surface Air Temperature anomaly pattern closely linked to SST; (3) a positive North Atlantic Oscillation (NAO)-like pattern; (4) a northward shift of the Intertropical Convergence Zone. The primary mode of AMOC variability is associated with decadal changes in the Labrador Sea and the Greenland Iceland Norwegian (GIN) Seas, in both cases linked to the tropical activity about 15 years earlier. These decadal changes are controlled by the low-frequency NAO that may be associated with a rapid atmospheric teleconnection from the tropics to the extratropics. Poleward advection of salinity anomalies in the mixed layer also leads to AMOC changes that are linked to processes in the Labrador Sea. A secondary mode of AMOC variability is associated with interannual changes in the Labrador and GIN Seas, through the impact of the NAO on local surface density.

  15. Telephoto lens view of Silver Spur in the Hadley Delta region from Apollo 15

    NASA Technical Reports Server (NTRS)

    1971-01-01

    A telephoto lens view of the prominent feature called Silver Spur in the Hadley Delta region, photographed during the Apollo 15 lunar surface extravehicular activity at the Hadley-Apennine landing site. The distance from the camera to the spur is about 10 miles. The field of view across the bottom is about one mile. Structural formations in the mountain are clearly visible. There are two major units. The upper unit is characterized by massive subunits, each one of which is approximately 200 feet deep. The lower major unit is characterized by thinner bedding and cross bedding.

  16. Spanning the Pacific Ocean through Voice-Over Internet Protocol Chat with the Hadley School for the Blind--China

    ERIC Educational Resources Information Center

    Gilson, Christie L.; Rongqiang, Xia

    2007-01-01

    Founded in 1920, the Hadley School for the Blind is known worldwide for its tuition-free distance-education courses for people who are visually impaired. Hadley's main school in the United States serves more than 9,000 students, and the overseas school in the People's Republic of China provides vital educational services to more than 1,000 Chinese…

  17. Tropical cyclogenesis in warm climates simulated by a cloud-system resolving model

    NASA Astrophysics Data System (ADS)

    Fedorov, Alexey V.; Muir, Les; Boos, William R.; Studholme, Joshua

    2018-03-01

    Here we investigate tropical cyclogenesis in warm climates, focusing on the effect of reduced equator-to-pole temperature gradient relevant to past equable climates and, potentially, to future climate change. Using a cloud-system resolving model that explicitly represents moist convection, we conduct idealized experiments on a zonally periodic equatorial β-plane stretching from nearly pole-to-pole and covering roughly one-fifth of Earth's circumference. To improve the representation of tropical cyclogenesis and mean climate at a horizontal resolution that would otherwise be too coarse for a cloud-system resolving model (15 km), we use the hypohydrostatic rescaling of the equations of motion, also called reduced acceleration in the vertical. The simulations simultaneously represent the Hadley circulation and the intertropical convergence zone, baroclinic waves in mid-latitudes, and a realistic distribution of tropical cyclones (TCs), all without use of a convective parameterization. Using this model, we study the dependence of TCs on the meridional sea surface temperature gradient. When this gradient is significantly reduced, we find a substantial increase in the number of TCs, including a several-fold increase in the strongest storms of Saffir-Simpson categories 4 and 5. This increase occurs as the mid-latitudes become a new active region of TC formation and growth. When the climate warms we also see convergence between the physical properties and genesis locations of tropical and warm-core extra-tropical cyclones. While end-members of these types of storms remain very distinct, a large distribution of cyclones forming in the subtropics and mid-latitudes share properties of the two.

  18. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

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

    PubMed

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

    2010-11-28

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

  20. Telephoto lens view of Silver Spur in the Hadley Delta region from Apollo 15

    NASA Image and Video Library

    1971-07-31

    AS15-84-11250 (31 July-2 Aug. 1971) --- A telephoto lens view of the prominent feature called Silver Spur in the Hadley Delta region, photographed during the Apollo 15 lunar surface extravehicular activity (EVA) at the Hadley-Apennine landing site. The distance from the camera to the spur is about 10 miles. The field of view across the bottom is about one mile. Structural formations in the mountain are clearly visible. There are two major units. The upper unit is characterized by massive subunits, each one of which is approximately 200 feet deep. The lower major unit is characterized by thinner bedding and cross bedding.

  1. Idealized climate change simulations with a high-resolution physical model: HadGEM3-GC2

    NASA Astrophysics Data System (ADS)

    Senior, Catherine A.; Andrews, Timothy; Burton, Chantelle; Chadwick, Robin; Copsey, Dan; Graham, Tim; Hyder, Pat; Jackson, Laura; McDonald, Ruth; Ridley, Jeff; Ringer, Mark; Tsushima, Yoko

    2016-06-01

    Idealized climate change simulations with a new physical climate model, HadGEM3-GC2 from The Met Office Hadley Centre are presented and contrasted with the earlier MOHC model, HadGEM2-ES. The role of atmospheric resolution is also investigated. The Transient Climate Response (TCR) is 1.9 K/2.1 K at N216/N96 and Effective Climate Sensitivity (ECS) is 3.1 K/3.2 K at N216/N96. These are substantially lower than HadGEM2-ES (TCR: 2.5 K; ECS: 4.6 K) arising from a combination of changes in the size of climate feedbacks. While the change in the net cloud feedback between HadGEM3 and HadGEM2 is relatively small, there is a change in sign of its longwave and a strengthening of its shortwave components. At a global scale, there is little impact of the increase in atmospheric resolution on the future climate change signal and even at a broad regional scale, many features are robust including tropical rainfall changes, however, there are some significant exceptions. For the North Atlantic and western Europe, the tripolar pattern of winter storm changes found in most CMIP5 models is little impacted by resolution but for the most intense storms, there is a larger percentage increase in number at higher resolution than at lower resolution. Arctic sea-ice sensitivity shows a larger dependence on resolution than on atmospheric physics.

  2. Artist's concept of Hadley-Apennine landing site with LRV traverses outlined

    NASA Technical Reports Server (NTRS)

    1971-01-01

    An artist's concept of the Hadley-Apennine landing site, depicting the traverses planned on the Apollo 15 lunar landing mission using the Lunar Roving Vehicle (LRV). The Roman numerals indicate the three periods of extravehicular activity (EVA). The Arabic numbers represent the station stops. Art work by Jerry Elmore.

  3. The influence of tropical heating displacements on the extratropical climate

    NASA Technical Reports Server (NTRS)

    Hou, Arthur Y.

    1993-01-01

    The hypothesis is advanced that a latitudinal shift in the tropical convective heating pattern can significantly alter temperatures in the extratropics. Results of a simplified general circulation model (GCM) show that the shift of a prescribed tropical heating toward the summer pole, on time scales longer than a few weeks, leads to a more intense cross-equatorial 'winter' Hadley circulation, enhanced upper-level tropical easterlies, and a slightly stronger subtropical winter jet, accompanied by warming at the winter middle and high latitudes as a result of increased dynamical heating. The indications are that there is a robust connection between the net dynamic heating in the extratropics and the implied changes in the subtropical wind shear resulting from adjustments in the Hadley circulation associated with convective heating displacements in the tropics. The implications are that (1) the low-frequency temporal variability in the Hadley circulation may play an important role in modulating wave transport in the winter extratropics, (2) the global climate may be sensitive to those processes that control deep cumulus convection in the tropics, and (3) systematic temperature biases in GCMs may be reduced by improving the tropical rainfall simulation.

  4. Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

    NASA Astrophysics Data System (ADS)

    Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

    2018-05-01

    A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

  5. The impact of equilibrating hemispheric albedos on tropical performance in the HadGEM2-ES coupled climate model

    DOE PAGES

    Haywood, Jim M.; Jones, Andy; Dunstone, Nick; ...

    2016-01-14

    Despite the fact that the southern hemisphere contains a far greater proportion of dark ocean than the northern hemisphere, the total amount of sunlight reflected from the hemispheres is equal. However, the majority of climate models do not adequately represent this equivalence. Here we examine the impact of equilibrating hemispheric albedos by various idealised methods in a comprehensive coupled climate model and find significant improvements in what have been considered longstanding and apparently intractable model biases. Monsoon precipitation biases almost vanish over all continental land areas, the penetration of monsoon rainfall across the Sahel and the west African monsoon “jump”more » become well represented, and indicators of hurricane frequency are significantly improved. The results appear not to be model specific, implying that hemispheric albedo equivalence may provide a fundamental constraint for climate models that must be satisfied if the dynamics driving these processes, in particular the strength of the Hadley cell, are to be adequately represented. Cross-equatorial energy transport is implicated as a crucial component that must be accurately modelled in coupled general circulation models. The results also suggest that the commonly used practice of prescribing sea-surface temperatures in models provides a less accurate represention of precipitation than constraining the hemispheric albedos.« less

  6. General-circulation-model simulations of future snowpack in the western United States

    USGS Publications Warehouse

    McCabe, G.J.; Wolock, D.M.

    1999-01-01

    April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western US. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.

  7. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  8. Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

    NASA Astrophysics Data System (ADS)

    Toh, Ying Ying; Turner, Andrew G.; Johnson, Stephanie J.; Holloway, Christopher E.

    2018-02-01

    The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model's local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

  9. Robust Hadley Circulation changes and increasing global dryness due to CO2 warming from CMIP5 model projections.

    PubMed

    Lau, William K M; Kim, Kyu-Myong

    2015-03-24

    In this paper, we investigate changes in the Hadley Circulation (HC) and their connections to increased global dryness (suppressed rainfall and reduced tropospheric relative humidity) under CO2 warming from Coupled Model Intercomparison Project Phase 5 (CMIP5) model projections. We find a strengthening of the HC manifested in a "deep-tropics squeeze" (DTS), i.e., a deepening and narrowing of the convective zone, enhanced ascent, increased high clouds, suppressed low clouds, and a rise of the level of maximum meridional mass outflow in the upper troposphere (200-100 hPa) of the deep tropics. The DTS induces atmospheric moisture divergence and reduces tropospheric relative humidity in the tropics and subtropics, in conjunction with a widening of the subsiding branches of the HC, resulting in increased frequency of dry events in preferred geographic locations worldwide. Among various water-cycle parameters examined, global dryness is found to have the highest signal-to-noise ratio. Our results provide a physical basis for inferring that greenhouse warming is likely to contribute to the observed prolonged droughts worldwide in recent decades.

  10. Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  11. Modeling impacts of climate change on the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand.

    PubMed

    Suwannatrai, A; Pratumchart, K; Suwannatrai, K; Thinkhamrop, K; Chaiyos, J; Kim, C S; Suwanweerakamtorn, R; Boonmars, T; Wongsaroj, T; Sripa, B

    2017-01-01

    Global climate change is now regarded as imposing a significant threat of enhancing transmission of parasitic diseases. Maximum entropy species distribution modeling (MaxEnt) was used to explore how projected climate change could affect the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand. A range of climate variables was used: the Hadley Global Environment Model 2-Earth System (HadGEM2-ES) climate change model and also the IPCC scenarios A2a for 2050 and 2070. Occurrence data from surveys conducted in 2009 and 2014 were obtained from the Department of Disease Control, Ministry of Public Health, Thailand. The MaxEnt model performed better than random for O. viverrini with training AUC values greater than 0.8 under current and future climatic conditions. The current distribution of O. viverrini is significantly affected by precipitation and minimum temperature. According to current conditions, parts of Thailand climatically suitable for O. viverrini are mostly in the northeast and north, but the parasite is largely absent from southern Thailand. Under future climate change scenarios, the distribution of O. viverrini in 2050 should be significantly affected by precipitation, maximum temperature, and mean temperature of the wettest quarter, whereas in 2070, significant factors are likely to be precipitation during the coldest quarter, maximum, and minimum temperatures. Maps of predicted future distribution revealed a drastic decrease in presence of O. viverrini in the northeast region. The information gained from this study should be a useful reference for implementing long-term prevention and control strategies for O. viverrini in Thailand.

  12. Acidification at the Surface in the East Sea: A Coupled Climate-carbon Cycle Model Study

    NASA Astrophysics Data System (ADS)

    Park, Young-Gyu; Seol, Kyung-Hee; Boo, Kyung-On; Lee, Johan; Cho, Chunho; Byun, Young-Hwa; Seo, Seongbong

    2018-05-01

    This modeling study investigates the impacts of increasing atmospheric CO2 concentration on acidification in the East Sea. A historical simulation for the past three decades (1980 to 2010) was performed using the Hadley Centre Global Environmental Model (version 2), a coupled climate model with atmospheric, terrestrial and ocean cycles. As the atmospheric CO2 concentration increased, acidification progressed in the surface waters of the marginal sea. The acidification was similar in magnitude to observations and models of acidification in the global ocean. However, in the global ocean, the acidification appears to be due to increased in-situ oceanic CO2 uptake, whereas local processes had stronger effects in the East Sea. pH was lowered by surface warming and by the influx of water with higher dissolved inorganic carbon (DIC) from the northwestern Pacific. Due to the enhanced advection of DIC, the partial pressure of CO2 increased faster than in the overlying air; consequently, the in-situ oceanic uptake of CO2 decreased.

  13. Three-dimensional baroclinic instability of a Hadley cell for small Richardson number

    NASA Technical Reports Server (NTRS)

    Antar, B. N.; Fowlis, W. W.

    1983-01-01

    For the case of a baroclinic flow whose Richardson number, Ri, is of order unity, a three-dimensional linear stability analysis is conducted on the basis of a model for a thin, horizontal, rotating fluid layer which is subjected to horizontal and vertical temperature gradients. The Hadley cell basic state and stability analysis are both based on the Navier-Stokes and energy equations, and perturbations possessing zonal, meridional, and vertical structures are considered. An attempt is made to extend the previous theoretical work on three-dimensional baroclinic instability for small Ri to a more realistic model involving the Prandtl and Ekman numbers, as well as to finite growth rates and a wider range of the zonal wavenumber. In general, it is found that the symmetric modes of maximum growth are not purely symmetric, but have a weak zonal structure.

  14. Manifestation of remote response over the equatorial Pacific in a climate model

    NASA Astrophysics Data System (ADS)

    Misra, Vasubandhu; Marx, L.

    2007-10-01

    In this paper we examine the simulations over the tropical Pacific Ocean from long-term simulations of two different versions of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model that have a different global distribution of the inversion clouds. We find that subtle changes made to the numerics of an empirical parameterization of the inversion clouds can result in a significant change in the coupled climate of the equatorial Pacific Ocean. In one coupled simulation of this study we enforce a simple linear spatial filtering of the diagnostic inversion clouds to ameliorate its spatial incoherency (as a result of the Gibbs effect) while in the other we conduct no such filtering. It is found from the comparison of these two simulations that changing the distribution of the shallow inversion clouds prevalent in the subsidence region of the subtropical high over the eastern oceans in this manner has a direct bearing on the surface wind stress through surface pressure modifications. The SST in the warm pool region responds to this modulation of the wind stress, thus affecting the convective activity over the warm pool region and also the large-scale Walker and Hadley circulation. The interannual variability of SST in the eastern equatorial Pacific Ocean is also modulated by this change to the inversion clouds. Consequently, this sensitivity has a bearing on the midlatitude height response. The same set of two experiments were conducted with the respective versions of the atmosphere general circulation model uncoupled to the ocean general circulation model but forced with observed SST to demonstrate that this sensitivity of the mean climate of the equatorial Pacific Ocean is unique to the coupled climate model where atmosphere, ocean and land interact. Therefore a strong case is made for adopting coupled ocean-land-atmosphere framework to develop climate models as against the usual practice of developing component models independent of each other.

  15. View of Commemorative plaque left on moon at Hadley-Apennine landing site

    NASA Image and Video Library

    1971-08-01

    AS15-88-11894 (31 July-2 Aug. 1971) --- A close-up view of a commemorative plaque left on the moon at the Hadley-Apennine landing site in memory of 14 NASA astronauts and USSR cosmonauts, now deceased. Their names are inscribed in alphabetical order on the plaque. The plaque was stuck in the lunar soil by astronauts David R. Scott, commander, and James B. Irwin, lunar module pilot, during their Apollo 15 lunar surface extravehicular activity (EVA). The names on the plaque are Charles A. Bassett II, Pavel I. Belyayev, Roger B. Chaffee, Georgi Dobrovolsky, Theodore C. Freeman, Yuri A. Gagarin, Edward G. Givens Jr., Virgil I. Grissom, Vladimir Komarov, Viktor Patsayev, Elliot M. See Jr., Vladislav Volkov, Edward H. White II, and Clifton C. Williams Jr. The tiny, man-like object represents the figure of a fallen astronaut/cosmonaut. While astronauts Scott and Irwin descended in the Lunar Module (LM) "Falcon" to explore the Hadley-Apennine area of the moon, astronaut Alfred M. Worden, command module pilot, remained with the Command and Service Modules (CSM) in lunar orbit.

  16. Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2010-01-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with

  17. A topographically forced asymmetry in the martian circulation and climate.

    PubMed

    Richardson, Mark I; Wilson, R John

    2002-03-21

    Large seasonal and hemispheric asymmetries in the martian climate system are generally ascribed to variations in solar heating associated with orbital eccentricity. As the orbital elements slowly change (over a period of >104 years), characteristics of the climate such as dustiness and the vigour of atmospheric circulation are thought to vary, as should asymmetries in the climate (for example, the deposition of water ice at the northern versus the southern pole). Such orbitally driven climate change might be responsible for the observed layering in Mars' polar deposits by modulating deposition of dust and water ice. Most current theories assume that climate asymmetries completely reverse as the angular distance between equinox and perihelion changes by 180 degrees. Here we describe a major climate mechanism that will not precess in this way. We show that Mars' global north-south elevation difference forces a dominant southern summer Hadley circulation that is independent of perihelion timing. The Hadley circulation, a tropical overturning cell responsible for trade winds, largely controls interhemispheric transport of water and the bulk dustiness of the atmosphere. The topography therefore imprints a strong handedness on climate, with water ice and the active formation of polar layered deposits more likely in the north.

  18. Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers.

    PubMed

    Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T

    2018-08-01

    Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.

  19. Robust Hadley Circulation Changes and Increasing Global Dryness Due to CO2 Warming from CMIP-5 Model Projections

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Kim, K. M.

    2015-01-01

    In this paper, we investigate changes in the Hadley Circulation (HC) and their connections to increased global dryness under CO2 warming from CMIP-5 model projections. We find a strengthening of the ascending branch of the HC manifested in a deep-tropics squeeze (DTS), i.e., a deepening and narrowing of the convective zone, increased high clouds, and a rise of the level of maximum meridional mass outflow in the upper troposphere (200-100 hectopascals) of the deep tropics. The DTS induces atmospheric moisture divergence, reduces tropospheric relative humidity in the tropics and subtropics, in conjunction with a widening of the subsiding branches of the HC, resulting in increased frequency of dry events in preferred geographic locations worldwide. Among water cycle parameters examined, global dryness has the highest signal-to-noise ratio. Our results provide scientific bases for inferring that the observed tend of prolonged droughts in recent decades is likely attributable to greenhouse warming.

  20. Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries

    USGS Publications Warehouse

    Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won

    2012-01-01

    As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on

  1. Decadal climate prediction (project GCEP).

    PubMed

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

    2009-03-13

    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  2. Understanding the robustness of Hadley cell response to wide variations in ocean heat transport

    NASA Astrophysics Data System (ADS)

    Rencurrel, M. C.; Rose, B. E. J.

    2017-12-01

    One important aspect of our climate system is the relationship between surface climate and the poleward energy transport in the atmosphere and ocean. Previous studies have shown that increases in poleward ocean heat transport (OHT) tend to warm the midlatitudes without strongly affecting tropical SSTs, resulting in a reduction in the equator-to-pole temperature gradient. This "tropical thermostat" effect depends crucially on a slowdown of the Hadley circulation (HC), with consequent changes in surface evaporation, atmospheric water vapor, and cloudiness. Here we extend previous studies by considering a wide range of spatial patterns of OHT, which we impose in a suite of slab-ocean aquaplanet GCM simulations. The forcing patterns are idealized but sample a variety of ocean circulation features. We find that the tropical thermostat and HC slowdown effects are relatively robust across all forcing patterns. A 1 PW increase in the amplitude of the prescribed OHT spatial pattern results in a global mean warming and a roughly 5 x 1010 kg/s decrease in HC mass flux, regardless of the detailed spatial structure of the imposed OHT. While the rate of HC slowdown is relatively robust, the mechanisms driving it are less so. Smaller, equator-to-subtropical scale OHT patterns are associated with greater reduced Gross Moist Stability (GMS) than the larger-scale OHT patterns. As the imposed OHT is limited equatorward, the HC becomes less efficient at transporting energy out of the tropics, implying that GMS has a modulating effect on the dynamical response of the cell. These experiments offer some new insights on the interplay between atmospheric dynamics and the radiative and hydrological aspects of global climate.

  3. Global warming and climate change in Amazonia: Climate-vegetation feedback and impacts on water resources

    NASA Astrophysics Data System (ADS)

    Marengo, José; Nobre, Carlos A.; Betts, Richard A.; Cox, Peter M.; Sampaio, Gilvan; Salazar, Luis

    This chapter constitutes an updated review of long-term climate variability and change in the Amazon region, based on observational data spanning more than 50 years of records and on climate-change modeling studies. We start with the early experiments on Amazon deforestation in the late 1970s, and the evolution of these experiments to the latest studies on greenhouse gases emission scenarios and land use changes until the end of the twenty-first century. The "Amazon dieback" simulated by the HadCM3 model occurs after a "tipping point" of CO2 concentration and warming. Experiments on Amazon deforestation and change of climate suggest that once a critical deforestation threshold (or tipping point) of 40-50% forest loss is reached in eastern Amazonia, climate would change in a way which is dangerous for the remaining forest. This may favor a collapse of the tropical forest, with a substitution of the forest by savanna-type vegetation. The concept of "dangerous climate change," as a climate change, which induces positive feedback, which accelerate the change, is strongly linked to the occurrence of tipping points, and it can be explained as the presence of feedback between climate change and the carbon cycle, particularly involving a weakening of the current terrestrial carbon sink and a possible reversal from a sink (as in present climate) to a source by the year 2050. We must, therefore, currently consider the drying simulated by the Hadley Centre model(s) as having a finite probability under global warming, with a potentially enormous impact, but with some degree of uncertainty.

  4. The Influence of the Regional Hadley and Walker Circulations on Precipitation Patterns over Africa in El Niño, La Niña, and Neutral Years

    NASA Astrophysics Data System (ADS)

    de Oliveira, Cristiano Prestrelo; Aímola, Luis; Ambrizzi, Tércio; Freitas, Ana Carolina Vasques

    2018-02-01

    This study focuses on the differential impacts of the positive (El Niño), negative (La Niña), and neutral phases of the El Niño Southern Oscillation (ENSO) on precipitation over Africa during DJF and JJA, evaluated through changes in the regional Hadley and Walker Circulations. Identification of the Hadley and Walker Cells was done using stream function mass transport calculations of ERA-Interim reanalysis data from 1979 to 2014. Analysis of the spatial pattern of precipitation anomalies shows that during DJF, El Niño (La Niña) negatively (positively) impacts precipitation over the African continent. During JJA, El Niño (La Niña) influences precipitation variability over the Sahel region, producing positive (negative) anomalies. Negative precipitation anomalies associated with El Niño (DJF) over southern Africa are linked to a strengthening in subsidence of the descending branch of the regional Hadley Cell, and during JJA the negative precipitation anomalies over the Sahel are associated with a weakening of the ascending branch of the regional Hadley Cell. During La Niña events in DJF, there is a tendency toward increased convection in southern Africa, associated with a stronger ascending branch and weaker descending branch of the regional Hadley Cell. During La Niña events in JJA, positive precipitation anomalies over the Sahel are associated with an intensification of the ascending branch of the regional Hadley Cell north of the equator.

  5. Climate change and forest fires.

    PubMed

    Flannigan, M D; Stocks, B J; Wotton, B M

    2000-11-15

    This paper addresses the impacts of climate change on forest fires and describes how this, in turn, will impact on the forests of the United States. In addition to reviewing existing studies on climate change and forest fires we have used two transient general circulation models (GCMs), namely the Hadley Centre and the Canadian GCMs, to estimate fire season severity in the middle of the next century. Ratios of 2 x CO2 seasonal severity rating (SSR) over present day SSR were calculated for the means and maximums for North America. The results suggest that the SSR will increase by 10-50% over most of North America; although, there are regions of little change or where the SSR may decrease by the middle of the next century. Increased SSRs should translate into increased forest fire activity. Thus, forest fires could be viewed as an agent of change for US forests as the fire regime will respond rapidly to climate warming. This change in the fire regime has the potential to overshadow the direct effects of climate change on species distribution and migration.

  6. Three-dimensional baroclinic instability of a Hadley cell for small Richardson number

    NASA Technical Reports Server (NTRS)

    Antar, B. N.; Fowlis, W. W.

    1985-01-01

    A three-dimensional, linear stability analysis of a baroclinic flow for Richardson number, Ri, of order unity is presented. The model considered is a thin horizontal, rotating fluid layer which is subjected to horizontal and vertical temperature gradients. The basic state is a Hadley cell which is a solution of the complete set of governing, nonlinear equations and contains both Ekman and thermal boundary layers adjacent to the rigid boundaries; it is given in a closed form. The stability analysis is also based on the complete set of equations; and perturbation possessing zonal, meridional, and vertical structures were considered. Numerical methods were developed for the stability problem which results in a stiff, eighth-order, ordinary differential eigenvalue problem. The previous work on three-dimensional baroclinic instability for small Ri was extended to a more realistic model involving the Prandtl number, sigma, and the Ekman number, E, and to finite growth rates and a wider range of the zonal wavenumber.

  7. High Resolution Regional Climate Modeling for Lebanon, Eastern Mediterranean Coast

    NASA Astrophysics Data System (ADS)

    Katurji, Marwan; Soltanzadeh, Iman; Kuhnlein, Meike; Zawar-Reza, Peyman

    2013-04-01

    The Eastern Mediterranean coast consists of Lebanon, Palestine, Syria, Israel and a small part of southern Turkey. The region lies between latitudes 30 degrees S and 40 degrees N, which makes its climate affected by westerly propagating wintertime cyclones spinning off mid-latitude troughs (December, January and February), while during summer (June, July and August) the area is strongly affected by the sub-tropical anti-cyclonic belt as a result of the descending air of the Hadley cell circulation system. The area is considered to be in a transitional zone between tropical to mid-latitude climate regimes, and having a coastal topography up to 3000 m in elevation (like in the Western Ranges of Lebanon), which emphasizes the complexity of climate variability in this area under future predictions of climate change. This research incorporates both regional climate numerical simulations, Tropical Rainfall Measuring Mission (TRMM) satellite derived and surface rain gauge rainfall data to evaluate the Regional Climate Model (RegCM) version 4 ability to represent both the mean and variance of observed precipitation in the Eastern Mediterranean Region, with emphasis on the Lebanese coastal terrain and mountain ranges. The adopted methodology involves dynamically down scaling climate data from reanalysis synoptic files through a double nesting procedure. The retrospective analysis of 13 years with both 50 and 10 km spatial resolution allows for the assessment of the model results on both a climate scale and specific high intensity precipitating events. The spatial averaged mean bias error in precipitation rate for the rainy season predicted by RegCM 50 and 10 km resolution grids was 0.13 and 0.004 mm hr-1 respectively. When correlating RegCM and TRMM precipitation rate for the domain covering Lebanon's coastal mountains, the root mean square error (RMSE) for the mean quantities over the 13-year period was only 0.03, while the RMSE for the standard deviation was higher by one

  8. Modelling the climate and ice sheets of the mid-Pliocene warm period: a test of model dependency

    NASA Astrophysics Data System (ADS)

    Dolan, Aisling; Haywood, Alan; Lunt, Daniel; Hill, Daniel

    2010-05-01

    The mid-Pliocene warm period (MPWP; c. 3.0 - 3.3 million years ago) has been the subject of a large number of published studies during the last decade. It is an interval in Earth history, where conditions were similar to those predicted by climate models for the end of the 21st Century. Not only is it important to increase our understanding of the climate dynamics in a warmer world, it is also important to determine exactly how well numerical models can retrodict a climate significantly different from the present day, in order to have confidence in them for predicting the future climate. Previous General Circulation Model (GCM) simulations have indicated that MPWP mean annual surface temperatures were on average 2 to 3˚C warmer than the pre-industrial era. Coastal stratigraphy and benthic oxygen isotope records suggest that terrestrial ice volumes were reduced when compared to modern. Ice sheet modelling studies have supported this decrease in cryospheric extent. Generally speaking, both climate and ice sheet modelling studies have only used results from one numerical model when simulating the climate of the MPWP. However, recent projects such as PMIP (the Palaeoclimate Modelling Intercomparison Project) have emphasised the need to explore the dependency of past climate predictions on the specific climate model which is used. Here we present a comparison of MPWP climatologies produced by three atmosphere only GCMs from the Goddard Institute of Space Studies (GISS), the National Centre for Atmospheric Research (NCAR) and the Hadley Centre for Climate Prediction and Research (GCMAM3, CAM3-CLM and HadAM3 respectively). We focus on the ability of the GCMs to simulate climate fields needed to drive an offline ice sheet model to assess whether there are any significant differences between the climatologies. By taking the different temperature and precipitation predictions simulated by the three models as a forcing, and adopting GCM-specific topography, we have used the

  9. Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

    NASA Astrophysics Data System (ADS)

    Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

    2009-04-01

    Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg

  10. Potential effect of climate change on malaria transmission in Africa.

    PubMed

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

    2003-11-29

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

  11. Estimation of the global climate effect of brown carbon

    NASA Astrophysics Data System (ADS)

    Zhang, A.; Wang, Y.; Zhang, Y.; Weber, R. J.; Song, Y.

    2017-12-01

    Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The global distribution and climate effect of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning region and that the resulting heating tends to stabilize the atmosphere. Yet current climate models do not include proper treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory from Global Fire Emissions Database 4 (GFED4) and developed a BrC module in the Community Atmosphere Model version 5 (CAM5) of Community Earth System Model (CESM) model. The model simulations compared well to BrC observations of the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC-3) campaigns and includes BrC bleaching. Model results suggested that BrC in the upper troposphere due to convective transport is as important an absorber as BC globally. Upper tropospheric BrC radiative forcing is particularly significant over the tropics, affecting the atmosphere stability and Hadley circulation.

  12. A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate

    NASA Astrophysics Data System (ADS)

    Lima, Carlos H. R.; Kwon, Hyun-Han; Kim, Jin-Young

    2016-09-01

    The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.

  13. Compositional variation in the Hadley Apennine region

    NASA Technical Reports Server (NTRS)

    Clark, P. E.; Hawke, B. R.

    1982-01-01

    Orbital geochemical data in the Hadley Apennine region are related to typical rock compositions and used in determining the distribution of soils derived from the rock types found in this region. Orbital XRF Mg/Si and Al/Si intensities are the orbital data that are used primarily. These data are corrected for spurious interorbit variation using a modification of a previously developed method. The corrected values are than converted to % MgO and % Al2O3, respectively, from theoretical considerations, and as such are compared with similar concentrations for typical lunar rocks and soils of the Apollo 15 landing site. The relationship of the XRF values to Fe, Ti, and Th concentrations, derived from gamma-ray observations, is also considered. It is established that the orbital geochemistry data for this region are consistent with the presence of a mixture of ANT suite and Fra Mauro basalt components frequently dominated by a KREEP basalt component toward the west and by a mafic pyroclastic component toward the east.

  14. Prediction of climate change in Brunei Darussalam using statistical downscaling model

    NASA Astrophysics Data System (ADS)

    Hasan, Dk. Siti Nurul Ain binti Pg. Ali; Ratnayake, Uditha; Shams, Shahriar; Nayan, Zuliana Binti Hj; Rahman, Ena Kartina Abdul

    2017-06-01

    Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment, energy management, food security and water resources. Brunei Darussalam located within the heart of Borneo will be affected both in terms of precipitation and temperature. Therefore, it is crucial to comprehend and assess how important climate indicators like temperature and precipitation are expected to vary in the future in order to minimise its impact. This study assesses the application of a statistical downscaling model (SDSM) for downscaling General Circulation Model (GCM) results for maximum and minimum temperatures along with precipitation in Brunei Darussalam. It investigates future climate changes based on numerous scenarios using Hadley Centre Coupled Model, version 3 (HadCM3), Canadian Earth System Model (CanESM2) and third-generation Coupled Global Climate Model (CGCM3) outputs. The SDSM outputs were improved with the implementation of bias correction and also using a monthly sub-model instead of an annual sub-model. The outcomes of this assessment show that monthly sub-model performed better than the annual sub-model. This study indicates a satisfactory applicability for generation of maximum temperatures, minimum temperatures and precipitation for future periods of 2017-2046 and 2047-2076. All considered models and the scenarios were consistent in predicting increasing trend of maximum temperature, increasing trend of minimum temperature and decreasing trend of precipitations. Maximum overall trend of Tmax was also observed for CanESM2 with Representative Concentration Pathways (RCP) 8.5 scenario. The increasing trend is 0.014 °C per year. Accordingly, by 2076, the highest prediction of average maximum temperatures is that it will increase by 1.4 °C. The same model predicts an increasing trend of Tmin of 0.004 °C per year, while the highest trend is seen under CGCM3-A2 scenario which is 0.009

  15. View of Commemorative plaque left on moon at Hadley-Apennine landing site

    NASA Technical Reports Server (NTRS)

    1971-01-01

    A close-up view of a commemorative plaque left on the Moon at the Hadley-Apennine landing site in memory of 14 NASA astronauts and USSR cosmonauts, now deceased. Their names are inscribed in alphabetical order on the plaque. The plaque was stuck in the lunar soil by Astronauts David R. Scott and James B. Irwin during their Apollo 15 lunar surface extravehicular activity. The tin, man-like object represents the figure of a fallen astronaut/cosmonaut.

  16. Amazonian forest dieback under climate-carbon cycle projections for the 21st century

    NASA Astrophysics Data System (ADS)

    Cox, P. M.; Betts, R. A.; Collins, M.; Harris, P. P.; Huntingford, C.; Jones, C. D.

    The first GCM climate change projections to include dynamic vegetation and an interactive carbon cycle produced a very significant amplification of global warming over the 21st century. Under the IS92a ``business as usual'' emissions scenario CO2 concentrations reached about 980ppmv by 2100, which is about 280ppmv higher than when these feedbacks were ignored. The major contribution to the increased CO2 arose from reductions in soil carbon because global warming is assumed to accelerate respiration. However, there was also a lesser contribution from an alarming loss of the Amazonian rainforest. This paper describes the phenomenon of Amazonian forest dieback under elevated CO2 in the Hadley Centre climate-carbon cycle model.

  17. Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulations

    NASA Astrophysics Data System (ADS)

    Davis, Nicholas A.; Seidel, Dian J.; Birner, Thomas; Davis, Sean M.; Tilmes, Simone

    2016-08-01

    Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause

  18. The Effect of Changes in the Hadley Circulation on Oceanic Oxygen Minimum Zones

    NASA Astrophysics Data System (ADS)

    De La Cruz Tello, G.; Ummenhofer, C.; Karnauskas, K. B.

    2014-12-01

    Recent research argued that the Hadley circulation (HC) is composed of three regional cells located at the eastern edges of the ocean basins, rather than a single, globe-encircling cell as the classic textbook view suggests. The HC is expected to expand in concert with global warming, which means that the dry regions beneath the descending branches of the HC are projected to become even drier. Changes in the HC are thus likely to impact freshwater resources on land, as well as the underlying ocean in the subtropics. The eastern edges of ocean basins are characterized by oxygen minimum zones (OMZs), which are regions of very low oxygen concentrations. They affect marine life, as many animals cannot handle the stress caused by such conditions. OMZs have expanded and shoaled in the last 50 years, and they are expected to continue to do so as global climate changes. The purpose of this research is to find links between the projected changes in OMZs and the HC. The National Center for Atmospheric Research (NCAR) Community Earth System Model 1.0 (CESM), Representative Concentration Pathways 8.5 (RCP8.5) experiment with a resolution of 0.9 by 1.25 degrees, which formed part of the Coupled Model Intercomparison Project phase 5 (CMIP5), was used for this analysis. Meridional winds and oceanic oxygen concentrations were the primarily analyzed variables. Latitudinal ocean oxygen slices demonstrate the OMZs' location along the eastern edges of ocean basins. Meridional winds overlayed with oxygen concentration are consistent with the idea that surface meridional 'Hadleywise flow' (i.e., towards the equator at the surface and towards the poles aloft) and OMZs are linked through changes in upwelling. Area-averaged time series spanning the historical period through to the end of the 21st century with RCP8.5 confirm that future changes in OMZs and the HC may be connected. Further research could lead to improved understanding of the factors that drive changes in both, which could

  19. Bjerknes Compensation in Meridional Heat Transport under Freshwater Forcing and the Role of Climate Feedback

    NASA Astrophysics Data System (ADS)

    Wen, Qin

    2017-04-01

    Using a coupled Earth climate model, freshwater experiments are performed to study the Bjerknes compensation (BJC) between meridional atmosphere heat transport (AHT) and meridional ocean heat transport (OHT). Freshwater hosing in the North Atlantic weakens the Atlantic meridional overturning circulation (AMOC) and thus reduces the northward OHT in the Atlantic significantly, leading to a cooling (warming) in surface layer in the Northern (Southern) Hemisphere. This results in an enhanced Hadley Cell and northward AHT. Meanwhile, the OHT in the Indo-Pacific is increased in response to the Hadley Cell change, partially offsetting the reduced OHT in the Atlantic. Two compensations occur here: compensation between the AHT and the Atlantic OHT, and that between the Indo-Pacific OHT and the Atlantic OHT. The AHT change compensates the OHT change very well in the extratropics, while the former overcompensates the latter in the tropics due to the Indo-Pacific change. The BJC can be understood from the viewpoint of large-scale circulation change. However, the intrinsic mechanism of BJC is related to the climate feedback of Earth system. Our coupled model experiments confirm that the occurrence of BJC is an intrinsic requirement of local energy balance, and local climate feedback determines the extent of BJC, consistent with previous theoretical results. Even during the transient period of climate change in the model, the BJC is well established when the ocean heat storage is slowly varying and its change is weaker than the net heat flux changes at the ocean surface and the top of the atmosphere. The BJC can be deduced from the local climate feedback. Under the freshwater forcing, the overcompensation in the tropics (undercompensation in the extratropics) is mainly caused by the positive longwave feedback related to cloud (negative longwave feedback related to surface temperature change). Different dominant feedbacks determine different BJC scenarios in different regions

  20. A zonally symmetric model for the monsoon-Hadley circulation with stochastic convective forcing

    NASA Astrophysics Data System (ADS)

    De La Chevrotière, Michèle; Khouider, Boualem

    2017-02-01

    Idealized models of reduced complexity are important tools to understand key processes underlying a complex system. In climate science in particular, they are important for helping the community improve our ability to predict the effect of climate change on the earth system. Climate models are large computer codes based on the discretization of the fluid dynamics equations on grids of horizontal resolution in the order of 100 km, whereas unresolved processes are handled by subgrid models. For instance, simple models are routinely used to help understand the interactions between small-scale processes due to atmospheric moist convection and large-scale circulation patterns. Here, a zonally symmetric model for the monsoon circulation is presented and solved numerically. The model is based on the Galerkin projection of the primitive equations of atmospheric synoptic dynamics onto the first modes of vertical structure to represent free tropospheric circulation and is coupled to a bulk atmospheric boundary layer (ABL) model. The model carries bulk equations for water vapor in both the free troposphere and the ABL, while the processes of convection and precipitation are represented through a stochastic model for clouds. The model equations are coupled through advective nonlinearities, and the resulting system is not conservative and not necessarily hyperbolic. This makes the design of a numerical method for the solution of this system particularly difficult. Here, we develop a numerical scheme based on the operator time-splitting strategy, which decomposes the system into three pieces: a conservative part and two purely advective parts, each of which is solved iteratively using an appropriate method. The conservative system is solved via a central scheme, which does not require hyperbolicity since it avoids the Riemann problem by design. One of the advective parts is a hyperbolic diagonal matrix, which is easily handled by classical methods for hyperbolic equations, while

  1. End-of-century projections of North American atmospheric river events in CMIP5 climate models

    NASA Astrophysics Data System (ADS)

    Warner, M.; Mass, C.; Salathe, E. P., Jr.

    2013-12-01

    Most extreme precipitation events that occur along the North American west coast are associated with narrow plumes of above-average water vapor concentration that stretch from the tropics or subtropics to the West Coast. These events generally occur during the wet season (October-March) and are referred to as atmospheric rivers (AR). ARs can cause major river management problems, damage from flooding or landslides, and loss of life. It is expected that anthropogenic global warming could lead to changes in the general circulation of the atmosphere, such as Hadley Cell expansion and jet stream and storm track shifts. Since AR events are associated with cyclonic activity that originates near and propagates along the jet stream, the jet stream configuration influences the frequency and location of AR landfall along the North American west coast. Therefore, it is probable that any changes in the general circulation of the atmosphere will result in changes in the frequency, orientation, and location of AR landfalls. Generally, along the West Coast, CMIP5 models predict increases in integrated water vapor and precipitation, and little change in low-level wind associated with AR events. In this study, CMIP5 RCP 8.5 climate models and high resolution regional climate models are used to analyze predicted changes in frequency and location of AR events impacting the West Coast from the contemporary period (1970-1999) to the end of this century (2070-2099).

  2. Climatic trends over Ethiopia: regional signals and drivers

    USGS Publications Warehouse

    Jury, Mark R.; Funk, Christopher C.

    2013-01-01

    This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.

  3. Emissions pathways, climate change, and impacts on California

    USGS Publications Warehouse

    Hayhoe, K.; Cayan, D.; Field, C.B.; Frumhoff, P.C.; Maurer, E.P.; Miller, N.L.; Moser, S.C.; Schneider, S.H.; Cahill, K.N.; Cleland, E.E.; Dale, L.; Drapek, R.; Hanemann, R.M.; Kalkstein, L.S.; Lenihan, J.; Lunch, C.K.; Neilson, R.P.; Sheridan, S.C.; Verville, J.H.

    2004-01-01

    The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.

  4. Emissions pathways, climate change, and impacts on California

    PubMed Central

    Hayhoe, Katharine; Cayan, Daniel; Field, Christopher B.; Frumhoff, Peter C.; Maurer, Edwin P.; Miller, Norman L.; Moser, Susanne C.; Schneider, Stephen H.; Cahill, Kimberly Nicholas; Cleland, Elsa E.; Dale, Larry; Drapek, Ray; Hanemann, R. Michael; Kalkstein, Laurence S.; Lenihan, James; Lunch, Claire K.; Neilson, Ronald P.; Sheridan, Scott C.; Verville, Julia H.

    2004-01-01

    The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50–75%; and Sierra snowpack is reduced 30–70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75–90%; and snowpack declines 73–90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades. PMID:15314227

  5. Fewer clouds in the Mediterranean: consistency of observations and climate simulations

    PubMed Central

    Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

    2017-01-01

    Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

  6. Climate Models

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.

    2012-01-01

    Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

  7. Projected climate change impacts in rainfall erosivity over Brazil.

    PubMed

    Almagro, André; Oliveira, Paulo Tarso S; Nearing, Mark A; Hagemann, Stefan

    2017-08-15

    The impacts of climate change on soil erosion may bring serious economic, social and environmental problems. However, few studies have investigated these impacts on continental scales. Here we assessed the influence of climate change on rainfall erosivity across Brazil. We used observed rainfall data and downscaled climate model output based on Hadley Center Global Environment Model version 2 (HadGEM2-ES) and Model for Interdisciplinary Research On Climate version 5 (MIROC5), forced by Representative Concentration Pathway 4.5 and 8.5, to estimate and map rainfall erosivity and its projected changes across Brazil. We estimated mean values of 10,437 mm ha -1  h -1 year -1 for observed data (1980-2013) and 10,089 MJ mm ha -1  h -1 year -1 and 10,585 MJ mm ha -1  h -1 year -1 for HadGEM2-ES and MIROC5, respectively (1961-2005). Our analysis suggests that the most affected regions, with projected rainfall erosivity increases ranging up to 109% in the period 2007-2040, are northeastern and southern Brazil. Future decreases of as much as -71% in the 2071-2099 period were estimated for the southeastern, central and northwestern parts of the country. Our results provide an overview of rainfall erosivity in Brazil that may be useful for planning soil and water conservation, and for promoting water and food security.

  8. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    NASA Astrophysics Data System (ADS)

    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2018-04-01

    The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

  9. Ecosystem responses in the southern Caribbean Sea to global climate change

    PubMed Central

    Taylor, Gordon T.; Muller-Karger, Frank E.; Thunell, Robert C.; Scranton, Mary I.; Astor, Yrene; Varela, Ramon; Ghinaglia, Luis Troccoli; Lorenzoni, Laura; Fanning, Kent A.; Hameed, Sultan; Doherty, Owen

    2012-01-01

    Over the last few decades, rising greenhouse gas emissions have promoted poleward expansion of the large-scale atmospheric Hadley circulation that dominates the Tropics, thereby affecting behavior of the Intertropical Convergence Zone (ITCZ) and North Atlantic Oscillation (NAO). Expression of these changes in tropical marine ecosystems is poorly understood because of sparse observational datasets. We link contemporary ecological changes in the southern Caribbean Sea to global climate change indices. Monthly observations from the CARIACO Ocean Time-Series between 1996 and 2010 document significant decadal scale trends, including a net sea surface temperature (SST) rise of ∼1.0 ± 0.14 °C (±SE), intensified stratification, reduced delivery of upwelled nutrients to surface waters, and diminished phytoplankton bloom intensities evident as overall declines in chlorophyll a concentrations (ΔChla = −2.8 ± 0.5%⋅y−1) and net primary production (ΔNPP = −1.5 ± 0.3%⋅y−1). Additionally, phytoplankton taxon dominance shifted from diatoms, dinoflagellates, and coccolithophorids to smaller taxa after 2004, whereas mesozooplankton biomass increased and commercial landings of planktivorous sardines collapsed. Collectively, our results reveal an ecological state change in this planktonic system. The weakening trend in Trade Winds (−1.9 ± 0.3%⋅y−1) and dependent local variables are largely explained by trends in two climatic indices, namely the northward migration of the Azores High pressure center (descending branch of Hadley cell) by 1.12 ± 0.42°N latitude and the northeasterly progression of the ITCZ Atlantic centroid (ascending branch of Hadley cell), the March position of which shifted by about 800 km between 1996 and 2009. PMID:23071299

  10. Integrated Assessment of Hadley Centre (HadCM2) Climate Change Projections on Agricultural Productivity and Irrigation Water Supply in the Conterminous United States.I. Climate change scenarios and impacts on irrigation water supply simulated with the HUMUS model.

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

    Rosenberg, Norman J.; Brown, Robert A.; Izaurralde, R Cesar C.

    This paper describes methodology and results of a study by researchers at PNNL contributing to the water sector study of the U.S. National Assessment of Climate Change. The vulnerability of water resources in the conterminous U.S. to climate change in 10-y periods centered on 2030 and 2095--as projected by the HadCM2 general circulation model--was modeled with HUMUS (Hydrologic Unit Model of the U.S.). HUMUS consists of a GIS that provides data on soils, land use and climate to drive the hydrology model Soil Water Assessment Tool (SWAT). The modeling was done at the scale of the 2101 8-digit USGS hydrologicmore » unit areas (HUA). Results are aggregated to the 4-digit and 2-digit (Major Water Resource Region, MWRR) scales for various purposes. Daily records of temperature and precipitation for 1961-1990 provided the baseline climate. Water yields (WY)--sum of surface and subsurface runoff--increases from the baseline period over most of the U.S. in 2030 and 2095. In 2030, WY increases in the western US and decreases in the central and southeast regions. Notably, WY increases by 139 mm from baseline in the Pacific NW. Decreased WY is projected for the Lower Mississippi and Texas Gulf basins, driven by higher temperatures and reduced precipitation. The HadCM2 2095 scenario projects a climate significantly wetter than baseline, resulting in WY increases of 38%. WY increases are projected throughout the eastern U.S. WY also increases in the western U.S. Climate change also affects the seasonality of the hydrologic cycle. Early snowmelt is induced in western basins, leading to dramatically increased WYs in late winter and early spring. The simulations were run at current (365 ppm) and elevated (560 ppm) atmospheric CO2 concentrations to account for the potential impacts of the CO2-fertilization effect. The effects of climate change scenario were considerably greater than those due to elevated CO2 but the latter, overall, decreased losses and augmented increases in

  11. Responses of the Tropical Atmospheric Circulation to Climate Change and Connection to the Hydrological Cycle

    NASA Astrophysics Data System (ADS)

    Ma, Jian; Chadwick, Robin; Seo, Kyong-Hwan; Dong, Changming; Huang, Gang; Foltz, Gregory R.; Jiang, Jonathan H.

    2018-05-01

    This review describes the climate change–induced responses of the tropical atmospheric circulation and their impacts on the hydrological cycle. We depict the theoretically predicted changes and diagnose physical mechanisms for observational and model-projected trends in large-scale and regional climate. The tropical circulation slows down with moisture and stratification changes, connecting to a poleward expansion of the Hadley cells and a shift of the intertropical convergence zone. Redistributions of regional precipitation consist of thermodynamic and dynamical components, including a strong offset between moisture increase and circulation weakening throughout the tropics. This allows other dynamical processes to dominate local circulation changes, such as a surface warming pattern effect over oceans and multiple mechanisms over land. To improve reliability in climate projections, more fundamental understandings of pattern formation, circulation change, and the balance of various processes redistributing land rainfall are suggested to be important.

  12. Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

    NASA Technical Reports Server (NTRS)

    Chen, Wei-Ting; Liao, Hong; Seinfeld, John H.

    2007-01-01

    Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the

  13. Climate change and potato cropping in the Peruvian Altiplano

    NASA Astrophysics Data System (ADS)

    Sanabria, J.; Lhomme, J. P.

    2013-05-01

    The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071-2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO2 concentration (A2) and moderate CO2 concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato ( Solanum tuberosum) and the bitter potato ( Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO2 on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.

  14. Regional climate model data used within the SWURVE project - 1: projected changes in seasonal patterns and estimation of PET

    NASA Astrophysics Data System (ADS)

    Ekström, M.; Jones, P. D.; Fowler, H. J.; Lenderink, G.; Buishand, T. A.; Conway, D.

    2007-04-01

    Climate data for studies within the SWURVE (Sustainable Water: Uncertainty, Risk and Vulnerability in Europe) project, assessing the risk posed by future climatic change to various hydrological and hydraulic systems were obtained from the regional climate model HadRM3H, developed at the Hadley Centre of the UK Met Office. This paper gives some background to HadRM3H; it also presents anomaly maps of the projected future changes in European temperature, rainfall and potential evapotranspiration (PET, estimated using a variant of the Penman formula). The future simulations of temperature and rainfall, following the SRES A2 emissions scenario, suggest that most of Europe will experience warming in all seasons, with heavier precipitation in winter in much of western Europe (except for central and northern parts of the Scandinavian mountains) and drier summers in most parts of western and central Europe (except for the north-west and the eastern part of the Baltic Sea). Particularly large temperature anomalies (>6°C) are projected for north-east Europe in winter and for southern Europe, Asia Minor and parts of Russia in summer. The projected PET displayed very large increases in summer for a region extending from southern France to Russia. The unrealistically large values could be the result of an enhanced hydrological cycle in HadRM3H, affecting several of the input parameters to the PET calculation. To avoid problems with hydrological modelling schemes, PET was re-calculated, using empirical relationships derived from observational values of temperature and PET.

  15. The Martian climate and energy balance models with CO2/H2O atmospheres

    NASA Technical Reports Server (NTRS)

    Hoffert, M. I.

    1986-01-01

    The analysis begins with a seasonal energy balance model (EBM) for Mars. This is used to compute surface temperature versus x = sin(latitude) and time over the seasonal cycle. The core model also computes the evolving boundaries of the CO2 icecaps, net sublimational/condensation rates, and the resulting seasonal pressure wave. Model results are compared with surface temperature and pressure history data at Viking lander sites, indicating fairly good agreement when meridional heat transport is represented by a thermal diffusion coefficient D approx. 0.015 W/sq. m/K. Condensational wind distributions are also computed. An analytic model of Martian wind circulation is then proposed, as an extension of the EMB, which incorporates vertical wind profiles containing an x-dependent function evaluated by substitution in the equation defining the diffusion coefficient. This leads to a parameterization of D(x) and of the meridional circulation which recovers the high surface winds predicted by dynamic Mars atmosphere models (approx. 10 m/sec). Peak diffusion coefficients, D approx. 0.6 w/sq m/K, are found over strong Hadley zones - some 40 times larger than those of high-latitude baroclinic eddies. When the wind parameterization is used to find streamline patterns over Martian seasons, the resulting picture shows overturning hemispheric Hadley cells crossing the equator during solstices, and attaining peak intensities during the south summer dust storm season, while condensational winds are most important near the polar caps.

  16. Climate change, humidity, and mortality in the United States

    PubMed Central

    Barreca, Alan I.

    2014-01-01

    This paper estimates the effects of humidity and temperature on mortality rates in the United States (c. 1973–2002) in order to provide an insight into the potential health impacts of climate change. I find that humidity, like temperature, is an important determinant of mortality. Coupled with Hadley CM3 climate-change predictions, I project that mortality rates are likely to change little on the aggregate for the United States. However, distributional impacts matter: mortality rates are likely to decline in cold and dry areas, but increase in hot and humid areas. Further, accounting for humidity has important implications for evaluating these distributional effects. PMID:25328254

  17. Estimates of runoff using water-balance and atmospheric general circulation models

    USGS Publications Warehouse

    Wolock, D.M.; McCabe, G.J.

    1999-01-01

    The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water-balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade-to-decade variability in GCM-based mean annual runoff and errors in GCM-based runoff. The differences in simulated runoff between the two GCMs, together with decade-to-decade variability and errors in GCM-based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.

  18. The Poleward Shift of Storm Tracks Under Climate Change: Tracking Cyclones in CMIP5

    NASA Astrophysics Data System (ADS)

    Kaspi, Y.; Tamarin, T.

    2017-12-01

    Extratropical cyclones dominate the distribution of precipitation and wind in the midlatitudes, and therefore their frequency, intensity, and paths have a significant effect on weather and climate. Comprehensive climate models forced by enhanced greenhouse gas emissions suggest that under a climate change scenario, the latitudinal band of storm tracks would shift poleward. While the poleward shift is a robust response across most models, there is currently no consensus on what is the dominant dynamical mechanism. Here we use a Lagrangian approach to study the poleward shift, by employing a storm-tracking algorithm on an ensemble of CMIP5 models forced by increased CO2 emissions. We demonstrate that in addition to a poleward shift in the latitude of storm genesis, associated with the expansion of the Hadley cell, the averaged cyclonic storm also propagates more poleward until it reaches its maximum intensity. A mechanism for enhanced poleward motion of cyclones in a warmer climate is proposed, supported by idealized global warming experiments, and relates the shift to changes in upper level jet and atmospheric water vapour content. Our results imply that under the RCP8.5 climate change scenario, the averaged latitude of peak cyclone intensity shifts poleward by about 1.2○ (1.0○) in the Atlantic (Pacific) storm track in the Northern Hemisphere (NH), and by about 1.6○ in the Southern Hemisphere (SH) storm track. These changes in cyclone tracks can have a significant impact on midlatitude climate.

  19. The Asian monsoon's role in atmospheric heat transport responses to orbital and millennial-scale climate change

    NASA Astrophysics Data System (ADS)

    McGee, D.; Green, B.; Donohoe, A.; Marshall, J.

    2015-12-01

    Recent studies have provided a framework for understanding the zonal-mean position of the tropical rain belt by documenting relationships between rain belt latitude and atmospheric heat transport across the equator (Donohoe et al., 2013). Modern seasonal and interannual variability in globally-averaged rain belt position (often referred to as 'ITCZ position') reflects the interhemispheric heat balance, with the rain belt's displacement toward the warmer hemisphere directly proportional to atmospheric heat transport into the cooler hemisphere. Model simulations suggest that rain belt shifts are likely to have obeyed the same relationship with interhemispheric heat transport in response to past changes in orbital parameters, ice sheets, and ocean circulation. This relationship implies that even small (±1 degree) shifts in the mean rain belt require large changes in hemispheric heat budgets, placing tight bounds on mean rain belt shifts in past climates. This work has primarily viewed tropical circulation in two dimensions, as a pair of zonal-mean Hadley cells on either side of the rain belt that are displaced north and south by perturbations in hemispheric energy budgets, causing the atmosphere to transport heat into the cooler hemisphere. Here we attempt to move beyond this zonal-mean perspective, motivated by arguments that the Asian monsoon system, rather than the zonal-mean circulation, plays the dominant role in annual-mean heat transport into the southern hemisphere in the modern climate (Heaviside and Czaja, 2012; Marshall et al., 2014). We explore a range of climate change experiments, including simulations of North Atlantic cooling and mid-Holocene climate, to test whether changes in interhemispheric atmospheric heat transport are primarily driven by the mean Hadley circulation, the Asian monsoon system, or other regional-scale atmospheric circulation changes. The scalings that this work identifies between Asian monsoon changes and atmospheric heat

  20. Polar Climate: Arctic sea ice

    USGS Publications Warehouse

    Stone, R.S.; Douglas, David C.; Belchansky, G.I.; Drobot, S.D.

    2005-01-01

    Recent decreases in snow and sea ice cover in the high northern latitudes are among the most notable indicators of climate change. Northern Hemisphere sea ice extent for the year as a whole was the third lowest on record dating back to 1973, behind 1995 (lowest) and 1990 (second lowest; Hadley Center–NCEP). September sea ice extent, which is at the end of the summer melt season and is typically the month with the lowest sea ice extent of the year, has decreased by about 19% since the late 1970s (Fig. 5.2), with a record minimum observed in 2002 (Serreze et al. 2003). A record low extent also occurred in spring (Chapman 2005, personal communication), and 2004 marked the third consecutive year of anomalously extreme sea ice retreat in the Arctic (Stroeve et al. 2005). Some model simulations indicate that ice-free summers will occur in the Arctic by the year 2070 (ACIA 2004).

  1. Ensemble climate projections of mean and extreme rainfall over Vietnam

    NASA Astrophysics Data System (ADS)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2017-01-01

    A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be

  2. Improved Decadal Climate Prediction in the North Atlantic using EnOI-Assimilated Initial Condition

    NASA Astrophysics Data System (ADS)

    Li, Q.; Xin, X.; Wei, M.; Zhou, W.

    2017-12-01

    Decadal prediction experiments of Beijing Climate Center climate system model version 1.1(BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961-2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal Oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.

  3. Influence of enhanced Asian NOx emissions on ozone in the upper troposphere and lower stratosphere in chemistry-climate model simulations

    NASA Astrophysics Data System (ADS)

    Roy, Chaitri; Fadnavis, Suvarna; Müller, Rolf; Ayantika, D. C.; Ploeger, Felix; Rap, Alexandru

    2017-01-01

    The Asian summer monsoon (ASM) anticyclone is the most pronounced circulation pattern in the upper troposphere and lower stratosphere (UTLS) during northern hemispheric summer. ASM convection plays an important role in efficient vertical transport from the surface to the upper-level anticyclone. In this paper we investigate the potential impact of enhanced anthropogenic nitrogen oxide (NOx) emissions on the distribution of ozone in the UTLS using the fully coupled aerosol-chemistry-climate model, ECHAM5-HAMMOZ. Ozone in the UTLS is influenced both by the convective uplift of ozone precursors and by the uplift of enhanced-NOx-induced tropospheric ozone anomalies. We performed anthropogenic NOx emission sensitivity experiments over India and China. In these simulations, covering the years 2000-2010, anthropogenic NOx emissions have been increased by 38 % over India and by 73 % over China with respect to the emission base year 2000. These emission increases are comparable to the observed linear trends of 3.8 % per year over India and 7.3 % per year over China during the period 2000 to 2010. Enhanced NOx emissions over India by 38 % and China by 73 % increase the ozone radiative forcing in the ASM anticyclone (15-40° N, 60-120° E) by 16.3 and 78.5 mW m-2 respectively. These elevated NOx emissions produce significant warming over the Tibetan Plateau and increase precipitation over India due to a strengthening of the monsoon Hadley circulation. However, increase in NOx emissions over India by 73 % (similar to the observed increase over China) results in large ozone production over the Indo-Gangetic Plain and Tibetan Plateau. The higher ozone concentrations, in turn, induce a reversed monsoon Hadley circulation and negative precipitation anomalies over India. The associated subsidence suppresses vertical transport of NOx and ozone into the ASM anticyclone.

  4. Climate change impacts on crop yield and quality with CO2 fertilization in China

    PubMed Central

    Erda, Lin; Wei, Xiong; Hui, Ju; Yinlong, Xu; Yue, Li; Liping, Bai; Liyong, Xie

    2005-01-01

    A regional climate change model (PRECIS) for China, developed by the UK's Hadley Centre, was used to simulate China's climate and to develop climate change scenarios for the country. Results from this project suggest that, depending on the level of future emissions, the average annual temperature increase in China by the end of the twenty-first century may be between 3 and 4 °C. Regional crop models were driven by PRECIS output to predict changes in yields of key Chinese food crops: rice, maize and wheat. Modelling suggests that climate change without carbon dioxide (CO2) fertilization could reduce the rice, maize and wheat yields by up to 37% in the next 20–80 years. Interactions of CO2 with limiting factors, especially water and nitrogen, are increasingly well understood and capable of strongly modulating observed growth responses in crops. More complete reporting of free-air carbon enrichment experiments than was possible in the Intergovernmental Panel on Climate Change's Third Assessment Report confirms that CO2 enrichment under field conditions consistently increases biomass and yields in the range of 5–15%, with CO2 concentration elevated to 550 ppm Levels of CO2 that are elevated to more than 450 ppm will probably cause some deleterious effects in grain quality. It seems likely that the extent of the CO2 fertilization effect will depend upon other factors such as optimum breeding, irrigation and nutrient applications. PMID:16433100

  5. Modeling the Climatic Effect of Convergent Tectonics During the Middle to Late Miocene: Effective Closure of the Indonesian Seaway, Himalayan Uplift and the East Asian Monsoon

    NASA Astrophysics Data System (ADS)

    DeConto, R. M.; MacConnell, A.; Leckie, R.

    2001-05-01

    During the middle to late Miocene, the northward drift of Australia and New Guinea progressively restricted Indonesian throughflow (ITF). Today, ITF plays an important role in modulating inter-basin fresh water flux, heat transport, and the volume of the Western Pacific Warm Pool (WPWP). Today's WPWP is a center for deep convection that contributes considerable diabatic heating to the tropical atmosphere, affecting both the Walker and Hadley circulation. The WPWP fuels the East Asian Monsoon with moisture and latent heat and is an important component of ENSO. As the Indonesian Seaway became restricted, India was impinging on Asia. Asian continentality was increased and Himalayan/Tibetan uplift begun affecting zonal atmospheric flow and land-surface albedo. In order to better understand the climate system's response to changing Miocene paleogeography (horizontal and vertical tectonics), we have begun a series of climate model experiments using atmosphere, ocean, and coupled atmosphere-ocean general circulation models (GCMs). The GCM experiments are designed to isolate the possible response to effective Indonesian gateway closure within the framework of evolving Miocene Paleogeography between 11 and 7 Ma. In the first phase of our modeling study, an AGCM was used to test the sensitivity of tropical Indo-Pacific and Asian climate (including monsoonal intensity) to the presence of a WPWP in a pre and post Himalayan/Tibetan Plateau world. The results of the GCM simulations will be discussed in the context of the hypotheses that 1) a proto-WPWP became established as the Indonesian Seaway became increasingly restricted during the late middle to late Miocene; and 2) the growth of the WPWP had a first order affect on tropical Pacific climate and the East Asian monsoon.

  6. An assessment of irrigation needs and crop yield for the United States under potential climate changes

    USGS Publications Warehouse

    Brumbelow, Kelly; Georgakakos, Aris P.

    2000-01-01

    Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently

  7. Comparison of mid-Pliocene climate predictions produced by the HadAM3 and GCMAM3 General Circulation Models

    USGS Publications Warehouse

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

    2009-01-01

    The mid-Pliocene warm period (ca. 3 to 3.3??million years ago) has become an important interval of time for palaeoclimate modelling exercises, with a large number of studies published during the last decade. However, there has been no attempt to assess the degree of model dependency of the results obtained. Here we present an initial comparison of mid-Pliocene climatologies produced by the Goddard Institute for Space Studies and Hadley Centre for Climate Prediction and Research atmosphere-only General Circulation Models (GCMAM3 and HadAM3). Whilst both models are consistent in the simulation of broad-scale differences in mid-Pliocene surface air temperature and total precipitation rates, significant variation is noted on regional and local scales. There are also significant differences in the model predictions of total cloud cover. A terrestrial data/model comparison, facilitated by the BIOME 4 model and a new data set of Piacenzian Stage land cover [Salzmann, U., Haywood, A.M., Lunt, D.J., Valdes, P.J., Hill, D.J., (2008). A new global biome reconstruction and data model comparison for the Middle Pliocene. Global Ecology and Biogeography 17, 432-447, doi:10.1111/j.1466-8238.2007.00381.x] and combined with the use of Kappa statistics, indicates that HadAM3-based biome predictions provide a closer fit to proxy data in the mid to high-latitudes. However, GCMAM3-based biomes in the tropics provide the closest fit to proxy data. ?? 2008 Elsevier B.V.

  8. Studies of climate dynamics with innovative global-model simulations

    NASA Astrophysics Data System (ADS)

    Shi, Xiaoming

    Climate simulations with different degrees of idealization are essential for the development of our understanding of the climate system. Studies in this dissertation employ carefully designed global-model simulations for the goal of gaining theoretical and conceptual insights into some problems of climate dynamics. Firstly, global warming-induced changes in extreme precipitation are investigated using a global climate model with idealized geography. The precipitation changes over an idealized north-south mid-latitude mountain barrier at the western margin of an otherwise flat continent are studied. The intensity of the 40 most intense events on the western slopes increases by about ~4°C of surface warming. In contrast, the intensity of the top 40 events on the eastern mountain slopes increases at about ~6°C. This higher sensitivity is due to enhanced ascent during the eastern-slope events, which can be explained in terms of linear mountain-wave theory relating to global warming-induced changes in the upper-tropospheric static stability and the tropopause level. Dominated by different dynamical factors, changes in the intensity of extreme precipitation events over plains and oceans might differ from changes over mountains. So the response of extreme precipitation over mountains and flat areas are further compared using larger data sets of simulated extreme events over the two types of surfaces. It is found that the sensitivity of extreme precipitation to increases in global mean surface temperature is 3% per °C lower over mountains than over the oceans or the plains. The difference in sensitivity among these regions is not due to thermodynamic effects, but rather to differences between the gravity-wave dynamics governing vertical velocities over the mountains and the cyclone dynamics governing vertical motions over the oceans and plains. The strengthening of latent heating in the storms over oceans and plains leads to stronger ascent in the warming climate

  9. Integrating biomass, sulphate and sea-salt aerosol responses into a microphysical chemical parcel model: implications for climate studies.

    PubMed

    Ghosh, S; Smith, M H; Rap, A

    2007-11-15

    Aerosols are known to influence significantly the radiative budget of the Earth. Although the direct effect (whereby aerosols scatter and absorb solar and thermal infrared radiation) has a large perturbing influence on the radiation budget, the indirect effect (whereby aerosols modify the microphysical and hence the radiative properties and amounts of clouds) poses a greater challenge to climate modellers. This is because aerosols undergo chemical and physical changes while in the atmosphere, notably within clouds, and are removed largely by precipitation. The way in which aerosols are processed by clouds depends on the type, abundance and the mixing state of the aerosols concerned. A parametrization with sulphate and sea-salt aerosol has been successfully integrated within the Hadley Centre general circulation model (GCM). The results of this combined parametrization indicate a significantly reduced role, compared with previous estimates, for sulphate aerosol in cloud droplet nucleation and, consequently, in indirect radiative forcing. However, in this bicomponent system, the cloud droplet number concentration, N(d) (a crucial parameter that is used in GCMs for radiative transfer calculations), is a smoothly varying function of the sulphate aerosol loading. Apart from sea-salt and sulphate aerosol particles, biomass aerosol particles are also present widely in the troposphere. We find that biomass smoke can significantly perturb the activation and growth of both sulphate and sea-salt particles. For a fixed salt loading, N(d) increases linearly with modest increases in sulphate and smoke masses, but significant nonlinearities are observed at higher non-sea-salt mass loadings. This non-intuitive N(d) variation poses a fresh challenge to climate modellers.

  10. Climate in the absence of ocean heat transport

    NASA Astrophysics Data System (ADS)

    Rose, B. E. J.

    2017-12-01

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

  11. The contrasting response of Hadley circulation to different meridional structure of sea surface temperature in CMIP5

    NASA Astrophysics Data System (ADS)

    Feng, Juan; Li, Jianping; Zhu, Jianlei; Li, Yang; Li, Fei

    2018-02-01

    The response of the Hadley circulation (HC) to the sea surface temperature (SST) is determined by the meridional structure of SST and varies according to the changing nature of this meridional structure. The capability of the models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) is utilized to represent the contrast response of the HC to different meridional SST structures. To evaluate the responses, the variations of HC and SST were linearly decomposed into two components: the equatorially asymmetric (HEA for HC, and SEA for SST) and equatorially symmetric (HES for HC, and SES for SST) components. The result shows that the climatological features of HC and tropical SST (including the spatial structures and amplitude) are reasonably simulated in all the models. However, the response contrast of HC to different SST meridional structures shows uncertainties among models. This may be due to the fact that the long-term temporal variabilities of HEA, HES, and SEA are limited reproduced in the models, although the spatial structures of their long-term variabilities are relatively reasonably simulated. These results indicate that the performance of the CMIP5 models to simulate long-term temporal variability of different meridional SST structures and related HC variations plays a fundamental role in the successful reproduction of the response of HC to different meridional SST structures.

  12. Identifying robust regional precipitation responses to regional aerosol emissions perturbations in three coupled chemistry-climate models

    NASA Astrophysics Data System (ADS)

    Westervelt, D. M.; Fiore, A. M.; Lamarque, J. F.; Previdi, M. J.; Conley, A. J.; Shindell, D. T.; Mascioli, N. R.; Correa, G. J. P.; Faluvegi, G.; Horowitz, L. W.

    2017-12-01

    Regional emissions of anthropogenic aerosols and their precursors will likely decrease for the remainder of the 21st century, due to emission reduction policies enacted to protect human health. Although there is some evidence that regional climate effects of aerosols can be significant, we currently lack a robust understanding of the magnitude, spatio-temporal pattern, statistical significance, and physical processes responsible for these influences, especially for precipitation. Here, we aim to quantify systematically the precipitation response to regional changes in aerosols and investigate underlying mechanisms using three fully coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (CESM), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). The central approach we use is to contrast a long control experiment (400 years, run with perpetual year 2000 emissions) with 14 individual aerosol emissions perturbation experiments ( 200 years each). We perturb emissions of sulfur dioxide (SO2) and carbonaceous aerosol (BC and OM) within several world regions and assess which responses are significant relative to internal variability determined by the control run and robust across the three models. Initial results show significant changes in precipitation in several vulnerable regions including the Western Sahel and the Indian subcontinent. SO2 emissions reductions from Europe and the United States have the largest impact on precipitation among most of the selected response regions. The precipitation response to emissions changes from these regions projects onto known modes of variability, such as the North Atlantic Oscillation (NAO) and the El Niño Southern Oscillation (ENSO). Across all perturbation experiments, we find a strong linear relationship between the responses of Sahel precipitation and the interhemispheric temperature difference, suggesting a common mechanism of an

  13. Satellite Sounder Observations of Contrasting Tropospheric Moisture Transport Regimes: Saharan Air Layers, Hadley Cells, and Atmospheric Rivers

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

    Nalli, Nicholas R.; Barnet, Christopher D.; Reale, Tony

    This paper examines the performance of satellite sounder atmospheric vertical moisture proles (AVMP) under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs) and Pacific Ocean moisture conveyer belts (MCBs) commonly referred to as atmospheric rivers (ARs), both of these being mesoscale to synoptic meteorological phenomena within the vicinity of subtropical Hadley subsidence zones. Operational AVMP environmental data records retrieved from the Suomi National Polar-orbiting Partnership (SNPP) NOAA-Unique Combined Atmospheric Processing System (NUCAPS) are collocated with dedicated radiosonde observations (RAOBs) obtained from ocean-based intensive field campaigns; these RAOBs provide uniquelymore » independent correlative truth data not assimilated into numerical weather prediction models for satellite sounder validation over open ocean. Using these marine-based data, we empirically assess the performance of the operational NUCAPS AVMP product for detecting and resolving these tropospheric moisture features over otherwise RAOB-sparse regions.« less

  14. Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

    NASA Astrophysics Data System (ADS)

    Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; Chang, Ping

    2017-10-01

    We alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ˜8-50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the global average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.

  15. Climate Change Scenarios in the Yucatan Peninsula to the year 2020

    NASA Astrophysics Data System (ADS)

    Orellana, R.; Espadas, C.; Conde, C.; Gay, C.

    2010-03-01

    A topic that has not been sufficiently analyzed is that the global warming is already affecting, and that it will have worst consequences in those regions with transitional climates, which have more sensibility to changes. This is the case of the Yucatan Peninsula which is semi-arid in their northern portion, and toward the south is subhumid, with a tendency to be more rainy toward the south. To have an estimation of what could happen in the future, the Intergovernmental Panel of Climatic Change (IPCC) has promoted the use of General Circulation Models (GCM), as well as the construction of possible emission scenarios that integrate different global and regional socioeconomic and demographic conditions, which project then a possible increase of emissions of greenhouse gases. These conditions are recognized as the decisive forces that will determine the variations of temperature and of precipitation. These projections are useful for the analysis of climatic change, and in particular for the assessments of the possible impacts and of the initiatives of adaptation and of mitigation that should be implemented in every country or region. In Mexico, most of those evaluations of climate change have been carried out generally at country level. For that reason, it is necessary to direct the research at regional level. In this work, we evaluated the potential climatic changes on the Yucatan Peninsula, considering the different changes of temperature and precipitation as a consequence for different emission scenarios and for the horizon 2020. To project the environmental responses of the region, we used as a base scenario the available temperature and precipitation information of the period 1961-1990, registered in 85 meteorological stations of the peninsula. With these data, we generated climate change scenarios using the outputs of four General Circulation Models: HADLEY, ECHAM, GFDL and CGCM, and the emission scenarios A1FI, A2, B1 and B2. The outputs of these models were

  16. Impacts of weighting climate models for hydro-meteorological climate change studies

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

    2017-06-01

    Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

  17. Climate Model Diagnostic Analyzer

    NASA Technical Reports Server (NTRS)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  18. Now, Here's the Weather Forecast...

    ERIC Educational Resources Information Center

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  19. An observational and modeling study of the regional impacts of climate variability

    NASA Astrophysics Data System (ADS)

    Horton, Radley M.

    ) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be

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

    Lu, Jian; Vecchi, Gabriel A.

    The Hadley circulation, a prominent circulation feature characterized by rising air near the Equator and sinking air in the subtropics, defines the position of dry subtropical areas and is a fundamental regulator of the earth’s energy and momentum budgets. The character of the Hadley circulation, and its related precipitation regimes, exhibits variation and change in response to both climate variability and radiative forcing changes. The strength and position of the Hadley circulation change from year to year paced by El Niño and La Niña events. Over the last few decades of the twentieth century, the Hadley cell has expanded polewardmore » in both hemispheres, with changes in atmospheric composition (including stratospheric ozone depletion and greenhouse gas increases) thought to have contributed to its expansion. This article introduces the basic phenomenology and driving mechanism of the Hadley circulation and discusses its variations under both natural and anthropogenic climate forcings.« less

  1. Large-Scale Circulation and Climate Variability. Chapter 5

    NASA Technical Reports Server (NTRS)

    Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

    2017-01-01

    The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

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

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

    Oglesby, Robert J; Erickson III, David J

    2009-12-01

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

  3. Modeling glacial climates

    NASA Technical Reports Server (NTRS)

    North, G. R.; Crowley, T. J.

    1984-01-01

    Mathematical climate modelling has matured as a discipline to the point that it is useful in paleoclimatology. As an example a new two dimensional energy balance model is described and applied to several problems of current interest. The model includes the seasonal cycle and the detailed land-sea geographical distribution. By examining the changes in the seasonal cycle when external perturbations are forced upon the climate system it is possible to construct hypotheses about the origin of midlatitude ice sheets and polar ice caps. In particular the model predicts a rather sudden potential for glaciation over large areas when the Earth's orbital elements are only slightly altered. Similarly, the drift of continents or the change of atmospheric carbon dioxide over geological time induces radical changes in continental ice cover. With the advance of computer technology and improved understanding of the individual components of the climate system, these ideas will be tested in far more realistic models in the near future.

  4. The effects of future nationwide forest transition to discharge in the 21st century with regard to general circulation model climate change scenarios.

    PubMed

    Mouri, Goro; Nakano, Katsuhiro; Tsuyama, Ikutaro; Tanaka, Nobuyuki

    2016-08-01

    Forest disturbance (or land-cover change) and climatic variability are commonly recognised as two major drivers interactively influencing hydrology in forested watersheds. Future climate changes and corresponding changes in forest type and distribution are expected to generate changes in rainfall runoff that pose a threat to river catchments. It is therefore important to understand how future climate changes will effect average rainfall distribution and temperature and what effect this will have upon forest types across Japan. Recent deforestation of the present-day coniferous forest and expected increases in evergreen forest are shown to influence runoff processes and, therefore, to influence future runoff conditions. We strongly recommend that variations in forest type be considered in future plans to ameliorate projected climate changes. This will help to improve water retention and storage capacities, enhance the flood protection function of forests, and improve human health. We qualitatively assessed future changes in runoff including the effects of variation in forest type across Japan. Four general circulation models (GCMs) were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM), and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble including multiple physics configurations and different reference concentration pathways (RCP2.6, 4.5, and 8.5), the results of which have produced monthly data sets for the whole of Japan. The impacts of future climate changes on forest type in Japan are based on the balance amongst changes in rainfall distribution, temperature and hydrological factors. Methods for assessing the impact of such changes include the

  5. Linking models of human behaviour and climate alters projected climate change

    NASA Astrophysics Data System (ADS)

    Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

    2018-01-01

    Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

  6. Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

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

    Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.

    Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the globalmore » average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.« less

  7. Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

    DOE PAGES

    Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; ...

    2017-09-13

    Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the globalmore » average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.« less

  8. Selecting global climate models for regional climate change studies

    PubMed Central

    Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

    2009-01-01

    Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652

  9. Deriving user-informed climate information from climate model ensemble results

    NASA Astrophysics Data System (ADS)

    Huebener, Heike; Hoffmann, Peter; Keuler, Klaus; Pfeifer, Susanne; Ramthun, Hans; Spekat, Arne; Steger, Christian; Warrach-Sagi, Kirsten

    2017-07-01

    Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.

  10. National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

    NASA Astrophysics Data System (ADS)

    Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

    2006-12-01

    Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

  11. Linking models of human behaviour and climate alters projected climate change

    DOE PAGES

    Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; ...

    2018-01-01

    Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less

  12. Linking models of human behaviour and climate alters projected climate change

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

    Beckage, Brian; Gross, Louis J.; Lacasse, Katherine

    Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less

  13. The Monash University Interactive Simple Climate Model

    NASA Astrophysics Data System (ADS)

    Dommenget, D.

    2013-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  14. How climate change might influence the potential distribution of weed, bushmint (Hyptis suaveolens)?

    PubMed

    Padalia, Hitendra; Srivastava, Vivek; Kushwaha, S P S

    2015-04-01

    Invasive species and climate change are considered as the most serious global environmental threats. In this study, we investigated the influence of projected global climate change on the potential distribution of one of the world's most successful invader weed, bushmint (Hyptis suaveolens (L.) Poit.). We used spatial data on 20 environmental variables at a grid resolution of 5 km, and 564 presence records of bushmint from its native and introduced range. The climatic profiles of the native and invaded sites were analyzed in a multi-variate space in order to examine the differences in the position of climatic niches. Maximum Entropy (MaxEnt) model was used to predict the potential distribution of bushmint using presence records from entire range (invaded and native) along with 14 eco-physiologically relevant predictor variables. Subsequently, the trained MaxEnt model was fed with Hadley Centre Coupled Model (HadCM3) climate projections to predict potential distribution of bushmint by the year 2050 under A2a and B2a emission scenarios. MaxEnt predictions were very accurate with an Area Under Curve (AUC) value of 0.95. The results of Principal Component Analysis (PCA) indicated that climatic niche of bushmint on the invaded sites is not entirely similar to its climatic niche in the native range. A vast area spread between 34 ° 02' north and 28 ° 18' south latitudes in tropics was predicted climatically suitable for bushmint. West and middle Africa, tropical southeast Asia, and northern Australia were predicted at high invasion risk. Study indicates enlargement, retreat, or shift across bushmint's invasion range under the influence of climate change. Globally, bushmint's potential distribution might shrink in future with more shrinkage for A2a scenario than B2a. The study outcome has immense potential for undertaking effective preventive/control measures and long-term management strategies for regions/countries, which are at higher risk of bushmint's invasion.

  15. Projected changes in rainfall and temperature over homogeneous regions of India

    NASA Astrophysics Data System (ADS)

    Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

    2018-01-01

    The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

  16. SEEPLUS: A SIMPLE ONLINE CLIMATE MODEL

    NASA Astrophysics Data System (ADS)

    Tsutsui, Junichi

    A web application for a simple climate model - SEEPLUS (a Simple climate model to Examine Emission Pathways Leading to Updated Scenarios) - has been developed. SEEPLUS consists of carbon-cycle and climate-change modules, through which it provides the information infrastructure required to perform climate-change experiments, even on a millennial-timescale. The main objective of this application is to share the latest scientific knowledge acquired from climate modeling studies among the different stakeholders involved in climate-change issues. Both the carbon-cycle and climate-change modules employ impulse response functions (IRFs) for their key processes, thereby enabling the model to integrate the outcome from an ensemble of complex climate models. The current IRF parameters and forcing manipulation are basically consistent with, or within an uncertainty range of, the understanding of certain key aspects such as the equivalent climate sensitivity and ocean CO2 uptake data documented in representative literature. The carbon-cycle module enables inverse calculation to determine the emission pathway required in order to attain a given concentration pathway, thereby providing a flexible way to compare the module with more advanced modeling studies. The module also enables analytical evaluation of its equilibrium states, thereby facilitating the long-term planning of global warming mitigation.

  17. Weather Forecaster Understanding of Climate Models

    NASA Astrophysics Data System (ADS)

    Bol, A.; Kiehl, J. T.; Abshire, W. E.

    2013-12-01

    Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

  18. Forecasting the combined effects of urbanization and climate change on stream ecosystems: from impacts to management options

    PubMed Central

    Nelson, Kären C; Palmer, Margaret A; Pizzuto, James E; Moglen, Glenn E; Angermeier, Paul L; Hilderbrand, Robert H; Dettinger, Michael; Hayhoe, Katharine

    2009-01-01

    Streams collect runoff, heat, and sediment from their watersheds, making them highly vulnerable to anthropogenic disturbances such as urbanization and climate change. Forecasting the effects of these disturbances using process-based models is critical to identifying the form and magnitude of likely impacts. Here, we integrate a new biotic model with four previously developed physical models (downscaled climate projections, stream hydrology, geomorphology, and water temperature) to predict how stream fish growth and reproduction will most probably respond to shifts in climate and urbanization over the next several decades. The biotic submodel couples dynamics in fish populations and habitat suitability to predict fish assemblage composition, based on readily available biotic information (preferences for habitat, temperature, and food, and characteristics of spawning) and day-to-day variability in stream conditions. We illustrate the model using Piedmont headwater streams in the Chesapeake Bay watershed of the USA, projecting ten scenarios: Baseline (low urbanization; no on-going construction; and present-day climate); one Urbanization scenario (higher impervious surface, lower forest cover, significant construction activity); four future climate change scenarios [Hadley CM3 and Parallel Climate Models under medium-high (A2) and medium-low (B2) emissions scenarios]; and the same four climate change scenarios plus Urbanization. Urbanization alone depressed growth or reproduction of 8 of 39 species, while climate change alone depressed 22 to 29 species. Almost every recreationally important species (i.e. trouts, basses, sunfishes) and six of the ten currently most common species were predicted to be significantly stressed. The combined effect of climate change and urbanization on adult growth was sometimes large compared to the effect of either stressor alone. Thus, the model predicts considerable change in fish assemblage composition, including loss of diversity

  19. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    NASA Astrophysics Data System (ADS)

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

  20. Climate and atmospheric modeling studies

    NASA Technical Reports Server (NTRS)

    1992-01-01

    The climate and atmosphere modeling research programs have concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global model, and an upper ocean model. Principal applications were the study of the impact of CO2, aerosols, and the solar 'constant' on climate.

  1. North Atlantic forcing of tropical Indian Ocean climate.

    PubMed

    Mohtadi, Mahyar; Prange, Matthias; Oppo, Delia W; De Pol-Holz, Ricardo; Merkel, Ute; Zhang, Xiao; Steinke, Stephan; Lückge, Andreas

    2014-05-01

    The response of the tropical climate in the Indian Ocean realm to abrupt climate change events in the North Atlantic Ocean is contentious. Repositioning of the intertropical convergence zone is thought to have been responsible for changes in tropical hydroclimate during North Atlantic cold spells, but the dearth of high-resolution records outside the monsoon realm in the Indian Ocean precludes a full understanding of this remote relationship and its underlying mechanisms. Here we show that slowdowns of the Atlantic meridional overturning circulation during Heinrich stadials and the Younger Dryas stadial affected the tropical Indian Ocean hydroclimate through changes to the Hadley circulation including a southward shift in the rising branch (the intertropical convergence zone) and an overall weakening over the southern Indian Ocean. Our results are based on new, high-resolution sea surface temperature and seawater oxygen isotope records of well-dated sedimentary archives from the tropical eastern Indian Ocean for the past 45,000 years, combined with climate model simulations of Atlantic circulation slowdown under Marine Isotope Stages 2 and 3 boundary conditions. Similar conditions in the east and west of the basin rule out a zonal dipole structure as the dominant forcing of the tropical Indian Ocean hydroclimate of millennial-scale events. Results from our simulations and proxy data suggest dry conditions in the northern Indian Ocean realm and wet and warm conditions in the southern realm during North Atlantic cold spells.

  2. Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

    NASA Astrophysics Data System (ADS)

    Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

    2017-12-01

    limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for

  3. Documenting Climate Models and Their Simulations

    DOE PAGES

    Guilyardi, Eric; Balaji, V.; Lawrence, Bryan; ...

    2013-05-01

    The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. We describe a pilot community initiative to collect and make available documentation of climatemore » models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). We expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.« less

  4. General Circulation Model Simulations of the Annual Cycle of Martian Climate

    NASA Astrophysics Data System (ADS)

    Wilson, R.; Richardson, M.; Rodin, A.

    Observations of the martian atmosphere have revealed a strong annual modulation of global mean atmospheric temperature that has been attributed to the pronounced seasonal asymmetry in solar radiation and the highly variable distribution of aerosol. These observations indicate little interannual variability during the relatively cool aphelion season and considerable variability in the perihelion season that is associated with the episodic occurrence of regional and major dust storms. The atmospheric circulation responds to the evolving spatial distribution of aerosol-induced heating and, in turn, plays a major role in determining the sources, sinks, and transport of radiatively active aerosol. We will present simulations employing the GFDL Mars General Circulation Model (MGCM) that show that aspects of the seasonally evolving climate may be simulated in a self-consistent manner using simple dust source parameterizations that represent the effects of lifting associated with local dust storms, dust devil activity, and other processes. Aerosol transport is accomplished, in large part, by elements of the large-scale circulation such as the Hadley circulation, baroclinic storms, tides, etc. A seasonal cycle of atmospheric opacity and temperature results from the variation in the strength and distribution of dust sources as well as from seasonal variations in the efficiency of atmospheric transport associated with changes in the circulation between solstice and equinox, and between perihelion and aphelion. We examine the efficiency of atmospheric transport of dust lifted along the perimeter of the polar caps to gauge the influence of these storms on the global circulation. We also consider the influence of water, as the formation of water ice clouds on dust nuclei may also affect the vertical distribution of dust and strongly influence the aerosol radiative properties.

  5. Modeling the Climatic Consequences of Geoengineering

    NASA Astrophysics Data System (ADS)

    Somerville, R. C.

    2005-12-01

    The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert

  6. Evaluation of mean climate in a chemistry-climate model simulation

    NASA Astrophysics Data System (ADS)

    Hong, S.; Park, H.; Wie, J.; Park, R.; Lee, S.; Moon, B. K.

    2017-12-01

    Incorporation of the interactive chemistry is essential for understanding chemistry-climate interactions and feedback processes in climate models. Here we assess a newly developed chemistry-climate model (GRIMs-Chem), which is based on the Global/Regional Integrated Model system (GRIMs) including the aerosol direct effect as well as stratospheric linearized ozone chemistry (LINOZ). We conducted GRIMs-Chem with observed sea surface temperature during the period of 1979-2010, and compared the simulation results with observations and also with CMIP models. To measure the relative performance of our model, we define the quantitative performance metric using the Taylor diagram. This metric allow us to assess overall features in simulating multiple variables. Overall, our model better reproduce the zonal mean spatial pattern of temperature, horizontal wind, vertical motion, and relative humidity relative to other models. However, the model did not produce good simulations at upper troposphere (200 hPa). It is currently unclear which model processes are responsible for this. AcknowledgementsThis research was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program."

  7. Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

    PubMed

    Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

    2015-08-28

    There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of

  8. Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

    NASA Astrophysics Data System (ADS)

    Tatsumi, Kenichi; Oizumi, Tsutao; Yamashiki, Yosuke

    2015-04-01

    In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071-2099) and the base period (1961-1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and

  9. Coupling Climate Models and Forward-Looking Economic Models

    NASA Astrophysics Data System (ADS)

    Judd, K.; Brock, W. A.

    2010-12-01

    Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward

  10. Mapping the impact of climate change on surface recession of carbonate buildings in Europe.

    PubMed

    Bonazza, Alessandra; Messina, Palmira; Sabbioni, Cristina; Grossi, Carlota M; Brimblecombe, Peter

    2009-03-01

    Climate change is currently attracting interest at both research and policy levels. However, it is usually explored in terms of its effect on agriculture, water, industry, energy, transport and health and as yet has been insufficiently addressed as a factor threatening cultural heritage. Among the climate parameters critical to heritage conservation and expected to change in the future, precipitation plays an important role in surface recession of stone. The Lipfert function has been taken under consideration to quantify the annual surface recession of carbonate stone, due to the effects of clean rain, acid rain and dry deposition of pollutants. The present paper provides Europe-wide maps showing quantitative predictions of surface recession on carbonate stones for the 21st century, combining a modified Lipfert function with output from the Hadley global climate model. Chemical dissolution of carbonate stones, via the karst effect, will increase with future CO(2) concentrations, and will come to dominate over sulfur deposition and acid rain effects on monuments and buildings in both urban and rural areas. During the present century the rainfall contribution to surface recession is likely to have a small effect, while the increase in atmospheric CO(2) concentration is shown to be the main factor in increasing weathering via the karst effect.

  11. The Community Climate System Model.

    NASA Astrophysics Data System (ADS)

    Blackmon, Maurice; Boville, Byron; Bryan, Frank; Dickinson, Robert; Gent, Peter; Kiehl, Jeffrey; Moritz, Richard; Randall, David; Shukla, Jagadish; Solomon, Susan; Bonan, Gordon; Doney, Scott; Fung, Inez; Hack, James; Hunke, Elizabeth; Hurrell, James; Kutzbach, John; Meehl, Jerry; Otto-Bliesner, Bette; Saravanan, R.; Schneider, Edwin K.; Sloan, Lisa; Spall, Michael; Taylor, Karl; Tribbia, Joseph; Washington, Warren

    2001-11-01

    The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users. The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a flux coupler that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1% per year. In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several pro-jections of the climate of the twenty-first century. The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface

  12. Enabling the use of climate model data in the Dutch climate effect community

    NASA Astrophysics Data System (ADS)

    Som de Cerff, Wim; Plieger, Maarten

    2010-05-01

    Within the climate effect community the usage of climate model data is emerging. Where mostly climate time series and weather generators were used, there is a shift to incorporate climate model data into climate effect models. The use of climate model data within the climate effect models is difficult, due to missing metadata, resolution and projection issues, data formats and availability of the parameters of interest. Often the climate effect modelers are not aware of available climate model data or are not aware of how they can use it. Together with seven other partners (CERFACS, CNR-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 IS ENES (http://www.enes.org) project work package 10/JRA5 ‘Bridging Climate Research Data and the Needs of the Impact Community. The aims of this work package are to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. Phase one is to define use cases together with the Dutch climate effect community, which describe the intended use of climate model data in climate effect models. We defined four use cases: 1) FEWS hydrological Framework (Deltares) 2) METAPHOR, a plants and species dispersion model (Wageningen University) 3) Natuurplanner, an Ecological model suite (Wageningen University) 4) Land use models (Free University/JRC). Also the other partners in JRA5 have defined use cases, which are representative for the climate effect and impact communities in their country. Goal is to find commonalities between all defined use cases. The common functionality will be implemented as e-tools and incorporated in the IS-ENES data portal. Common issues relate to e.g., need for high resolution: downscaling from GCM to local scale (also involves interpolation); parameter selection; finding extremes; averaging methods. At the conference we will describe the FEWS case in more detail: Delft FEWS is an open shell system (in development since 1995) for performing

  13. Strategic Planning for Drought Mitigation Under Climate Change

    NASA Astrophysics Data System (ADS)

    Cai, X.; Zeng, R.; Valocchi, A. J.; Song, J.

    2012-12-01

    long-term planning, respectively, compared to the baseline of the climate of 1980-2000. To handle uncertainty in climate change projections, outputs from three General Circulation Models (GCMs) with Regional Climate Model (RCM) for dynamic downscaling (PCM-RCM, Hadley-RCM, and CCSM-RCM) and four CO2 emission scenarios are used to represent the various possible climatic conditions in the mid-term (2040's) and long-term (2090's) time horizons. The model results show the relative roles of mid- and long-term investments and the complementary relationships between wait-and-see decisions and here-and-now decisions on infrastructure expansion. Even the best tactical measures (irrigation operation) alone are not sufficient for drought mitigation in the future. Infrastructure expansion is critical especially for environmental conversation purposes. With increasing budget, investment should be shifted from tactical measures to strategic measures for drought preparedness. Infrastructure expansion is preferred for the long term plan than the mid-term plan, i.e., larger investment is proposed in 2040s than the current, due to a larger likelihood of drought in 2090s than 2040s. Thus larger BMP expansion is proposed in 2040s for droughts preparedness in 2090s.

  14. Validating predictions from climate envelope models

    USGS Publications Warehouse

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  15. The Art and Science of Climate Model Tuning

    DOE PAGES

    Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...

    2017-03-31

    The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

  16. The Art and Science of Climate Model Tuning

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

    Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew

    The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

  17. A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

    NASA Astrophysics Data System (ADS)

    Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

    2011-12-01

    Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples

  18. Uncertainty Quantification in Climate Modeling and Projection

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

    Qian, Yun; Jackson, Charles; Giorgi, Filippo

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

  19. Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

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

    Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith

    2011-02-01

    Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less

  20. Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin -Upper Blue Nile Basin of Ethiopia.

    PubMed

    Dile, Yihun Taddele; Berndtsson, Ronny; Setegn, Shimelis G

    2013-01-01

    Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.

  1. Hydrological Response to Climate Change for Gilgel Abay River, in the Lake Tana Basin - Upper Blue Nile Basin of Ethiopia

    PubMed Central

    Dile, Yihun Taddele; Berndtsson, Ronny; Setegn, Shimelis G.

    2013-01-01

    Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin. PMID:24250755

  2. Energy-balance climate models

    NASA Technical Reports Server (NTRS)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1980-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  3. Energy balance climate models

    NASA Technical Reports Server (NTRS)

    North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

    1981-01-01

    An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

  4. Climate simulations and projections with a super-parameterized climate model

    DOE PAGES

    Stan, Cristiana; Xu, Li

    2014-07-01

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

  5. Modeling Climate Dynamically

    ERIC Educational Resources Information Center

    Walsh, Jim; McGehee, Richard

    2013-01-01

    A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

  6. 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

  7. Probabilistic Evaluation of Competing Climate Models

    NASA Astrophysics Data System (ADS)

    Braverman, A. J.; Chatterjee, S.; Heyman, M.; Cressie, N.

    2017-12-01

    A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. Here, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data, over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. We compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set, as an illustration.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  9. Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate

    NASA Astrophysics Data System (ADS)

    Kröner, Nico; Kotlarski, Sven; Fischer, Erich; Lüthi, Daniel; Zubler, Elias; Schär, Christoph

    2017-05-01

    Climate models robustly project a strong overall summer warming across Europe showing a characteristic north-south gradient with enhanced warming and drying in southern Europe. However, the processes that are responsible for this pattern are not fully understood. We here employ an extended surrogate or pseudo-warming approach to disentangle the contribution of different mechanisms to this response pattern. The basic idea of the surrogate technique is to use a regional climate model and apply a large-scale warming to the lateral boundary conditions of a present-day reference simulation, while maintaining the relative humidity (and thus implicitly increasing the specific moisture content). In comparison to previous studies, our approach includes two important extensions: first, different vertical warming profiles are applied in order to separate the effects of a mean warming from lapse-rate effects. Second, a twin-design is used, in which the climate change signals are not only added to present-day conditions, but also subtracted from a scenario experiment. We demonstrate that these extensions provide an elegant way to separate the full climate change signal into contributions from large-scale thermodynamic (TD), lapse-rate (LR), and circulation and other remaining effects (CO). The latter in particular include changes in land-ocean contrast and spatial variations of the SST warming patterns. We find that the TD effect yields a large-scale warming across Europe with no distinct latitudinal gradient. The LR effect, which is quantified for the first time in our study, leads to a stronger warming and some drying in southern Europe. It explains about 50 % of the warming amplification over the Iberian Peninsula, thus demonstrating the important role of lapse-rate changes. The effect is linked to an extending Hadley circulation. The CO effect as inherited from the driving GCM is shown to further amplify the north-south temperature change gradient. In terms of mean summer

  10. Modeling human-climate interaction

    NASA Astrophysics Data System (ADS)

    Jacoby, Henry D.

    If policymakers and the public are to be adequately informed about the climate change threat, climate modeling needs to include components far outside its conventional boundaries. An integration of climate chemistry and meteorology, oceanography, and terrestrial biology has been achieved over the past few decades. More recently the scope of these studies has been expanded to include the human systems that influence the planet, the social and ecological consequences of potential change, and the political processes that lead to attempts at mitigation and adaptation. For example, key issues—like the relative seriousness of climate change risk, the choice of long-term goals for policy, and the analysis of today's decisions when uncertainty may be reduced tomorrow—cannot be correctly understood without joint application of the natural science of the climate system and social and behavioral science aspects of human response. Though integration efforts have made significant contributions to understanding of the climate issue, daunting intellectual and institutional barriers stand in the way of needed progress. Deciding appropriate policies will be a continuing task over the long term, however, so efforts to extend the boundaries of climate modeling and assessment merit long-term attention as well. Components of the effort include development of a variety of approaches to analysis, the maintenance of a clear a division between close-in decision support and science/policy research, and the development of funding institutions that can sustain integrated research over the long haul.

  11. Sensitivity of South American tropical climate to Last Glacial Maximum boundary conditions: focus on teleconnections with tropics and extratropics (Invited)

    NASA Astrophysics Data System (ADS)

    Khodri, M.; Kageyama, M.; Roche, D. M.

    2009-12-01

    Proxy data over tropical latitudes for the Last Glacial Maximum (LGM) has been interpreted as a southward shift of the Inter Tropical Convergence Zone (ITCZ) and so far linked to a mechanism analogous to the modern day “meridional-mode” in the Atlantic Ocean. Here we have explored alternative mechanisms, related to the direct impact of the LGM global changes in the dry static stability on tropical moist deep convection. We have used a coupled ocean-atmosphere model capable of capturing the thermodynamical structure of the atmosphere and the tropical component of the Hadley and Walker circulations. In each experiment, we have applied either all the LGM forcings, or the individual contributions of greenhouse gases (GHG) concentrations, ice sheet topography and/or albedo to explore the hydrological response over tropical latitudes with a focus on South America. The dominant forcing for the LGM tropical temperature and precipitation changes is found to be due to the reduced GHG, through the direct effect of reduced radiative heating (Clausius-Clapeyron relationship). The LGM GHG is also responsible for increased extra-tropical static stability which strengthens the Hadley Cell. Stronger subsidence over northern tropics then produces an amplification of the northern tropics drying initially due to the direct cooling effect. The land ice sheet is also able to promote the Hadley cell feedback mostly via the topographic effect on the extra-tropical dry static stability and on the position of the subtropical jets. Our results therefore suggest that the communication between the extratropics and the tropics is tighter during LGM and does not necessarily rely on the “meridional-mode” mechanism. The Hadley cell response is constrained by the requirement that diabatic heating in the tropics balances cooling in subtropics. We show that such extratropics-tropics dependence is stronger at the LGM because of the stronger perturbation of northern extra tropical thermal and

  12. Reconstructing Holocene climate using a climate model: Model strategy and preliminary results

    NASA Astrophysics Data System (ADS)

    Haberkorn, K.; Blender, R.; Lunkeit, F.; Fraedrich, K.

    2009-04-01

    An Earth system model of intermediate complexity (Planet Simulator; PlaSim) is used to reconstruct Holocene climate based on proxy data. The Planet Simulator is a user friendly general circulation model (GCM) suitable for palaeoclimate research. Its easy handling and the modular structure allow for fast and problem dependent simulations. The spectral model is based on the moist primitive equations conserving momentum, mass, energy and moisture. Besides the atmospheric part, a mixed layer-ocean with sea ice and a land surface with biosphere are included. The present-day climate of PlaSim, based on an AMIP II control-run (T21/10L resolution), shows reasonable agreement with ERA-40 reanalysis data. Combining PlaSim with a socio-technological model (GLUES; DFG priority project INTERDYNAMIK) provides improved knowledge on the shift from hunting-gathering to agropastoral subsistence societies. This is achieved by a data assimilation approach, incorporating proxy time series into PlaSim to initialize palaeoclimate simulations during the Holocene. For this, the following strategy is applied: The sensitivities of the terrestrial PlaSim climate are determined with respect to sea surface temperature (SST) anomalies. Here, the focus is the impact of regionally varying SST both in the tropics and the Northern Hemisphere mid-latitudes. The inverse of these sensitivities is used to determine the SST conditions necessary for the nudging of land and coastal proxy climates. Preliminary results indicate the potential, the uncertainty and the limitations of the method.

  13. Climate Sensitivity of the Community Climate System Model, Version 4

    DOE PAGES

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

    2012-05-01

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

  14. Developing Models for Predictive Climate Science

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

    Drake, John B; Jones, Philip W

    2007-01-01

    The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of

  15. The climate4impact platform: Providing, tailoring and facilitating climate model data access

    NASA Astrophysics Data System (ADS)

    Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

    2017-04-01

    One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European

  16. ARM-Led Improvements Aerosols in Climate and Climate Models

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

    Ghan, Steven J.; Penner, Joyce E.

    2016-07-25

    The DOE ARM program has played a foundational role in efforts to quantify aerosol effects on climate, beginning with the early back-of-the-envelope estimates of direct radiative forcing by anthropogenic sulfate and biomass burning aerosol (Penner et al., 1994). In this chapter we review the role that ARM has played in subsequent detailed estimates based on physically-based representations of aerosols in climate models. The focus is on quantifying the direct and indirect effects of anthropogenic aerosol on the planetary energy balance. Only recently have other DOE programs applied the aerosol modeling capability to simulate the climate response to the radiative forcing.

  17. Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

    USGS Publications Warehouse

    Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

    2014-01-01

    Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

  18. The Finer Details: Climate Modeling

    NASA Technical Reports Server (NTRS)

    2000-01-01

    If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

  19. Climate Model Diagnostic Analyzer Web Service System

    NASA Astrophysics Data System (ADS)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

    2015-12-01

    Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

  20. Modeling and assessing international climate financing

    NASA Astrophysics Data System (ADS)

    Wu, Jing; Tang, Lichun; Mohamed, Rayman; Zhu, Qianting; Wang, Zheng

    2016-06-01

    Climate financing is a key issue in current negotiations on climate protection. This study establishes a climate financing model based on a mechanism in which donor countries set up funds for climate financing and recipient countries use the funds exclusively for carbon emission reduction. The burden-sharing principles are based on GDP, historical emissions, and consumptionbased emissions. Using this model, we develop and analyze a series of scenario simulations, including a financing program negotiated at the Cancun Climate Change Conference (2010) and several subsequent programs. Results show that sustained climate financing can help to combat global climate change. However, the Cancun Agreements are projected to result in a reduction of only 0.01°C in global warming by 2100 compared to the scenario without climate financing. Longer-term climate financing programs should be established to achieve more significant benefits. Our model and simulations also show that climate financing has economic benefits for developing countries. Developed countries will suffer a slight GDP loss in the early stages of climate financing, but the longterm economic growth and the eventual benefits of climate mitigation will compensate for this slight loss. Different burden-sharing principles have very similar effects on global temperature change and economic growth of recipient countries, but they do result in differences in GDP changes for Japan and the FSU. The GDP-based principle results in a larger share of financial burden for Japan, while the historical emissions-based principle results in a larger share of financial burden for the FSU. A larger burden share leads to a greater GDP loss.

  1. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

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

    Auffhammer, M.; Hsiang, S. M.; Schlenker, W.

    2013-06-28

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overviewmore » of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.« less

  2. Analysis of heat wave occurrences in the Carpathian basin using regional climate model simulations

    NASA Astrophysics Data System (ADS)

    Bartha, E. B.; Pongracz, R.; Bartholy, J.

    2012-04-01

    Human health is very likely affected by regional consequences of global warming. One of the most severe impacts is probably associated to temperature-related climatological extremes, such as heat waves. In the coming decades hot conditions in most regions of the world are very likely to occur more frequently and more intensely than in the recent decades. In order to develop adaptation and mitigation strategies on local scale, it is essential to analyze the projected changes related to warming climatic conditions including heat waves. In 2004, a Heat Health Watch Warning System was developed in Hungary on the basis of a retrospective analysis of mortality and meteorological data to anticipate heat waves that may result in a large excess of mortality. In the frame of this recently introduced Health Watch System, three levels of heat wave warning are applied. They are associated to the daily mean temperature values, and defined as follows: - Warning level 1 (advisory for internal use) is issued when the daily mean temperature exceeds 25 °C. - Warning level 2 (heat wave watch) is issued when the daily mean temperature for at least 3 consecutive days exceeds 25 °C. - Warning level 3 (heat wave alert) is issued when the daily mean temperature for at least 3 consecutive days exceeds 27 °C. In the present study, frequency of the above climatic conditions are analyzed using regional climate model (RCM) experiments are analyzed for the recent past and the coming decades (1961-2100) for the Carpathian basin. At the Dept. of Meteorology, Eotvos Lorand University two different RCMs have been adapted: RegCM (with 10 km horizontal resolution, originally developed by Giorgi et al., currently, available from the International Centre for Theoretical Physics, ICTP) and PRECIS (with 25 km horizontal resolution, developed at the UK Met Office, Hadley Centre). Their initial and lateral boundary conditions have been provided by global climate models ECHAM and HadCM3, respectively. For

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

    PubMed

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

    2016-01-01

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

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

    DOE PAGES

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

    2016-09-28

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

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

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

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

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

  6. Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

    NASA Astrophysics Data System (ADS)

    Daron, Joseph

    2010-05-01

    Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci

  7. Climate Ocean Modeling on Parallel Computers

    NASA Technical Reports Server (NTRS)

    Wang, P.; Cheng, B. N.; Chao, Y.

    1998-01-01

    Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

  8. Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales

    NASA Astrophysics Data System (ADS)

    Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.

    2017-12-01

    Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.

  9. Modelling the Climate - Greenland Ice Sheet Interaction in the Coupled Ice-sheet/Climate Model EC-EARTH - PISM

    NASA Astrophysics Data System (ADS)

    Yang, S.; Madsen, M. S.; Rodehacke, C. B.; Svendsen, S. H.; Adalgeirsdottir, G.

    2014-12-01

    Recent observations show that the Greenland ice sheet (GrIS) has been losing mass with an increasing speed during the past decades. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems with an explicit and physically consistent ice sheet module. A fully coupled global climate model with a dynamical ice sheet model for the GrIS has recently been developed. The model system, EC-EARTH - PISM, consists of the EC-EARTH, an atmosphere, ocean and sea ice model system, and the Parallel Ice Sheet Model (PISM). The coupling of PISM includes a modified surface physical parameterization in EC-EARTH adapted to the land ice surface over glaciated regions in Greenland. The PISM ice sheet model is forced with the surface mass balance (SMB) directly computed inside the EC-EARTH atmospheric module and accounting for the precipitation, the surface evaporation, and the melting of snow and ice over land ice. PISM returns the simulated basal melt, ice discharge and ice cover (extent and thickness) as boundary conditions to EC-EARTH. This coupled system is mass and energy conserving without being constrained by any anomaly correction or flux adjustment, and hence is suitable for investigation of ice sheet - climate feedbacks. Three multi-century experiments for warm climate scenarios under (1) the RCP85 climate forcing, (2) an abrupt 4xCO2 and (3) an idealized 1% per year CO2 increase are performed using the coupled model system. The experiments are compared with their counterparts of the standard CMIP5 simulations (without the interactive ice sheet) to evaluate the performance of the coupled system and to quantify the GrIS feedbacks. In particular, the evolution of the Greenland ice sheet under the warm climate and its impacts on the climate system are investigated. Freshwater fluxes from the Greenland ice sheet melt to the Arctic

  10. An Exploration of Mechanisms for Mediating the Influence of Extratropical Glaciation on the Tropical Climate

    NASA Astrophysics Data System (ADS)

    Pierrehumbert, R. T.; Frierson, D. M.

    2006-05-01

    the NHWARM and NHCOLD cases, despite the substantial reduction in atmospheric water vapor in the cold case. The extremely strong midlatitude cooling produces a modest southward shift in the January ITCZ, and none at all in the July ITCZ, indicating that basic Hadley dynamics can make the ITCZ very resistant to moving; we find that the ITCZ position closely follows the tropical temperature maximum. The ITCZ shifts are discussed in terms of theoretical concepts applying to the Hadley circulation. Using an energy balance model (EBM) based on diffusion of moist static energy, Frierson and Held have shown that there is a compensation between changes in latent and sensible heat transport as climate warms, provided the meridional distribution of absorbed solar radiation remains fixed. We have extended this analysis to the case in which the solar forcing gradient is allowed to change, as is the case in our simulations owing to the change in surface albedo between the two simulations. In this case, the EBM does not require strict compensation, and in fact correctly reproduces the fact that tropical heat export increases in the NHCOLD case. However, the EBM over-estimates the penetration of the cooling past the Equator, owing to inadequacies in the diffusive treatment of the Hadley circulation. The EBM also misprepresents the magnitude of midlatitude heat flux changes, owing to the bottom-trapped nature of extratropical cooling seen in the GCM experiments, which is not reflected in the assumptions about the vertical profile of temperature built into the EBM. The implications of incorporating this effect will be discussed.

  11. COP21 climate negotiators' responses to climate model forecasts

    NASA Astrophysics Data System (ADS)

    Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo

    2017-02-01

    Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest.

  12. Modeling erosion under future climates with the WEPP model

    Treesearch

    Timothy Bayley; William Elliot; Mark A. Nearing; D. Phillp Guertin; Thomas Johnson; David Goodrich; Dennis Flanagan

    2010-01-01

    The Water Erosion Prediction Project Climate Assessment Tool (WEPPCAT) was developed to be an easy-to-use, web-based erosion model that allows users to adjust climate inputs for user-specified climate scenarios. WEPPCAT allows the user to modify monthly mean climate parameters, including maximum and minimum temperatures, number of wet days, precipitation, and...

  13. Anticipating Installation Natural Resource Climate Change Concerns: The Data

    DTIC Science & Technology

    2013-10-15

    period of development (1 to 2 decades) include: 1. CM2.1 (GFDL model — NOAA Princeton) 2. E-H and E-R ( NASA GISS) 3. HadGEM1 (Hadley UKMO) 4. CGCM3...sixth GCM, the Australian CSIRO model, to increase the sample. Thus the adopted GCMs include: 1. GFDL model (NOAA Princeton) 6. GISS Model e ( NASA ...Sciences La- boratory ( USDA 2012) created data that would be useful to the related threshold project. This US Forest Service date were similar to those of

  14. Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

    NASA Astrophysics Data System (ADS)

    Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain

    2011-12-01

    Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.

  15. Data-driven Climate Modeling and Prediction

    NASA Astrophysics Data System (ADS)

    Kondrashov, D. A.; Chekroun, M.

    2016-12-01

    Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results

  16. Global precipitation measurements for validating climate models

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

  17. Amazon Basin climate under global warming: the role of the sea surface temperature.

    PubMed

    Harris, Phil P; Huntingford, Chris; Cox, Peter M

    2008-05-27

    The Hadley Centre coupled climate-carbon cycle model (HadCM3LC) predicts loss of the Amazon rainforest in response to future anthropogenic greenhouse gas emissions. In this study, the atmospheric component of HadCM3LC is used to assess the role of simulated changes in mid-twenty-first century sea surface temperature (SST) in Amazon Basin climate change. When the full HadCM3LC SST anomalies (SSTAs) are used, the atmosphere model reproduces the Amazon Basin climate change exhibited by HadCM3LC, including much of the reduction in Amazon Basin rainfall. This rainfall change is shown to be the combined effect of SSTAs in both the tropical Atlantic and the Pacific, with roughly equal contributions from each basin. The greatest rainfall reduction occurs from May to October, outside of the mature South American monsoon (SAM) season. This dry season response is the combined effect of a more rapid warming of the tropical North Atlantic relative to the south, and warm SSTAs in the tropical east Pacific. Conversely, a weak enhancement of mature SAM season rainfall in response to Atlantic SST change is suppressed by the atmospheric response to Pacific SST. This net wet season response is sufficient to prevent dry season soil moisture deficits from being recharged through the SAM season, leading to a perennial soil moisture reduction and an associated 30% reduction in annual Amazon Basin net primary productivity (NPP). A further 23% NPP reduction occurs in response to a 3.5 degrees C warmer air temperature associated with a global mean SST warming.

  18. The climate of Mars

    NASA Astrophysics Data System (ADS)

    Haberle, R. M.

    1986-05-01

    The composition of the primitive Martian atmosphere and its development into the present environment are described. The primitive atmosphere consisted of water vapor, carbon dioxide, and nitrogen released from rocks; the greenhouse effect which maintained the surface temperature above the frost point of water is examined. Volcanic activity reduced the greenhouse effect and along with CO2 removal from the atmosphere caused a lowering of the planet temperature. The global circulation patterns on earth and Mars are compared; the similarities in the circulation patterns and Mars' seasonal variations are studied. The carbon dioxide and water cycles on Mars are analyzed; the carbon dioxide cycle determines seasonal variations in surface pressure and the behavior of the water cycle. The behavior of the atmospheric dust and the relationship between the seasonal dust cycle and Hadley circulation are investigated. The periodic variations in the three orbital parameters of Mars, which affect the climate by changing the seasonal and latitudinal distribution of incoming solar energy are discussed

  19. Objective calibration of regional climate models

    NASA Astrophysics Data System (ADS)

    Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

    2012-12-01

    Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented

  20. Impacts of Climate Change on Management of the Colorado River Reservoir System

    NASA Astrophysics Data System (ADS)

    Christensen, N. S.; Lettenmaier, D. P.

    2002-05-01

    The Colorado River system provides water supply to a large area of the interior west. It drains a mostly arid area, with naturalized flow (effects of reservoirs and diversions removed) averaging only 40 mm/yr over the 630,000 km2 drainage area at the mouth of the river. Total reservoir storage (mostly behind Hoover and Glen Canyon Dams) is equivalent to over four times the mean flow of the river. Runoff is heavily dominated by high elevation source areas in the Rocky Mountain headwaters, and the seasonal runoff pattern throughout the Colorado basin is strongly dominated by winter snow accumulation and spring melt. Because of the arid nature of the basin and the low runoff per unit area, performance of the reservoir system is potentially susceptible to changes in streamflow that would result from global warming, although those manifestations are somewhat different than elsewhere in the west where reservoir storage is relatively much smaller. We evaluate, using the macroscale Variable Infiltration Capacity (VIC) model, possible changes in streamflow over the next century using three 100-year ensemble climate simulations of the NCAR/DOE Parallel Climate Model corresponding to business-as-usual (BAU) future greenhouse gas emissions. Single ensemble simulations of the U.K. Hadley Center, and the Max Planck Institute, are considered as well. For most of the climate scenarios, the peak runoff shifts about one month earlier relative to the recent past. However, unlike reservoir systems elsewhere in the west, the effect of these timing shifts is largely mitigated by the size of the reservoir system, and changes in reservoir system reliability (for agricultural water supply and hydropower production) are dominated by streamflow volume shifts, which vary considerably across the climate scenarios.

  1. Integrated approaches to climate-crop modelling: needs and challenges.

    PubMed

    Betts, Richard A

    2005-11-29

    This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation

  2. Selection of climate change scenario data for impact modelling.

    PubMed

    Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

  3. An introduction to three-dimensional climate modeling

    NASA Technical Reports Server (NTRS)

    Washington, W. M.; Parkinson, C. L.

    1986-01-01

    The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

  4. Simulating fire regimes in the Amazon in response to climate change and deforestation.

    PubMed

    Silvestrini, Rafaella Almeida; Soares-Filho, Britaldo Silveira; Nepstad, Daniel; Coe, Michael; Rodrigues, Hermann; Assunção, Renato

    2011-07-01

    Fires in tropical forests release globally significant amounts of carbon to the atmosphere and may increase in importance as a result of climate change. Despite the striking impacts of fire on tropical ecosystems, the paucity of robust spatial models of forest fire still hampers our ability to simulate tropical forest fire regimes today and in the future. Here we present a probabilistic model of human-induced fire occurrence for the Amazon that integrates the effects of a series of anthropogenic factors with climatic conditions described by vapor pressure deficit. The model was calibrated using NOAA-12 night satellite hot pixels for 2003 and validated for the years 2002, 2004, and 2005. Assessment of the fire risk map yielded fitness values > 85% for all months from 2002 to 2005. Simulated fires exhibited high overlap with NOAA-12 hot pixels regarding both spatial and temporal distributions, showing a spatial fit of 50% within a radius of 11 km and a maximum yearly frequency deviation of 15%. We applied this model to simulate fire regimes in the Amazon until 2050 using IPCC's A2 scenario climate data from the Hadley Centre model and a business-as-usual (BAU) scenario of deforestation and road expansion from SimAmazonia. Results show that the combination of these scenarios may double forest fire occurrence outside protected areas (PAs) in years of extreme drought, expanding the risk of fire even to the northwestern Amazon by midcentury. In particular, forest fires may increase substantially across southern and southwestern Amazon, especially along the highways slated for paving and in agricultural zones. Committed emissions from Amazon forest fires and deforestation under a scenario of global warming and uncurbed deforestation may amount to 21 +/- 4 Pg of carbon by 2050. BAU deforestation may increase fires occurrence outside PAs by 19% over the next four decades, while climate change alone may account for a 12% increase. In turn, the combination of climate change

  5. Using a Global Climate Model in an On-line Climate Change Course

    NASA Astrophysics Data System (ADS)

    Randle, D. E.; Chandler, M. A.; Sohl, L. E.

    2012-12-01

    Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

  6. Modeling lakes and reservoirs in the climate system

    USGS Publications Warehouse

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

  7. Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

    NASA Astrophysics Data System (ADS)

    Bermudez, L. E.; Percivall, G.; Idol, T. A.

    2015-12-01

    Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues

  8. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

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

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

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds

  9. Model falsifiability and climate slow modes

    NASA Astrophysics Data System (ADS)

    Essex, Christopher; Tsonis, Anastasios A.

    2018-07-01

    The most advanced climate models are actually modified meteorological models attempting to capture climate in meteorological terms. This seems a straightforward matter of raw computing power applied to large enough sources of current data. Some believe that models have succeeded in capturing climate in this manner. But have they? This paper outlines difficulties with this picture that derive from the finite representation of our computers, and the fundamental unavailability of future data instead. It suggests that alternative windows onto the multi-decadal timescales are necessary in order to overcome the issues raised for practical problems of prediction.

  10. A personal perspective on modelling the climate system.

    PubMed

    Palmer, T N

    2016-04-01

    Given their increasing relevance for society, I suggest that the climate science community itself does not treat the development of error-free ab initio models of the climate system with sufficient urgency. With increasing levels of difficulty, I discuss a number of proposals for speeding up such development. Firstly, I believe that climate science should make better use of the pool of post-PhD talent in mathematics and physics, for developing next-generation climate models. Secondly, I believe there is more scope for the development of modelling systems which link weather and climate prediction more seamlessly. Finally, here in Europe, I call for a new European Programme on Extreme Computing and Climate to advance our ability to simulate climate extremes, and understand the drivers of such extremes. A key goal for such a programme is the development of a 1 km global climate system model to run on the first exascale supercomputers in the early 2020s.

  11. A personal perspective on modelling the climate system

    PubMed Central

    Palmer, T. N.

    2016-01-01

    Given their increasing relevance for society, I suggest that the climate science community itself does not treat the development of error-free ab initio models of the climate system with sufficient urgency. With increasing levels of difficulty, I discuss a number of proposals for speeding up such development. Firstly, I believe that climate science should make better use of the pool of post-PhD talent in mathematics and physics, for developing next-generation climate models. Secondly, I believe there is more scope for the development of modelling systems which link weather and climate prediction more seamlessly. Finally, here in Europe, I call for a new European Programme on Extreme Computing and Climate to advance our ability to simulate climate extremes, and understand the drivers of such extremes. A key goal for such a programme is the development of a 1 km global climate system model to run on the first exascale supercomputers in the early 2020s. PMID:27274686

  12. Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

    NASA Technical Reports Server (NTRS)

    Thiele, O. (Editor); Schiffer, R. A. (Editor)

    1985-01-01

    The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

  13. Climate Change: Modeling the Human Response

    NASA Astrophysics Data System (ADS)

    Oppenheimer, M.; Hsiang, S. M.; Kopp, R. E.

    2012-12-01

    Integrated assessment models have historically relied on forward modeling including, where possible, process-based representations to project climate change impacts. Some recent impact studies incorporate the effects of human responses to initial physical impacts, such as adaptation in agricultural systems, migration in response to drought, and climate-related changes in worker productivity. Sometimes the human response ameliorates the initial physical impacts, sometimes it aggravates it, and sometimes it displaces it onto others. In these arenas, understanding of underlying socioeconomic mechanisms is extremely limited. Consequently, for some sectors where sufficient data has accumulated, empirically based statistical models of human responses to past climate variability and change have been used to infer response sensitivities which may apply under certain conditions to future impacts, allowing a broad extension of integrated assessment into the realm of human adaptation. We discuss the insights gained from and limitations of such modeling for benefit-cost analysis of climate change.

  14. The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

    NASA Astrophysics Data System (ADS)

    Ines, A. V. M.; Han, E.; Baethgen, W.

    2017-12-01

    Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

  15. Development of ALARO-Climate regional climate model for a very high resolution

    NASA Astrophysics Data System (ADS)

    Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

    2013-04-01

    ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

  16. Crop response to climate: ecophysical models

    USDA-ARS?s Scientific Manuscript database

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

  17. Modelling climate change and malaria transmission.

    PubMed

    Parham, Paul E; Michael, Edwin

    2010-01-01

    The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here

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

    PubMed Central

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

    2015-01-01

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

  19. Assessing NARCCAP climate model effects using spatial confidence regions.

    PubMed

    French, Joshua P; McGinnis, Seth; Schwartzman, Armin

    2017-01-01

    We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  20. Assessing NARCCAP climate model effects using spatial confidence regions

    PubMed Central

    French, Joshua P.; McGinnis, Seth; Schwartzman, Armin

    2017-01-01

    We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference. PMID:28936474

  1. Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change.

    PubMed

    Lawing, A Michelle; Polly, P David

    2011-01-01

    Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr).

  2. Pleistocene Climate, Phylogeny, and Climate Envelope Models: An Integrative Approach to Better Understand Species' Response to Climate Change

    PubMed Central

    Lawing, A. Michelle; Polly, P. David

    2011-01-01

    Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr). PMID:22164305

  3. Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

    NASA Astrophysics Data System (ADS)

    Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

    2015-04-01

    Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from

  4. Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

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

    Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

    This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less

  5. Intercomparison of model response and internal variability across climate model ensembles

    NASA Astrophysics Data System (ADS)

    Kumar, Devashish; Ganguly, Auroop R.

    2017-10-01

    Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

  6. The role of soil moisture in land surface-atmosphere coupling: climate model sensitivity experiments over India

    NASA Astrophysics Data System (ADS)

    Williams, Charles; Turner, Andrew

    2015-04-01

    It is generally acknowledged that anthropogenic land use changes, such as a shift from forested land into irrigated agriculture, may have an impact on regional climate and, in particular, rainfall patterns in both time and space. India provides an excellent example of a country in which widespread land use change has occurred during the last century, as the country tries to meet its growing demand for food. Of primary concern for agriculture is the Indian summer monsoon (ISM), which displays considerable seasonal and subseasonal variability. Although it is evident that changing rainfall variability will have a direct impact on land surface processes (such as soil moisture variability), the reverse impact is less well understood. However, the role of soil moisture in the coupling between the land surface and atmosphere needs to be properly explored before any potential impact of changing soil moisture variability on ISM rainfall can be understood. This paper attempts to address this issue, by conducting a number of sensitivity experiments using a state-of-the-art climate model from the UK Meteorological Office Hadley Centre: HadGEM2. Several experiments are undertaken, with the only difference between them being the extent to which soil moisture is coupled to the atmosphere. Firstly, the land surface is fully coupled to the atmosphere, globally (as in standard model configurations); secondly, the land surface is entirely uncoupled from the atmosphere, again globally, with soil moisture values being prescribed on a daily basis; thirdly, the land surface is uncoupled from the atmosphere over India but fully coupled elsewhere; and lastly, vice versa (i.e. the land surface is coupled to the atmosphere over India but uncoupled elsewhere). Early results from this study suggest certain 'hotspot' regions where the impact of soil moisture coupling/uncoupling may be important, and many of these regions coincide with previous studies. Focusing on the third experiment, i

  7. Refining climate models

    ScienceCinema

    Warren, Jeff; Iversen, Colleen; Brooks, Jonathan; Ricciuto, Daniel

    2018-02-13

    Using dogwood trees, Oak Ridge National Laboratory researchers are gaining a better understanding of the role photosynthesis and respiration play in the atmospheric carbon dioxide cycle. Their findings will aid computer modelers in improving the accuracy of climate simulations.

  8. Animating climate model data

    NASA Astrophysics Data System (ADS)

    DaPonte, John S.; Sadowski, Thomas; Thomas, Paul

    2006-05-01

    This paper describes a collaborative project conducted by the Computer Science Department at Southern Connecticut State University and NASA's Goddard Institute for Space Science (GISS). Animations of output from a climate simulation math model used at GISS to predict rainfall and circulation have been produced for West Africa from June to September 2002. These early results have assisted scientists at GISS in evaluating the accuracy of the RM3 climate model when compared to similar results obtained from satellite imagery. The results presented below will be refined to better meet the needs of GISS scientists and will be expanded to cover other geographic regions for a variety of time frames.

  9. Assess Climate Change's Impact on Coastal Rivers using a Coupled Climate-Hydrology Model

    NASA Astrophysics Data System (ADS)

    Xue, Z. G.; Gochis, D.; Yu, W.; Zang, Z.; Sampson, K. M.; Keim, B. D.

    2016-12-01

    In this study we present a coupled climate-hydrological model reproducing the water cycle of three coastal river basins along the northern Gulf of Mexico for the past three decades (1985-2014). Model simulated climate condition, surface physics, and streamflow were well validated against in situ data and satellite-derived products, giving us the confidence that the newly developed WRF-Hydro model can be a robust tool for evaluating climate change's impact on hydrological regime. Trend analysis of model simulated monthly and annual time series indicates that local climate is getting hotter and dryer, specifically during the growing season. Wavelet analysis reveals that local evapotranspiration is strongly correlated with temperature, while soil moisture, water surplus, and streamflow are coupled with precipitation. In addition, local climate is closely correlated with large-scale climate dynamics such as AMO and ENSO. A possible change-point is detected around year 2004, after which, the monthly precipitation decreased by 14.2%, evapotranspiration increased by 2.9%, and water surplus decreased by 36.5%. The implication of the difference between the water surplus (runoff) calculated using the classic Thornthwaite method and river discharge estimated using streamflow records to the coastal environment is also discussed.

  10. Evaluating models of climate and forest vegetation

    NASA Technical Reports Server (NTRS)

    Clark, James S.

    1992-01-01

    Understanding how the biosphere may respond to increasing trace gas concentrations in the atmosphere requires models that contain vegetation responses to regional climate. Most of the processes ecologists study in forests, including trophic interactions, nutrient cycling, and disturbance regimes, and vital components of the world economy, such as forest products and agriculture, will be influenced in potentially unexpected ways by changing climate. These vegetation changes affect climate in the following ways: changing C, N, and S pools; trace gases; albedo; and water balance. The complexity of the indirect interactions among variables that depend on climate, together with the range of different space/time scales that best describe these processes, make the problems of modeling and prediction enormously difficult. These problems of predicting vegetation response to climate warming and potential ways of testing model predictions are the subjects of this chapter.

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

    NASA Astrophysics Data System (ADS)

    Wozniak, Matthew C.; Steiner, Allison L.

    2017-11-01

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

  12. Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

    NASA Astrophysics Data System (ADS)

    Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

    2017-12-01

    Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.

  13. Study of the global and regional climatic impacts of ENSO magnitude using SPEEDY AGCM

    NASA Astrophysics Data System (ADS)

    Dogar, Muhammad Mubashar; Kucharski, Fred; Azharuddin, Syed

    2017-03-01

    ENSO is considered as a strong atmospheric teleconnection that has pronounced global and regional circulation effects. It modifies global monsoon system, especially, Asian and African monsoons. Previous studies suggest that both the frequency and magnitude of ENSO events have increased over the last few decades resulting in a need to study climatic impacts of ENSO magnitude both at global and regional scales. Hence, to better understand the impact of ENSO amplitude over the tropical and extratropical regions focussing on the Asian and African domains, ENSO sensitivity experiments are conducted using ICTPAGCM (`SPEEDY'). It is anticipated that the tropical Pacific SST forcing will be enough to produce ENSO-induced teleconnection patterns; therefore, the model is forced using NINO3.4 regressed SST anomalies over the tropical Pacific only. SPEEDY reproduces the impact of ENSO over the Pacific, North and South America and African regions very well. However, it underestimates ENSO teleconnection patterns and associated changes over South Asia, particularly in the Indian region, which suggests that the tropical Pacific SST forcing is not sufficient to represent ENSO-induced teleconnection patterns over South Asia. Therefore, SST forcing over the tropical Indian Ocean together with air-sea coupling is also required for better representation of ENSO-induced changes in these regions. Moreover, results obtained by this pacemaker experiment show that ENSO impacts are relatively stronger over the Inter-Tropical Convergence Zone (ITCZ) compared to extratropics and high latitude regions. The positive phase of ENSO causes weakening in rainfall activity over African tropical rain belt, parts of South and Southeast Asia, whereas, the La Niña phase produces more rain over these regions during the summer season. Model results further reveal that ENSO magnitude has a stronger impact over African Sahel and South Asia, especially over the Indian region because of its significant impact

  14. Weighting climate model projections using observational constraints.

    PubMed

    Gillett, Nathan P

    2015-11-13

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

  15. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  16. A dynamic, climate-driven model of Rift Valley fever.

    PubMed

    Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

    2016-03-31

    Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  17. Development of ALARO-Climate regional climate model for a very high resolution

    NASA Astrophysics Data System (ADS)

    Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

    2014-05-01

    ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1

  18. Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.

    PubMed

    Tao, Fulu; Rötter, Reimund P; Palosuo, Taru; Gregorio Hernández Díaz-Ambrona, Carlos; Mínguez, M Inés; Semenov, Mikhail A; Kersebaum, Kurt Christian; Nendel, Claas; Specka, Xenia; Hoffmann, Holger; Ewert, Frank; Dambreville, Anaelle; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G; Salo, Tapio; Ferrise, Roberto; Bindi, Marco; Cammarano, Davide; Schulman, Alan H

    2018-03-01

    Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive

  19. The Future of Planetary Climate Modeling and Weather Prediction

    NASA Technical Reports Server (NTRS)

    Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

    2017-01-01

    Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

  20. The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

    PubMed

    Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

    2004-06-01

    The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

  1. Changes in the Martian Circulation and Climate in Response to Orbital Parameter Variations

    NASA Astrophysics Data System (ADS)

    Richardson, M. I.; Wilson, R. J.

    2000-10-01

    Martian orbital parameters are known to vary on time scales greater than 105 years. Such variations, especially in obliquity, have important consequences for the spatial distribution of solar heating of the surface and atmosphere, and hence are expected to affect some form of quasi-periodic climate change. The impact of changing obliquity on surface temperatures, and hence on volatile stability have been widely addressed. However, the changing insolation patterns should also modify the circulation of the atmosphere. As the nature and rate of volatile transport, and the vigour of dust lifting and transport from the surface are critical aspects of the climate, the circulation response to orbital variations needs to be assessed. In this presentation, we show results from the Geophysical Fluid Dynamics Laboratory (GFDL) Mars General Circulation Model (GCM) in which the orbit of Mars has been varied: obliquities between 0 and 60, perihelion passage between Ls=70 and 250, and eccentricities between 0 and 0.12. In general, the total atmosphere and cap CO2 budget is held constant (i.e. we assume no exchange with the regolith), and that the rate of dust supply into the lowest model level remains constant. The impact of these assumptions are examined. Many of the anticipated changes in circulation are found to occur as obliquity is increased from 0: The Hadley cell strength and that of the winter polar jet are found to increase; The magnitude of the seasonal CO2 cycle increases, resulting in extensive seasonal ice caps; Surface winds strengthen resulting in greater surface stresses and likely stronger dust lifting; The cycle of water becomes more vigourous, with large column vapour amounts in the polar regions corresponding to higher cap surface temperatures. However, some results contrast with expectations: Although the surface wind strengths change with orbital parameters, the mean directions tend not to, with implications for aeolian geological features; Even at low

  2. Understanding National Models for Climate Assessments

    NASA Astrophysics Data System (ADS)

    Dave, A.; Weingartner, K.

    2017-12-01

    National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.

  3. Climate change projections for Greek viticulture as simulated by a regional climate model

    NASA Astrophysics Data System (ADS)

    Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

    2017-07-01

    Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.

  4. Interactive, process-oriented climate modeling with CLIMLAB

    NASA Astrophysics Data System (ADS)

    Rose, B. E. J.

    2016-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

  5. Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

    NASA Astrophysics Data System (ADS)

    Dabanlı, İsmail; Şen, Zekai

    2018-04-01

    The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

  6. Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

    NASA Technical Reports Server (NTRS)

    Skiles, J. W.

    1995-01-01

    Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

  7. Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

    NASA Astrophysics Data System (ADS)

    Nicholls, S.; Mohr, K. I.

    2014-12-01

    The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

  8. Modeling U.S. water resources under climate change

    NASA Astrophysics Data System (ADS)

    Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

    2014-04-01

    Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

  9. Evaluation of the new EMAC-SWIFT chemistry climate model

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  10. New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

    NASA Astrophysics Data System (ADS)

    Deser, C.

    2017-12-01

    Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

  11. Evolution of extreme temperature events in short term climate projection for Iberian Peninsula.

    NASA Astrophysics Data System (ADS)

    Rodriguez, Alfredo; Tarquis, Ana M.; Sanchez, Enrique; Dosio, Alessandro; Ruiz-Ramos, Margarita

    2014-05-01

    Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 ×50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance. The objective of the work is to evaluate the utility of these short term projections for potential users, as for instance insurance companies. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116,D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research,Volume 117, D17, doi: 0.1029/2012JD017968 Herrera et. al. (2012) Development and Analysis of a 50 year high

  12. The use of Meteonorm weather generator for climate change studies

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

    . Meteonorm can therefore be used as a relatively simple method to enhance the spatial and temporal resolution instead of using complicated and time consuming downscaling methods based on regional climate models. The combination of Meteonorm, gridded historical (based on work of Luterbach et al.) and IPCC results has been used for studies of vegetation simulation between 1660 and 2600 (publication of first version based on IS92a scenario and limited time period 1950 - 2100: http://www.pbl.nl/images/H5_Part2_van%20CCE_opmaak%28def%29_tcm61-46625.pdf). It's also applicable for other adaptation studies for e.g. road surfaces or building simulation. In Meteonorm 6.1 one scenario (IS92a) and one climate model has been included (Hadley CM3). In the new Meteonorm 7 (coming spring 2011) the model averages of the three above mentioned scenarios of the IPCC AR4 will be included.

  13. Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario

    PubMed Central

    Gross, Markus; Magar, Vanesa

    2016-01-01

    In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will

  14. Offshore Wind Energy Climate Projection Using UPSCALE Climate Data under the RCP8.5 Emission Scenario.

    PubMed

    Gross, Markus; Magar, Vanesa

    2016-01-01

    In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide

  15. Normal forms for reduced stochastic climate models

    PubMed Central

    Majda, Andrew J.; Franzke, Christian; Crommelin, Daan

    2009-01-01

    The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOFs) (also known as Principal Component Analysis, Karhunen–Loéve and Proper Orthogonal Decomposition) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It is shown below that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large scales by the small scales and simultaneously strong cubic damping. These normal forms should prove useful for developing systematic strategies for the estimation of stochastic models from climate data. As an illustrative example the one-dimensional normal form is applied below to low-frequency patterns such as the North Atlantic Oscillation (NAO) in a climate model. The results here also illustrate the short comings of a recent linear scalar CAM noise model proposed elsewhere for low-frequency variability. PMID:19228943

  16. 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

  17. 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.; hide

    2016-01-01

    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 present-day climate and expected future climate change, 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 present-day climate. Quadrupling CO2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO2-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 CO2; 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. This survey illustrates TRACMIP's potential to engender a deeper understanding of global and regional climate and to address questions on past and future climate change.

  18. An evaluation of the variable-resolution CESM for modeling California's climate: Evaluation of VR-CESM for Modeling California's Climate

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

    Huang, Xingying; Rhoades, Alan M.; Ullrich, Paul A.

    In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (~ 28 km) and 0.125° (~ 14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)—the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. VR-CESM tended to produce a warmer summer (by about 1–3°C) and overestimated overall winter precipitation (about 25%–35%) compared tomore » reference data sets when sea surface temperatures were prescribed. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ~1–3°C colder than the reference data sets, underestimated precipitation by ~20%–30% at 27 km resolution, and overestimated precipitation by ~ 65–85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. Moreover, this assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.« less

  19. An evaluation of the variable-resolution CESM for modeling California's climate: Evaluation of VR-CESM for Modeling California's Climate

    DOE PAGES

    Huang, Xingying; Rhoades, Alan M.; Ullrich, Paul A.; ...

    2016-03-01

    In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (~ 28 km) and 0.125° (~ 14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)—the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. VR-CESM tended to produce a warmer summer (by about 1–3°C) and overestimated overall winter precipitation (about 25%–35%) compared tomore » reference data sets when sea surface temperatures were prescribed. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ~1–3°C colder than the reference data sets, underestimated precipitation by ~20%–30% at 27 km resolution, and overestimated precipitation by ~ 65–85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. Moreover, this assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.« less

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

    PubMed

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

    2013-10-28

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

  1. PNNL: Climate Modelling

    Science.gov Websites

    Runs [ Open Access : Password Protected ] CESM Development CESM Runs [ Open Access : Password Protected ] WRF Development WRF Runs [ Open Access : Password Protected ] Climate Modeling Home Projects Links Literature Manuscripts Publications Polar Group Meeting (2012) ASGC Home ASGC Jobs Web Calendar Wiki Internal

  2. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    NASA Technical Reports Server (NTRS)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  3. Reconstructing Climate Change: The Model-Data Ping-Pong

    NASA Astrophysics Data System (ADS)

    Stocker, T. F.

    2017-12-01

    When Cesare Emiliani, the father of paleoceanography, made the first attempts at a quantitative reconstruction of Pleistocene climate change in the early 1950s, climate models were not yet conceived. The understanding of paleoceanographic records was therefore limited, and scientists had to resort to plausibility arguments to interpret their data. With the advent of coupled climate models in the early 1970s, for the first time hypotheses about climate processes and climate change could be tested in a dynamically consistent framework. However, only a model hierarchy can cope with the long time scales and the multi-component physical-biogeochemical Earth System. There are many examples how climate models have inspired the interpretation of paleoclimate data on the one hand, and conversely, how data have questioned long-held concepts and models. In this lecture I critically revisit a few examples of this model-data ping-pong, such as the bipolar seesaw, the mid-Holocene greenhouse gas increase, millennial and rapid CO2 changes reconstructed from polar ice cores, and the interpretation of novel paleoceanographic tracers. These examples also highlight many of the still unsolved questions and provide guidance for future research. The combination of high-resolution paleoceanographic data and modeling has never been more relevant than today. It will be the key for an appropriate risk assessment of impacts on the Earth System that are already underway in the Anthropocene.

  4. A climate robust integrated modelling framework for regional impact assessment of climate change

    NASA Astrophysics Data System (ADS)

    Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

    2013-04-01

    Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change

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

    DOE PAGES

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

    2017-08-11

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

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

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

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

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

  7. The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

    NASA Astrophysics Data System (ADS)

    Dessens, Olivier

    2016-04-01

    Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of

  8. Application of CarboSOIL model to predict the effects of climate change on soil organic carbon stocks in agro-silvo-pastoral Mediterranean management systems

    NASA Astrophysics Data System (ADS)

    Muñoz-Rojas, Miriam; Doro, Luca; Ledda, Luigi; Francaviglia, Rosa

    2014-05-01

    ñoz-Rojas et al., 2012) or olive groves (Lozano-García and Parras-Alcántara, 2013). The local climate is warm temperate with dry and hot summers, with a mean annual rainfall of 623 mm (range 367-811 mm) and mean annual temperature of 15.0?C (13.8-16.4?C). Climate change scenarios were generated from the baseline climate with two Global Climate Models: GISS (Goddard Institute of Space Studies, USA), and HadCM3 (Met Office, Hadley Centre, UK), for two of the Intergovernmental Panel on Climate Change (IPCC) emission scenarios (A2 and B2). Three time horizons were chosen for climate change projections: 2020, mean climate change for the period 2010-2039; 2050 for the period 2040-2069; and 2080 for the period 2070-2099, providing respectively a very close, an intermediate, and a fully realized climate change scenario. The agreement of model predictions with the measured values of soil organic carbon stocks was tested using the correlation coefficient R2, the root mean square error RMSE and the modelling efficiency EF. For a good model performance, RMSE should have approximately the same order of magnitude of the standard deviation, while EF should be positive and close to 1. With reference to the three soil depths (0-25, 25-50, 50-75 cm), R2, RMSE and EF are in the range 0.76-0.99, 5.07-8.42, and 0.63-0.98 respectively. CarboSOIL predictions are fully acceptable since the linear regression coefficients are always significant at p

  9. 21 Layer troposphere-stratosphere climate model

    NASA Technical Reports Server (NTRS)

    Rind, D.; Suozzo, R.; Lacis, A.; Russell, G.; Hansen, J.

    1984-01-01

    The global climate model is extended through the stratosphere by increasing the vertical resolution and raising the rigid model top to the 0.01 mb (75 km) level. The inclusion of a realistic stratosphere is necessary for the investigation of the climate effects of stratospheric perturbations, such as changes of ozone, aerosols or solar ultraviolet irradiance, as well as for studying the effect on the stratosphere of tropospheric climate changes. The observed temperature and wind patterns throughout the troposphere and stratosphere are simulated. In addition to the excess planetary wave amplitude in the upper stratosphere, other model deficiences include the Northern Hemisphere lower stratospheric temperatures being 5 to 10 C too cold in winter at high latitudes and the temperature at 50 to 60 km altitude near the equator are too cold. Methods of correcting these deficiencies are discussed.

  10. Considerations for building climate-based species distribution models

    USGS Publications Warehouse

    Bucklin, David N.; Basille, Mathieu; Romañach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.

    2016-01-01

    Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.

  11. The local, remote, and global consequences of climate feedbacks

    NASA Astrophysics Data System (ADS)

    Feldl, Nicole

    Climate feedbacks offer a powerful framework for revealing the energetic pathways by which the system adjusts to an imposed forcing, such as an increase in atmospheric CO2. We investigate how local atmospheric feedbacks, such as those associated with Arctic sea ice and the Walker circulation, affect both global climate sensitivity and spatial patterns of warming. Emphasis is placed on a general circulation model with idealized boundary conditions, for the clarity it provides. For this aquaplanet simulation, we account for rapid tropospheric adjustments to CO2 and explicitly diagnose feedbacks (using radiative kernels) and forcing for this precise model set-up. In particular, a detailed closure of the energy budget within a clean experimental set-up allows us to consider nonlinear interactions between feedbacks. The inclusion of a tropical Walker circulation is found to prime the Hadley Circulation for a larger deceleration under CO2 doubling, by altering subtropical stratus decks and the meridional feedback gradient. We perform targeted experiments to isolate the atmospheric processes responsible for the variability in climate sensitivity, with implications for high-sensitivity paleoclimates. The local climate response is characterized in terms of the meridional structure of feedbacks, atmospheric heat transport, nonlinearities, and forcing. Our results display a combination of positive subtropical feedbacks and polar amplified warming. These two factors imply a critical role for transport and nonlinear effects, with the latter acting to substantially reduce global climate sensitivity. At the hemispheric scale, a rich picture emerges: anomalous divergence of heat flux away from positive feedbacks in the subtropics; clear-sky nonlinearities that reinforce the pattern of tropical cooling and high-latitude warming tendencies; and strong ice-line feedbacks that drive further amplification of polar warming. These results have implications for regional climate

  12. Climate model biases and statistical downscaling for application in hydrologic model

    USDA-ARS?s Scientific Manuscript database

    Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

  13. Agricultural climate impacts assessment for economic modeling and decision support

    NASA Astrophysics Data System (ADS)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  14. Regional Impacts of Climate Change on the Amazon Rainforest: 2080-2100

    NASA Astrophysics Data System (ADS)

    Cook, K. H.; Vizy, E. K.

    2006-12-01

    A regional climate model with resolution of 60 km is coupled with a potential vegetation model to simulate future climate over South America. The following steps are taken to effectively communicate the results across disciplines and to make them useful to the policy and impacts communities: the simulation is aimed at a particular time period (2081-2100), the climate change results are translated into changes in vegetation distribution, and the results are reported on regional space scales relative to political boundaries. In addition, the model validation in clearly presented to provide perspective on uncertainty for the prognosis. The model reproduces today's climate and vegetation over tropical and subtropical South America accurately. In simulations of the future, the model is forced by the IPCC's A2 scenario of future emissions, which assumes that CO2 emissions continue to grow at essentially today's rate throughout the 21st century, reaching 757 ppmv averaged over 2081-2100. The model is constrained on its lateral boundaries by atmospheric conditions simulated by a global climate model, applied as anomalies to present day conditions, and predicted changes in sea surface temperatures. The extent of the Amazon rainforest is reduced by about 70 per cent in the simulation, and the shrubland (caatinga) vegetation of Brazil's Nordeste region spreads westward and southward well into the continental interior. Bolivia, Paraguay, and Argentina lose all of their rainforest vegetation, and Brazil and Peru lose most of it. The surviving rain forest is concentrated near the equator. Columbia's rainforest survives largely intact and, along the northern coast, Venezuela and French Guiana suffer relatively small reductions. The loss in Guyana and Surinam is 30-50 per cent. Much of the rainforest in the central Amazon north of about 15S is replaced by savanna vegetation, but in southern Bolivia, northern Paraguay, and southern Brazil, grasslands take the place of the

  15. Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

    NASA Astrophysics Data System (ADS)

    Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

    2017-04-01

    Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

  16. [Lake eutrophication modeling in considering climatic factors change: a review].

    PubMed

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  17. Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

    PubMed Central

    Yuan, Naiming; Fu, Zuntao; Liu, Shida

    2014-01-01

    Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

  18. Reconstructing the climate states of the Late Pleistocene with the MIROC climate model

    NASA Astrophysics Data System (ADS)

    Chan, Wing-Le; Abe-Ouchi, Ayako; O'ishi, Ryouta; Takahashi, Kunio

    2014-05-01

    The Late Pleistocene was a period which lasted from the Eemian interglacial period to the start of the warm Holocene and was characterized mostly by widespread glacial ice. It was also a period which saw modern humans spread throughout the world and other species of the same genus, like the Neanderthals, become extinct. Various hypotheses have been put forward to explain the extinction of Neanderthals, about 30,000 years ago. Among these is one which involves changes in past climate and the inability of Neanderthals to adapt to such changes. The last traces of Neanderthals coincide with the end of Marine Isotope Stage 3 (MIS3) which was marked by large fluctuations in temperature and so-called Heinrich events, as suggested by geochemical records from ice cores. It is thought that melting sea ice or icebergs originating from the Laurentide ice sheet led to a large discharge of freshwater into the North Atlantic Ocean during the Heinrich events and severely weakened the Atlantic meridional overturning circulation, with important environmental ramifications across parts of Europe such as sharp decreases in temperature and reduction in forest cover. In order to assess the effects of past climate change on past hominin migration and on the extinction of certain species, it is first important to have a good understanding of the past climate itself. In this study, we have used three variants of MIROC (The Model for Interdisciplinary Research on Climate), a global climate model, for a time slice experiment within the Late Pleistocene: two mid-resolution models (an atmosphere model and a coupled atmosphere-ocean model) and a high-resolution atmosphere model. To obtain a fuller picture, we also look at a cool stadial state as obtained from a 'freshwater hosing' coupled-model experiment, designed to mimic the effects of freshwater discharge in the North Atlantic. We next use the sea surface temperature response from this experiment to drive the atmosphere models. We discuss

  19. Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

    NASA Astrophysics Data System (ADS)

    Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

    2012-12-01

    The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of transient daily river flow and monthly groundwater levels projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with

  20. Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

    NASA Astrophysics Data System (ADS)

    Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

    2013-03-01

    The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  2. Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India.

    PubMed

    A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

    2017-01-01

    India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.

  3. Evaluation of potential impacts on Great Lakes water resources based on climate scenarios of two GCMs

    USGS Publications Warehouse

    Lofgren, B.M.; Quinn, F.H.; Clites, A.H.; Assel, R.A.; Eberhardt, A.J.; Luukkonen, C.L.

    2002-01-01

    The results of general circulation model predictions of the effects of climate change from the Canadian Centre for Climate Modeling and Analysis (model CGCM1) and the United Kingdom Meteorological Office's Hadley Centre (model HadCM2) have been used to derive potential impacts on the water resources of the Great Lakes basin. These impacts can influence the levels of the Great Lakes and the volumes of channel flow among them, thus affecting their value for interests such as riparians, shippers, recreational boaters, and natural ecosystems. On one hand, a hydrological modeling suite using input data from the CGCM1 predicts large drops in lake levels, up to a maximum of 1.38 m on Lakes Michigan and Huron by 2090. This is due to a combination of a decrease in precipitation and an increase in air temperature that leads to an increase in evaporation. On the other hand, using input from HadCM2, rises in lake levels are predicted, up to a maximum of 0.35 m on Lakes Michigan and Huron by 2090, due to increased precipitation and a reduced increase in air temperature. An interest satisfaction model shows sharp decreases in the satisfaction of the interests of commercial navigation, recreational boating, riparians, and hydropower due to lake level decreases. Most interest satisfaction scores are also reduced by lake level increases. Drastic reductions in ice cover also result from the temperature increases such that under the CGCM1 predictions, most of Lake Erie has 96% of its winters ice-free by 2090. Assessment is also made of impacts on the groundwater-dependent region of Lansing, Michigan.

  4. Practice and philosophy of climate model tuning across six US modeling centers

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

    Schmidt, Gavin A.; Bader, David; Donner, Leo J.

    Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

  5. Practice and philosophy of climate model tuning across six US modeling centers

    NASA Astrophysics Data System (ADS)

    Schmidt, Gavin A.; Bader, David; Donner, Leo J.; Elsaesser, Gregory S.; Golaz, Jean-Christophe; Hannay, Cecile; Molod, Andrea; Neale, Richard B.; Saha, Suranjana

    2017-09-01

    Model calibration (or tuning) is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

  6. Practice and philosophy of climate model tuning across six US modeling centers

    DOE PAGES

    Schmidt, Gavin A.; Bader, David; Donner, Leo J.; ...

    2017-09-01

    Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

  7. A Model for Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

    Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.

  8. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

    NASA Technical Reports Server (NTRS)

    Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.; hide

    2013-01-01

    The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

  9. Improved Analysis of Earth System Models and Observations using Simple Climate Models

    NASA Astrophysics Data System (ADS)

    Nadiga, B. T.; Urban, N. M.

    2016-12-01

    Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using

  10. Climate and atmospheric modeling studies. Climate applications of Earth and planetary observations. Chemistry of Earth and environment

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The research conducted during the past year in the climate and atmospheric modeling programs concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols and the solar 'constant' on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree x 1 degree resolution has been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method was developed to simulate the hydraulic behavior of soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water (or colored water) throughout the planet. Each isotope or colored water source is a fraction of the climate model's water. It participates in condensation and surface evaporation at different fractionation rates and is transported by the dynamics. A major benefit of this project has been to improve the programming techniques and physical simulation of the water vapor budget of the climate model.

  11. An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models

    USGS Publications Warehouse

    David E. Rupp,

    2016-05-05

    The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.

  12. A Practical Philosophy of Complex Climate Modelling

    NASA Technical Reports Server (NTRS)

    Schmidt, Gavin A.; Sherwood, Steven

    2014-01-01

    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

  13. Conceptual Model of Climate Change Impacts at LANL

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

    Dewart, Jean Marie

    Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual modelmore » of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).« less

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  15. Pollen-proxies say cooler, climate models say warmer: resolving conflicting views of the Holocene climate of the Mediterranean region

    NASA Astrophysics Data System (ADS)

    Russo, E.; Mauri, A.; Davis, B. A. S.; Cubasch, U.

    2017-12-01

    The evolution of the Mediterranean region's climate during the Holocene has been the subject of long-standing debate within the paleoclimate community. Conflicting hypotheses have emerged from the analysis of different climate reconstructions based on proxy records and climate models outputs.In particular, pollen-based reconstructions of cooler summer temperatures during the Holocene have been criticized based on a hypothesis that the Mediterranean vegetation is mainly limited by effective precipitation and not summer temperature. This criticism is important because climate models show warmer summer temperatures during the Holocene over the Mediterranean region, in direct contradiction of the pollen-based evidence. Here we investigate this problem using a high resolution model simulation of the climate of the Mediterranean region during the mid-to-late Holocene, which we compare against pollen-based reconstructions using two different approaches.In the first, we compare the simulated climate from the model directly with the climate derived from the pollen data. In the second, we compare the simulated vegetation from the model directly with the vegetation from the pollen data.Results show that the climate model is unable to simulate neither the climate nor the vegetation shown by the pollen-data. The pollen data indicates an expansion in cool temperate vegetation in the mid-Holocene while the model suggests an expansion in warm arid vegetation. This suggests that the data-model discrepancy is more likely the result of bias in climate models, and not bias in the pollen-climate calibration transfer-function.

  16. A common fallacy in climate model evaluation

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  17. Do bioclimate variables improve performance of climate envelope models?

    USGS Publications Warehouse

    Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

    2012-01-01

    Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

  18. Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

    NASA Astrophysics Data System (ADS)

    Tselioudis, G.; Bauer, M.; Rossow, W.

    2009-04-01

    Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

  19. OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

    NASA Astrophysics Data System (ADS)

    Erickson, T. A.; Koziol, B. W.; Rood, R. B.

    2011-12-01

    The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

  20. The Urgent Need for Improved Climate Models and Predictions

    NASA Astrophysics Data System (ADS)

    Goddard, Lisa; Baethgen, Walter; Kirtman, Ben; Meehl, Gerald

    2009-09-01

    An investment over the next 10 years of the order of US$2 billion for developing improved climate models was recommended in a report (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf) from the May 2008 World Modelling Summit for Climate Prediction, held in Reading, United Kingdom, and presented by the World Climate Research Programme. The report indicated that “climate models will, as in the past, play an important, and perhaps central, role in guiding the trillion dollar decisions that the peoples, governments and industries of the world will be making to cope with the consequences of changing climate.” If trillions of dollars are going to be invested in making decisions related to climate impacts, an investment of $2 billion, which is less than 0.1% of that amount, to provide better climate information seems prudent. One example of investment in adaptation is the World Bank's Climate Investment Fund, which has drawn contributions of more than $6 billion for work on clean technologies and adaptation efforts in nine pilot countries and two pilot regions. This is just the beginning of expenditures on adaptation efforts by the World Bank and other mechanisms, focusing on only a small fraction of the nations of the world and primarily aimed at anticipated anthropogenic climate change. Moreover, decisions are being made now, all around the world—by individuals, companies, and governments—that affect people and their livelihoods today, not just 50 or more years in the future. Climate risk management, whether related to projects of the scope of the World Bank's or to the planning and decisions of municipalities, will be best guided by meaningful climate information derived from observations of the past and model predictions of the future.

  1. Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

    2016-11-01

    Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

  2. The epistemology of climate models and some of its implications for climate science and the philosophy of science

    NASA Astrophysics Data System (ADS)

    Katzav, Joel

    2014-05-01

    I bring out the limitations of four important views of what the target of useful climate model assessment is. Three of these views are drawn from philosophy. They include the views of Elisabeth Lloyd and Wendy Parker, and an application of Bayesian confirmation theory. The fourth view I criticise is based on the actual practice of climate model assessment. In bringing out the limitations of these four views, I argue that an approach to climate model assessment that neither demands too much of such assessment nor threatens to be unreliable will, in typical cases, have to aim at something other than the confirmation of claims about how the climate system actually is. This means, I suggest, that the Intergovernmental Panel on Climate Change's (IPCC's) focus on establishing confidence in climate model explanations and predictions is misguided. So too, it means that standard epistemologies of science with pretensions to generality, e.g., Bayesian epistemologies, fail to illuminate the assessment of climate models. I go on to outline a view that neither demands too much nor threatens to be unreliable, a view according to which useful climate model assessment typically aims to show that certain climatic scenarios are real possibilities and, when the scenarios are determined to be real possibilities, partially to determine how remote they are.

  3. Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

    NASA Astrophysics Data System (ADS)

    Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

    2018-04-01

    This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

  4. A review on regional convection permitting climate modeling

    NASA Astrophysics Data System (ADS)

    van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

    2016-04-01

    With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light

  5. CONSTABLE: A Global Climate Model for Classroom Use.

    ERIC Educational Resources Information Center

    Cerveny, Randall S.; And Others

    1985-01-01

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

  6. Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

    NASA Astrophysics Data System (ADS)

    Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

    2018-04-01

    In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

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

    Vallis, Geoffrey K.

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

  8. Stress testing hydrologic models using bottom-up climate change assessment

    NASA Astrophysics Data System (ADS)

    Stephens, C.; Johnson, F.; Marshall, L. A.

    2017-12-01

    Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

  9. Improving poverty and inequality modelling in climate research

    NASA Astrophysics Data System (ADS)

    Rao, Narasimha D.; van Ruijven, Bas J.; Riahi, Keywan; Bosetti, Valentina

    2017-12-01

    As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments.

  10. Quercus pollen season dynamics in the Iberian peninsula: response to meteorological parameters and possible consequences of climate change.

    PubMed

    Garcia-Mozo, Herminia; Galan, Carmen; Jato, Victoria; Belmonte, Jordina; de la Guardia, Consuelo; Fernandez, Delia; Gutierrez, Montserrat; Aira, M; Roure, Joan; Ruiz, Luis; Trigo, Mar; Dominguez-Vilches, Eugenio

    2006-01-01

    The main characteristics of the Quercus pollination season were studied in 14 different localities of the Iberian Peninsula from 1992-2004. Results show that Quercus flowering season has tended to start earlier in recent years, probably due to the increased temperatures in the pre-flowering period, detected at study sites over the second half of the 20th century. A Growing Degree Days forecasting model was used, together with future meteorological data forecast using the Regional Climate Model developed by the Hadley Meteorological Centre, in order to determine the expected advance in the start of Quercus pollination in future years. At each study site, airborne pollen curves presented a similar pattern in all study years, with different peaks over the season attributable in many cases to the presence of several species. High pollen concentrations were recorded, particularly at Mediterranean sites. This study also proposes forecasting models to predict both daily pollen values and annual pollen emission. All models were externally validated using data for 2001 and 2004, with acceptable results. Finally, the impact of the highly-likely climate change on Iberian Quercus pollen concentration values was studied by applying RCM meteorological data for different future years, 2025, 2050, 2075 and 2099. Results indicate that under a doubled CO(2) scenario at the end of the 21st century Quercus pollination season could start on average one month earlier and airborne pollen concentrations will increase by 50 % with respect to current levels, with higher values in Mediterranean inland areas.

  11. The Software Architecture of Global Climate Models

    NASA Astrophysics Data System (ADS)

    Alexander, K. A.; Easterbrook, S. M.

    2011-12-01

    It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  13. Oscillations in a simple climate-vegetation model

    NASA Astrophysics Data System (ADS)

    Rombouts, J.; Ghil, M.

    2015-05-01

    We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.

  14. Oscillations in a simple climate-vegetation model

    NASA Astrophysics Data System (ADS)

    Rombouts, J.; Ghil, M.

    2015-02-01

    We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various time scales is discussed.

  15. Agent-based Model for the Coupled Human-Climate System

    NASA Astrophysics Data System (ADS)

    Zvoleff, A.; Werner, B.

    2006-12-01

    Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

  16. Modelling rainfall erosion resulting from climate change

    NASA Astrophysics Data System (ADS)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  17. Reduced connection between the East Asian Summer Monsoon and Southern Hemisphere Circulation on interannual timescales under intense global warming

    NASA Astrophysics Data System (ADS)

    Yu, Tianlei; Guo, Pinwen; Cheng, Jun; Hu, Aixue; Lin, Pengfei; Yu, Yongqiang

    2018-03-01

    Previous studies show a close relationship between the East Asian Summer Monsoon (EASM) and Southern Hemisphere (SH) circulation on interannual timescales. In this study, we investigate whether this close relationship will change under intensive greenhouse-gas effect by analyzing simulations under two different climate background states: preindustrial era and Representative Concentration Pathway (RCP) 8.5 stabilization from the Community Climate System Model Version 4 (CCSM4). Results show a significantly reduced relationship under stabilized RCP8.5 climate state, such a less correlated EASM with the sea level pressure in the southern Indian Ocean and the SH branch of local Hadley Cell. Further analysis suggests that the collapse of the Atlantic Meridional Overturning Circulation (AMOC) due to this warming leads to a less vigorous northward meridional heat transport, a decreased intertropical temperature contrast in boreal summer, which produces a weaker cross-equatorial Hadley Cell in the monsoonal region and a reduced Interhemispheric Mass Exchange (IME). Since the monsoonal IME acts as a bridge connecting EASM and SH circulation, the reduced IME weakens this connection. By performing freshwater hosing experiment using the Flexible Global Ocean—Atmosphere—Land System model, Grid-point Version 2 (FGOALS-g2), we show a weakened relationship between the EASM and SH circulation as in CCSM4 when AMOC collapses. Our results suggest that a substantially weakened AMOC is the main driver leading to the EASM, which is less affected by SH circulation in the future warmer climate.

  18. The Effects of Climate Model Similarity on Local, Risk-Based Adaptation Planning

    NASA Astrophysics Data System (ADS)

    Steinschneider, S.; Brown, C. M.

    2014-12-01

    The climate science community has recently proposed techniques to develop probabilistic projections of climate change from ensemble climate model output. These methods provide a means to incorporate the formal concept of risk, i.e., the product of impact and probability, into long-term planning assessments for local systems under climate change. However, approaches for pdf development often assume that different climate models provide independent information for the estimation of probabilities, despite model similarities that stem from a common genealogy. Here we utilize an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to develop probabilistic climate information, with and without an accounting of inter-model correlations, and use it to estimate climate-related risks to a local water utility in Colorado, U.S. We show that the tail risk of extreme climate changes in both mean precipitation and temperature is underestimated if model correlations are ignored. When coupled with impact models of the hydrology and infrastructure of the water utility, the underestimation of extreme climate changes substantially alters the quantification of risk for water supply shortages by mid-century. We argue that progress in climate change adaptation for local systems requires the recognition that there is less information in multi-model climate ensembles than previously thought. Importantly, adaptation decisions cannot be limited to the spread in one generation of climate models.

  19. Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions

    NASA Astrophysics Data System (ADS)

    Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V.

    2018-06-01

    Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach.

  20. Towards a regional climate model coupled to a comprehensive hydrological model

    NASA Astrophysics Data System (ADS)

    Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

    2010-12-01

    When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

  1. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

    PubMed Central

    Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

    2018-01-01

    Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to

  2. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

    PubMed

    Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

    2018-01-01

    Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according

  3. Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations

    NASA Astrophysics Data System (ADS)

    Joshi, Sneh; Kar, Sarat C.

    2018-02-01

    Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.

  4. Climate models with delay differential equations

    NASA Astrophysics Data System (ADS)

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  5. Climate models with delay differential equations.

    PubMed

    Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M

    2017-11-01

    A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

  6. Comparative Climates of the Trappist-1 Planetary System: Results from a Simple Climate-vegetation Model

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

    Alberti, Tommaso; Carbone, Vincenzo; Lepreti, Fabio

    The recent discovery of the planetary system hosted by the ultracool dwarf star TRAPPIST-1 could open new paths for investigations of the planetary climates of Earth-sized exoplanets, their atmospheres, and their possible habitability. In this paper, we use a simple climate-vegetation energy-balance model to study the climate of the seven TRAPPIST-1 planets and the climate dependence on various factors: the global albedo, the fraction of vegetation that could cover their surfaces, and the different greenhouse conditions. The model allows us to investigate whether liquid water could be maintained on the planetary surfaces (i.e., by defining a “surface water zone (SWZ)”)more » in different planetary conditions, with or without the presence of a greenhouse effect. It is shown that planet TRAPPIST-1d seems to be the most stable from an Earth-like perspective, since it resides in the SWZ for a wide range of reasonable values of the model parameters. Moreover, according to the model, outer planets (f, g, and h) cannot host liquid water on their surfaces, even with Earth-like conditions, entering a snowball state. Although very simple, the model allows us to extract the main features of the TRAPPIST-1 planetary climates.« less

  7. Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

    NASA Astrophysics Data System (ADS)

    Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

    2002-12-01

    The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

  8. On the generation of climate model ensembles

    NASA Astrophysics Data System (ADS)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

    2014-10-01

    Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

  9. Identifying misbehaving models using baseline climate variance

    NASA Astrophysics Data System (ADS)

    Schultz, Colin

    2011-06-01

    The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

  10. Climate change hotspots in the CMIP5 global climate model ensemble.

    PubMed

    Diffenbaugh, Noah S; Giorgi, Filippo

    2012-01-10

    We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21 st century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2°C of global warming (relative to the late-20 th -century baseline), but not at the higher levels of global warming that occur in the late-21 st -century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.

  11. Ecological Assimilation of Land and Climate Observations - the EALCO model

    NASA Astrophysics Data System (ADS)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  12. Climate change and health modeling: horses for courses.

    PubMed

    Ebi, Kristie L; Rocklöv, Joacim

    2014-01-01

    Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome ('horses for courses'). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

  13. Climate modeling with decision makers in mind

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

    Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

    The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

  14. Climate modeling with decision makers in mind

    DOE PAGES

    Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

    2016-04-27

    The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

  15. Berry composition and climate: responses and empirical models.

    PubMed

    Barnuud, Nyamdorj N; Zerihun, Ayalsew; Gibberd, Mark; Bates, Bryson

    2014-08-01

    Climate is a strong modulator of berry composition. Accordingly, the projected change in climate is expected to impact on the composition of berries and of the resultant wines. However, the direction and extent of climate change impact on fruit composition of winegrape cultivars are not fully known. This study utilised a climate gradient along a 700 km transect, covering all wine regions of Western Australia, to explore and empirically describe influences of climate on anthocyanins, pH and titratable acidity (TA) levels in two or three cultivars of Vitis vinifera (Cabernet Sauvignon, Chardonnay and Shiraz). The results showed that, at a common maturity of 22° Brix total soluble solids, berries from the warmer regions had low levels of anthocyanins and TA as well as high pH compared to berries from the cooler regions. Most of these regional variations in berry composition reflected the prevailing climatic conditions of the regions. Thus, depending on cultivar, 82-87 % of TA, 83 % of anthocyanins and about half of the pH variations across the gradient were explained by climate-variable-based empirical models. Some of the variables that were relevant in describing the variations in berry attributes included: diurnal ranges and ripening period temperature (TA), vapour pressure deficit in October and growing degree days (pH), and ripening period temperatures (anthocyanins). Further, the rates of change in these berry attributes in response to climate variables were cultivar dependent. Based on the observed patterns along the climate gradient, it is concluded that: (1) in a warming climate, all other things being equal, berry anthocyanins and TA levels will decline whereas pH levels will rise; and (2) despite variations in non-climatic factors (e.g. soil type and management) along the sampling transect, variations in TA and anthocyanins were satisfactorily described using climate-variable-based empirical models, indicating the overriding impact of climate on berry

  16. Berry composition and climate: responses and empirical models

    NASA Astrophysics Data System (ADS)

    Barnuud, Nyamdorj N.; Zerihun, Ayalsew; Gibberd, Mark; Bates, Bryson

    2014-08-01

    Climate is a strong modulator of berry composition. Accordingly, the projected change in climate is expected to impact on the composition of berries and of the resultant wines. However, the direction and extent of climate change impact on fruit composition of winegrape cultivars are not fully known. This study utilised a climate gradient along a 700 km transect, covering all wine regions of Western Australia, to explore and empirically describe influences of climate on anthocyanins, pH and titratable acidity (TA) levels in two or three cultivars of Vitis vinifera (Cabernet Sauvignon, Chardonnay and Shiraz). The results showed that, at a common maturity of 22° Brix total soluble solids, berries from the warmer regions had low levels of anthocyanins and TA as well as high pH compared to berries from the cooler regions. Most of these regional variations in berry composition reflected the prevailing climatic conditions of the regions. Thus, depending on cultivar, 82-87 % of TA, 83 % of anthocyanins and about half of the pH variations across the gradient were explained by climate-variable-based empirical models. Some of the variables that were relevant in describing the variations in berry attributes included: diurnal ranges and ripening period temperature (TA), vapour pressure deficit in October and growing degree days (pH), and ripening period temperatures (anthocyanins). Further, the rates of change in these berry attributes in response to climate variables were cultivar dependent. Based on the observed patterns along the climate gradient, it is concluded that: (1) in a warming climate, all other things being equal, berry anthocyanins and TA levels will decline whereas pH levels will rise; and (2) despite variations in non-climatic factors (e.g. soil type and management) along the sampling transect, variations in TA and anthocyanins were satisfactorily described using climate-variable-based empirical models, indicating the overriding impact of climate on berry

  17. Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

    NASA Astrophysics Data System (ADS)

    Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

    2001-12-01

    A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations

  18. Using historical and projected future climate model simulations as drivers of agricultural and biological models (Invited)

    NASA Astrophysics Data System (ADS)

    Stefanova, L. B.

    2013-12-01

    Climate model evaluation is frequently performed as a first step in analyzing climate change simulations. Atmospheric scientists are accustomed to evaluating climate models through the assessment of model climatology and biases, the models' representation of large-scale modes of variability (such as ENSO, PDO, AMO, etc) and the relationship between these modes and local variability (e.g. the connection between ENSO and the wintertime precipitation in the Southeast US). While these provide valuable information about the fidelity of historical and projected climate model simulations from an atmospheric scientist's point of view, the application of climate model data to fields such as agriculture, ecology and biology may require additional analyses focused on the particular application's requirements and sensitivities. Typically, historical climate simulations are used to determine a mapping between the model and observed climate, either through a simple (additive for temperature or multiplicative for precipitation) or a more sophisticated (such as quantile matching) bias correction on a monthly or seasonal time scale. Plants, animals and humans however are not directly affected by monthly or seasonal means. To assess the impact of projected climate change on living organisms and related industries (e.g. agriculture, forestry, conservation, utilities, etc.), derivative measures such as the heating degree-days (HDD), cooling degree-days (CDD), growing degree-days (GDD), accumulated chill hours (ACH), wet season onset (WSO) and duration (WSD), among others, are frequently useful. We will present a comparison of the projected changes in such derivative measures calculated by applying: (a) the traditional temperature/precipitation bias correction described above versus (b) a bias correction based on the mapping between the historical model and observed derivative measures themselves. In addition, we will present and discuss examples of various application-based climate

  19. 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

  20. Climate Forcing of Ripple Migration and Crest Alignment in the Last 400 kyr in Meridiani Planum, Mars

    NASA Astrophysics Data System (ADS)

    Fenton, Lori K.; Carson, Helen C.; Michaels, Timothy I.

    2018-04-01

    The plains ripples of Meridiani Planum are the first paleo-aeolian bedforms on Mars to have had their last migration episode constrained in time (to 50-200 ka). Here we test how variations in orbital configuration, air pressure, and atmospheric dust loading over the past 400 kyr affect bedform mobility and crest alignment. Using the National Aeronautics and Space Administration Ames Mars Global Climate Model, we ran a series of sensitivity tests under a number of different conditions, seeking changes in wind patterns relative to those modeled for present-day conditions. Results indicate that enhanced sand drift potential in Meridiani Planum correlates with (1) high axial obliquity, (2) a longitude of perihelion (Lp) near southern summer solstice, and (3) a greater air pressure. The last pulse of westward plains ripple migration likely occurred during the most recent obliquity (relative) maximum, from 111 to 86 ka. At Lp coinciding with southern summer solstice, the Mars Global Climate Model produced a westward resultant drift direction, consistent with the observed north-south plains ripple crest alignment. However, smaller superposed ripples, aligned NNE-SSW, are consistent with a strengthened northern summer Hadley return flow, occurring when Lp coincided with northern summer solstice. The superposed NNE-SSW ripples likely formed as the axial obliquity decreased during the last relative maximum and Lp swung toward northern summer, from 86 to 72 ka. The timeline of bedform activity supports the proposed sequence of CO2 sequestration in the south polar residual cap over the past 400 kyr.

  1. Assessing Climate Change Risks Using a Multi-Model Approach

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  2. Predicting climate change effects on surface soil organic carbon of Louisiana, USA.

    PubMed

    Zhong, Biao; Xu, Yi Jun

    2014-10-01

    This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5° × 0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001-2010, 2041-2050, and 2091-2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p < 0.01) adjusted means into letter comparisons. The study found that for most of the next 100 years in Louisiana, monthly mean temperature under all three emissions projections will increase; and monthly precipitation will, however, decrease. Under three emission scenarios, A1FI, A2, and B2, the mean SOC in the upper 30-cm depth of Louisiana forest soils will decrease from 33.0 t/ha in 2001 to 26.9, 28.4, and 29.2 t/ha in 2100, respectively; the mean SOC of Louisiana cropland soils will decrease from 44.4 t/ha in 2001 to 36.3, 38.4, and 39.6 t/ha in 2100, respectively; the mean SOC of Louisiana grassland soils will change from 30.7 t/ha in 2001 to 25.4, 26.6, and 27.0 t/ha in 2100, respectively. Annual SOC

  3. A scalable climate health justice assessment model

    PubMed Central

    McDonald, Yolanda J.; Grineski, Sara E.; Collins, Timothy W.; Kim, Young-An

    2014-01-01

    This paper introduces a scalable “climate health justice” model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008–2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to

  4. A scalable climate health justice assessment model.

    PubMed

    McDonald, Yolanda J; Grineski, Sara E; Collins, Timothy W; Kim, Young-An

    2015-05-01

    This paper introduces a scalable "climate health justice" model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008-2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to

  5. Cross-validation of an employee safety climate model in Malaysia.

    PubMed

    Bahari, Siti Fatimah; Clarke, Sharon

    2013-06-01

    Whilst substantial research has investigated the nature of safety climate, and its importance as a leading indicator of organisational safety, much of this research has been conducted with Western industrial samples. The current study focuses on the cross-validation of a safety climate model in the non-Western industrial context of Malaysian manufacturing. The first-order factorial validity of Cheyne et al.'s (1998) [Cheyne, A., Cox, S., Oliver, A., Tomas, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work and Stress, 12(3), 255-271] model was tested, using confirmatory factor analysis, in a Malaysian sample. Results showed that the model fit indices were below accepted levels, indicating that the original Cheyne et al. (1998) safety climate model was not supported. An alternative three-factor model was developed using exploratory factor analysis. Although these findings are not consistent with previously reported cross-validation studies, we argue that previous studies have focused on validation across Western samples, and that the current study demonstrates the need to take account of cultural factors in the development of safety climate models intended for use in non-Western contexts. The results have important implications for the transferability of existing safety climate models across cultures (for example, in global organisations) and highlight the need for future research to examine cross-cultural issues in relation to safety climate. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  6. Climate-methane cycle feedback in global climate model model simulations forced by RCP scenarios

    NASA Astrophysics Data System (ADS)

    Eliseev, Alexey V.; Denisov, Sergey N.; Arzhanov, Maxim M.; Mokhov, Igor I.

    2013-04-01

    Methane cycle module of the global climate model of intermediate complexity developed at the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) is extended by coupling with a detailed module for thermal and hydrological processes in soil (Deep Soil Simulator, (Arzhanov et al., 2008)). This is an important improvement with respect with the earlier IAP RAS CM version (Eliseev et al., 2008) which has employed prescribed soil hydrology to simulate CH4 emissions from soil. Geographical distribution of water inundated soil in the model was also improved by replacing the older Olson's ecosystem data base by the data based on the SCIAMACHY retrievals (Bergamaschi et al., 2007). New version of the IAP RAS CM module for methane emissions from soil is validated by using the simulation protocol adopted in the WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project). In addition, atmospheric part of the IAP RAS CM methane cycle is extended by temperature dependence of the methane life-time in the atmosphere in order to mimic the respective dependence of the atmospheric methane chemistry (Denisov et al., 2012). The IAP RAS CM simulations are performed for the 18th-21st centuries according with the CMIP5 protocol taking into account natural and anthropogenic forcings. The new IAP RAS CM version realistically reproduces pre-industrial and present-day characteristics of the global methane cycle including CH4 concentration qCH4 in the atmosphere and CH4 emissions from soil. The latter amounts 150 - 160 TgCH4-yr for the late 20th century and increases to 170 - 230 TgCH4-yr in the late 21st century. Atmospheric methane concentration equals 3900 ppbv under the most aggressive anthropogenic scenario RCP 8.5 and 1850 - 1980 ppbv under more moderate scenarios RCP 6.0 and RCP 4.5. Under the least aggressive scenario RCP 2.6 qCH4 reaches maximum 1730 ppbv in 2020s and declines afterwards. Climate change impact on the methane emissions from

  7. Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

    NASA Astrophysics Data System (ADS)

    Parsons, Luke Alexander

    Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

  8. Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

    NASA Astrophysics Data System (ADS)

    Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.

    2009-04-01

    The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional

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

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  10. Downscaling GISS ModelE Boreal Summer Climate over Africa

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Fulakeza, Matthew

    2015-01-01

    The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

  11. Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

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

    Lobell, D; Field, C; Cahill, K

    2006-01-10

    Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiplemore » climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.« less

  12. Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India

    PubMed Central

    A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

    2017-01-01

    India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future. PMID:28753605

  13. Simulation of the West African monsoon onset using the HadGEM3-RA regional climate model

    NASA Astrophysics Data System (ADS)

    Diallo, Ismaïla; Bain, Caroline L.; Gaye, Amadou T.; Moufouma-Okia, Wilfran; Niang, Coumba; Dieng, Mame D. B.; Graham, Richard

    2014-08-01

    The performance of the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) in simulating the West African monsoon (WAM) is investigated. We focus on performance for monsoon onset timing and for rainfall totals over the June-July-August (JJA) season and on the model's representation of the underlying dynamical processes. Experiments are driven by the ERA-Interim reanalysis and follow the CORDEX experimental protocol. Simulations with the HadGEM3 global model, which shares a common physical formulation with HadGEM3-RA, are used to gain insight into the causes of HadGEM3-RA simulation errors. It is found that HadGEM3-RA simulations of monsoon onset timing are realistic, with an error in mean onset date of two pentads. However, the model has a dry bias over the Sahel during JJA of 15-20 %. Analysis suggests that this is related to errors in the positioning of the Saharan heat low, which is too far south in HadGEM3-RA and associated with an insufficient northward reach of the south-westerly low-level monsoon flow and weaker moisture convergence over the Sahel. Despite these biases HadGEM3-RA's representation of the general rainfall distribution during the WAM appears superior to that of ERA-Interim when using Global Precipitation Climatology Project or Tropical Rain Measurement Mission data as reference. This suggests that the associated dynamical features seen in HadGEM3-RA can complement the physical picture available from ERA-Interim. This approach is supported by the fact that the global HadGEM3 model generates realistic simulations of the WAM without the benefit of pseudo-observational forcing at the lateral boundaries; suggesting that the physical formulation shared with HadGEM3-RA, is able to represent the driving processes. HadGEM3-RA simulations confirm previous findings that the main rainfall peak near 10°N during June-August is maintained by a region of mid-tropospheric ascent located, latitudinally, between the cores of

  14. The Status of Mars Climate Change Modeling

    NASA Technical Reports Server (NTRS)

    Haberle, Robert M.

    1997-01-01

    Researchers have reviewed the evidence that the climate of Mars has changed throughout its history. In this paper, the discussion focuses on where we stand in terms of modeling these climate changes. For convenience, three distinct types of climate regimes are considered: very early in the planet's history (more than 3.5 Ga), when warm wet conditions are thought to have prevailed; the bulk of the planet's history (3.5-1 Ga), during which episodic ocean formation has been suggested; and relatively recently in the planet's history (less than 1 Ga), when orbitally induced climate change is thought to have occurred.

  15. Regional-Scale Climate Change: Observations and Model Simulations

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

    Bradley, Raymond S; Diaz, Henry F

    2010-12-14

    This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, andmore » we conducted studies of changes in phonological indicators based on various climatic thresholds.« less

  16. Tuning a climate model using nudging to reanalysis.

    NASA Astrophysics Data System (ADS)

    Cheedela, S. K.; Mapes, B. E.

    2014-12-01

    Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

  17. Assessment of the Impact of Climate Change on the Water Balances and Flooding Conditions of Peninsular Malaysia watersheds by a Coupled Numerical Climate Model - Watershed Hydrology Model

    NASA Astrophysics Data System (ADS)

    Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.

    2017-12-01

    Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.

  18. Continental-scale river flow in climate models

    NASA Technical Reports Server (NTRS)

    Miller, James R.; Russell, Gary L.; Caliri, Guilherme

    1994-01-01

    The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4 deg x 5 deg and 2 deg x 2.5 deg resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model (Hansen et al.). The land source runoff from the 4 deg x 5 deg resolution model is quartered onto a 2 deg x 2.5 deg grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a global error function for river flow is used to evaluate the routing model and its sensitivity to physical parameters. Three basinwide parameters are introduced: the river length weighted by source runoff, the turnover rate, and the basinwide speed. Although the values of these parameters depend on the resolution at which the rivers are defined, the values should converge as the grid resolution becomes finer. When the routing scheme described here is coupled with a climate model's source runoff, it provides the basis for closing the hydrologic cycle in coupled atmosphere-ocean models by realistically allowing water to return to the ocean at the correct location and with the proper magnitude and timing.

  19. 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.

  20. Climate: Policy, Modeling, and Federal Priorities (Invited)

    NASA Astrophysics Data System (ADS)

    Koonin, S.; Department Of Energy Office Of The Under SecretaryScience

    2010-12-01

    The Administration has set ambitious national goals to reduce our dependence on fossil fuels and reduce anthropogenic greenhouse gas (GHG) emissions. The US and other countries involved in the U.N. Framework Convention on Climate Change continue to work toward a goal of establishing a viable treaty that would encompass limits on emissions and codify actions that nations would take to reduce emissions. These negotiations are informed by the science of climate change and by our understanding of how changes in technology and the economy might affect the overall climate in the future. I will describe the present efforts within the U.S. Department of Energy, and the federal government more generally, to address issues related to climate change. These include state-of-the-art climate modeling and uncertainty assessment, economic and climate scenario planning based on best estimates of different technology trajectories, adaption strategies for climate change, and monitoring and reporting for treaty verification.

  1. Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

    PubMed

    Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

    2012-09-01

    Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor

  2. Ensemble catchment hydrological modelling for climate change impact analysis

    NASA Astrophysics Data System (ADS)

    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions

  3. Ensemble of regional climate model projections for Ireland

    NASA Astrophysics Data System (ADS)

    Nolan, Paul; McGrath, Ray

    2016-04-01

    The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season

  4. Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

    NASA Astrophysics Data System (ADS)

    Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

    2018-06-01

    The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

  5. Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

    EPA Science Inventory

    The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

  6. Multi-model approach to assess the impact of climate change on runoff

    NASA Astrophysics Data System (ADS)

    Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

    2015-10-01

    The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a

  7. Eco-hydrological Modeling in the Framework of Climate Change

    NASA Astrophysics Data System (ADS)

    Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

    2010-05-01

    A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately

  8. 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.

  9. A Global Climate Model for Instruction.

    ERIC Educational Resources Information Center

    Burt, James E.

    This paper describes a simple global climate model useful in a freshman or sophomore level course in climatology. There are three parts to the paper. The first part describes the model, which is a global model of surface air temperature averaged over latitude and longitude. Samples of the types of calculations performed in the model are provided.…

  10. Regional climate models reduce biases of global models and project smaller European summer warming

    NASA Astrophysics Data System (ADS)

    Soerland, S.; Schar, C.; Lüthi, D.; Kjellstrom, E.

    2017-12-01

    The assessment of regional climate change and the associated planning of adaptation and response strategies are often based on complex model chains. Typically, these model chains employ global and regional climate models (GCMs and RCMs), as well as one or several impact models. It is a common belief that the errors in such model chains behave approximately additive, thus the uncertainty should increase with each modeling step. If this hypothesis were true, the application of RCMs would not lead to any intrinsic improvement (beyond higher-resolution detail) of the GCM results. Here, we investigate the bias patterns (offset during the historical period against observations) and climate change signals of two RCMs that have downscaled a comprehensive set of GCMs following the EURO-CORDEX framework. The two RCMs reduce the biases of the driving GCMs, reduce the spread and modify the amplitude of the GCM projected climate change signal. The GCM projected summer warming at the end of the century is substantially reduced by both RCMs. These results are important, as the projected summer warming and its likely impact on the water cycle are among the most serious concerns regarding European climate change.

  11. 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

  12. Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.

    2002-01-01

    This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

  13. Projecting the Influence of Climate Change on Extreme Ground-level Ozone Events in Selected Ontario Cities =

    NASA Astrophysics Data System (ADS)

    Leung, Kinson He Yin

    ppb (the current Ontario 1-hour Ambient Air Quality criterion for extreme ozone concentration) will have an increase of over 60%, 50% and 62% respectively by the year of 2100 under the different future scenarios in the third version of the Coupled Global Climate Model (CGCM3) and the Hadley Centre's Climate Model (HadCM3).

  14. Prediction of future climate change for the Blue Nile, using a nested Regional Climate Model

    NASA Astrophysics Data System (ADS)

    Soliman, E.; Jeuland, M.

    2009-04-01

    Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future

  15. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  16. Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

    NASA Technical Reports Server (NTRS)

    Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

    2016-01-01

    We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

  17. Lake Representations in Global Climate Models: An End-User Perspective

    NASA Astrophysics Data System (ADS)

    Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

    2017-12-01

    The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

  18. Investigating the Climatic Impacts of Globally Shifted Anthropogenic Emissions

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Jiang, J. H.; Su, H.

    2014-12-01

    With a quasi-exponential growth in industrialization since the mid-1990s, Asia has undergone a dramatic increase in anthropogenic emissions of aerosol and precursor gases to the atmosphere. Meanwhile, such emissions have been stabilized or reduced over North America and Europe. This geographical shift of global emission sources could potentially perturb the regional and global climate due to impact of aerosols on cloud properties, precipitation, and large-scale circulation. We use an atmospheric general circulation model (AGCM) with different aerosol scenarios to investigate the radiative and microphysical effects of anthropogenic aerosols on the large-scale circulation and regional climate over the globe. We conduct experiments to simulate the continental shift of aerosol distribution by contrasting two simulations using 1970 and 2010 anthropogenic emission sources. We found the elevation of aerosol concentrations in East and South Asia results in regional surface temperature cooling of -0.10° to -0.17°C, respectively, due to the enhanced solar extinction by aerosols and cloud reflectivity. The reduction of the local aerosol loadings in Europe causes a significant warming of +0.4°C. However, despite recent decreasing in aerosol emission, North America shows a cooling of -0.13°C, likely caused by increasing of cloudiness under the influence of modulated general circulation. These aerosol induced temperature changes are consistent with the observed temperature trends from 1980 to 2013 in the reanalysis data. Our study also predicts weaker East/South Asia summer monsoons due to strong regional aerosol forcing. Moreover, the ascending motion in the northern tropics is found to be weakened by asymmetrical aerosol forcing, resulting in the cross-equatorial shift of Hadley Circulation.

  19. Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

    NASA Astrophysics Data System (ADS)

    Taner, M. U.; Wi, S.; Brown, C.

    2017-12-01

    The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

  20. Creating "Intelligent" Climate Model Ensemble Averages Using a Process-Based Framework

    NASA Astrophysics Data System (ADS)

    Baker, N. C.; Taylor, P. C.

    2014-12-01

    The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to

  1. Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

    NASA Technical Reports Server (NTRS)

    Waliser, Duane

    2011-01-01

    Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

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

    NASA Astrophysics Data System (ADS)

    Somerville, R. C.

    2010-12-01

    As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already

  3. Evaluation of regional climate simulations for air quality modelling purposes

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

    2013-05-01

    In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

  4. Regional model simulations of New Zealand climate

    NASA Astrophysics Data System (ADS)

    Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

    1998-03-01

    Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

  5. From Global Climate Model Projections to Local Impacts Assessments: Analyses in Support of Planning for Climate Change

    NASA Astrophysics Data System (ADS)

    Snover, A. K.; Littell, J. S.; Mantua, N. J.; Salathe, E. P.; Hamlet, A. F.; McGuire Elsner, M.; Tohver, I.; Lee, S.

    2010-12-01

    Assessing and planning for the impacts of climate change require regionally-specific information. Information is required not only about projected changes in climate but also the resultant changes in natural and human systems at the temporal and spatial scales of management and decision making. Therefore, climate impacts assessment typically results in a series of analyses, in which relatively coarse-resolution global climate model projections of changes in regional climate are downscaled to provide appropriate input to local impacts models. This talk will describe recent examples in which coarse-resolution (~150 to 300km) GCM output was “translated” into information requested by decision makers at relatively small (watershed) and large (multi-state) scales using regional climate modeling, statistical downscaling, hydrologic modeling, and sector-specific impacts modeling. Projected changes in local air temperature, precipitation, streamflow, and stream temperature were developed to support Seattle City Light’s assessment of climate change impacts on hydroelectric operations, future electricity load, and resident fish populations. A state-wide assessment of climate impacts on eight sectors (agriculture, coasts, energy, forests, human health, hydrology and water resources, salmon, and urban stormwater infrastructure) was developed for Washington State to aid adaptation planning. Hydro-climate change scenarios for approximately 300 streamflow locations in the Columbia River basin and selected coastal drainages west of the Cascades were developed in partnership with major water management agencies in the Pacific Northwest to allow planners to consider how hydrologic changes may affect management objectives. Treatment of uncertainty in these assessments included: using “bracketing” scenarios to describe a range of impacts, using ensemble averages to characterize the central estimate of future conditions (given an emissions scenario), and explicitly assessing

  6. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2017-11-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  7. The East Asian Jet Stream and Asian-Pacific-American Climate

    NASA Technical Reports Server (NTRS)

    Yang, Song; Lau, K.-M.; Kim, K.-M.

    2000-01-01

    The upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region during winter. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet stream is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation especially over East Asia. The variabilities of the EAJ on these time scales have been relatively well documented. It has also been understood since decades ago that the interannual. variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation. However, many questions remain for the year-to-year variabilities of the EAJ and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the EAJ and ENSO play different roles in modulating the APA climate? How is the jet stream linked to the non-ENSO-related sea surface temperature (SST) anomalies and to the Pacific/North American (PNA) teleconnection pattern?

  8. Climate Model Diagnostic Analyzer Web Service System

    NASA Astrophysics Data System (ADS)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2013-12-01

    The latest Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with newly available global observations. The traditional approach to climate model evaluation, which compares a single parameter at a time, identifies symptomatic model biases and errors but fails to diagnose the model problems. The model diagnosis process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. To address these challenges, we are developing a parallel, distributed web-service system that enables the physics-based multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation and (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, and (4) the calculation of difference between two variables. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use

  9. A potato model intercomparison across varying climates and productivity levels

    USDA-ARS?s Scientific Manuscript database

    A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) ...

  10. Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

    NASA Astrophysics Data System (ADS)

    Erfanian, A.; Fomenko, L.; Wang, G.

    2016-12-01

    Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

  11. A new framework for climate sensitivity and prediction: a modelling perspective

    NASA Astrophysics Data System (ADS)

    Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

    2016-03-01

    The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new

  12. 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

  13. 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.

  14. Process-oriented Observational Metrics for CMIP6 Climate Model Assessments

    NASA Astrophysics Data System (ADS)

    Jiang, J. H.; Su, H.

    2016-12-01

    Observational metrics based on satellite observations have been developed and effectively applied during post-CMIP5 model evaluation and improvement projects. As new physics and parameterizations continue to be included in models for the upcoming CMIP6, it is important to continue objective comparisons between observations and model results. This talk will summarize the process-oriented observational metrics and methodologies for constraining climate models with A-Train satellite observations and support CMIP6 model assessments. We target parameters and processes related to atmospheric clouds and water vapor, which are critically important for Earth's radiative budget, climate feedbacks, and water and energy cycles, and thus reduce uncertainties in climate models.

  15. What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?

    NASA Astrophysics Data System (ADS)

    Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.

    2009-12-01

    “…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility

  16. NAME Modeling and Climate Process Team

    NASA Astrophysics Data System (ADS)

    Schemm, J. E.; Williams, L. N.; Gutzler, D. S.

    2007-05-01

    NAME Climate Process and Modeling Team (CPT) has been established to address the need of linking climate process research to model development and testing activities for warm season climate prediction. The project builds on two existing NAME-related modeling efforts. One major component of this project is the organization and implementation of a second phase of NAMAP, based on the 2004 season. NAMAP2 will re-examine the metrics proposed by NAMAP, extend the NAMAP analysis to transient variability, exploit the extensive observational database provided by NAME 2004 to analyze simulation targets of special interest, and expand participation. Vertical column analysis will bring local NAME observations and model outputs together in a context where key physical processes in the models can be evaluated and improved. The second component builds on the current NAME-related modeling effort focused on the diurnal cycle of precipitation in several global models, including those implemented at NCEP, NASA and GFDL. Our activities will focus on the ability of the operational NCEP Global Forecast System (GFS) to simulate the diurnal and seasonal evolution of warm season precipitation during the NAME 2004 EOP, and on changes to the treatment of deep convection in the complicated terrain of the NAMS domain that are necessary to improve the simulations, and ultimately predictions of warm season precipitation These activities will be strongly tied to NAMAP2 to ensure technology transfer from research to operations. Results based on experiments conducted with the NCEP CFS GCM will be reported at the conference with emphasis on the impact of horizontal resolution in predicting warm season precipitation over North America.

  17. What is the importance of climate model bias when projecting the impacts of climate change on land surface processes?

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

    Liu, M. L.; Rajagopalan, K.; Chung, S. H.

    2014-05-16

    Regional climate change impact (CCI) studies have widely involved downscaling and bias-correcting (BC) Global Climate Model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables(evapotranspiration, ET; runoff; snow water equivalent, SWE; and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW)more » Region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ Andrews). Simulation results from the coupled ECHAM5/MPI-OM model with A1B emission scenario were firstly dynamically downscaled to 12 km resolutions with WRF model. Then a quantile mapping based statistical downscaling model was used to downscale them into 1/16th degree resolution daily climate data over historical and future periods. Two series climate data were generated according to the option of bias-correction (i.e. with bias-correction (BC) and without bias-correction, NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological datasets. These im20 pact models include a macro-scale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrologic model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However

  18. Modeling climate change impacts on overwintering bald eagles.

    PubMed

    Harvey, Chris J; Moriarty, Pamela E; Salathé, Eric P

    2012-03-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems.

  19. Modeling climate change impacts on overwintering bald eagles

    PubMed Central

    Harvey, Chris J; Moriarty, Pamela E; Salathé Jr, Eric P

    2012-01-01

    Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems. PMID:22822430

  20. On the limitations of General Circulation Climate Models

    NASA Technical Reports Server (NTRS)

    Stone, Peter H.; Risbey, James S.

    1990-01-01

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

  1. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

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

    Jablonowski, Christiane

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively withmore » advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research

  2. Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS

    NASA Technical Reports Server (NTRS)

    Pawson, Steven; Kodera, Kunihiko

    2003-01-01

    The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.

  3. Learning About Climate and Atmospheric Models Through Machine Learning

    NASA Astrophysics Data System (ADS)

    Lucas, D. D.

    2017-12-01

    From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  4. The impact of ARM on climate modeling

    DOE PAGES

    Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; ...

    2016-07-15

    Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less

  5. Statistical surrogate models for prediction of high-consequence climate change.

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

    Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

    2011-09-01

    In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

  6. Cluster-based analysis of multi-model climate ensembles

    NASA Astrophysics Data System (ADS)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  7. Local control on precipitation in a fully coupled climate-hydrology model.

    PubMed

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  8. Local control on precipitation in a fully coupled climate-hydrology model

    PubMed Central

    Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

    2016-01-01

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

  9. pyhector: A Python interface for the simple climate model Hector

    DOE PAGES

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

    2017-04-01

    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

  10. 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

  11. Population response to climate change: linear vs. non-linear modeling approaches.

    PubMed

    Ellis, Alicia M; Post, Eric

    2004-03-31

    Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

  12. A Model Based Mars Climate Database for the Mission Design

    NASA Technical Reports Server (NTRS)

    2005-01-01

    A viewgraph presentation on a model based climate database is shown. The topics include: 1) Why a model based climate database?; 2) Mars Climate Database v3.1 Who uses it ? (approx. 60 users!); 3) The new Mars Climate database MCD v4.0; 4) MCD v4.0: what's new ? 5) Simulation of Water ice clouds; 6) Simulation of Water ice cycle; 7) A new tool for surface pressure prediction; 8) Acces to the database MCD 4.0; 9) How to access the database; and 10) New web access

  13. [Prediction of heat-related mortality impacts under climate change scenarios in Shanghai].

    PubMed

    Guo, Ya-fei; Li, Tian-tian; Cheng, Yan-li; Ge, Tan-xi; Chen, Chen; Liu, Fan

    2012-11-01

    To project the future impacts of climate change on heat-related mortality in shanghai. The statistical downscaling techniques were applied to simulate the daily mean temperatures of Shanghai in the middle and farther future under the changing climate. Based on the published exposure-reaction relationship of temperature and mortality in Shanghai, we projected the heat-related mortality in the middle and farther future under the circumstance of high speed increase of carbon e mission (A2) and low speed increase of carbon emission (B2). The data of 1961 to 1990 was used to establish the model, and the data of 1991 - 2001 was used to testify the model, and then the daily mean temperature from 2030 to 2059 and from 2070 to 2099 were simulated and the heat-related mortality was projected. The data resources were from U.S. National Climatic Data Center (NCDC), U.S. National Centers for Environmental Prediction Reanalysis Data in SDSM Website and UK Hadley Centre Coupled Model Data in SDSM Website. The explained variance and the standard error of the established model was separately 98.1% and 1.24°C. The R(2) value of the simulated trend line equaled to 0.978 in Shanghai, as testified by the model. Therefore, the temperature prediction model simulated daily mean temperatures well. Under A2 scenario, the daily mean temperature in 2030 - 2059 and 2070 - 2099 were projected to be 17.9°C and 20.4°C, respectively, increasing by 1.1°C and 3.6°C when compared to baseline period (16.8°C). Under B2 scenario, the daily mean temperature in 2030 - 2059 and 2070 - 2099 were projected to be 17.8°C and 19.1°C, respectively, increasing by 1.0°C and 2.3°C when compared to baseline period (16.8°C). Under A2 scenario, annual average heat-related mortality were projected to be 516 cases and 1191 cases in 2030 - 2059 and 2070 - 2099, respectively, increasing 53.6% and 254.5% when compared with baseline period (336 cases). Under B2 scenario, annual average heat-related mortality were

  14. Scale dependency of regional climate modeling of current and future climate extremes in Germany

    NASA Astrophysics Data System (ADS)

    Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

    2017-11-01

    A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

  15. Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

    NASA Astrophysics Data System (ADS)

    Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

    2017-04-01

    Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V

  16. Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

    DOE PAGES

    Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...

    2014-02-24

    The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less

  17. Climate Modeling and Analysis with Decision Makers in Mind

    NASA Astrophysics Data System (ADS)

    Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

    2016-12-01

    There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

  18. Modeling climate change impacts on water trading.

    PubMed

    Luo, Bin; Maqsood, Imran; Gong, Yazhen

    2010-04-01

    This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

  19. Key challenges and priorities for modelling European grasslands under climate change.

    PubMed

    Kipling, Richard P; Virkajärvi, Perttu; Breitsameter, Laura; Curnel, Yannick; De Swaef, Tom; Gustavsson, Anne-Maj; Hennart, Sylvain; Höglind, Mats; Järvenranta, Kirsi; Minet, Julien; Nendel, Claas; Persson, Tomas; Picon-Cochard, Catherine; Rolinski, Susanne; Sandars, Daniel L; Scollan, Nigel D; Sebek, Leon; Seddaiu, Giovanna; Topp, Cairistiona F E; Twardy, Stanislaw; Van Middelkoop, Jantine; Wu, Lianhai; Bellocchi, Gianni

    2016-10-01

    Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research

  20. Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

    NASA Astrophysics Data System (ADS)

    Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

    2008-12-01

    Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

  1. The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

    NASA Technical Reports Server (NTRS)

    Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

    1988-01-01

    A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

  2. A commentary on the Atlantic meridional overturning circulation stability in climate models

    NASA Astrophysics Data System (ADS)

    Gent, Peter R.

    2018-02-01

    The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models.

  3. Global Warming and Northern Hemisphere Sea Ice Extent.

    PubMed

    Vinnikov; Robock; Stouffer; Walsh; Parkinson; Cavalieri; Mitchell; Garrett; Zakharov

    1999-12-03

    Surface and satellite-based observations show a decrease in Northern Hemisphere sea ice extent during the past 46 years. A comparison of these trends to control and transient integrations (forced by observed greenhouse gases and tropospheric sulfate aerosols) from the Geophysical Fluid Dynamics Laboratory and Hadley Centre climate models reveals that the observed decrease in Northern Hemisphere sea ice extent agrees with the transient simulations, and both trends are much larger than would be expected from natural climate variations. From long-term control runs of climate models, it was found that the probability of the observed trends resulting from natural climate variability, assuming that the models' natural variability is similar to that found in nature, is less than 2 percent for the 1978-98 sea ice trends and less than 0.1 percent for the 1953-98 sea ice trends. Both models used here project continued decreases in sea ice thickness and extent throughout the next century.

  4. Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

    NASA Astrophysics Data System (ADS)

    Drijfhout, Sybren; Bathiany, Sebastian; Beaulieu, Claudie; Brovkin, Victor; Claussen, Martin; Huntingford, Chris; Scheffer, Marten; Sgubin, Giovanni; Swingedouw, Didier

    2015-10-01

    Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change.

  5. Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

    PubMed Central

    Drijfhout, Sybren; Bathiany, Sebastian; Beaulieu, Claudie; Brovkin, Victor; Claussen, Martin; Huntingford, Chris; Scheffer, Marten; Sgubin, Giovanni; Swingedouw, Didier

    2015-01-01

    Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change. PMID:26460042

  6. Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models.

    PubMed

    Drijfhout, Sybren; Bathiany, Sebastian; Beaulieu, Claudie; Brovkin, Victor; Claussen, Martin; Huntingford, Chris; Scheffer, Marten; Sgubin, Giovanni; Swingedouw, Didier

    2015-10-27

    Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change.

  7. A Narrowing Target for Early Mars Climate Models: Which Models Survive Confrontation with Improved Hydrology Constraints?

    NASA Astrophysics Data System (ADS)

    Kite, E. S.; Goldblatt, C.; Gao, P.; Mayer, D. P.; Sneed, J.; Wilson, S. A.

    2016-12-01

    The wettest climates in Mars' geologic history represent habitability optima, and also set the tightest constraints on climate models. For lake-forming climates on Early Mars, geologic data constrain discharge, duration, intermittency, and the number of lake-forming events. We synthesise new and existing data to suggest that post-Noachian lake-forming climates were widely separated in time, lasted >10^4 yr individually, were few in number, but cumulatively lasted <10^7 yr (to allow olivine to survive globally). We compare these data against existing models, set out a new model involving methane bursts, and conclude with future directions for Early Mars geologic analysis and modelling work.

  8. Chapter 7: Developing climate-informed state-and-transition models

    Treesearch

    Miles A. Hemstrom; Jessica E. Halofsky; David R. Conklin; Joshua S. Halofsky; Dominique Bachelet; Becky K. Kerns

    2014-01-01

    Land managers and others need ways to understand the potential effects of climate change on local vegetation types and how management activities might be impacted by climate change. To date, climate change impact models have not included localized vegetation communities or the integrated effects of vegetation development dynamics, natural disturbances, and management...

  9. Linking the Weather Generator with Regional Climate Model

    NASA Astrophysics Data System (ADS)

    Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

    2013-04-01

    One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102

  10. Evaluating the sensitivity of agricultural model performance to different climate inputs

    PubMed Central

    Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

    2017-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

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

    NASA Astrophysics Data System (ADS)

    Wu, Z.; Ahlström, A.; Smith, B.; Ardö, J.; Eklundh, L.; Fensholt, R.; Lehsten, V.

    2016-12-01

    Models used to project global vegetation and carbon cycle differ in their estimates of historical fluxes and pools. These differences arise not only from differences between models but also from differences in the environmental and climatic data that forces the models. Here we investigate the role of uncertainties in historical climate data, encapsulated by a set of six historical climate datasets. We focus on terrestrial gross primary productivity (GPP) and analyze the results from a dynamic process-based vegetation model (LPJ-GUESS) forced by six different climate datasets and two empirical datasets of GPP (derived from flux towers and remote sensing). We find that the climate induced uncertainty, defined as the difference among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 33 Pg C yr-1 globally (19% of mean GPP). The uncertainty is partitioned into the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (the data range) and the sensitivity of the modeled GPP to the driver (the ecosystem sensitivity). The analysis is performed globally and stratified into five land cover classes. We find that the dynamic vegetation model overestimates GPP, compared to empirically based GPP data over most areas, except for the tropical region. Both the simulations and empirical estimates agree that the tropical region is a disproportionate source of uncertainty in GPP estimation. This is mainly caused by uncertainties in shortwave radiation forcing, of which climate data range contributes slightly higher uncertainty than ecosystem sensitivity to shortwave radiation. We also find that precipitation dominated the climate induced uncertainty over nearly half of terrestrial vegetated surfaces, which is mainly due to large ecosystem sensitivity to

  12. Climate Model Response from the Geoengineering Model Intercomparison Project (GeoMIP)

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

    Kravitz, Benjamin S.; Caldeira, Ken; Boucher, Olivier

    2013-08-09

    Solar geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwisemore » occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2mmday-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.« less

  13. Climate model response from the Geoengineering Model Intercomparison Project (GeoMIP)

    NASA Astrophysics Data System (ADS)

    Kravitz, Ben; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; Alterskjær, Kari; Karam, Diana Bou; Cole, Jason N. S.; Curry, Charles L.; Haywood, James M.; Irvine, Peter J.; Ji, Duoying; Jones, Andy; Kristjánsson, Jón Egill; Lunt, Daniel J.; Moore, John C.; Niemeier, Ulrike; Schmidt, Hauke; Schulz, Michael; Singh, Balwinder; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

    2013-08-01

    geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2 mm day-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.

  14. Climate Modeling and Causal Identification for Sea Ice Predictability

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

    Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

    This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

  15. Climate Change and Runoff Statistics: a Process Study for the Rhine Basin using a coupled Climate-Runoff Model

    NASA Astrophysics Data System (ADS)

    Kleinn, J.; Frei, C.; Gurtz, J.; Vidale, P. L.; Schär, C.

    2003-04-01

    The consequences of extreme runoff and extreme water levels are within the most important weather induced natural hazards. The question about the impact of a global climate change on the runoff regime, especially on the frequency of floods, is of utmost importance. In winter-time, two possible climate effects could influence the runoff statistis of large Central European rivers: the shift from snowfall to rain as a consequence of higher temperatures and the increase of heavy precipitation events due to an intensification of the hydrological cycle. The combined effect on the runoff statistics is examined in this study for the river Rhine. To this end, sensitivity experiments with a model chain including a regional climate model and a distributed runoff model are presented. The experiments are based on an idealized surrogate climate change scenario which stipulates a uniform increase in temperature by 2 Kelvin and an increase in atmospheric specific humidity by 15% (resulting from unchanged relative humidity) in the forcing fields for the regional climate model. The regional climate model CHRM is based on the mesoscale weather prediction model HRM of the German Weather Service (DWD) and has been adapted for climate simulations. The model is being used in a nested mode with horizontal resolutions of 56 km and 14 km. The boundary conditions are taken from the original ECMWF reanalysis and from a modified version representing the surrogate scenario. The distributed runoff model (WaSiM) is used at a horizontal resolution of 1 km for the whole Rhine basin down to Cologne. The coupling of the models is provided by a downscaling of the climate model fields (precipitaion, temperature, radiation, humidity, and wind) to the resolution of the distributed runoff model. The simulations cover the period of September 1987 to January 1994 with a special emphasis on the five winter seasons 1989/90 until 1993/94, each from November until January. A detailed validation of the control

  16. Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

    NASA Technical Reports Server (NTRS)

    Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

    2013-01-01

    Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

  17. Carbon-climate-human interactions in an integrated human-Earth system model

    NASA Astrophysics Data System (ADS)

    Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

    2016-12-01

    The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

  18. Modelling climate impacts on the aviation sector

    NASA Astrophysics Data System (ADS)

    Williams, Paul

    2017-04-01

    The climate is changing, not just where we live at ground level, but also where we fly at 35,000 feet. We have long known that air travel contributes to climate change through its emissions. However, we have only recently become aware that climate change could have significant consequences for air travel. This presentation will give an overview of the possible impacts of climate change on the aviation sector. The presentation will describe how the impacts are modelled and how their social and economic costs are estimated. The impacts are discussed in the International Civil Aviation Organization's (ICAO's) latest Environmental Report (Puempel and Williams 2016). Some of the possible impacts are as follows. Rising sea levels and storm surges threaten coastal airports, such as La Guardia in New York, which was flooded by the remnants of Hurricane Sandy in 2012. Warmer air at ground level reduces the lift force and makes it more difficult for planes to take-off (Coffel and Horton 2015). More extreme weather may cause flight disruptions and delays. Clear-air turbulence is expected to become up to 40% stronger and twice as common (Williams and Joshi 2013). Transatlantic flights may collectively be airborne for an extra 2,000 hours each year because of changes to the jet stream, burning an extra 7.2 million gallons of jet fuel at a cost of US 22 million, and emitting an extra 70 million kg of carbon dioxide (Williams 2016). These modelled impacts provide further evidence of the two-way interaction between aviation and climate change. References Coffel E and Horton R (2015) Climate change and the impact of extreme temperatures on aviation. Weather, Climate, and Society, 7, 94-102. http://dx.doi.org/10.1175/WCAS-D-14-00026.1 Puempel H and Williams PD (2016) The impacts of climate change on aviation: Scientific challenges and adaptation pathways. ICAO Environmental Report 2016: On Board A Sustainable Future, pp 205-207. http

  19. Investigations of the Climate System Response to Climate Engineering in a Hierarchy of Models

    NASA Astrophysics Data System (ADS)

    McCusker, Kelly E.

    Global warming due to anthropogenic emissions of greenhouse gases is causing negative impacts on diverse ecological and human systems around the globe, and these impacts are projected to worsen as climate continues to warm. In the absence of meaningful greenhouse gas emissions reductions, new strategies have been proposed to engineer the climate, with the aim of preventing further warming and avoiding associated climate impacts. We investigate one such strategy here, falling under the umbrella of `solar radiation management', in which sulfate aerosols are injected into the stratosphere. We use a global climate model with a coupled mixed-layer depth ocean and with a fully-coupled ocean general circulation model to simulate the stabilization of climate by balancing increasing carbon dioxide with increasing stratospheric sulfate concentrations. We evaluate whether or not severe climate impacts, such as melting Arctic sea ice, tropical crop failure, or destabilization of the West Antarctic ice sheet, could be avoided. We find that while tropical climate emergencies might be avoided by use of stratospheric aerosol injections, avoiding polar emergencies cannot be guaranteed due to large residual climate changes in those regions, which are in part due to residual atmospheric circulation anomalies. We also find that the inclusion of a fully-coupled ocean is important for determining the regional climate response because of its dynamical feedbacks. The efficacy of stratospheric sulfate aerosol injections, and solar radiation management more generally, depends on its ability to be maintained indefinitely, without interruption from a variety of possible sources, such as technological failure, a breakdown in global cooperation, lack of funding, or negative unintended consequences. We next consider the scenario in which stratospheric sulfate injections are abruptly terminated after a multi- decadal period of implementation while greenhouse gas emissions have continued unabated

  20. Constraining the Late Miocene paleo-CO2 estimates through GCM model-data comparisons

    NASA Astrophysics Data System (ADS)

    Bradshaw, Catherine; Pound, Matthew; Lunt, Daniel; Flecker, Rachel; Salzmann, Ulrich; Haywood, Alan; Riding, James; Francis, Jane

    2010-05-01

    The period following the Mid-Miocene Climatic Optimum experienced a continued downward trend in the δ18O record - a record acknowledged as a proxy indicator of both ice volume and temperature (Zachos et al., 2001). Given the link between atmospheric CO2 and temperature (IPCC, 2007), it could be thought that the timeline throughout the Late Miocene would show a general decline in CO2 in accordance with the δ18O record. However, examination of the palaeo-CO2 record shows a relatively flat profile across this time, or perhaps even a slight increase, but there is a wide variation in the palaeo-CO2 estimate for the differing approximation methods. We use the fully coupled atmosphere-ocean-vegetation model of the Hadley Centre, HadCM3L, which has a low resolution ocean (Hadley Centre Coupled Model, Version 3 - low resolution ocean) with TRIFFID (Top-down Representation of Interactive Foliage and Flora Including Dynamics: Cox, 2001) to generate CO2 sensitivity scenarios for the Late Miocene: 180ppmv, 280ppmv and 400ppmv, as well as a preindustrial control simulation: 280 ppmv. We also run the BIOME4 model offline to produce predicted biome distributions for each of our scenarios. We compare both marine and terrestrial modelled temperatures, and the predicted vegetation distributions for these scenarios against available palaeodata As we simulate with a coupled dynamic ocean model, we use planktonic and benthic foraminiferal-based proxy palaeotemperature estimates to compare to the modelled marine temperatures at the depths consistent with the reconstructed palaeoecology of the foraminifera. We compare our modelled terrestrial temperatures to vegetation-based proxy palaeotemperatures, and we use a newly compiled vegetation reconstruction for the Late Miocene to compare to our modelled vegetation distributions. The new Late Miocene vegetation reconstruction is based on a 200+ point database of palaeobotanical sites. Each location is classified into a biome consistent with

  1. Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

    DOE PAGES

    Eum, Hyung-Il; Gachon, Philippe; Laprise, René

    2016-01-01

    This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

  2. Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

    Eum, Hyung-Il; Gachon, Philippe; Laprise, René

    This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

  3. Educational and Scientific Applications of Climate Model Diagnostic Analyzer

    NASA Astrophysics Data System (ADS)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

    2016-12-01

    Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of

  4. Issues related to incorporating northern peatlands into global climate models

    NASA Astrophysics Data System (ADS)

    Frolking, Steve; Roulet, Nigel; Lawrence, David

    Northern peatlands cover ˜3-4 million km2 (˜10% of the land north of 45°N) and contain ˜200-400 Pg carbon (˜10-20% of total global soil carbon), almost entirely as peat (organic soil). Recent developments in global climate models have included incorporation of the terrestrial carbon cycle and representation of several terrestrial ecosystem types and processes in their land surface modules. Peatlands share many general properties with upland, mineral-soil ecosystems, and general ecosystem carbon, water, and energy cycle functions (productivity, decomposition, water infiltration, evapotranspiration, runoff, latent, sensible, and ground heat fluxes). However, northern peatlands also have several unique characteristics that will require some rethinking or revising of land surface algorithms in global climate models. Here we review some of these characteristics, deep organic soils, a significant fraction of bryophyte vegetation, shallow water tables, spatial heterogeneity, anaerobic biogeochemistry, and disturbance regimes, in the context of incorporating them into global climate models. With the incorporation of peatlands, global climate models will be able to simulate the fate of northern peatland carbon under climate change, and estimate the magnitude and strength of any climate system feedbacks associated with the dynamics of this large carbon pool.

  5. Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate

    NASA Astrophysics Data System (ADS)

    Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Calvin, K. V.

    2016-12-01

    The C4MIP and CMIP5 model intercomparison projects (MIPs) highlighted uncertainties in climate projections, driven to a large extent by interactions between the terrestrial carbon cycle and climate feedbacks. In addition, the importance of feedbacks between human (energy and economic) systems and natural (carbon and climate) systems is poorly understood, and not considered in the previous MIP protocols. The experiments conducted under the previous Integrated Earth System Model (iESM) project, which coupled a earth system model with an integrated assessment model (GCAM), found that the inclusion of climate feedbacks on the terrestrial system in an RCP4.5 scenario increased ecosystem productivity, resulting in declines in cropland extent and increases in bioenergy production and forest cover. As a follow-up to these studies and to further understand climate-carbon cycle interactions and feedbacks, we examined the robustness of these results by running a suite of GCAM-only experiments using changes in ecosystem productivity derived from both the CMIP5 archive and the Agricultural Model Intercomparison Project. In our results, the effects of climate on yield in an RCP8.5 scenario tended to be more positive than those of AgMIP, but more negative than those of the other CMIP models. We discuss these results and the implications of model-to-model variability for integrated coupling studies of the future earth system.

  6. DOE unveils climate model in advance of global test

    NASA Astrophysics Data System (ADS)

    Popkin, Gabriel

    2018-05-01

    The world's growing collection of climate models has a high-profile new entry. Last week, after nearly 4 years of work, the U.S. Department of Energy (DOE) released computer code and initial results from an ambitious effort to simulate the Earth system. The new model is tailored to run on future supercomputers and designed to forecast not just how climate will change, but also how those changes might stress energy infrastructure. Results from an upcoming comparison of global models may show how well the new entrant works. But so far it is getting a mixed reception, with some questioning the need for another model and others saying the $80 million effort has yet to improve predictions of the future climate. Even the project's chief scientist, Ruby Leung of the Pacific Northwest National Laboratory in Richland, Washington, acknowledges that the model is not yet a leader.

  7. Physical-Socio-Economic Modeling of Climate Change

    NASA Astrophysics Data System (ADS)

    Chamberlain, R. G.; Vatan, F.

    2008-12-01

    Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media

  8. Evaluating wind extremes in CMIP5 climate models

    NASA Astrophysics Data System (ADS)

    Kumar, Devashish; Mishra, Vimal; Ganguly, Auroop R.

    2015-07-01

    Wind extremes have consequences for renewable energy sectors, critical infrastructures, coastal ecosystems, and insurance industry. Considerable debates remain regarding the impacts of climate change on wind extremes. While climate models have occasionally shown increases in regional wind extremes, a decline in the magnitude of mean and extreme near-surface wind speeds has been recently reported over most regions of the Northern Hemisphere using observed data. Previous studies of wind extremes under climate change have focused on selected regions and employed outputs from the regional climate models (RCMs). However, RCMs ultimately rely on the outputs of global circulation models (GCMs), and the value-addition from the former over the latter has been questioned. Regional model runs rarely employ the full suite of GCM ensembles, and hence may not be able to encapsulate the most likely projections or their variability. Here we evaluate the performance of the latest generation of GCMs, the Coupled Model Intercomparison Project phase 5 (CMIP5), in simulating extreme winds. We find that the multimodel ensemble (MME) mean captures the spatial variability of annual maximum wind speeds over most regions except over the mountainous terrains. However, the historical temporal trends in annual maximum wind speeds for the reanalysis data, ERA-Interim, are not well represented in the GCMs. The historical trends in extreme winds from GCMs are statistically not significant over most regions. The MME model simulates the spatial patterns of extreme winds for 25-100 year return periods. The projected extreme winds from GCMs exhibit statistically less significant trends compared to the historical reference period.

  9. Documenting Climate Models and Simulations: the ES-DOC Ecosystem in Support of CMIP

    NASA Astrophysics Data System (ADS)

    Pascoe, C. L.; Guilyardi, E.

    2017-12-01

    The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now non-specialists such as government officials, policy-makers, and the general public, all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. Here we describe the ES-DOC community-govern project to collect and make available documentation of climate models and their simulations for the internationally coordinated modeling activity CMIP6 (Coupled Model Intercomparison Project, Phase 6). An overview of the underlying standards, key properties and features, the evolution from CMIP5, the underlying tools and workflows as well as what modelling groups should expect and how they should engage with the documentation of their contribution to CMIP6 is also presented.

  10. High Resolution Modeling of Hurricanes in a Climate Context

    NASA Astrophysics Data System (ADS)

    Knutson, T. R.

    2007-12-01

    Modeling of tropical cyclone activity in a climate context initially focused on simulation of relatively weak tropical storm-like disturbances as resolved by coarse grid (200 km) global models. As computing power has increased, multi-year simulations with global models of grid spacing 20-30 km have become feasible. Increased resolution also allowed for simulation storms of increasing intensity, and some global models generate storms of hurricane strength, depending on their resolution and other factors, although detailed hurricane structure is not simulated realistically. Results from some recent high resolution global model studies are reviewed. An alternative for hurricane simulation is regional downscaling. An early approach was to embed an operational (GFDL) hurricane prediction model within a global model solution, either for 5-day case studies of particular model storm cases, or for "idealized experiments" where an initial vortex is inserted into an idealized environments derived from global model statistics. Using this approach, hurricanes up to category five intensity can be simulated, owing to the model's relatively high resolution (9 km grid) and refined physics. Variants on this approach have been used to provide modeling support for theoretical predictions that greenhouse warming will increase the maximum intensities of hurricanes. These modeling studies also simulate increased hurricane rainfall rates in a warmer climate. The studies do not address hurricane frequency issues, and vertical shear is neglected in the idealized studies. A recent development is the use of regional model dynamical downscaling for extended (e.g., season-length) integrations of hurricane activity. In a study for the Atlantic basin, a non-hydrostatic model with grid spacing of 18km is run without convective parameterization, but with internal spectral nudging toward observed large-scale (basin wavenumbers 0-2) atmospheric conditions from reanalyses. Using this approach, our

  11. Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

    PubMed

    Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

    2016-12-05

    Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.

  12. The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

    NASA Astrophysics Data System (ADS)

    Hurrell, J. W.; Holland, G. J.; Large, W. G.

    2008-12-01

    The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is

  13. Handling Uncertainty in Palaeo-Climate Models and Data

    NASA Astrophysics Data System (ADS)

    Voss, J.; Haywood, A. M.; Dolan, A. M.; Domingo, D.

    2017-12-01

    The study of palaeoclimates can provide data on the behaviour of the Earth system with boundary conditions different from the ones we observe in the present. One of the main challenges in this approach is that data on past climates comes with large uncertainties, since quantities of interest cannot be observed directly, but must be derived from proxies instead. We consider proxy-derived data from the Pliocene (around 3 millions years ago; the last interval in Earth history when CO2 was at modern or near future levels) and contrast this data to the output of complex climate models. In order to perform a meaningful data-model comparison, uncertainties must be taken into account. In this context, we discuss two examples of complex data-model comparison problems. Both examples have in common that they involve fitting a statistical model to describe how the output of the climate simulations depends on various model parameters, including atmospheric CO2 concentration and orbital parameters (obliquity, excentricity, and precession). This introduces additional uncertainties, but allows to explore a much larger range of model parameters than would be feasible by only relying on simulation runs. The first example shows how Gaussian process emulators can be used to perform data-model comparison when simulation runs only differ in the choice of orbital parameters, but temperature data is given in the (somewhat inconvenient) form of "warm peak averages". The second example shows how a simpler approach, based on linear regression, can be used to analyse a more complex problem where we use a larger and more varied ensemble of climate simulations with the aim to estimate Earth System Sensitivity.

  14. Impacts of climate change and socio-economic scenarios on flow and water quality of the Ganges, Brahmaputra and Meghna (GBM) river systems: low flow and flood statistics.

    PubMed

    Whitehead, P G; Barbour, E; Futter, M N; Sarkar, S; Rodda, H; Caesar, J; Butterfield, D; Jin, L; Sinha, R; Nicholls, R; Salehin, M

    2015-06-01

    The potential impacts of climate change and socio-economic change on flow and water quality in rivers worldwide is a key area of interest. The Ganges-Brahmaputra-Meghna (GBM) is one of the largest river basins in the world serving a population of over 650 million, and is of vital concern to India and Bangladesh as it provides fresh water for people, agriculture, industry, conservation and for the delta system downstream. This paper seeks to assess future changes in flow and water quality utilising a modelling approach as a means of assessment in a very complex system. The INCA-N model has been applied to the Ganges, Brahmaputra and Meghna river systems to simulate flow and water quality along the rivers under a range of future climate conditions. Three model realisations of the Met Office Hadley Centre global and regional climate models were selected from 17 perturbed model runs to evaluate a range of potential futures in climate. In addition, the models have also been evaluated using socio-economic scenarios, comprising (1) a business as usual future, (2) a more sustainable future, and (3) a less sustainable future. Model results for the 2050s and the 2090s indicate a significant increase in monsoon flows under the future climates, with enhanced flood potential. Low flows are predicted to fall with extended drought periods, which could have impacts on water and sediment supply, irrigated agriculture and saline intrusion. In contrast, the socio-economic changes had relatively little impact on flows, except under the low flow regimes where increased irrigation could further reduce water availability. However, should large scale water transfers upstream of Bangladesh be constructed, these have the potential to reduce flows and divert water away from the delta region depending on the volume and timing of the transfers. This could have significant implications for the delta in terms of saline intrusion, water supply, agriculture and maintaining crucial ecosystems such

  15. Modelling impacts of climate change on arable crop diseases: progress, challenges and applications.

    PubMed

    Newbery, Fay; Qi, Aiming; Fitt, Bruce Dl

    2016-08-01

    Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored. Impact assessments are still concentrated on few crops and few diseases but are beginning to investigate arable crop disease dynamics at the landscape level. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  16. Using climate models to estimate the quality of global observational data sets.

    PubMed

    Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J

    2016-10-28

    Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.

  17. Multi-model assessment of water scarcity under climate change

    NASA Astrophysics Data System (ADS)

    Schewe, J.; Heinke, J.; Gerten, D.; Haddeland, I.; Arnell, N. W.; Clark, D. B.; Dankers, R.; Eisner, S.; Fekete, B. M.; Colon-Gonzalez, F. J.; Gosling, S. N.; KIM, H.; Liu, X.; Masaki, Y.; Portmann, F. T.; Satoh, Y.; Stacke, T.; Tang, Q.; Wada, Y.; Wisser, D.; albrecht, T.; Frieler, K.; Piontek, F.; Warszawski, L.; Kabat, P.

    2013-12-01

    Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. In the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) we use a large ensemble of global hydrological models (GHMs) forced by five global climate models (GCMs) and the latest greenhouse--gas concentration scenarios (RCPs) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that up to a global warming of 2°C above present (approx. 2.7°C above pre--industrial), each additional degree of warming will confront an additional approx. 7% of the global population with a severe decrease in water resources; and that climate change will increase the number of people living under absolute water scarcity (<500m3/capita/year) by another 40% (according to some models, more than 100%) compared to the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between present--day and 2°C, while indicators of very severe impacts increase unabated beyond 2°C. At the same time, the study highlights large uncertainties associated with these estimates, with both GCMs and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development. Relative change in annual discharge at 2°C compared to present-day, under RCP8.5, from an ensemble of 11 global hydrological models (GHMs) driven by five

  18. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    NASA Astrophysics Data System (ADS)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  19. Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

    NASA Astrophysics Data System (ADS)

    Gampe, D.; Ludwig, R.

    2017-12-01

    Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and

  20. Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

    Wood, Andrew W; Leung, Lai R; Sridhar, V

    Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able

  1. Devon Ice cap's future: results from climate and ice dynamics modelling via surface mass balance modelling

    NASA Astrophysics Data System (ADS)

    Rodehacke, C. B.; Mottram, R.; Boberg, F.

    2017-12-01

    The Devon Ice Cap is an example of a relatively well monitored small ice cap in the Canadian Arctic. Close to Greenland, it shows a similar surface mass balance signal to glaciers in western Greenland. Here we various boundary conditions, ranging from ERA-Interim reanalysis data via global climate model high resolution (5km) output from the regional climate model HIRHAM5, to determine the surface mass balance of the Devon ice cap. These SMB estimates are used to drive the PISM glacier model in order to model the present day and future prospects of this small Arctic ice cap. Observational data from the Devon Ice Cap in Arctic Canada is used to evaluate the surface mass balance (SMB) data output from the HIRHAM5 model for simulations forced with the ERA-Interim climate reanalysis data and the historical emissions scenario run by the EC-Earth global climate model. The RCP8.5 scenario simulated by EC-Earth is also downscaled by HIRHAM5 and this output is used to force the PISM model to simulate the likely future evolution of the Devon Ice Cap under a warming climate. We find that the Devon Ice Cap is likely to continue its present day retreat, though in the future increased precipitation partly offsets the enhanced melt rates caused by climate change.

  2. Simulation of modern climate with the new version of the INM RAS climate model

    NASA Astrophysics Data System (ADS)

    Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykosov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Yakovlev, N. G.

    2017-03-01

    The INMCM5.0 numerical model of the Earth's climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved.

  3. Modeling Climate Change and Sturgeon Populations in the Missouri River

    USGS Publications Warehouse

    Wildhaber, Mark L.

    2010-01-01

    The U.S. Geological Survey (USGS) Columbia Environmental Research Center (CERC), in collaboration with researchers from the University of Missouri and Iowa State University, is conducting research to address effects of climate change on sturgeon populations (Scaphirhynchus spp.) in the Missouri River. The CERC is conducting laboratory, field, and modeling research to identify causative factors for the responses of fish populations to natural and human-induced environmental changes and using this information to understand sensitivity of sturgeon populations to potential climate change in the Missouri River drainage basin. Sturgeon response information is being used to parameterize models predicting future population trends. These models will provide a set of tools for natural resource managers to assess management strategies in the context of global climate change. This research complements and builds on the ongoing Comprehensive Sturgeon Research Program (CSRP) at the CERC. The CSRP is designed to provide information critical to restoration of the Missouri River ecosystem and the endangered pallid sturgeon (S. albus). Current research is being funded by USGS through the National Climate Change Wildlife Science Center (NCCWSC) and the Science Support Partnership (SSP) Program that is held by the USGS and the U.S. Fish and Wildlife Service. The national mission of the NCCWSC is to improve the capacity of fish and wildlife agencies to respond to climate change and to address high-priority climate change effects on fish and wildlife. Within the national context, the NCCWSC research on the Missouri River focuses on temporal and spatial downscaling and associated uncertainty in modeling climate change effects on sturgeon species in the Missouri River. The SSP research focuses on improving survival and population estimates for pallid sturgeon population models.

  4. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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

    Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

    The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

  5. Predicting climate-induced range shifts: model differences and model reliability.

    Treesearch

    Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein

    2006-01-01

    Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common data set, we investigated the potential implications of alternative modeling approaches for...

  6. 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.

  7. 3D climate-carbon modelling of the early Earth

    NASA Astrophysics Data System (ADS)

    Charnay, B.; Le Hir, G.; Fluteau, F.; Forget, F.; Catling, D.

    2017-09-01

    We revisit the climate and carbon cycle of the early Earth at 3.8 Ga using a 3D climate-carbon model. Our resultsfavor cold or temperate climates with global mean temperatures between around 8°C (281 K) and 30°C (303 K) and with 0.1-0.36 bar of CO2 for the late Hadean and early Archean.

  8. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models.

    PubMed

    Ramírez-Albores, Jorge E; Bustamante, Ramiro O; Badano, Ernesto I

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  9. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    PubMed Central

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  10. PREDICTING CLIMATE-INDUCED RANGE SHIFTS: MODEL DIFFERENCES AND MODEL RELIABILITY

    EPA Science Inventory

    Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common ...

  11. Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

    NASA Astrophysics Data System (ADS)

    Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

    2010-12-01

    NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center

  12. The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium

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

    Potter, Gerald L; Bader, David C; Riches, Michael

    Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session

  13. Future Bloom and Blossom Frost Risk for Malus domestica Considering Climate Model and Impact Model Uncertainties

    PubMed Central

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

    The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021–2050 compared to 1971–2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078–2087. The projected phenophases advanced by 5.5 d K−1, showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day. PMID:24116022

  14. Future bloom and blossom frost risk for Malus domestica considering climate model and impact model uncertainties.

    PubMed

    Hoffmann, Holger; Rath, Thomas

    2013-01-01

    The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021-2050 compared to 1971-2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078-2087. The projected phenophases advanced by 5.5 d K(-1), showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.

  15. A Biome map for Modelling Global Mid-Pliocene Climate Change

    NASA Astrophysics Data System (ADS)

    Salzmann, U.; Haywood, A. M.

    2006-12-01

    The importance of vegetation-climate feedbacks was highlighted by several paleo-climate modelling exercises but their role as a boundary condition in Tertiary modelling has not been fully recognised or explored. Several paleo-vegetation datasets and maps have been produced for specific time slabs or regions for the Tertiary, but the vegetation classifications that have been used differ, thus making meaningful comparisons difficult. In order to facilitate further investigations into Tertiary climate and environmental change we are presently implementing the comprehensive GIS database TEVIS (Tertiary Environment and Vegetation Information System). TEVIS integrates marine and terrestrial vegetation data, taken from fossil pollen, leaf or wood, into an internally consistent classification scheme to produce for different time slabs global Tertiary Biome and Mega- Biome maps (Harrison & Prentice, 2003). In the frame of our ongoing 5-year programme we present a first global vegetation map for the mid-Pliocene time slab, a period of sustained global warmth. Data were synthesised from the PRISM data set (Thompson and Fleming 1996) after translating them to the Biome classification scheme and from new literature. The outcomes of the Biome map are compared with modelling results using an advanced numerical general circulation model (HadAM3) and the BIOME 4 vegetation model. Our combined proxy data and modelling approach will provide new palaeoclimate datasets to test models that are used to predict future climate change, and provide a more rigorous picture of climate and environmental changes during the Neogene.

  16. Modulation of Heavy Rainfall in the Middle East and North Africa by Madden-Julian Oscillation Using High Resolution Atmospheric General Circulation Model

    NASA Astrophysics Data System (ADS)

    Deng, L.; Stenchikov, G. L.; McCabe, M. F.; Bangalath, H. K.

    2014-12-01

    Recently, the modulation of subtropical rainfall by the dominant tropical intraseasonal signal of the Madden-Julian Oscillation (MJO), has been explored through the discussion of the MJO-convection-induced Kelvin and Rossby wave related teleconnection patterns. Our study focuses on characterizing the modulation of heavy rainfall in the Middle East and North Africa (MENA) region by the MJO, using the Geophysical Fluid Dynamics Laboratory (GFDL) global High Resolution Atmospheric Model (HIRAM) simulations (25-km; 1979-2012) and a combination of available atmospheric products from satellite, in-situ and reanalysis data. The observed Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the simulated SST from GFDL's global coupled carbon-climate Earth System Models (ESM2M) are employed in HIRAM to investigate the sensitivity of the simulated heavy rainfall and MJO to SST. The future trend of the extreme rainfalls and their links to the MJO response to climate change are examined using HIRAM simulations of 2012-2050 with the RCP4.5 and RCP 8.5 scenarios to advance the possibility of characterization and forecasting of future extreme rainfall events in the MENA region.

  17. Misleading prioritizations from modelling range shifts under climate change

    USGS Publications Warehouse

    Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

    2018-01-01

    AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and

  18. Can we trust climate models to realistically represent severe European windstorms?

    NASA Astrophysics Data System (ADS)

    Trzeciak, Tomasz M.; Knippertz, Peter; Owen, Jennifer S. R.

    2014-05-01

    Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models started from predefined initial conditions and run in a numerical weather prediction mode on the time scale of several days. Such a cost-effective case-study approach, which draws from and expands on the concepts from the Transpose-AMIP initiative, has recently been undertaken in the SEAMSEW project at the University of Leeds funded by the AXA Research Fund. Key results from this work focusing on 20 historical storms and using different lead times and horizontal and vertical resolutions include: (a) Tracks are represented reasonably well by most hindcasts. (b) Sensitivity to vertical resolution is low. (c) There is a systematic underprediction of cyclone depth for a coarse resolution of T63, but surprisingly no systematic bias is found for higher-resolution runs using T127, showing that climate models are in fact able to represent the

  19. Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

    NASA Astrophysics Data System (ADS)

    Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

    2015-12-01

    Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

  20. Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

    NASA Astrophysics Data System (ADS)

    Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

    2017-12-01

    At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.