Neoproterozoic 'snowball Earth' simulations with a coupled climate/ice-sheet model.

PubMed

Hyde, W T; Crowley, T J; Baum, S K; Peltier, W R

2000-05-25

Ice sheets may have reached the Equator in the late Proterozoic era (600-800 Myr ago), according to geological and palaeomagnetic studies, possibly resulting in a 'snowball Earth'. But this period was a critical time in the evolution of multicellular animals, posing the question of how early life survived under such environmental stress. Here we present computer simulations of this unusual climate stage with a coupled climate/ice-sheet model. To simulate a snowball Earth, we use only a reduction in the solar constant compared to present-day conditions and we keep atmospheric CO2 concentrations near present levels. We find rapid transitions into and out of full glaciation that are consistent with the geological evidence. When we combine these results with a general circulation model, some of the simulations result in an equatorial belt of open water that may have provided a refugium for multicellular animals.

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.

Reliability of regional climate simulations

NASA Astrophysics Data System (ADS)

Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.

2003-04-01

Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.

Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

USGS Publications Warehouse

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

European summer heatwaves and North Atlantic weather regimes in the last Millennium

NASA Astrophysics Data System (ADS)

Alvarez Castro, Maria del Carmen; Trasancos, Romain; Yiou, Pascal

2015-04-01

The European summer heatwaves have been increasing in frequency and magnitude in the past decades. A higher confidence in future changes in such extremes necessitates to have a better knowledge about extremes behavior in the past climate. The last millennium is well documented in terms of climate forcings. Modelling efforts have provided a wealth of climate simulations covering the last millennium. We want to exploit such data in order to assess how models simulate extreme summer heatwaves. The surface temperature and precipitation are closely related to atmospheric patterns. It has been shown that rainy winter/spring seasons reduce the frequency of hot summer days whereas dry seasons can be followed by summers with high or low frequency of hot days. In this poster, we show the relation between winter/spring precipitation with the frequency of hot days in the 10 hottest summers in Europe and Southern Europe during the Medieval Warm Period (MWP 1150-1250), the Little Ice Age (LIA 1650-1750), and the historical-present period (1850-2005). We first focus on a millennium simulations with the IPSL model (IPSL-CM5). We use daily temperature, precipitation, and SLP data from CMIP5 (Coupled Model Intercomparison Project phase 5) and a couple of IPSL simulations with diferents forcings. Summer weather regimes has been computed as well for NCEP sea level pressure data in order to compare observations with the same period (1948-2005) in CMIP5 and IPSL simulations outputs. We discuss and present the results comparing the effects of hydrological deficits in the preceding season, and the occurrence of specific weather regimes, during the hottest summers over Europe and SouthWestern Europe. This analysis compares differents climate forcings simulations.

Preindustrial to Present-Day Changes in Tropospheric Hydroxyl Radical and Methane Lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

NASA Technical Reports Server (NTRS)

Naik, V.; Voulgarakis, A.; Fiore, A. M.; Horowitz, L. W.; Lamarque, J.-F.; Lin, M.; Prather, M. J.; Young, P. J.; Bergmann, D.; Cameron-Smith, P. J.;

Sensitivity, stability and future evolution of the world's northernmost ice cap, Hans Tausen Iskappe (Greenland)

NASA Astrophysics Data System (ADS)

Zekollari, Harry; Huybrechts, Philippe; Noël, Brice; van de Berg, Willem Jan; van den Broeke, Michiel R.

2017-03-01

In this study the dynamics and sensitivity of Hans Tausen Iskappe (western Peary Land, Greenland) to climatic forcing is investigated with a coupled ice flow-mass balance model. The surface mass balance (SMB) is calculated from a precipitation field obtained from the Regional Atmospheric Climate Model (RACMO2.3), while runoff is calculated from a positive-degree-day runoff-retention model. For the ice flow a 3-D higher-order thermomechanical model is used, which is run at a 250 m resolution. A higher-order solution is needed to accurately represent the ice flow in the outlet glaciers. Under 1961-1990 climatic conditions a steady-state ice cap is obtained that is overall similar in geometry to the present-day ice cap. Ice thickness, temperature and flow velocity in the interior agree well with observations. For the outlet glaciers a reasonable agreement with temperature and ice thickness measurements can be obtained with an additional heat source related to infiltrating meltwater. The simulations indicate that the SMB-elevation feedback has a major effect on the ice cap response time and stability. This causes the southern part of the ice cap to be extremely sensitive to a change in climatic conditions and leads to thresholds in the ice cap evolution. Under constant 2005-2014 climatic conditions the entire southern part of the ice cap cannot be sustained, and the ice cap loses about 80 % of its present-day volume. The projected loss of surrounding permanent sea ice and resultant precipitation increase may attenuate the future mass loss but will be insufficient to preserve the present-day ice cap for most scenarios. In a warmer and wetter climate the ice margin will retreat, while the interior is projected to thicken, leading to a steeper ice cap, in line with the present-day observed trends. For intermediate- (+4 °C) and high- warming scenarios (+8 °C) the ice cap is projected to disappear around AD 2400 and 2200 respectively, almost independent of the projected precipitation regime and the simulated present-day geometry.

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

Hourly test reference weather data in the changing climate of Finland for building energy simulations.

PubMed

Jylhä, Kirsti; Ruosteenoja, Kimmo; Jokisalo, Juha; Pilli-Sihvola, Karoliina; Kalamees, Targo; Mäkelä, Hanna; Hyvönen, Reijo; Drebs, Achim

2015-09-01

Dynamic building energy simulations need hourly weather data as input. The same high temporal resolution is required for assessments of future heating and cooling energy demand. The data presented in this article concern current typical values and estimated future changes in outdoor air temperature, wind speed, relative humidity and global, diffuse and normal solar radiation components. Simulated annual and seasonal delivered energy consumptions for heating of spaces, heating of ventilation supply air and cooling of spaces in the current and future climatic conditions are also presented for an example house, with district heating and a mechanical space cooling system. We provide details on how the synthetic future weather files were created and utilised as input data for dynamic building energy simulations by the IDA Indoor Climate and Energy program and also for calculations of heating and cooling degree-day sums. The information supplied here is related to the research article titled "Energy demand for the heating and cooling of residential houses in Finland in a changing climate" [1].

Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

NASA Astrophysics Data System (ADS)

Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

2017-12-01

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

A new synoptic scale resolving global climate simulation using the Community Earth System Model

NASA Astrophysics Data System (ADS)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution AGCM based on the RCP scenarios

NASA Astrophysics Data System (ADS)

Woo, Sumin; Singh, Gyan Prakash; Oh, Jai-Ho; Lee, Kyoung-Min

2018-05-01

Seasonal changes in precipitation characteristics over India were projected using a high-resolution (40-km) atmospheric general circulation model (AGCM) during the near- (2010-2039), mid- (2040-2069), and far- (2070-2099) futures. For the model evaluation, we simulated an Atmospheric Model Intercomparison Project-type present-day climate using AGCM with observed sea-surface temperature and sea-ice concentration. Based on this simulation, we have simulated the current climate from 1979 to 2009 and subsequently the future climate projection until 2100 using a CMCC-CM model from Coupled Model Intercomparison Project phase 5 models based on RCP4.5 and RCP8.5 scenarios. Using various observed precipitation data, the validation of the simulated precipitation indicates that the AGCM well-captured the high and low rain belts and also onset and withdrawal of monsoon in the present-day climate simulation. Future projections were performed for the above-mentioned time slices (near-, mid-, and far futures). The model projected an increase in summer precipitation from 7 to 18% under RCP4.5 and from 14 to 18% under RCP8.5 from the mid- to far futures. Projected summer precipitation from different time slices depicts an increase over northwest (NWI) and west-south peninsular India (SPI) and a reduction over northeast and north-central India. The model projected an eastward shift of monsoon trough around 2° longitude and expansion and intensification of Mascarene High and Tibetan High seems to be associated with projected precipitation. The model projected extreme precipitation events show an increase (20-50%) in rainy days over NWI and SPI. While a significant increase of about 20-50% is noticed in heavy rain events over SPI during the far future.

Realism of modelled Indian summer monsoon correlation with the tropical Indo-Pacific affects projected monsoon changes.

PubMed

Li, Ziguang; Lin, Xiaopei; Cai, Wenju

2017-07-10

El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) tend to exert an offsetting impact on Indian summer monsoon rainfall (ISMR), with an El Niño event tending to lower, whereas a positive IOD tending to increase ISMR. Simulation of these relationships in Phase Five of the Coupled Model Intercomparison Project has not been fully assessed, nor is their impact on the response of ISMR to greenhouse warming. Here we show that the majority of models simulate an unrealistic present-day IOD-ISMR correlation due to an overly strong control by ENSO. As such, a positive IOD is associated with an ISMR reduction in the simulated present-day climate. This unrealistic present-day correlation is relevant to future ISMR projection, inducing an underestimation in the projected ISMR increase. Thus uncertainties in ISMR projection can be in part induced by present-day simulation of ENSO, the IOD, their relationship and their rainfall correlations.

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Understanding the varied response of the extratropical storm tracks to climate change

PubMed Central

O’Gorman, Paul A.

2010-01-01

Transient eddies in the extratropical storm tracks are a primary mechanism for the transport of momentum, energy, and water in the atmosphere, and as such are a major component of the climate system. Changes in the extratropical storm tracks under global warming would impact these transports, the ocean circulation and carbon cycle, and society through changing weather patterns. I show that the southern storm track intensifies in the multimodel mean of simulations of 21st century climate change, and that the seasonal cycle of storm-track intensity increases in amplitude in both hemispheres. I use observations of the present-day seasonal cycle to confirm the relationship between storm-track intensity and the mean available potential energy of the atmosphere, and show how this quantitative relationship can be used to account for much of the varied response in storm-track intensity to global warming, including substantially different responses in simulations with different climate models. The results suggest that storm-track intensity is not related in a simple way to global-mean surface temperature, so that, for example, a stronger southern storm track in response to present-day global warming does not imply it was also stronger in hothouse climates of the past. PMID:20974916

Understanding the varied response of the extratropical storm tracks to climate change.

PubMed

O'Gorman, Paul A

2010-11-09

Transient eddies in the extratropical storm tracks are a primary mechanism for the transport of momentum, energy, and water in the atmosphere, and as such are a major component of the climate system. Changes in the extratropical storm tracks under global warming would impact these transports, the ocean circulation and carbon cycle, and society through changing weather patterns. I show that the southern storm track intensifies in the multimodel mean of simulations of 21st century climate change, and that the seasonal cycle of storm-track intensity increases in amplitude in both hemispheres. I use observations of the present-day seasonal cycle to confirm the relationship between storm-track intensity and the mean available potential energy of the atmosphere, and show how this quantitative relationship can be used to account for much of the varied response in storm-track intensity to global warming, including substantially different responses in simulations with different climate models. The results suggest that storm-track intensity is not related in a simple way to global-mean surface temperature, so that, for example, a stronger southern storm track in response to present-day global warming does not imply it was also stronger in hothouse climates of the past.

Inverse relationship between present-day tropical precipitation and its sensitivity to greenhouse warming

NASA Astrophysics Data System (ADS)

Ham, Yoo-Geun; Kug, Jong-Seong; Choi, Jun-Young; Jin, Fei-Fei; Watanabe, Masahiro

2018-01-01

Future changes in rainfall have serious impacts on human adaptation to climate change, but quantification of these changes is subject to large uncertainties in climate model projections. To narrow these uncertainties, significant efforts have been made to understand the intermodel differences in future rainfall changes. Here, we show a strong inverse relationship between present-day precipitation and its future change to possibly calibrate future precipitation change by removing the present-day bias in climate models. The results of the models with less tropical (40° S-40° N) present-day precipitation are closely linked to the dryness over the equatorial central-eastern Pacific, and project weaker regional precipitation increase due to the anthropogenic greenhouse forcing1-6 with stronger zonal Walker circulation. This induces Indo-western Pacific warming through Bjerknes feedback, which reduces relative humidity by the enhanced atmospheric boundary-layer mixing in the future projection. This increases the air-sea humidity difference to enhance tropical evaporation and the resultant precipitation. Our estimation of the sensitivity of the tropical precipitation per 1 K warming, after removing a common bias in the present-day simulation, is about 50% greater than the original future multi-model projection.

Present-day dynamics and future evolution of the world's northernmost ice cap, Hans Tausen Iskappe (Greenland)

NASA Astrophysics Data System (ADS)

Zekollari, Harry; Huybrechts, Philippe; Noël, Brice; van de Berg, Willem Jan; van den Broeke, Michiel R.

2017-04-01

In this study the dynamics of Hans Tausen Iskappe (western Peary Land, Greenland) are investigated with a coupled ice flow - mass balance model. Precipitation is obtained from the Regional Climate Model RACMO 2.3 and the surface mass balance is calculated from a Positive Degree-Day runoff/retention model, for which the input parameters are derived from field observations. For the ice flow a 3-D higher-order thermo-mechanical model is used, which is run at a 250 m resolution. Under 1961-1990 climatic conditions a steady state ice cap is obtained that is overall similar in geometry to the present-day ice cap. Ice thickness, temperature and flow velocity in the interior agree well with observations. For the outlet glaciers a reasonable agreement with temperature and ice thickness measurements can only be obtained with an additional heat source related to infiltrating meltwater. The simulations indicate that the SMB-elevation feedback has a major effect on the ice cap response time and stability. This causes the southern part of the ice cap to be extremely sensitive to a change in climatic conditions and leads to thresholds in the ice cap evolution. Under constant 2005-2014 climatic conditions the entire southern part of the ice cap cannot be sustained and the ice cap loses about 80% of its present-day volume. The future projected loss of surrounding permanent sea-ice and corresponding potential sharp precipitation increase may however lead to an attenuation of the retreat and even potential stabilization of the ice cap for a warming of up to 2-3°C. In a warmer and wetter climate the ice margin will retreat while the interior is projected to grow, leading to a steeper ice cap, in line with the present-day observed trends. For intermediate (+4°C) and high warming scenarios (+8°C) the ice cap is projected to disappear respectively around 2400 and 2200 A.D., almost irrespective of the projected precipitation regime and the simulated present-day geometry.

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

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

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

Wang, Na; Makhmalbaf, Atefe; Srivastava, Viraj

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity andmore » solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.« less

Brief communication: Improved simulation of the present-day Greenland firn layer (1960-2016)

NASA Astrophysics Data System (ADS)

Ligtenberg, Stefan R. M.; Kuipers Munneke, Peter; Noël, Brice P. Y.; van den Broeke, Michiel R.

2018-05-01

By providing pore space for storage or refreezing of meltwater, the Greenland ice sheet firn layer strongly modulates runoff. Correctly representing the firn layer is therefore crucial for Greenland (surface) mass balance studies. Here, we present a simulation of the Greenland firn layer with the firn model IMAU-FDM forced by the latest output of the regional climate model RACMO2, version 2.3p2. In the percolation zone, much improved agreement is found with firn density and temperature observations. A full simulation of Greenland firn at high temporal (10 days) and spatial (11 km) resolution is available for the period 1960-2016.

Climate Response to the Increase in Tropospheric Ozone since Preindustrial Times: A Comparison between Ozone and Equivalent CO2 Forcings

NASA Technical Reports Server (NTRS)

Mickley L. J.; Jacob, D. J.; Field, B. D.; Rind, D.

2004-01-01

We examine the characteristics of the climate response to anthropogenic changes in tropospheric ozone. Using a general circulation model, we have carried out a pair of equilibrium climate simulations with realistic present-day and preindustrial ozone distributions. We find that the instantaneous radiative forcing of 0.49 W m(sup -2) due to the increase in tropospheric ozone since preindustrial times results in an increase in global mean surface temperature of 0.28 C. The increase is nearly 0.4 C in the Northern Hemisphere and about 0.2 C in the Southern Hemisphere. The largest increases (greater than 0.8 C) are downwind of Europe and Asia and over the North American interior in summer. In the lower stratosphere, global mean temperatures decrease by about 0.2 C due to the diminished upward flux of radiation at 9.6 micrometers. The largest stratospheric cooling, up to 1.0 C, occurs over high northern latitudes in winter, with possibly important implications for the formation of polar stratospheric clouds. To identify the characteristics of climate forcing unique to tropospheric ozone, we have conducted two additional climate equilibrium simulations: one in which preindustrial tropospheric ozone concentrations were increased everywhere by 18 ppb, producing the same global radiative forcing as present-day ozone but without the heterogeneity; and one in which CO2 was decreased by 25 ppm relative to present day, with ozone at present-day values, to again produce the same global radiative forcing but with the spectral signature of CO2 rather than ozone. In the first simulation (uniform increase of ozone), the global mean surface temperature increases by 0.25 C, with an interhemispheric difference of only 0.03 C, as compared with nearly 0.2 C for the heterogeneous ozone increase. In the second simulation (equivalent CO2), the global mean surface temperature increases by 0.36 C, 30% higher than the increase from tropospheric ozone. The stronger surface warming from CO2 is in part because CO2 forcing (obscured by water vapor) is shifted relatively poleward where the positive ice-albedo feedback amplifies the climate response and in part because the magnitude of the CO2 forcing in the mid-troposphere is double that of ozone. However, we find that CO2 is far less effective than tropospheric ozone in driving lower stratospheric cooling at high northern latitudes in winter.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Simulated climate change conditions unveil the toxic potential of the fungicide pyrimethanil on the midge Chironomus riparius: a multigeneration experiment

PubMed Central

Müller, Ruth; Seeland, Anne; Jagodzinski, Lucas S; Diogo, Joao B; Nowak, Carsten; Oehlmann, Jörg

2012-01-01

Although it has been suggested that temperature increase may alter the toxic potential of environmental pollutants, few studies have investigated the potential risk of chemical stressors for wildlife under Global Climate Change (GCC) impact. We applied a bifactorial multigeneration study in order to test if GCC conditions alter the effects of low pesticide concentrations on life history and genetic diversity of the aquatic model organism Chironomus riparius. Experimental populations of the species were chronically exposed to a low concentration of the fungicide pyrimethanil (half of the no-observed-adverse-effect concentration: NOAEC/2) under two dynamic present-day temperature simulations (11.0–22.7°C; 14.0–25.2°C) and one future scenario (16.5–28.1°C). During the 140-day multigeneration study, survival, emergence, reproduction, population growth, and genetic diversity of C. riparius were analyzed. Our results reveal that high temperature and pyrimethanil act synergistically on the midge C. riparius. In simulated present-day scenarios, a NOAEC/2 of pyrimethanil as derived from a life-cycle toxicity test provoked only slight-to-moderate beneficial or adverse effects on C. riparius. In contrast, exposure to a NOAEC/2 concentration of pyrimethanil at a thermal situation likely for a summer under GCC conditions uncovered adverse effects on mortality and population growth rate. In addition, genetic diversity was considerably reduced by pyrimethanil in the future scenario, but only slightly under current climatic conditions. Our multigeneration study under near-natural (climatic) conditions indicates that not only the impact of climate change, but also low concentrations of pesticides may pose a reasonable risk for aquatic insects in future. PMID:22408736

Reconciling divergent trends and millennial variations in Holocene temperatures.

PubMed

Marsicek, Jeremiah; Shuman, Bryan N; Bartlein, Patrick J; Shafer, Sarah L; Brewer, Simon

2018-01-31

Cooling during most of the past two millennia has been widely recognized and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch). However, long-term cooling has been difficult to reconcile with global forcing, and climate models consistently simulate long-term warming. The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches. Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3). CCSM3 simulates increases in 'growing degree days'-a measure of the accumulated warmth above five degrees Celsius per year-of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

The Origin of Antarctic Precipitation: A Modeling Approach

NASA Technical Reports Server (NTRS)

Delaygue, Gilles; Masson, Valerie; Jouzel, Jean; Koster, Randal D.; Healy, Richard J.

1998-01-01

Isotope concentrations in polar ice cores have long been used to estimate paleotemperatures. Underlying the use of this "isotope paleothermometer" is the assumption that the relationship between surface temperature and isotope concentration over time at a single geographical point is the same as that observed over space during the present-day climate. The validity of this assumption may in fact be compromised by several factors related to climate change. The specific factor studied in this paper involves the evaporative sources for polar precipitation. Climatic changes in the relative strengths of these sources would imply a need for a recalibration of the paleothermometer. To quantify such changes, we performed two GCM simulations, one of present-day climate and the other of the climate during the Last Glacial Maximum (LGM), roughly 18000 years ago. Evaporative sources of Antarctic precipitation were established using special tracer diagnostics. Results suggest that polar precipitation during the LGM does indeed consist of (relatively) more water from tropical oceans, a direct reflection of the LGM's increased equator-to-pole temperature gradient and its increased sea ice extent, which reduces high latitude evaporation. This result implies that an uncalibrated ice core paleothermometer would produce LGM temperatures that are biased slightly low. Because LGM boundary conditions are still under debate, we performed a third GCM simulation using a modified set of LGM boundary conditions. Using this simulation gives some qualitatively similar results, though the tropical contribution is not quite as high. Uncertainties in the LGM boundary conditions does hamper success in calibrating the paleothermometer.

Was Venus the first habitable world of our solar system?

NASA Astrophysics Data System (ADS)

Way, M. J.; Del Genio, Anthony D.; Kiang, Nancy Y.; Sohl, Linda E.; Grinspoon, David H.; Aleinov, Igor; Kelley, Maxwell; Clune, Thomas

2016-08-01

Present-day Venus is an inhospitable place with surface temperatures approaching 750 K and an atmosphere 90 times as thick as Earth's. Billions of years ago the picture may have been very different. We have created a suite of 3-D climate simulations using topographic data from the Magellan mission, solar spectral irradiance estimates for 2.9 and 0.715 Gya, present-day Venus orbital parameters, an ocean volume consistent with current theory, and an atmospheric composition estimated for early Venus. Using these parameters we find that such a world could have had moderate temperatures if Venus had a prograde rotation period slower than ~16 Earth days, despite an incident solar flux 46-70% higher than Earth receives. At its current rotation period, Venus's climate could have remained habitable until at least 0.715 Gya. These results demonstrate the role rotation and topography play in understanding the climatic history of Venus-like exoplanets discovered in the present epoch.

Was Venus the First Habitable World of our Solar System?

PubMed

Way, M J; Del Genio, Anthony D; Kiang, Nancy Y; Sohl, Linda E; Grinspoon, David H; Aleinov, Igor; Kelley, Maxwell; Clune, Thomas

2016-08-28

Present-day Venus is an inhospitable place with surface temperatures approaching 750K and an atmosphere 90 times as thick as Earth's. Billions of years ago the picture may have been very different. We have created a suite of 3-D climate simulations using topographic data from the Magellan mission, solar spectral irradiance estimates for 2.9 and 0.715 Gya, present-day Venus orbital parameters, an ocean volume consistent with current theory, and an atmospheric composition estimated for early Venus. Using these parameters we find that such a world could have had moderate temperatures if Venus had a rotation period slower than ~16 Earth days, despite an incident solar flux 46-70% higher than Earth receives. At its current rotation period, Venus's climate could have remained habitable until at least 715 million years ago. These results demonstrate the role rotation and topography play in understanding the climatic history of Venus-like exoplanets discovered in the present epoch.

Was Venus the First Habitable World of our Solar System?

PubMed Central

Way, M. J.; Del Genio, Anthony D.; Kiang, Nancy Y.; Sohl, Linda E.; Grinspoon, David H.; Aleinov, Igor; Kelley, Maxwell; Clune, Thomas

2017-01-01

Present-day Venus is an inhospitable place with surface temperatures approaching 750K and an atmosphere 90 times as thick as Earth's. Billions of years ago the picture may have been very different. We have created a suite of 3-D climate simulations using topographic data from the Magellan mission, solar spectral irradiance estimates for 2.9 and 0.715 Gya, present-day Venus orbital parameters, an ocean volume consistent with current theory, and an atmospheric composition estimated for early Venus. Using these parameters we find that such a world could have had moderate temperatures if Venus had a rotation period slower than ~16 Earth days, despite an incident solar flux 46−70% higher than Earth receives. At its current rotation period, Venus’s climate could have remained habitable until at least 715 million years ago. These results demonstrate the role rotation and topography play in understanding the climatic history of Venus-like exoplanets discovered in the present epoch. PMID:28408771

Simulating crop yield losses in Switzerland for historical and present Tambora climate scenarios

NASA Astrophysics Data System (ADS)

Flückiger, Simon; Brönnimann, Stefan; Holzkämper, Annelie; Fuhrer, Jürg; Krämer, Daniel; Pfister, Christian; Rohr, Christian

2017-07-01

Severe climatic anomalies in summer 1816, partly due to the eruption of Tambora in April 1815, contributed to delayed growth and poor harvests of important crops in Central Europe. Coinciding with adverse socio-economic conditions, this event triggered the last subsistence crisis in the western World. Here, we model reductions in potential crop yields for 1816 and 1817 and address the question, what impact a similar climatic anomaly would have today. We reconstructed daily weather for Switzerland for 1816/17 on a 2 km grid using historical observations and an analogue resampling method. These data were used to simulate potential crop yields for potato, grain maize, and winter barley using the CropSyst model calibrated for current crop cultivars. We also simulated yields for the same weather anomalies, but referenced to a present-day baseline temperature. Results show that reduced temperature delayed growth and harvest considerably, and in combination with reduced solar irradiance led to a substantial reduction (20%-50%) in the potential yield of potato in 1816. Effects on winter barley were smaller. Significant reductions were also modelled for 1817 and were mainly due to a cold late spring. Relative reductions for the present-day scenario for the two crops were almost indistinguishable from the historical ones. An even stronger response was found for maize, which was not yet common in 1816/17. Waterlogging, which we assessed using a stress-day approach, likely added to the simulated reductions. The documented, strong east-west gradient in malnutrition across Switzerland in 1817/18 could not be explained by biophysical yield limitations (though excess-water limitation might have contributed), but rather by economic, political and social factors. This highlights the importance of these factors for a societies’ ability to cope with extreme climate events. While the adaptive capacity of today’s society in Switzerland is much greater than in the early 19th century, our results emphasize the need for interdisciplinary approaches to climate change adaptation considering not only biophysical, but also social, economic and political aspects.

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 rainforest. Over a large portion of eastern Brazil, present day savanna is replaced by shrubland as the so-called caatinga vegetation of the Nordeste region spreads, and the present day caatinga vegetation is replaced by barren land. The simulated changes in vegetation are caused by changes in moisture, not temperature. Reductions in annual mean precipitation are widespread and rainfall becomes insufficient to support the rainforest in these regions, but some areas receive more precipitation. The length of the dry season increases in the central and southern Amazon in association with changes in the global-scale tropical Hadley circulation. Without this change in seasonality, local "refugia" of Amazon vegetation would be preserved and the retreat of the rainforest would be somewhat less extensive.

Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic Study

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Trnka, M.; Skalak, P.

2013-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series, interpolated, and then modified according to the GCM- or RCM-based climate change scenarios. The present contribution, in which the parametric daily weather generator M&Rfi is linked to the high-resolution RCM output (ALADIN-Climate/CZ model) and GCM-based climate change scenarios, consists of two parts: The first part focuses on a methodology. Firstly, the gridded WG representing the baseline climate is created by merging information from observations and high resolution RCM outputs. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with RCM-simulated weather series vs. spatially scarcer observations. To represent the future climate, the WG parameters are modified according to the 'WG-friendly' climate change scenarios. These scenarios are defined in terms of changes in WG parameters and include - apart from changes in the means - changes in WG parameters, which represent the additional characteristics of the weather series (e.g. probability of wet day occurrence and lag-1 autocorrelation of daily mean temperature). The WG-friendly scenarios for the present experiment are based on comparison of future vs baseline surface weather series simulated by GCMs from a CMIP3 database. The second part will present results of climate change impact study based on an above methodology applied to Central Europe. The changes in selected climatic (focusing on the extreme precipitation and temperature characteristics) and agroclimatic (including number of days during vegetation season with heat and drought stresses) characteristics will be analysed. In discussing the results, the emphasis will be put on 'added value' of various aspects of above methodology (e.g. inclusion of changes in 'advanced' WG parameters into the climate change scenarios). Acknowledgements: The present experiment is made within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), and VALUE (COST ES 1102 action).

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

NASA Astrophysics Data System (ADS)

Fuhrer, Oliver; Chadha, Tarun; Hoefler, Torsten; Kwasniewski, Grzegorz; Lapillonne, Xavier; Leutwyler, David; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph; Schulthess, Thomas C.; Vogt, Hannes

2018-05-01

The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth - the dominant bottleneck of climate codes - is being used.

Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes

USGS Publications Warehouse

Bartlein, P.J.; Edwards, M.E.; Hostetler, Steven W.; Shafer, Sarah; Anderson, P.M.; Brubaker, L. B; Lozhkin, A. V

2015-01-01

Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modeling and paleo-observations. The subcontinental region of Beringia (northeastern Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia's early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present-day simulations of regional climate – one with modern and one with 11 ka geography – plus another simulation for 6 ka. In addition, we performed five ~ 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka Control, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present-day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present-day distribution of lakes and wetlands, and (v) post-11 ka All, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season.

Projected climate change impacts on winter recreation in the ...

EPA Pesticide Factsheets

A physically-based water and energy balance model is used to simulate natural snow accumulation at 247 winter recreation locations across the continental United States. We combine this model with projections of snowmaking conditions to determine downhill skiing, cross-country skiing, and snowmobiling season lengths under baseline and future climates, using data from five climate models and two emissions scenarios. The present-day simulations from the snow model without snowmaking are validated with observations of snow-water-equivalent from snow monitoring sites. Projected season lengths are combined with baseline estimates of winter recreation activity to monetize impacts to the selected winter recreation activity categories for the years 2050 and 2090. Estimate the physical and economic impact of climate change on winter recreation in the contiguous U.S.

Simulated Extreme Prepitation Indices over Northeast Brasil in Current Climate and Future Scenarios RCP4.5 and RCP8.5

NASA Astrophysics Data System (ADS)

Wender Santiago Marinho, Marcos; Araújo Costa, Alexandre; Cassain Sales, Domingo; Oliveira Guimarães, Sullyandro; Mariano da Silva, Emerson; das Chagas Vasconcelos Júnior, Francisco

2013-04-01

In this study, we analyzed extreme precipitation indices, for present and future modeled climates over Northeast of Brazil (NEB), from CORDEX simulations over the domain of Tropical Americas. The period for the model validation was from 1989-2007, using data from the European Center (ECWMF) Reanalysis, ERA-INTERIM, as input to drive the regional model (RAMS 6.0). Reanalysis data were assimilated via both lateral boundaries and the entire domain (a much weaker "central nudging"). Six indices of extreme precipitation were calculated over NEB: the average number of days above 10, 20 and 30 mm in one year (R10, R20, R30), the number of consecutive dry days (CDD), the number of consecutive wet days (CWD) and the maximum rainfall in five consecutive days (RX5). Those indices were compared against two independent databases: MERRA (Modern Era Retrospective analysis for Research and Applications) and TRMM (Tropical Rainfall Measuring Mission). After validation, climate simulations were performed for the present climate (1985-2005) and short-term (2015-2035), mid-term (2045-2065) and long-term (2079 to 2099) future climates for two scenarios: RCP 4.5 and RCP 8.5, nesting RAMS into HadGEM2-ES global model (a participant of CMIP5). Along with the indices, we also calculated Probability Distribution Functions (PDFs) to study the behavior of daily precipitation in the present and by the end of the 21st century (2079 to 2099) to assess possible changes under RCPs 4.5 and 8.5. The regional model is capable of representing relatively well the extreme precipitation indices for current climate, but there is some difficulties in performing a proper validation since the observed databases disagree significantly. Future projections show significant changes in most extreme indices. Rnn generally tend to increase, especially under RCP8.5. More significant changes are projected for the long-term period, under RCP8.5, which shows a pronounced R30 enhancement over northern states. CDD tends to decrease over most of NEB in the short but this trend is reverted toward the end of the century in both scenarios with a significant increase in the duration of the dry season over Northwestern and Eastern NEB (exceeding 50 days over certain areas), whereas projected CWD changes are smaller. Rx5 shows a general increasing trend especially in the long term period,under RCP8.5.

Response of North American freshwater lakes to simulated future climates

USGS Publications Warehouse

Hostetler, S.W.; Small, E.E.

1999-01-01

We apply a physically based lake model to assess the response of North American lakes to future climate conditions as portrayed by the transient trace-gas simulations conducted with the Max Planck Institute (ECHAM4) and the Canadian Climate Center (CGCM1) atmosphere-ocean general circulation models (A/OGCMs). To quantify spatial patterns of lake responses (temperature, mixing, ice cover, evaporation) we ran the lake model for theoretical lakes of specified area, depth, and transparency over a uniformly spaced (50 km) grid. The simulations were conducted for two 10-year periods that represent present climatic conditions and those around the time of CO2 doubling. Although the climate model output produces simulated lake responses that differ in specific regional details, there is broad agreement with regard to the direction and area of change. In particular, lake temperatures are generally warmer in the future as a result of warmer climatic conditions and a substantial loss (> 100 days/yr) of winter ice cover. Simulated summer lake temperatures are higher than 30??C ever the Midwest and south, suggesting the potential for future disturbance of existing aquatic ecosystems. Overall increases in lake evaporation combine with disparate changes in A/OGCM precipitation to produce future changes in net moisture (precipitation minus evaporation) that are of less fidelity than those of lake temperature.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Experimental evidence for beneficial effects of projected climate change on hibernating amphibians.

PubMed

Üveges, Bálint; Mahr, Katharina; Szederkényi, Márk; Bókony, Veronika; Hoi, Herbert; Hettyey, Attila

2016-05-27

Amphibians are the most threatened vertebrates today, experiencing worldwide declines. In recent years considerable effort was invested in exposing the causes of these declines. Climate change has been identified as such a cause; however, the expectable effects of predicted milder, shorter winters on hibernation success of temperate-zone Amphibians have remained controversial, mainly due to a lack of controlled experimental studies. Here we present a laboratory experiment, testing the effects of simulated climate change on hibernating juvenile common toads (Bufo bufo). We simulated hibernation conditions by exposing toadlets to current (1.5 °C) or elevated (4.5 °C) hibernation temperatures in combination with current (91 days) or shortened (61 days) hibernation length. We found that a shorter winter and milder hibernation temperature increased survival of toads during hibernation. Furthermore, the increase in temperature and shortening of the cold period had a synergistic positive effect on body mass change during hibernation. Consequently, while climate change may pose severe challenges for amphibians of the temperate zone during their activity period, the negative effects may be dampened by shorter and milder winters experienced during hibernation.

The role of sea-ice albedo in the climate of slowly rotating aquaplanets

NASA Astrophysics Data System (ADS)

Salameh, Josiane; Popp, Max; Marotzke, Jochem

2018-04-01

We investigate the influence of the rotation period (P_{rot}) on the mean climate of an aquaplanet, with a focus on the role of sea-ice albedo. We perform aquaplanet simulations with the atmospheric general circulation model ECHAM6 for various rotation periods from one Earth-day to 365 Earth-days in which case the planet is synchronously rotating. The global-mean surface temperature decreases with increasing P_{rot} and sea ice expands equatorwards. The cooling of the mean climate with increasing P_{rot} is caused partly by the high surface albedo of sea ice on the dayside and partly by the high albedo of the deep convective clouds over the substellar region. The cooling caused by these deep convective clouds is weak for non-synchronous rotations compared to synchronous rotation. Sensitivity simulations with the sea-ice model switched off show that the global-mean surface temperature is up to 27 K higher than in our main simulations with sea ice and thus highlight the large influence of sea ice on the climate. We present the first estimates of the influence of the rotation period on the transition of an Earth-like climate to global glaciation. Our results suggest that global glaciation of planets with synchronous rotation occurs at substantially lower incoming solar irradiation than for planets with slow but non-synchronous rotation.

Particulate matter air pollution in Europe in a +2 °C warming world

NASA Astrophysics Data System (ADS)

Lacressonnière, Gwendoline; Watson, Laura; Gauss, Michael; Engardt, Magnuz; Andersson, Camilla; Beekmann, Matthias; Colette, Augustin; Foret, Gilles; Josse, Béatrice; Marécal, Virginie; Nyiri, Agnes; Siour, Guillaume; Sobolowski, Stefan; Vautard, Robert

2017-04-01

In the framework of the IMPACT2C project, we have evaluated the future European particulate matter concentrations under the influence of climate change and anthropogenic emission reductions. To do so, 30-year simulations for present and future scenarios were performed with an ensemble of four regional Chemical Transport Models. +2 °C scenarios were issued from different regional climate simulations belonging to the CORDEX experiment (RCP4.5 scenario). Comparing present day simulations to observations shows that these simulations meet the requested quality criteria even if some biases do exist. Also, we showed that using regional climate models instead of meteorological reanalysis was not critical for the quality of our simulations. Present day as well as future scenarios show the large variability between models associated with different meteorology and process parameterizations. Future projections of PM concentrations show a large reduction of PM10 and PM2.5 concentrations in a +2 °C climate over the European continent (especially over Benelux), which can be mostly attributed to emission reduction policies. Under a current legislation scenario, annual PM10 could be reduced by between 1.8 and 2.9 μg m-3 (14.1-20.4%). If maximum technologically feasible emission reductions were implemented, further reductions of 1.4-1.9 μg m-3 (18.6-20.9%) are highlighted. Changes due to a +2 °C warming, in isolation from emission changes, are in general much weaker (-1.1 to +0.4 μg m-3,-0.3 to +5.1% for annual PM10 averaged over the European domain). Even if large differences exist between models, we have determined that the decrease of PM over Europe associated with emission reduction is a robust result. The patterns of PM changes resulting from climate change (for example the increase of PM over Spain and southern France and the decrease of PM10 over eastern Europe) are also robustly predicted even if its amplitude remains weak compared to changes associated with emission reductions.

Estimation and Correction of bias of long-term simulated climate data from Global Circulation Models (GCMs)

NASA Astrophysics Data System (ADS)

Mehan, S.; Gitau, M. W.

2017-12-01

Global circulation models are often used in simulating long-term climate data for use in hydrologic studies. However, some bias (difference between simulated values and observed data) has been observed especially while simulating precipitation events. The bias is especially evident with respect to simulating dry and wet days. This is because GCMs tend to underestimate large precipitation events with the associated precipitation amounts being distributed to some dry days, thus, leading to a larger number of wet days each with some amount of rainfall. The accuracy of precipitation simulations impacts the accuracy of other simulated components such as flow and water quality. It is, thus, very important to correct the bias associated with precipitation before it is used for any modeling applications. This study aims to correct the bias specifically associated with precipitation events with a focus on the Western Lake Erie Basin (WLEB). Analytical, statistical, and extreme event analyses for three different stations (Adrian, MI; Norwalk, OH; and Fort Wayne, IN) in the WLEB were carried out to quantify the bias. Findings indicated that GCMs overestimated the wet sequences and underestimated dry day probabilities. The number of wet sequences simulated by nine GCMs each from two different open sources were 310-678 (Fort Wayne, IN); 318-600 (Adrian, MI); and 346-638 (Norwalk, OH) compared with 166, 150, and 180, respectively. Predicted conditional probabilities of a dry day followed by wet day (P (D|W)) ranged between 0.16-0.42 (Fort Wayne, IN); 0.29-0.41(Adrian, MI); and 0.13-0.40 (Norwalk, OH) from the different GCMs compared to 0.52 (Fort Wayne, IN and Norwalk, OH); and 0.54 (Adrian, MI) from the observed climate data. There was a difference of 0-8.5% between the distribution of simulated climate values and observed climate data for precipitation and temperature for all three stations (Cohen's d effective size < 0.2). Further work involves the use of Stochastic Weather Generators to correct the conditional probabilities and better capture the dry and wet events for use in the hydrologic and water resources modeling.

Modelling the mid-Pliocene Warm Period with the IPSLGCM: contribution to PlioMIP and feedback mechanisms from the presence of mega-lakes

NASA Astrophysics Data System (ADS)

Contoux, C.; Jost, A.; Sepulchre, P.; Ramstein, G.

2012-04-01

The mid-Pliocene Warm Period (mPWP, ca. 3.3 -3 Ma) is the last geological period showing a warmer climate than the preindustrial during a sustained period of time, much longer than interglacial periods of the last million years. Moreover, mPWP position of the continents and atmospheric pCO2 are very close to present-day, both conditions making the mPWP a relevant analogue for future global warming. For these reasons, the mPWP has been the focus of Pliocene Modelling Intercomparison Project (PlioMIP), which associates data analysis and modelling. We use the IPSLCM5 Earth System model and its atmospheric component alone (LMDZ), to simulate the climate of the mPWP. Boundary conditions such as sea surface temperatures (SSTs), topography, ice sheet extent and vegetation are the ones used within the PlioMIP framework. On a global scale we show the impact of different boundary conditions with LMDZ, and of a global coupling on the simulated climate. Results from the Earth System model are also compared to SST reconstructions, particularly in the North Atlantic Ocean, where an important warming occurs, generally poorly reproduced by models. These results will then be part of the multi-model analysis for the Pliocene. The PlioMIP exercise is also about better understanding model/data mismatches. In the present-day desertic regions of Lake Chad (Africa) and Lake Eyre (Australia), vegetation data show the presence of tropical savanna at the expense of deserts during the mPWP. Vegetation models forced by mPWP climatic simulations fail to reproduce more humid vegetation in these locations. There might be a reason for this model/data discrepancy: geological data stand for the presence of mega-lakes in these two regions during the mPWP that are not accounted for in previous simulations. Such extended waterbodies could have important feedbacks on the hydrological cycle and regional climate. We use the LMDZ4 atmospheric model imbedding explicitly resolved lake surfaces to simulate the climate under mega-lake conditions, using a zoom on the regions of interest. This allows us to determine the viability of such waterbodies under mid-Pliocene climatic conditions as well as their feedbacks on the climate system.

Simulating vegetation dynamics in Chile from 21ka BP to present: Effects of climate change on vegetation functions and cover

NASA Astrophysics Data System (ADS)

Werner, Christian; Liakka, Johan; Schmid, Manuel; Fuentes, Juan-Pablo; Ehlers, Todd A.; Hickler, Thomas

2017-04-01

Vegetation composition and establishment is strongly dependent on climate conditions but also a result of vegetation dynamics (competition for light, water and nutrients). In addition, vegetation exerts control over the development of landscapes as it mediates the climatic and hydrological forces shaping the terrain via hillslope and fluvial processes. At the same time, topography as well as soil texture and soil depth affect the microclimate, soil water storage and rooting space that is defining the environmental envelope for vegetation development. Within the EarthShape research program (www.earthshape.net) we evaluate these interactions by simulating the co-evolution of landscape and vegetation with a dynamic vegetation model (LPJ-GUESS) and a landscape evolution model (LandLab). LPJ-GUESS is a mechanistic model driven by daily or monthly weather data and explicitly simulates vegetation physiology, succession, competition and water and nutrient cycling. Here we present the results of first transient vegetation simulations from 21kyr BP to present-day using the TraCE-21ka climate dataset for four focus sites along the coastal cordillera of Chile that are exposed to a substantial meridional climate gradient (ranging from hyper-arid to humid-temperate conditions). We show that the warming occurring in the region from LGM to present, in addition to the increase of atmospheric CO2 concentrations, led to a shift in vegetation composition and surface cover. Future work will show how these changes resonate in the dynamics of hillslope and fluvial erosion and ultimately bi-directional feedback mechanisms of vegetation development and landscape evolution/ soil formation (see also companion presentation by Schmid et al., this session).

Stable water isotope behavior during the last glacial maximum: A general circulation model analysis

NASA Technical Reports Server (NTRS)

Jouzel, Jean; Koster, Randal D.; Suozzo, Robert J.; Russell, Gary L.

1994-01-01

Global water isotope geochemisty during the last glacial maximum (LGM) is simulated with an 8 deg x 10 deg atmospheric general circulation model (GCM). The simulation results suggest that the spatial delta O-18/temperature relationships observed for the present day and LGM climates are very similar. Furthermore, the temporal delta O-18/temperature relationship is similar to the present-day spatial relationship in regions for which the LGM/present-day temperature change is significant. This helps justify the standard practice of applying the latter to the interpretation of paleodata, despite the possible influence of other factors, such as changes in the evaportive sources of precipitation or in the seasonality of precipitation. The model suggests, for example, that temperature shifts inferred from ice core data may differ from the true shifts by only about 30%.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Global Responses to Potential Climate Change: A Simulation.

ERIC Educational Resources Information Center

Williams, Mary Louise; Mowry, George

This interdisciplinary five-day unit provides students with an understanding of the issues in the debate on global climate change. Introductory lessons enhance understanding of the "greenhouse gases" and their sources with possible global effects of climate change. Students then roleplay negotiators from 10 nations in a simulation of the…

Characteristics of Quasi-Biennial Oscillation simulation in the Meteorological Research Institute earth system model

NASA Astrophysics Data System (ADS)

Yoshida, K.; Naoe, H.

2016-12-01

Whether climate models drive Quasi-Biennial Oscillation (QBO) appropriately is important to assess QBO impact on climate change such as global warming and solar related variation. However, there were few models generating QBO in the Coupled Model Intercomparison Project Phase 5 (CMIP5). This study focuses on dynamical structure of the QBO and its sensitivity to background wind pattern and model configuration. We present preliminary results of experiments designed by "Towards Improving the QBO in Global Climate Models (QBOi)", which is derived from the Stratosphere-troposphere processes and their role in climate (SPARC), in the Meteorological Research Institute earth system model, MRI-ESM2. The simulations were performed in present-day climate condition, repeated annual cycle condition with various CO2 level and sea surface temperatures, and QBO hindcast. In the present climate simulation, zonal wind in the equatorial stratosphere generally exhibits realistic behavior of the QBO. Equatorial zonal wind variability associated with QBO is overestimated in upper stratosphere and underestimated in lower stratosphere. In the MRI-ESM2, the QBO behavior is mainly driven by gravity wave drag parametrization (GWDP) introduced in Hines (1997). Comparing to reanalyses, shortage of resolved wave forcing is found especially in equatorial lower stratosphere. These discrepancies can be attributed to difference in wave forcing, background wind pattern and model configuration. We intend to show results of additional sensitivity experiments to examine how model configuration and background wind pattern affect resolved wave source, wave propagation characteristics, and QBO behavior.

Use of CMIP3 simulations to estimate the changes of temperature indicators over France and Europe during the 21st century

NASA Astrophysics Data System (ADS)

Leboucher, V.; Couillaux, A.; Parey, S.; Fil, C.

2007-12-01

Projections of changes in temperature are essential to assess the impact of climate change on the energy supply sector as heating and cooling, energy demand highly depends on temperature. A selection of temperature indicators and their changes are examined for several simulations using SRES Emission Scenario A2 from the CMIP3 archive. We compare the present day simulated indicators to those in European Center for Medium-Range Weather Forecasts (ECMWF) ERA40 reanalysis The results are analysed for six areas over Europe and two time periods during the 21st century. We focus our study on changes in number and duration of hot and cold events and on changes in heating degree-days and cooling degree-days, which are commonly used to estimate the weather-related variations in energy consumption. Results are presented for the different models with some comparisons to the regional model simulations from the European PRUDENCE project to evaluate uncertainties.

Future Heat Waves in Paris Metropolitan Area

NASA Astrophysics Data System (ADS)

Beaulant, A.; Lemonsu, A.; Somot, S.; Masson, V.

2010-12-01

Cities are particularly vulnerable to heat waves, firstly because they concentrate the majority of the population and, secondly because the heat island that characterizes the urban climate exacerbates heat wave effects. This work is part of the interdisciplinary VURCA project (Vulnerability of cities to heat waves), which deals with the evolution of heat wave events in the context of global warming, urban vulnerability and adaptation strategies. The aim of this study is to analyse urban heat wave events in present climate (1950-2009) and their evolution in an enhanced greenhouse gazes future climate (2010-2100). We used daily observations of temperature from several stations covering Paris metropolitan area and climate projections following three different IPCC-SRES scenarios (B1, A1B, A2) and issued from several ENSEMBLES regional climate models. The heat wave definition is based on the indexes of the operational French warning system. A heat wave is detected within observed or simulated time-series by a heat wave peak, when the temperatures exceed the value of the 99.9th percentile. Its duration is determined by all adjacent days to this peak, for which the temperatures are not durably smaller than the 99.9th percentile value minus 2 °C. The 99.9th percentile threshold is inferred from quantile-quantile plots produced for each climate model in comparison with observations for the reference period 1950-2000. Heat waves have been extracted within observations and 12 climatic simulations. The number of heat wave events and cumulated HW days per year have been calculated, the maximum being seven heat waves cumulating more than 60 HW days in one year in the case of the A2 scenario and until 50 days in the case of the more moderate A1B scenario. From 2050, the occurrence of three or four HW events per year is becoming the norm all scenarios taken together. The evolution of heat wave features has been analysed, highlighting the large variability of the climatic simulations, but also an overall trend to an increase in frequency and duration but less significantly in intensity. Further work will be carried out in order to assess the sensitivity of the Paris urban climate to different future heat wave events. Synthetic HW events will be built from future HW features as duration and intensity, and will be simulated using a urban-weather model. Then, the impacts in terms of energy consumption and bioclimatic comfort will be analysed and adaptation strategies will be proposed.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

Future changes in summer mean and extreme precipitation frequency in Japan by d4PDF regional climate simulations

NASA Astrophysics Data System (ADS)

Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.

2017-12-01

Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Chemistry-Climate Interactions in the GISS GCM. Part 1; Tropospheric Chemistry Model Description and Evaluation

NASA Technical Reports Server (NTRS)

Shindell, Drew T.; Grenfell, J. Lee; Rind, David; Price, Colin; Grewe, Volker; Hansen, James E. (Technical Monitor)

2001-01-01

A tropospheric chemistry module has been developed for use within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to study interactions between chemistry and climate change. The model uses a simplified chemistry scheme based on CO-NOx-CH4 chemistry, and also includes a parameterization for emissions of isoprene, the most important non-methane hydrocarbon. The model reproduces present day annual cycles and mean distributions of key trace gases fairly well, based on extensive comparisons with available observations. Examining the simulated change between present day and pre-industrial conditions, we find that the model has a similar response to that seen in other simulations. It shows a 45% increase in the global tropospheric ozone burden, within the 25% - 57% range seen in other studies. Annual average zonal mean ozone increases by more than 125% at Northern Hemisphere middle latitudes near the surface. Comparison of model runs that allow the calculated ozone to interact with the GCM's radiation and meteorology with those that do not shows only minor differences for ozone. The common usage of ozone fields that are not calculated interactively seems to be adequate to simulate both the present day and the pre-industrial ozone distributions. However, use of coupled chemistry does alter the change in tropospheric oxidation capacity, enlarging the overall decrease in OH concentrations from the pre-industrial to the present by about 10% (-5.3% global annual average in uncoupled mode, -5.9% in coupled mode). This indicates that there may be systematic biases in the simulation of the pre-industrial to present day decrease in the oxidation capacity of the troposphere (though a 10% difference is well within the total uncertainty). Global annual average radiative forcing from pre-industrial to present day ozone change is 0.32 W/sq m. The forcing seems to be increased by about 10% when the chemistry is coupled to the GCM. Forcing values greater than 0.8 W/sq m are seen over large areas of the United States, Southern Europe, North Africa, the Middle East, Central Asia, and the Arctic. Radiative forcing is greater than 1.5 W/sq m over parts of these areas during Northern summer Though there are local differences, the radiative forcing is overall in good agreement with the results of other modeling studies in both its magnitude and spatial distribution, demonstrating that the simplified chemistry is adequate for climate studies.

Assessing Australian Rainfall Projections in Two Model Resolutions

NASA Astrophysics Data System (ADS)

Taschetto, A.; Haarsma, R. D.; Sen Gupta, A.

2016-02-01

Australian climate is projected to change with increases in greenhouse gases. The IPCC reports an increase in extreme daily rainfall across the country. At the same time, mean rainfall over southeast Australia is projected to reduce during austral winter, but to increase during austral summer, mainly associated with changes in the surrounding oceans. Climate models agree better on the future reduction of average rainfall over the southern regions of Australia compared to the increase in extreme rainfall events. One of the reasons for this disagreement may be related to climate model limitations in simulating the observed mechanisms associated with the mid-latitude weather systems, in particular due to coarse model resolutions. In this study we investigate how changes in sea surface temperature (SST) affect Australian mean and extreme rainfall under global warming, using a suite of numerical experiments at two model resolutions: about 126km (T159) and 25km (T799). The numerical experiments are performed with the earth system model EC-EARTH. Two 6-member ensembles are produced for the present day conditions and a future scenario. The present day ensemble is forced with the observed daily SST from the NOAA National Climatic Data Center from 2002 to 2006. The future scenario simulation is integrated from 2094 to 2098 using the present day SST field added onto the future SST change created from a 17-member ensemble based on the RCP4.5 scenario. Preliminary results show an increase in extreme rainfall events over Tasmania associated with enhanced convection driven by the Tasman Sea warming. We will further discuss how the projected changes in SST will impact the southern mid-latitude weather systems that ultimately affect Australian rainfall.

Reconciling divergent trends and millennial variations in Holocene temperatures

NASA Astrophysics Data System (ADS)

Marsicek, Jeremiah; Shuman, Bryan N.; Bartlein, Patrick J.; Shafer, Sarah L.; Brewer, Simon

2018-02-01

Cooling during most of the past two millennia has been widely recognized and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch). However, long-term cooling has been difficult to reconcile with global forcing, and climate models consistently simulate long-term warming. The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches. Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3). CCSM3 simulates increases in ‘growing degree days’—a measure of the accumulated warmth above five degrees Celsius per year—of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

Present-day irrigation mitigates heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; Hirsch, Annette L.; Hauser, Mathias; Seneviratne, Sonia I.

2017-02-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.

Simulated warming shifts the flowering phenology and sexual reproduction of Cardamine hirsuta under different Planting densities

PubMed Central

Cao, YuSong; Xiao, Yian; Huang, Haiqun; Xu, Jiancheng; Hu, Wenhai; Wang, Ning

2016-01-01

Climate warming can shift the reproductive phenology of plant, and hence dramatically reduced the reproductive capacity both of density-dependent and -independent plant species. But it is still unclear how climate warming affects flowering phenology and reproductive allocation of plant under different planting densities. Here, we assessed the impact of simulated warming on flowering phenology and sexual reproduction in the ephemeral herb Cardamine hirsuta under four densities. We found that simulated warming delayed the onset of flowering averagely for 3.6 days but preceded the end of flowering for about 1 day, which indicated climate warming shortened the duration of the flowering. And the flowering amplitude in the peak flowering day also dramatically increased in the simulated warming treatment, which caused a mass-flowering pattern. Climate warming significantly increased the weights of the fruits, seeds and seed, but reduced fruit length and sexual reproductive allocation under all the four densities. The duration of flowering was shortened and the weights of the fruits, seeds and seed, and sexual reproductive allocation were reduced under The highest density. PMID:27296893

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

A Coupled Regional Climate Simulator for the Gulf of St. Lawrence, Canada

NASA Astrophysics Data System (ADS)

Faucher, M.; Saucier, F.; Caya, D.

2003-12-01

The climate of Eastern Canada is characterized by atmosphere-ocean-ice interactions due to the closeness of the North Atlantic Ocean and the Labrador Sea. Also, there are three relatively large inner basins: the Gulf of St-Lawrence, the Hudson Bay / Hudson Strait / Foxe Basin system and the Great Lakes, influencing the evolution of weather systems and therefore the regional climate. These basins are characterized by irregular coastlines and variables sea-ice in winter, so that the interactions between the atmosphere and the ocean are more complex. There are coupled general circulation models (GCMs) that are available to study the climate of Eastern Canada, but their resolution (near 350km) is to low to resolve the details of the regional climate of this area and to provide valuable information for climate impact studies. The goal of this work is to develop a coupled regional climate simulator for Eastern Canada to study the climate and its variability, necessary to assess the future climate in a double CO2 situation. An off-line coupling strategy through the interacting fields is used to link the Canadian Regional Climate Model developed at the "Universite du Quebec a Montreal" (CRCM, Caya and Laprise 1999) to the Gulf of St. Lawrence ocean model developed at the "Institut Maurice-Lamontagne" (GOM, Saucier et al. 2002). This strategy involves running both simulators separately and alternatively, using variables from the other simulator to supply the needed forcing fields every day. We present the results of a first series of seasonal simulations performed with this system to show the ability of our climate simulator to reproduce the known characteristics of the regional circulation such as mesoscale oceanic features, fronts and sea-ice. The simulations were done for the period from December 1st, 1989 to March 31st, 1990. The results are compared with those of previous uncoupled runs (Faucher et al. 2003) and with observations.

South Asia river flow projections and their implications for water resources

NASA Astrophysics Data System (ADS)

Mathison, C.; Wiltshire, A. J.; Falloon, P.; Challinor, A. J.

2015-06-01

South Asia is a region with a large and rising population and a high dependance on industries sensitive to water resource such as agriculture. The climate is hugely variable with the region relying on both the Asian Summer Monsoon (ASM) and glaciers for its supply of fresh water. In recent years, changes in the ASM, fears over the rapid retreat of glaciers and the increasing demand for water resources for domestic and industrial use, have caused concern over the reliability of water resources both in the present day and future for this region. The climate of South Asia means it is one of the most irrigated agricultural regions in the world, therefore pressures on water resource affecting the availability of water for irrigation could adversely affect crop yields and therefore food production. In this paper we present the first 25 km resolution regional climate projections of river flow for the South Asia region. ERA-Interim, together with two global climate models (GCMs), which represent the present day processes, particularly the monsoon, reasonably well are downscaled using a regional climate model (RCM) for the periods; 1990-2006 for ERA-Interim and 1960-2100 for the two GCMs. The RCM river flow is routed using a river-routing model to allow analysis of present day and future river flows through comparison with river gauge observations, where available. In this analysis we compare the river flow rate for 12 gauges selected to represent the largest river basins for this region; Ganges, Indus and Brahmaputra basins and characterize the changing conditions from east to west across the Himalayan arc. Observations of precipitation and runoff in this region have large or unknown uncertainties, are short in length or are outside the simulation period, hindering model development and validation designed to improve understanding of the water cycle for this region. In the absence of robust observations for South Asia, a downscaled ERA-Interim RCM simulation provides a benchmark for comparison against the downscaled GCMs. On the basis that these simulations are among the highest resolution climate simulations available we examine how useful they are for understanding the changes in water resources for the South Asia region. In general the downscaled GCMs capture the seasonality of the river flows, with timing of maximum river flows broadly matching the available observations and the downscaled ERA-Interim simulation. Typically the RCM simulations over-estimate the maximum river flows compared to the observations probably due to a positive rainfall bias and a lack of abstraction in the model although comparison with the downscaled ERA-Interim simulation is more mixed with only a couple of the gauges showing a bias compared with the downscaled GCM runs. The simulations suggest an increasing trend in annual mean river flows for some of the river gauges in this analysis, in some cases almost doubling by the end of the century; this trend is generally masked by the large annual variability of river flows for this region. The future seasonality of river flows does not change with the future maximum river flow rates still occuring during the ASM period, with a magnitude in some cases, greater than the present day natural variability. Increases in river flow during peak flow periods means additional water resource for irrigation, the largest usage of water in this region, but also has implications in terms of inundation risk. Low flow rates also increase which is likely to be important at times of the year when water is historically more scarce. However these projected increases in resource from rivers could be more than countered by changes in demand due to reductions in the quantity and quality of water available from groundwater, increases in domestic use due to a rising population or expansion of other industries such as hydro-electric power generation.

Assessment of six dissimilarity metrics for climate analogues

NASA Astrophysics Data System (ADS)

Grenier, Patrick; Parent, Annie-Claude; Huard, David; Anctil, François; Chaumont, Diane

2013-04-01

Spatial analogue techniques consist in identifying locations whose recent-past climate is similar in some aspects to the future climate anticipated at a reference location. When identifying analogues, one key step is the quantification of the dissimilarity between two climates separated in time and space, which involves the choice of a metric. In this communication, spatial analogues and their usefulness are briefly discussed. Next, six metrics are presented (the standardized Euclidean distance, the Kolmogorov-Smirnov statistic, the nearest-neighbor distance, the Zech-Aslan energy statistic, the Friedman-Rafsky runs statistic and the Kullback-Leibler divergence), along with a set of criteria used for their assessment. The related case study involves the use of numerical simulations performed with the Canadian Regional Climate Model (CRCM-v4.2.3), from which three annual indicators (total precipitation, heating degree-days and cooling degree-days) are calculated over 30-year periods (1971-2000 and 2041-2070). Results indicate that the six metrics identify comparable analogue regions at a relatively large scale, but best analogues may differ substantially. For best analogues, it is also shown that the uncertainty stemming from the metric choice does generally not exceed that stemming from the simulation or model choice. A synthesis of the advantages and drawbacks of each metric is finally presented, in which the Zech-Aslan energy statistic stands out as the most recommended metric for analogue studies, whereas the Friedman-Rafsky runs statistic is the least recommended, based on this case study.

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.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

Tropical climate and vegetation changes during Heinrich Event 1: comparing climate model output to pollen-based vegetation reconstructions with emphasis on the region around the tropical Atlantic Ocean

NASA Astrophysics Data System (ADS)

Handiani, D.; Paul, A.; Dupont, L.

2011-06-01

Abrupt climate changes associated with Heinrich Event 1 (HE1) about 18 to 15 thousand years before present (ka BP) strongly affected climate and vegetation patterns not only in the Northern Hemisphere, but also in tropical regions in the South Atlantic Ocean. We used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era (PI), the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). The HE1-like simulation with a glacial climate background produced sea surface temperature patterns and enhanced interhemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. It allowed us to investigate the vegetation changes that result from a transition to a drier climate as predicted for northern tropical Africa due to a southward shift of the Intertropical Convergence Zone (ITCZ). We found that a cooling of the Northern Hemisphere caused a southward shift of those plant-functional types (PFTs) in Northern Tropical Africa that are indicative of an increased desertification, and a retreat of broadleaf forests in Western Africa and Northern South America. We used the PFTs generated by the model to calculate mega-biomes to allow for a direct comparison between paleodata and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well to the modern and LGM sites of the BIOME6000 (v.4.2) reconstruction, except that our present-day simulation predicted the dominance of grassland in Southern Europe and our LGM simulation simulated more forest cover in tropical and sub-tropical South America. The mega-biomes from the HE1 simulation with glacial background climate were in agreement with paleovegetation data from land and ocean proxies in West, Central, and Northern Tropical Africa as well as Northeast South America. However, our model did not agree well with predicted biome distributions in Eastern South America.

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

NASA Astrophysics Data System (ADS)

Ban, Nikolina; Schmidli, Juerg; Schär, Christoph

2015-04-01

Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that sub-daily (e.g. hourly) precipitation extremes may increase at about twice this rate (referred to as super-adiabatic scaling). Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parameterize convective precipitation (i.e. thunderstorms and rain showers). Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with environmental temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Consistent with previous results, projections reveal a significant decrease of mean summer precipitation (by 30%). However, unlike previous studies, we find that increase in both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation in 2km simulation (Ban et al. 2015). Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day super-adiabatic precipitation scaling into the future. The applicability of the Clausius-Clapeyron scaling across the whole event spectrum is a potentially useful result for climate impact adaptation. Ban, N., J. Schmidli and C. Schär (2015): Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Submitted to GRL. Ban, N., J. Schmidli and C. Schär (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Transient climate simulation from the Maunder Minimum to present day using prescribed changes in GHG, total/spectral solar irradiance and ozone

NASA Astrophysics Data System (ADS)

Spangehl, Thomas; Cubasch, Ulrich; Schimanke, Semjon

A fully coupled AO-GCM including representation of the middle atmosphere is used for tran-sient simulation of climate from 1630 to 2000 AD. For better representation of changes in the UV/visible part of the solar spectrum an improved short-wave radiation scheme is implemented. The model is driven by changes in GHG concentrations, solar activity and volcanic eruptions. Solar variability is introduced via changes in total/spectral solar irradiance (TSI/SSI) and pre-scribed changes in stratospheric ozone. The secular trend in TSI is in the range of 0.1 percent increase from Maunder Minimum to present-day. Volcanic eruptions are represented via abrupt reduction in TSI. With the applied forcings the model does not simulate a clear reduction of the annual Northern Hemisphere (NH) mean near surface temperature during Maunder Minimum. By contrast the Dalton Minimum is characterized by distinct cooling and there is a significant raise of NH mean near surface temperature until the end of the 20th century. Focusing on the North Atlantic/European region the winter mean near surface temperature change pat-tern from Late Maunder Minimum (1675-1715) to present-day (1960-1990) reveals maximum warming over north-eastern Europe and cooling over the western North Atlantic with maxi-mum cooling west of Greenland. These changes can partly be explained by a shift of the NAO towards a more positive phase. The simulated changes in tropospheric circulation are discussed with special emphasize on the role of the solar forcing. Besides the stratospheric solar forcing which may affect NAO variability via downward propagation of the solar signal from the strato-sphere to the troposphere the magnitude of the secular trend in TSI might play a role. For the period from Maunder Minimum to present-day the simulation shows less near surface temper-ature increase especially over arctic regions when compared to simulations performed with the same model including the standard radiation scheme but applying larger TSI variations. The associated changes in lower tropospheric baroclinicity are more favourable for synoptic scale wave activity over the North Atlantic and might thereby contribute to strengthening of the NAO.

Assessment of CORDEX-South Asia experiments for monsoonal precipitation over Himalayan region for future climate

NASA Astrophysics Data System (ADS)

Choudhary, A.; Dimri, A. P.

2018-04-01

Precipitation is one of the important climatic indicators in the global climate system. Probable changes in monsoonal (June, July, August and September; hereafter JJAS) mean precipitation in the Himalayan region for three different greenhouse gas emission scenarios (i.e. representative concentration pathways or RCPs) and two future time slices (near and far) are estimated from a set of regional climate simulations performed under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. For each of the CORDEX-SA simulations and their ensemble, projections of near future (2020-2049) and far future (2070-2099) precipitation climatology with respect to corresponding present climate (1970-2005) over Himalayan region are presented. The variability existing over each of the future time slices is compared with the present climate variability to determine the future changes in inter annual fluctuations of monsoonal mean precipitation. The long-term (1970-2099) trend (mm/day/year) of monsoonal mean precipitation spatially distributed as well as averaged over Himalayan region is analyzed to detect any change across twenty-first century as well as to assess model uncertainty in simulating the precipitation changes over this period. The altitudinal distribution of difference in trend of future precipitation from present climate existing over each of the time slices is also studied to understand any elevation dependency of change in precipitation pattern. Except for a part of the Hindu-Kush area in western Himalayan region which shows drier condition, the CORDEX-SA experiments project in general wetter/drier conditions in near future for western/eastern Himalayan region, a scenario which gets further intensified in far future. Although, a gradually increasing precipitation trend is seen throughout the twenty-first century in carbon intensive scenarios, the distribution of trend with elevation presents a very complex picture with lower elevations showing a greater trend in far-future under RCP8.5 when compared with higher elevations.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Influence of an Internally-Generated QBO on Modeled Stratospheric Dynamics and Ozone

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Newman, P. A.; Song, I. S.

2011-01-01

A GEOS V2 CCM simulation with an internally generated quasi-biennial oscillation (QBO) signal is compared to an otherwise identical simulation without a QBO. In a present-day climate, inclusion of the modeled QBO makes a significant difference to stratospheric dynamics and ozone throughout the year. The QBO enhances variability in the tropics, as expected, but also in the polar stratosphere in some seasons. The modeled QBO also affects the mean stratospheric climate. Because tropical zonal winds in the baseline simulation are generally easterly, there is a relative increase in zonal wind magnitudes in tropical lower and middle stratosphere in the QBO simulation. Extra-tropical differences between the QBO and 'no QBO' simulations thus reflect a bias toward the westerly phase of the QBO: a relative strengthening and poleward shifting the polar stratospheric jets, and a reduction in Arctic lower stratospheric ozone.

Climate change and marine ecosystems (Invited)

NASA Astrophysics Data System (ADS)

Chavez, F.

2013-12-01

Impacts of climate variability on marine ecosystems are pervasive. Those associated with the interannual El Ni~no phenomena are the most studied and better understood. Longer term variations associated with the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO) have become more evident as the present-day instrumental record has increased in length. The biological (chlorophyll to fish) and chemical (nutrients, oxygen, carbon) consequences of these climate-driven variations are discussed with an emphasis on the eastern and equatorial Pacific. During warmer periods biological productivity in the eastern Pacific is reduced and larger mobile organisms dramatically change their abundance and/or geographic distributions. At the same time biological productivity in the western Pacific increases highlighting that present (and future) climate-driven changes in biological productivity and chemical distributions are not (and will not) be uniform. The presentation documents present day variations using global scale information from satellites and in situ databases, model simulations and data collected by intensive local time series. Paradoxically longer term changes associated with phenomena like the Little Ice Age (LIA), captured in the sedimentary record, do not seem to follow the same warm (poor), cold (productive) patterns in the eastern Pacific, in fact these are reversed. The presentation ends with speculation regarding long term changes associated with a warmer world.

The analyses of extreme climate events over China based on CMIP5 historical and future simulations

NASA Astrophysics Data System (ADS)

Yang, S.; Dong, W.; Feng, J.; Chou, J.

2013-12-01

The extreme climate events have a serious influence on human society. Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5), Climatic extremes and their changes over china in history and future scenarios of three Representative Concentration Pathways (RCPs) are analyzed. Because of the background of global warming, in observations, the frost days (FD) and low-temperature threshold days (TN10P) have decreasing trend, and summer days (SU), high-temperature threshold days (TX90P), the heavy precipitation days (R20) and contribution of heavy precipitation days (P95T) show an increasing trend. Most coupled models can basically simulate main characteristics of most extreme indexes. The models reproduce the mean FD and TX90P value best and can give basic trends of the FD, TN10P, SU and TX90P. High correlation coefficients between simulated results and observation are found in FD, SU and P95T. For FD and SU index, most of the models have good ability to capture the spatial differences between the mean state of the 1986-2005 and 1961-1980 periods, but for other indexes, most of models' simulation ability for spatial disparity are not so satisfactory and have to be promoted. Under the high emission scenario of RCP8.5, the century-scale linear changes of Multi-Model Ensembles (MME) for FD, SU, TN10P, TX90P, R20 and P95T are -46.9, 46.0, -27.1, 175.4, 2.9 days and 9.9%, respectively. Due to the complexities of physical process parameterizations and the limitation of forcing data, a large uncertainty still exists in the simulations of climatic extremes. Fig.1 Observed and modeled multi-year average for each index (Dotted line: observation) Table1. Extreme index definition

Global Warming Impacts on Heating and Cooling Degree-Days in the United States

NASA Astrophysics Data System (ADS)

Petri, Y.; Caldeira, K.

2014-12-01

Anthropogenic climate change is expected to significantly alter residential air conditioning and space heating requirements, which account for 41% of U.S. household energy expenditures. The degree-day method can be used for reliable estimation of weather related building energy consumption and costs, as well as outdoor climatic thermal comfort. Here, we use U.S. Climate Normals developed by NOAA based on weather station observations along with Climate Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble simulations. We add the projected change in heating and cooling degree-days based on the climate models to the estimates based on the NOAA U.S. Climate Normals to project future heating and cooling degree-days. We find locations with the lowest and highest combined index of cooling (CDDs) and heating degree-days (HDDs) for the historical period (1981 - 2010) and future period (2080 - 2099) under the Representation Concentration Pathway 8.5 (RCP8.5) climate change scenario. Our results indicate that in both time frames and among the lower 48 states, coastal areas in the West and South California will have the smallest degree-day sum (CDD + HDD), and hence from a climatic perspective become the best candidates for residential real estate. The Rocky Mountains region in Wyoming, in addition to northern Minnesota and North Dakota, will have the greatest CDD + HDD. While global warming is projected to reduce the median heating and cooling demand (- 5%) at the end of the century, CDD + HDD will decrease in the North, with an opposite effect in the South. This work could be helpful in deciding where to live in the United States based on present and future thermal comfort, and could also provide a basis for estimates of changes in heating and cooling energy demand.

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

DTIC Science & Technology

2012-09-30

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

Climate in the Absence of Ocean Heat Transport

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

The energy transported by the oceans to mid- and high latitudes is small compared to the atmosphere, yet exerts an outsized influence on the climate. A key reason is the strong interaction between ocean heat transport (OHT) and sea ice extent. I quantify this by comparing a realistic control climate simulation with a slab ocean simulation in which OHT is disabled. Using the state-of-the-art CESM with a realistic present-day continental configuration, I show that the absence of OHT leads to a 23 K global cooling and massive expansion of sea ice to near 30º latitude in both hemisphere. The ice expansion is asymmetric, with greatest extent in the South Pacific and South Indian ocean basins. I discuss implications of this enormous and asymmetric climate change for atmospheric circulation, heat transport, and tropical precipitation. Parameter sensitivity studies show that the simulated climate is far more sensitive to small changes in ice surface albedo in the absence of OHT, with some perturbations sufficient to cause a runaway Snowball Earth glaciation. 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 still rather uncertain. I will also present some ideas on adapting the simple energy balance model to account for the enhanced sensitivity of sea ice to heating from the ocean.

Toward 10-km mesh global climate simulations

NASA Astrophysics Data System (ADS)

Ohfuchi, W.; Enomoto, T.; Takaya, K.; Yoshioka, M. K.

2002-12-01

An atmospheric general circulation model (AGCM) that runs very efficiently on the Earth Simulator (ES) was developed. The ES is a gigantic vector-parallel computer with the peak performance of 40 Tflops. The AGCM, named AFES (AGCM for ES), was based on the version 5.4.02 of an AGCM developed jointly by the Center for Climate System Research, the University of Tokyo and the Japanese National Institute for Environmental Sciences. The AFES was, however, totally rewritten in FORTRAN90 and MPI while the original AGCM was written in FORTRAN77 and not capable of parallel computing. The AFES achieved 26 Tflops (about 65 % of the peak performance of the ES) at resolution of T1279L96 (10-km horizontal resolution and 500-m vertical resolution in middle troposphere to lower stratosphere). Some results of 10- to 20-day global simulations will be presented. At this moment, only short-term simulations are possible due to data storage limitation. As ten tera flops computing is achieved, peta byte data storage are necessary to conduct climate-type simulations at this super-high resolution global simulations. Some possibilities for future research topics in global super-high resolution climate simulations will be discussed. Some target topics are mesoscale structures and self-organization of the Baiu-Meiyu front over Japan, cyclogenecsis over the North Pacific and typhoons around the Japan area. Also improvement in local precipitation with increasing horizontal resolution will be demonstrated.

Change in atmospheric mineral aerosols in response to climate: Last glacial period, preindustrial, modern, and doubled carbon dioxide climates

USGS Publications Warehouse

Mahowald, N.M.; Muhs, D.R.; Levis, S.; Rasch, P.J.; Yoshioka, M.; Zender, C.S.; Luo, C.

2006-01-01

Desert dust simulations generated by the National Center for Atmospheric Research's Community Climate System Model for the current climate are shown to be consistent with present day satellite and deposition data. The response of the dust cycle to last glacial maximum, preindustrial, modern, and doubled-carbon dioxide climates is analyzed. Only natural (non-land use related) dust sources are included in this simulation. Similar to some previous studies, dust production mainly responds to changes in the source areas from vegetation changes, not from winds or soil moisture changes alone. This model simulates a +92%, +33%, and -60% change in dust loading for the last glacial maximum, preindustrial, and doubled-carbon dioxide climate, respectively, when impacts of carbon dioxide fertilization on vegetation are included in the model. Terrestrial sediment records from the last glacial maximum compiled here indicate a large underestimate of deposition in continental regions, probably due to the lack of simulation of glaciogenic dust sources. In order to include the glaciogenic dust sources as a first approximation, we designate the location of these sources, and infer the size of the sources using an inversion method that best matches the available data. The inclusion of these inferred glaciogenic dust sources increases our dust flux in the last glacial maximum from 2.1 to 3.3 times current deposition. Copyright 2006 by the American Geophysical Union.

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 action).

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future warming patterns linked to today’s climate variability

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

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Stationary Waves of the Ice Age Climate.

NASA Astrophysics Data System (ADS)

Cook, Kerry H.; Held, Isaac M.

1988-08-01

A linearized, steady state, primitive equation model is used to simulate the climatological zonal asymmetries (stationary eddies) in the wind and temperature fields of the 18 000 YBP climate during winter. We compare these results with the eddies simulated in the ice age experiments of Broccoli and Manabe, who used CLIMAP boundary conditions and reduced atmospheric CO2 in an atmospheric general circulation model (GCM) coupled with a static mixed layer ocean model. The agreement between the models is good, indicating that the linear model can be used to evaluate the relative influences of orography, diabatic heating, and transient eddy heat and momentum transports in generating stationary waves. We find that orographic forcing dominates in the ice age climate. The mechanical influence of the continental ice sheets on the atmosphere is responsible for most of the changes between the present day and ice age stationary eddies. This concept of the ice age climate is complicated by the sensitivity of the stationary eddies to the large increase in the magnitude of the zonal mean meridional temperature gradient simulated in the ice age GCM.

Regional dry-season climate changes due to three decades of Amazonian deforestation

NASA Astrophysics Data System (ADS)

Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert

2017-02-01

More than 20% of the Amazon rainforest has been cleared in the past three decades, triggering important hydroclimatic changes. Small-scale (a few kilometres) deforestation in the 1980s has caused thermally triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared with the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately +/-25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing that large-scale climate variability plays a negligible role. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry-season hydroclimate. Our study illustrates the strong scale sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally to a dynamically driven hydroclimatic regime.

How shorter black carbon lifetime alters its climate effect.

PubMed

Hodnebrog, Øivind; Myhre, Gunnar; Samset, Bjørn H

2014-09-25

Black carbon (BC), unlike most aerosol types, absorbs solar radiation. However, the quantification of its climate impact is uncertain and presently under debate. Recently, attention has been drawn both to a likely underestimation of global BC emissions in climate models, and an overestimation of BC at high altitudes. Here we show that doubling present day BC emissions in a model simulation, while reducing BC lifetime based on observational evidence, leaves the direct aerosol effect of BC virtually unchanged. Increased emissions, together with increased wet removal that reduces the lifetime, yields modelled BC vertical profiles that are in strongly improved agreement with recent aircraft observations. Furthermore, we explore the consequences of an altered BC profile in a global circulation model, and show that both the vertical profile of BC and rapid climate adjustments need to be taken into account in order to assess the total climate impact of BC.

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.

Present-day irrigation mitigates heat extremes

DOE PAGES

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; ...

2017-02-16

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

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

Feldman, D.R.; Algieri, C.A.; Ong, J.R.

2011-04-01

Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

Modeling forest dynamics along climate gradients in Bolivia

NASA Astrophysics Data System (ADS)

Seiler, C.; Hutjes, R. W. A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V. K.; Melton, J. R.; Hickler, T.; Kabat, P.

2014-05-01

Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model (Lund Potsdam Jena General Ecosystem Simulator) was adapted to simulate present-day potential vegetation as a baseline for climate change impact assessments in the evergreen and deciduous forests of Bolivia. Results were compared to biomass measurements (819 plots) and remote sensing data. Using regional parameter values for allometric relations, specific leaf area, wood density, and disturbance interval, a realistic transition from the evergreen Amazon to the deciduous dry forest was simulated. This transition coincided with threshold values for precipitation (1400 mm yr-1) and water deficit (i.e., potential evapotranspiration minus precipitation) (-830 mm yr-1), beyond which leaf abscission became a competitive advantage. Significant correlations were found between modeled and observed values of seasonal leaf abscission (R2 = 0.6, p <0.001) and vegetation carbon (R2 = 0.31, p <0.01). Modeled Gross Primary Productivity (GPP) and remotely sensed normalized difference vegetation index showed that dry forests were more sensitive to rainfall anomalies than wet forests. GPP was positively correlated to the El Niño-Southern Oscillation index in the Amazon and negatively correlated to consecutive dry days. Decreasing rainfall trends were simulated to reduce GPP in the Amazon. The current model setup provides a baseline for assessing the potential impacts of climate change in the transition zone from wet to dry tropical forests in Bolivia.

Simulated effects of increased recharge on the ground-water flow system of Yucca Mountain and vicinity, Nevada-California

USGS Publications Warehouse

Czarnecki, J.B.

1984-01-01

A study was performed to assess the potential effects of changes in future climatic conditions on the groundwater system in the vicinity of Yucca Mountain, the site of a potential mined geologic repository for high-level nuclear wastes. These changes probably would result in greater rates of precipitation and, consequently, greater rates of recharge. The study was performed by simulating the groundwater system, using a two-dimensional, finite-element, groundwater flow model. The simulated position of the water table rose as much as 130 meters near the U.S. Department of Energy 's preferred repository area at Yucca Mountain for a simulation involving a 100-percent increase in precipitation compared to modern-day conditions. Despite the water table rise, no flooding of the potential repository would occur at its current proposed location. According to the simulation, springs would discharge south and west of Timber Mountain, along Fortymile Canyon, in the Amargosa Desert near Lathrop Wells and Franklin Lake playa, and near Furnace Creek Ranch in Death Valley, where they presently discharge. Simulated directions of groundwater flow paths near the potential repository area generally would be the same for the baseline (modern-day climate) and the increased-recharge simulations, but the magnitude of flow would increase by 2 to 4 times that of the baseline-simulation flow. (USGS)

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 RegCM3 (run at 10 km horizontal resolution) was developed by Giorgi et al. and it is available from the ICTP (International Centre for Theoretical Physics). Analysis of the simulated daily temperature datasets suggests that the detected regional warming is expected to continue in the 21st century. Cold temperature extremes are projected to decrease while warm extremes tend to increase significantly. Expected changes of annual precipitation indices are small, but generally consistent with the detected trends of the 20th century. Based on the simulations, extreme precipitation events are expected to become more intense and more frequent in winter, while a general decrease of extreme precipitation indices is expected in summer.

Regional Climate Variability Under Model Simulations of Solar Geoengineering

NASA Astrophysics Data System (ADS)

Dagon, Katherine; Schrag, Daniel P.

2017-11-01

Solar geoengineering has been shown in modeling studies to successfully mitigate global mean surface temperature changes from greenhouse warming. Changes in land surface hydrology are complicated by the direct effect of carbon dioxide (CO2) on vegetation, which alters the flux of water from the land surface to the atmosphere. Here we investigate changes in boreal summer climate variability under solar geoengineering using multiple ensembles of model simulations. We find that spatially uniform solar geoengineering creates a strong meridional gradient in the Northern Hemisphere temperature response, with less consistent patterns in precipitation, evapotranspiration, and soil moisture. Using regional summertime temperature and precipitation results across 31-member ensembles, we show a decrease in the frequency of heat waves and consecutive dry days under solar geoengineering relative to a high-CO2 world. However in some regions solar geoengineering of this amount does not completely reduce summer heat extremes relative to present day climate. In western Russia and Siberia, an increase in heat waves is connected to a decrease in surface soil moisture that favors persistent high temperatures. Heat waves decrease in the central United States and the Sahel, while the hydrologic response increases terrestrial water storage. Regional changes in soil moisture exhibit trends over time as the model adjusts to solar geoengineering, particularly in Siberia and the Sahel, leading to robust shifts in climate variance. These results suggest potential benefits and complications of large-scale uniform climate intervention schemes.

Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: the role of vegetation parameters

NASA Astrophysics Data System (ADS)

Berrittella, C.; van Huissteden, J.

2011-10-01

Marine Isotope Stage 3 (MIS 3) interstadials are marked by a sharp increase in the atmospheric methane (CH4) concentration, as recorded in ice cores. Wetlands are assumed to be the major source of this CH4, although several other hypotheses have been advanced. Modelling of CH4 emissions is crucial to quantify CH4 sources for past climates. Vegetation effects are generally highly generalized in modelling past and present-day CH4 fluxes, but should not be neglected. Plants strongly affect the soil-atmosphere exchange of CH4 and the net primary production of the vegetation supplies organic matter as substrate for methanogens. For modelling past CH4 fluxes from northern wetlands, assumptions on vegetation are highly relevant since paleobotanical data indicate large differences in Last Glacial (LG) wetland vegetation composition as compared to modern wetland vegetation. Besides more cold-adapted vegetation, Sphagnum mosses appear to be much less dominant during large parts of the LG than at present, which particularly affects CH4 oxidation and transport. To evaluate the effect of vegetation parameters, we used the PEATLAND-VU wetland CO2/CH4 model to simulate emissions from wetlands in continental Europe during LG and modern climates. We tested the effect of parameters influencing oxidation during plant transport (fox), vegetation net primary production (NPP, parameter symbol Pmax), plant transport rate (Vtransp), maximum rooting depth (Zroot) and root exudation rate (fex). Our model results show that modelled CH4 fluxes are sensitive to fox and Zroot in particular. The effects of Pmax, Vtransp and fex are of lesser relevance. Interactions with water table modelling are significant for Vtransp. We conducted experiments with different wetland vegetation types for Marine Isotope Stage 3 (MIS 3) stadial and interstadial climates and the present-day climate, by coupling PEATLAND-VU to high resolution climate model simulations for Europe. Experiments assuming dominance of one vegetation type (Sphagnum vs. Carex vs. Shrubs) show that Carex-dominated vegetation can increase CH4 emissions by 50% to 78% over Sphagnum-dominated vegetation depending on the modelled climate, while for shrubs this increase ranges from 42% to 72%. Consequently, during the LG northern wetlands may have had CH4 emissions similar to their present-day counterparts, despite a colder climate. Changes in dominant wetland vegetation, therefore, may drive changes in wetland CH4 fluxes, in the past as well as in the future.

Will climate change increase the risk for critical infrastructure failures in Europe due to extreme precipitation?

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Ulbrich, Uwe

2016-04-01

An event based detection algorithm for extreme precipitation is applied to a multi-model ensemble of regional climate model simulations. The algorithm determines extent, location, duration and severity of extreme precipitation events. We assume that precipitation in excess of the local present-day 10-year return value will potentially exceed the capacity of the drainage systems that protect critical infrastructure elements. This assumption is based on legislation for the design of drainage systems which is in place in many European countries. Thus, events exceeding the local 10-year return value are detected. In this study we distinguish between sub-daily events (3 hourly) with high precipitation intensities and long-duration events (1-3 days) with high precipitation amounts. The climate change simulations investigated here were conducted within the EURO-CORDEX framework and exhibit a horizontal resolution of approximately 12.5 km. The period between 1971-2100 forced with observed and scenario (RCP 8.5 and RCP 4.5) greenhouse gas concentrations was analysed. Examined are changes in event frequency, event duration and size. The simulations show an increase in the number of extreme precipitation events for the future climate period over most of the area, which is strongest in Northern Europe. Strength and statistical significance of the signal increase with increasing greenhouse gas concentrations. This work has been conducted within the EU project RAIN (Risk Analysis of Infrastructure Networks in response to extreme weather).

Future Precipitation Extremes in China Under Climate Change and Their Possible Mechanisms by Regional Climate Model and Earth System Model Simulations

NASA Astrophysics Data System (ADS)

Qin, P.; Xie, Z.

2017-12-01

Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.

Effects of land cover change on the tropical circulation in a GCM

NASA Astrophysics Data System (ADS)

Jonko, Alexandra Karolina; Hense, Andreas; Feddema, Johannes Jan

2010-09-01

Multivariate statistics are used to investigate sensitivity of the tropical atmospheric circulation to scenario-based global land cover change (LCC), with the largest changes occurring in the tropics. Three simulations performed with the fully coupled Parallel Climate Model (PCM) are compared: (1) a present day control run; (2) a simulation with present day land cover and Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 greenhouse gas (GHG) projections; and (3) a simulation with SRES A2 land cover and GHG projections. Dimensionality of PCM data is reduced by projection onto a priori specified eigenvectors, consisting of Rossby and Kelvin waves produced by a linearized, reduced gravity model of the tropical circulation. A Hotelling T 2 test is performed on projection amplitudes. Effects of LCC evaluated by this method are limited to diabatic heating. A statistically significant and recurrent signal is detected for 33% of all tests performed for various combinations of parameters. Taking into account uncertainties and limitations of the present methodology, this signal can be interpreted as a Rossby wave response to prescribed LCC. The Rossby waves are shallow, large-scale motions, trapped at the equator and most pronounced in boreal summer. Differences in mass and flow fields indicate a shift of the tropical Walker circulation patterns with an anomalous subsidence over tropical South America.

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

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

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

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

Impact of Future Emissions and Climate Change on Surface Ozone over China

NASA Astrophysics Data System (ADS)

Ma, C. T.; Westervelt, D. M.; Fiore, A. M.; Rieder, H. E.; Kinney, P.; Wang, S.; Correa, G. J. P.

2017-12-01

China's immense ambient air pollution problem and world-leading greenhouse gas emissions place it at the forefront of global efforts to address these related environmental concerns. Here, we analyze the impact of ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) future emissions scenarios representative of current legislation (CLE) and maximum technically feasible emissions reductions (MFR) on surface ozone (O3) concentrations over China in the 2030s and 2050s, in the context of a changing climate. We use a suite of simulations performed with the NOAA Geophysical Fluid Dynamics Laboratory's AM3 global chemistry-climate model. To estimate the impact of climate change in isolation on Chinese air quality, we hold emissions of air pollutants including O3 precursors fixed at 2015 levels but allow climate (global sea surface temperatures and sea ice cover) to change according to decadal averages for the years 2026-2035 and 2046-2055 from a three-member ensemble of GFDL-CM3 simulations under the RCP8.5 high warming scenario. Evaluation of the present-day simulation (2015 CLE) with observations from 1497 chiefly urban air quality monitoring stations shows that simulated surface O3 is positively biased by 26 ppb on average over the domain of China. Previous studies, however, have shown that the modeled ozone response to changes in NOx emissions over the Eastern United States mirrors the magnitude and structure of observed changes in maximum daily average 8-hour (MDA8) O3 distributions. Therefore, we use the model's simulated changes for the 2030s and 2050s to project changes in policy-relevant MDA8 O3 concentrations. We find an overall increase in MDA8 O3 for CLE scenarios in which emissions of NOx precursors are projected to increase, and under MFR scenarios, an overall decrease, with the highest changes occurring in summertime for both 2030 and 2050 MFR. Under climate change alone, the model simulates a mean summertime decrease of 1.3 ppb and wintertime increase of 3.3 ppb by 2050. Adjustment of the observed site-level MDA8 O3 distribution to reflect regionally interpolated projected changes from AM3 allows us to examine changes in the number of days in exceedance of MDA8 O3 Level I (50 ppb) and Level II (80 ppb) Chinese national ambient air quality standards.

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 Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.

Modelling the potential impacts of afforestation on extreme precipitation over West Africa

NASA Astrophysics Data System (ADS)

Odoulami, Romaric C.; Abiodun, Babatunde J.; Ajayi, Ayodele E.

2018-05-01

This study examines how afforestation in West Africa could influence extreme precipitation over the region, with a focus on widespread extreme rainfall events (WEREs) over the afforestation area. Two regional climate models (RegCM and WRF) were applied to simulate the present-day climate (1971-2000) and future climate (2031-2060, under IPCC RCP 4.5 emission scenario) with and without afforestation of the Savannah zone in West Africa. The models give a realistic simulation of precipitation indices and WEREs over the subcontinent. On average, the regional models projected future decreases in total annual wet day precipitation (PRCPTOT) and total annual daily precipitation greater than or equal to the 95th percentile of daily precipitation threshold (R95pTOT) and increases in maximum number of consecutive dry days (CDD) over Sahel. Over Savannah, the models projected decreases in PRCPTOT but increases in R95pTOT and CDD. Also, an increase in WEREs frequency is projected over west, central and east Savannah, except that RegCM simulated a decrease in WEREs over east Savannah. In general, afforestation increases PRCPTOT and R95pTOT but decreases CDD over the afforestation area. The forest-induced increases in PRCPTOT and decreases in CDD affect all ecological zones in West Africa. However, the simulations show that afforestation of Savannah also decreases R95pTOT over the Guinea Coast. It further increases WEREs over west and central Savannah and decreases them over east Savannah because of the local decrease in R95pTOT. Results of this study suggest that the future changes in characteristics of extreme precipitation events over West Africa are sensitive to the ongoing land modification.

Future local and remote influences on Mediterranean ozone air quality and climate forcing

NASA Astrophysics Data System (ADS)

Arnold, Steve; Martin, Maria Val; Emmons, Louisa; Rap, Alex; Heald, Colette; Lamarque, Jean-Francois; Tilmes, Simone

2013-04-01

The Mediterranean region is expected to display large increases in population over the coming decades, and to exhibit strong sensitivity to projected climate change, with increasing frequency of extreme summer temperatures and decreases in precipitation. Understanding of how these changes will affect atmospheric composition in the region is limited. The eastern Mediterranean basin has been shown to exhibit a pronounced summertime local maximum in tropospheric ozone, which impacts both local air quality and the atmospheric radiation balance. In summer, the region is subject to import of pollution from Northern Europe in the boundary layer and lower troposphere, from North American sources in the large-scale westerly flow of the free mid and upper-troposphere, as well as import of pollution lofted in the Asian monsoon and carried west to the eastern Mediterranean in anticyclonic flow in the upper troposphere over north Africa. In addition, interactions with the land-surface through biogenic emission sources and dry deposition play important roles in the Mediterranean ozone budget. Here we use the NCAR Community Earth System Model (CESM) to investigate how tropospheric ozone in the Mediterranean region responds to climate, land surface and global emissions changes between present day and 2050. We simulate climate and atmospheric composition for the year 2050, based on greenhouse gas abundances, trace gas and aerosol emissions and land cover and use from two representative concentration pathway (RCP) scenarios (RCP4.5 & RCP8.5), designed for use by the Coupled Model Intercomparison Project Phase 5(CMIP5) experiments in support of the IPCC. By comparing these simulations with a present-day scenario, we investigate the effects of predicted changes in climate and emissions on air quality and climate forcing over the Mediterranean region. The simulations suggest decreases in boundary layer ozone and sulfate aerosol throughout the tropospheric column over the Mediterranean under both RCP scenarios, and a significant increase in ozone between 5-10km. Using tagged regional NOy and tropospheric ozone tracers, we show that this ozone increase is coincident with an increase in easterly import of ozone and precursors in upper tropospheric outflow from Asian monsoon convection in 2050. We present a breakdown of the projected Mediterranean ozone changes by precursor source (anthropogenic and biogenic), and contributions due to changes in climate. Finally, we estimate the implications of the predicted changes in tropospheric composition for Mediterranean air quality and climate in 2050, and the consequences for the effectiveness of European policies aimed at protecting the region's climate and public health.

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

LaRow, Timothy

The SSTs used in our study come from the Community Climate System Model version 4 (CCSM4) (Gent et al 2011) and from the Canadian Centre for Climate Modeling and Analysis (CanESM2) (Chylek et al20ll) climate models from the fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al2012). We've examined the tropical cyclones using both the historical simulation that employs volcanic and aerosol forcing as well as the representative concentration pathway 4.5 (RCP4.5). In addition, we've compared the present day North Atlantic tropical cyclone metrics from a previous study (LaRow, 2013) to these climate change experiments. The experimental setup is shownmore » in Table 1. We considered the CMIP5 experiment number '3.2 historical' (Taylor et al,201l), which provides simulations of the recent past (1850-2005). The second set of CMIP5 SSTs is the RCp4.5 experiment where the radiative forcing stabilizes at 45W m-2 after 2100 (experiment number 4.1 in Taylor etal2}ll).« less

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 provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. PMID:27788208

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 some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location.

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

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

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

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.

Change in the magnitude and mechanisms of global temperature variability with warming.

PubMed

Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming

NASA Astrophysics Data System (ADS)

Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.

2017-12-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

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

Radiative and Chemical Response to Interactive Stratospheric Sulfate Aerosols in Fully Coupled CESM1(WACCM)

NASA Astrophysics Data System (ADS)

Mills, Michael J.; Richter, Jadwiga H.; Tilmes, Simone; Kravitz, Ben; MacMartin, Douglas G.; Glanville, Anne A.; Tribbia, Joseph J.; Lamarque, Jean-François; Vitt, Francis; Schmidt, Anja; Gettelman, Andrew; Hannay, Cecile; Bacmeister, Julio T.; Kinnison, Douglas E.

2017-12-01

We present new insights into the evolution and interactions of stratospheric aerosol using an updated version of the Whole Atmosphere Community Climate Model (WACCM). Improved horizontal resolution, dynamics, and chemistry now produce an internally generated quasi-biennial oscillation and significant improvements to stratospheric temperatures and ozone compared to observations. We present a validation of WACCM column ozone and climate calculations against observations. The prognostic treatment of stratospheric sulfate aerosols accurately represents the evolution of stratospheric aerosol optical depth and perturbations to solar and longwave radiation following the June 1991 eruption of Mount Pinatubo. We confirm the inclusion of interactive OH chemistry as an important factor in the formation and initial distribution of aerosol following large inputs of sulfur dioxide (SO2) to the stratosphere. We calculate that depletion of OH levels within the dense SO2 cloud in the first weeks following the Pinatubo eruption significantly prolonged the average initial e-folding decay time for SO2 oxidation to 47 days. Previous observational and model studies showing a 30 day decay time have not accounted for the large (30-55%) losses of SO2 on ash and ice within 7-9 days posteruption and have not correctly accounted for OH depletion. We examine the variability of aerosol evolution in free-running climate simulations due to meteorology, with comparison to simulations nudged with specified dynamics. We assess calculated impacts of volcanic aerosols on ozone loss with comparisons to observations. The completeness of the chemistry, dynamics, and aerosol microphysics in WACCM qualify it for studies of stratospheric sulfate aerosol geoengineering.

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.;

Climate Variability and Wildfires: Insights from Global Earth System Models

NASA Astrophysics Data System (ADS)

Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.

2016-12-01

Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in climate over long timescales.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

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

Climate and human intervention effects on future fire activity and consequences for air pollution across the 21st century

NASA Astrophysics Data System (ADS)

Val Martin, M.; Pierce, J. R.; Heald, C. L.; Li, F.; Lawrence, D. M.; Wiedinmyer, C.; Tilmes, S.; Vitt, F.

2016-12-01

Emissions of aerosols and gases from fires have been shown to adversely affect air quality across the world. Fire activity is strongly related to climate and anthropogenic activities. Current fire projections for the 21st century seem very uncertain, ranging from increasing to declining depending on the climate, land cover change and population growth scenarios used. Here we present an analysis of the changes in future wildfire activity and consequences on air quality, with focus on PM2.5 and surface O3 over regions vulnerable to fire. We use the global Community Earth System Model (CESM) with a process-based fire model to simulate emissions from agriculture, peatland, deforestation and landscape fires for present-day and throughout the current century. We consider two future Representative Concentration Pathways climate scenarios combined with population density changes predicted from Shared Socio-economic Pathways to project climate and demographic effects on fire activity and further consequences for future air quality.

Seasonal variations of soil erosion in UK under climate change: simulations with the use of high-resolution regional climatic models

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Kendon, Elizabeth; Constantine, José Antonio; Schindewolf, Marcus; Hall, Ian

2017-04-01

Climate change is expected to have a significant impact on the hydrological cycle, twenty-first century climate change simulations for Great Britain forecast an increase of surface runoff and flooding frequency. Once quality and resolution of the simulated rainfall deeply influence the results, we adopted rainfall simulations issued of a high-resolution climate model recently carried out for extended periods (13 years for present-day and future periods 2100) at 1.5 km grid scale over the south of the United Kingdom (simulations, which for the future period use the Intergovernmental Panel on Climate Change RCP 8.5 scenario, Kendon et al., 2014). We simulated soil erosion with 3D soil erosion model Schmidt (1990) on two catchments of Great Britain: the Rother catchment (350 km2) in West Sussex, England, because it has reported some of the most erosive events observed during the last 50 years in the UK, and the Conwy catchment (628 Km2) in North Wales, which is extremely resilient to soil erosion because of the abundant natural vegetation. Estimation of changes in soil moisture, saturation deficit as well as vegetation cover at daily time step have been done with the Joint UK Land Environment Simulator (JULES) (Best et al, 2011). Our results confirm the Rother catchment is the most erosive, while the Conwy catchment is the more resilient to soil erosion. Sediment production is perceived increase in both cases for the end of the century (27% and 50%, respectively). Seasonal disaggregation of the results revels that, while the most part of soil erosion is produced in winter months (DJF), the higher soil erosion variability for future periods is observed in summer (JJA). This behaviour is supported by the rainfall simulation analyse which highlighted this dual behaviour in precipitations.

Dengue burden in India: recent trends and importance of climatic parameters.

PubMed

Mutheneni, Srinivasa Rao; Morse, Andrew P; Caminade, Cyril; Upadhyayula, Suryanaryana Murty

2017-08-09

For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8-15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6-96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model.

Dengue burden in India: recent trends and importance of climatic parameters

PubMed Central

Mutheneni, Srinivasa Rao; Morse, Andrew P; Caminade, Cyril; Upadhyayula, Suryanaryana Murty

2017-01-01

For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8–15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6–96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model. PMID:28790459

Modeling sediment supply of the Congo watershed since the last 23 ka.

NASA Astrophysics Data System (ADS)

Molliex, Stéphane; Kettner, Albert J.; Laurent, Dimitri; Droz, Laurence; Marsset, Tania; Laraque, Alain; Rabineau, Marina

2017-04-01

The Congo River is the world's second river in term of drainage area (3.7 millions of km2) and water discharge (42,000 m3.s-1). Located in equatorial Africa, the basin extends over the two hemispheres, leading to an annual homogeneous repartition of climatic parameters and modest variation in intra-annual discharge. Monitored for decades, a large dataset is available for both the hydrology and sediment load for the Congo system. Moreover, the Quaternary Congo turbidite system geometry has been widely studied and an abundance of paleo-environmental parameters have been inferred from chemical proxies analyzed from offshore cores. These numerous data, both onshore and offshore, allow for accurate calibration of numeric modeling and for efficient comparison between observed and simulated data. This study aims (i) to quantify the evolution of sediment supply leaving the Congo watershed during the last 23 ka; (ii) to decipher the forcing parameters controlling the sediment supply over glacial/interglacial stages. HydroTrend is a model that simulates water discharge and sediment load leaving a hydrologic system. It is based on morphologic, climatic, hydrologic, lithologic, land cover and anthropogenic factors. After calibrating the present-day discharge and sediment load, we simulated discharge and sediment supply over 23 ka, integrating the changes in environmental conditions during this period. Results show that present-day simulations fit the observed data well if a significant part of sediments is being trapped by the catchment, in the floodplain. The long-term simulations show that the changes in climatic conditions (temperature and precipitations) between glacial and interglacial stages only account for a maximum variation of about 20 % of the sediment supply. The resulting land cover changes are most likely a more significant factor controlling the sediment supply; the loss of forest during colder and dryer stages can be responsible for up to 50 % of sediment supply increase.

Attribution of future US ozone pollution to regional emissions, climate change, long-range transport, and model deficiency

NASA Astrophysics Data System (ADS)

He, H.; Liang, X.-Z.; Lei, H.; Wuebbles, D. J.

2014-10-01

A regional chemical transport model (CTM) is used to quantify the relative contributions of future US ozone pollution from regional emissions, climate change, long-range transport (LRT) of pollutants, and model deficiency. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, the representation of present-day US ozone pollution is notably improved. This nested system projects substantial surface ozone trends for 2050's: 6-10 ppbv decreases under the "clean" A1B scenario and ~15 ppbv increases under the "dirty" A1Fi scenario. Among the total trends, regional emissions changes dominate, contributing negative 20-50% in A1B and positive 20-40% in A1Fi, while LRT effects through chemical LBCs and climate changes account for respectively 15-50% and 10-30% in both scenarios. The projection uncertainty due to model biases is region dependent, ranging from -10 to 50%. It is shown that model biases of present-day simulations can propagate into future projections systematically but nonlinearly, and the accurate specification of LBCs is essential for US ozone projections.

Current and future climate- and air pollution-mediated impacts on human health.

PubMed

Doherty, Ruth M; Heal, Mathew R; Wilkinson, Paul; Pattenden, Sam; Vieno, Massimo; Armstrong, Ben; Atkinson, Richard; Chalabi, Zaid; Kovats, Sari; Milojevic, Ai; Stevenson, David S

2009-12-21

We describe a project to quantify the burden of heat and ozone on mortality in the UK, both for the present-day and under future emission scenarios. Mortality burdens attributable to heat and ozone exposure are estimated by combination of climate-chemistry modelling and epidemiological risk assessment. Weather forecasting models (WRF) are used to simulate the driving meteorology for the EMEP4UK chemistry transport model at 5 km by 5 km horizontal resolution across the UK; the coupled WRF-EMEP4UK model is used to simulate daily surface temperature and ozone concentrations for the years 2003, 2005 and 2006, and for future emission scenarios. The outputs of these models are combined with evidence on the ozone-mortality and heat-mortality relationships derived from epidemiological analyses (time series regressions) of daily mortality in 15 UK conurbations, 1993-2003, to quantify present-day health burdens. During the August 2003 heatwave period, elevated ozone concentrations > 200 microg m-3 were measured at sites in London and elsewhere. This and other ozone photochemical episodes cause breaches of the UK air quality objective for ozone. Simulations performed with WRF-EMEP4UK reproduce the August 2003 heatwave temperatures and ozone concentrations. There remains day-to-day variability in the high ozone concentrations during the heatwave period, which on some days may be explained by ozone import from the European continent.Preliminary calculations using extended time series of spatially-resolved WRF-EMEP4UK model output suggest that in the summers (May to September) of 2003, 2005 & 2006 over 6000 deaths were attributable to ozone and around 5000 to heat in England and Wales. The regional variation in these deaths appears greater for heat-related than for ozone-related burdens.Changes in UK health burdens due to a range of future emission scenarios will be quantified. These future emissions scenarios span a range of possible futures from assuming current air quality legislation is fully implemented, to a more optimistic case with maximum feasible reductions, through to a more pessimistic case with continued strong economic growth and minimal implementation of air quality legislation. Elevated surface ozone concentrations during the 2003 heatwave period led to exceedences of the current UK air quality objective standards. A coupled climate-chemistry model is able to reproduce these temperature and ozone extremes. By combining model simulations of surface temperature and ozone with ozone-heat-mortality relationships derived from an epidemiological regression model, we estimate present-day and future health burdens across the UK. Future air quality legislation may need to consider the risk of increases in future heatwaves.

Simulation of the present-day climate with the climate model INMCM5

NASA Astrophysics Data System (ADS)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.

2017-12-01

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

NASA Astrophysics Data System (ADS)

Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

2017-12-01

Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

Evaluation of large-scale meteorological patterns associated with temperature extremes in the NARCCAP regional climate model simulations

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Lee, Huikyo; Neelin, J. David; Lintner, Benjamin R.; McGinnis, Seth; Mearns, Linda O.; Kim, Jinwon

2015-12-01

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts.

Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols:methodology and application

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

Lamarque, J. F.; Bond, Tami C.; Eyring, Veronika

2010-08-11

We present and discuss a new dataset of gridded emissions covering the historical period (1850-2000) in decadal increments at a horizontal resolution of 0.5° in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment report. Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available atmore » this point; 40 regions and 12 sectors were used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, was then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Application of these emissions into two chemistry-climate models is used to test their ability to capture long-term changes in atmospheric ozone, carbon monoxide and aerosols distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations consistently underestimate the carbon monoxide trend, while capturing the long-term trend at the Mace Head station. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates.« less

Interactive coupling of regional climate and sulfate aerosol models over eastern Asia

NASA Astrophysics Data System (ADS)

Qian, Yun; Giorgi, Filippo

1999-03-01

The NCAR regional climate model (RegCM) is interactively coupled to a simple radiatively active sulfate aerosol model over eastern Asia. Both direct and indirect aerosol effects are represented. The coupled model system is tested for two simulation periods, November 1994 and July 1995, with aerosol sources representative of present-day anthropogenic sulfur emissions. The model sensitivity to the intensity of the aerosol source is also studied. The main conclusions from our work are as follows: (1) The aerosol distribution and cycling processes show substantial regional spatial variability, and temporal variability varying on a range of scales, from the diurnal scale of boundary layer and cumulus cloud evolution to the 3-10 day scale of synoptic scale events and the interseasonal scale of general circulation features; (2) both direct and indirect aerosol forcings have regional effects on surface climate; (3) the regional climate response to the aerosol forcing is highly nonlinear, especially during the summer, due to the interactions with cloud and precipitation processes; (4) in our simulations the role of the aerosol indirect effects is dominant over that of direct effects; (5) aerosol-induced feedback processes can affect the aerosol burdens at the subregional scale. This work constitutes the first step in a long term research project aimed at coupling a hierarchy of chemistry/aerosol models to the RegCM over the eastern Asia region.

Evaluation of Boreal Summer Monsoon Intraseasonal Variability in the GASS-YOTC Multi-Model Physical Processes Experiment

NASA Astrophysics Data System (ADS)

Mani, N. J.; Waliser, D. E.; Jiang, X.

2014-12-01

While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.

Impacts of oak pollen on allergic asthma in the United States ...

EPA Pesticide Factsheets

Oak pollen season length for moderate (RCP4.5) and severe climate change scenarios (RCP8.5) are estimated through 2090 using five climate models and published relationships between temperature, precipitation, and oak pollen season length. We calculated asthma ED visit counts associated with 1994-2010 average oak pollen concentrations and simulated future oak pollen season length changes using the Environmental Benefits Mapping and Analysis Program (BenMAP-CE), driven by epidemiologically-derived concentration-response relationships. Future climate change is expected to lengthen and intensify pollen seasons in the U.S., potentially increasing incidence of allergic asthma. We developed a proof-of-concept approach for estimating asthma emergency department (ED) visits in the U.S. associated with present-day and climate-induced changes in oak pollen.

Modeling the response of precipitation oxygen stable isotopes to the Eocene climate changes over Asia

NASA Astrophysics Data System (ADS)

Botsyun, Svetlana; Sepulchre, Pierre; Donnadieu, Yannick; Risi, Camille; Caves, Jeremy K.; Licht, Alexis

2017-04-01

The Himalayas and the Tibetan Plateau have become a focus of the Earth sciences because they provide a classical example of tectonics-climate interactions. Present-day high elevations of the Himalayas and the Tibetan Plateau is the ultimate result of the collision between Indian and Asia plates during the Cenozoic, however, the precise uplift history of the Himalayas and the Tibetan Plateau is still uncertain, especially for the early Cenozoic. For the purpose of paleoelevations reconstructions, multiple methods are available, but stable oxygen paleoaltimetry is considered to be one of the most efficient techniques and has been widely applied in Asia. However, paleoelevations studies using stable oxygen presume that climatic processes control δ18O in a uniform way through time. We use climate modeling tools in order to investigate Eocene climate and δ18O over Asia and its controlling factors. The state-of-the-art general circulation model embedded with isotopes LMDz-iso has been applied together with Eocene boundary conditions and varied Eocene topography of the Himalayas and Tibet. The results of our simulations suggest that topography change has a minor direct impact on δ18O over the Himalayas and the Tibetan Plateau. On the contrary, Eocene δ18O in precipitation is primarily controlled by the atmosphere circulation and global temperature changes. Based on our numerical experiments, we show that despite persistence of large-scale atmospheric flows such as the monsoons and westerlies, Eocene δ18O over the region is different from those of the present-day due to global higher temperatures, southward shift to a zone of strong convection and increased role of westerlies moisture source. We show that the Rayleigh distillation is not applicable for the Eocene Himalayas and conclude that the assumption about the stationarity of δ18O-elevation relationship through geological time is inaccurate and misleading for paleoelevation estimates. We also show that Eocene precipitation δ18O is rather insensitive to topographic height in Asia. However, carbonate δ18O still records paleoelevation because the fractionation between calcite and water is sensitive to temperature, which depends on altitude. Comparison of simulated Eocene δ18O patterns with data from the carbonate archives suggest that the Himalayas and the Tibetan Plateau did not reach high present-day like elevations during the Eocene. Our simulations highlight the limit of standard atmospheric distillation models when they are applied to deep time.

Climate-driven coral reorganisation influences aggressive behaviour in juvenile coral-reef fishes

NASA Astrophysics Data System (ADS)

Kok, Judith E.; Graham, Nicholas A. J.; Hoogenboom, Mia O.

2016-06-01

Globally, habitat degradation is altering the abundance and diversity of species in a variety of ecosystems. This study aimed to determine how habitat degradation, in terms of changing coral composition under climate change, affected abundance, species richness and aggressive behaviour of juveniles of three damselfishes ( Pomacentrus moluccensis, P. amboinensis and Dischistodus perspicillatus, in order of decreasing reliance on coral). Patch reefs were constructed to simulate two types of reefs: present-day reefs that are vulnerable to climate-induced coral bleaching, and reefs with more bleaching-robust coral taxa, thereby simulating the likely future of coral reefs under a warming climate. Fish communities were allowed to establish naturally on the reefs during the summer recruitment period. Climate-robust reefs had lower total species richness of coral-reef fishes than climate-vulnerable reefs, but total fish abundance was not significantly different between reef types (pooled across all species and life-history stages). The nature of aggressive interactions, measured as the number of aggressive chases, varied according to coral composition; on climate-robust reefs, juveniles used the substratum less often to avoid aggression from competitors, and interspecific aggression became relatively more frequent than intraspecific aggression for juveniles of the coral-obligate P. moluccensis. This study highlights the importance of coral composition as a determinant of behaviour and diversity of coral-reef fishes.

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

PubMed Central

Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna

2016-01-01

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

PubMed

Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

2016-05-17

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.

IPSL-CM5A2. An Earth System Model designed to run long simulations for past and future climates.

NASA Astrophysics Data System (ADS)

Sepulchre, Pierre; Caubel, Arnaud; Marti, Olivier; Hourdin, Frédéric; Dufresne, Jean-Louis; Boucher, Olivier

2017-04-01

The IPSL-CM5A model was developed and released in 2013 "to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5)" [Dufresne et al., 2013]. Although this model also has been used for numerous paleoclimate studies, a major limitation was its computation time, which averaged 10 model-years / day on 32 cores of the Curie supercomputer (on TGCC computing center, France). Such performances were compatible with the experimental designs of intercomparison projects (e.g. CMIP, PMIP) but became limiting for modelling activities involving several multi-millenial experiments, which are typical for Quaternary or "deeptime" paleoclimate studies, in which a fully-equilibrated deep-ocean is mandatory. Here we present the Earth-System model IPSL-CM5A2. Based on IPSL-CM5A, technical developments have been performed both on separate components and on the coupling system in order to speed up the whole coupled model. These developments include the integration of hybrid parallelization MPI-OpenMP in LMDz atmospheric component, the use of a new input-ouput library to perform parallel asynchronous input/output by using computing cores as "IO servers", the use of a parallel coupling library between the ocean and the atmospheric components. Running on 304 cores, the model can now simulate 55 years per day, opening new gates towards multi-millenial simulations. Apart from obtaining better computing performances, one aim of setting up IPSL-CM5A2 was also to overcome the cold bias depicted in global surface air temperature (t2m) in IPSL-CM5A. We present the tuning strategy to overcome this bias as well as the main characteristics (including biases) of the pre-industrial climate simulated by IPSL-CM5A2. Lastly, we shortly present paleoclimate simulations run with this model, for the Holocene and for deeper timescales in the Cenozoic, for which the particular continental configuration was overcome by a new design of the ocean tripolar grid.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

North Pacific Westerly Jet Influence of the Winter Hawaii Rainfall in the last 21,000 years

NASA Astrophysics Data System (ADS)

Li, S.; Elison Timm, O.

2017-12-01

Hawaii rainfall has a strong seasonality which has more rainfall during the winter than summer. Part of the winter rainfall is from extratropical weather disturbances. Kona lows (KL) are important contributors to the annual rainfall budget of the Hawaiian Islands. KL activity is found to have a strong relationship with the North Pacific climate variability. The goal of the research is to test the hypothesis that changes in the strength and position of the upper level zonal wind jet is a key driver for regional rainfall changes. The main objectives are (1) to identify the relationship between North Pacific westerly jet strength and KL activity in present day climate, (2) to test the stability of this relationship under past climatic conditions, and (3) to explore the teleconnection between Hawaii and North America. For the present-day analysis of the westerly jet, the zonal wind at 250hPa is used from ERA-interim data from 1979-2014. The potential vorticity is used as a measure of extratropical synoptic activity. The Hawaii Rainfall Index is from the Rainfall Atlas of Hawaii (seasonal means, 1920-2012). For the paleoclimatic study, the transient TraCE-21ka simulation is used for the zonal wind - Hawaii rainfall analysis. The results of present-day analysis show that when the jet extends farther into the eastern Pacific sector the Kona Low activity is reduced, less winter rainfall is observed over Hawaii and more rainfall over the California region. The jet position-rainfall relationship was investigated within the TrACE-21 simulation. For the TraCE-21ka dataset, there is an increasing rainfall trend from 21kBP to 14kBP; this period coincides with a gradual decrease in the strength of the westerly wind jet. The results show that the westerly jet strength has a strong influence of the Kona Low activity and the rainfall over Hawaii both in the present and the past.

Simulating the effects of climate and agricultural management practices on global crop yield

NASA Astrophysics Data System (ADS)

Deryng, D.; Sacks, W. J.; Barford, C. C.; Ramankutty, N.

2011-06-01

Climate change is expected to significantly impact global food production, and it is important to understand the potential geographic distribution of yield losses and the means to alleviate them. This study presents a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) that integrates, in addition to climate, the effect of planting dates and cultivar choices, irrigation, and fertilizer application on crop yield for maize, soybean, and spring wheat. PEGASUS combines carbon dynamics for crops with a surface energy and soil water balance model. It also benefits from the recent development of a suite of global data sets and analyses that serve as model inputs or as calibration data. These include data on crop planting and harvesting dates, crop-specific irrigated areas, a global analysis of yield gaps, and harvested area and yield of major crops. Model results for present-day climate and farm management compare reasonably well with global data. Simulated planting and harvesting dates are within the range of crop calendar observations in more than 75% of the total crop-harvested areas. Correlation of simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop-harvested area, of 0.81 for maize, 0.66 for soybean, and 0.45 for spring wheat. We found that changes in temperature and precipitation as predicted by global climate models for the 2050s lead to a global yield reduction if planting and harvesting dates remain unchanged. However, adapting planting dates and cultivar choices increases yield in temperate regions and avoids 7-18% of global losses.

Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

NASA Technical Reports Server (NTRS)

Doherty, R. M.; Wild, O.; Shindell, D. T.; Zeng, G.; MacKenzie, I. A.; Collins, W. J.; Fiore, A. M.; Stevenson, D. S.; Dentener, F. J.; Schultz, M. G.;

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Changes of climate regimes during the last millennium and the twenty-first century simulated by the Community Earth System Model

NASA Astrophysics Data System (ADS)

Huang, Wei; Feng, Song; Liu, Chang; Chen, Jie; Chen, Jianhui; Chen, Fahu

2018-01-01

This study examines the shifts in terrestrial climate regimes using the Köppen-Trewartha (K-T) climate classification by analyzing the Community Earth System Model Last Millennium Ensemble (CESM-LME) simulations for the period 850-2005 and CESM Medium Ensemble (CESM-ME), CESM Large Ensemble (CESM-LE) and CESM with fixed aerosols Medium Ensemble (CESM-LE_FixA) simulations for the period 1920-2080. We compare K-T climate types from the Medieval Climate Anomaly (MCA) (950-1250) with the Little Ice Age (LIA) (1550-1850), from present day (PD) (1971-2000) with the last millennium (LM) (850-1850), and from the future (2050-2080) with the LM in order to place anthropogenic changes in the context of changes due to natural forcings occurring during the last millennium. For CESM-LME, we focused on the simulations with all forcings, though the impacts of individual forcings (e.g., solar activities, volcanic eruptions, greenhouse gases, aerosols and land use changes) were also analyzed. We found that the climate types changed slightly between the MCA and the LIA due to weak changes in temperature and precipitation. The climate type changes in PD relative to the last millennium have been largely driven by greenhouse gas-induced warming, but anthropogenic aerosols have also played an important role on regional scales. At the end of the twenty-first century, the anthropogenic forcing has a much greater effect on climate types than the PD. Following the reduction of aerosol emissions, the impact of greenhouse gases will further promote global warming in the future. Compared to precipitation, changes in climate types are dominated by greenhouse gas-induced warming. The large shift in climate types by the end of this century suggests possible wide-spread redistribution of surface vegetation and a significant change in species distributions.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models

NASA Astrophysics Data System (ADS)

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

Simulating phenological shifts in French temperate forests under two climatic change scenarios and four driving global circulation models.

PubMed

Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin

2010-09-01

After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.

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 by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Analysing regional climate change in Africa in a 1.5 °C global warming world

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-04-01

At the 21st session of the UNFCCC Conference of the Parties (COP21) in Paris, a reaffirmation to strengthen the effort to limit the global temperature increase to 1.5 °C was decided. However, even if global warming is limited, some regions might still be substantially affected by climate change, especially for continents like Africa where the socio-economic conditions are strongly linked to the climatic conditions. Hence, providing a detailed analysis of the projected climate changes in a 1.5 °C global warming scenario will allow the African society to undertake measures for adaptation in order to mitigate potential negative consequences. In order to provide such climate change information, the existing CORDEX Africa ensemble for RCP2.6 scenario simulations has systematically been increased by conducting additional REMO simulations using data from various global circulation models (GCMs) as lateral boundary conditions. Based on this ensemble, which now consists of eleven CORDEX Africa RCP2.6 regional climate model simulations from three RCMs (forced with different GCMs), various temperature and precipitation indices such as number of cold/hot days and nights, duration of the rainy season, the amount of rainfall in the rainy seasons and the number of dry spells have been calculated for a 1.5 °C global warming scenario. The applied method to define the 1.5 °C global warming period has been already applied in the IMPACT2C project. In our presentation, we will discuss the analysis of the climate indices in a 1.5 °C global warming world for the CORDEX-Africa region. Amongst presenting the magnitude of projected changes, we will also address the question for selected indices if the changes projected in a 1.5 °C global warming scenario are already larger than the climate variability and we will also draw links to the changes projected under a more extreme scenario.

Biological responses to environmental heterogeneity under future ocean conditions.

PubMed

Boyd, Philip W; Cornwall, Christopher E; Davison, Andrew; Doney, Scott C; Fourquez, Marion; Hurd, Catriona L; Lima, Ivan D; McMinn, Andrew

2016-08-01

Organisms are projected to face unprecedented rates of change in future ocean conditions due to anthropogenic climate-change. At present, marine life encounters a wide range of environmental heterogeneity from natural fluctuations to mean climate change. Manipulation studies suggest that biota from more variable marine environments have more phenotypic plasticity to tolerate environmental heterogeneity. Here, we consider current strategies employed by a range of representative organisms across various habitats - from short-lived phytoplankton to long-lived corals - in response to environmental heterogeneity. We then discuss how, if and when organismal responses (acclimate/migrate/adapt) may be altered by shifts in the magnitude of the mean climate-change signal relative to that for natural fluctuations projected for coming decades. The findings from both novel climate-change modelling simulations and prior biological manipulation studies, in which natural fluctuations are superimposed on those of mean change, provide valuable insights into organismal responses to environmental heterogeneity. Manipulations reveal that different experimental outcomes are evident between climate-change treatments which include natural fluctuations vs. those which do not. Modelling simulations project that the magnitude of climate variability, along with mean climate change, will increase in coming decades, and hence environmental heterogeneity will increase, illustrating the need for more realistic biological manipulation experiments that include natural fluctuations. However, simulations also strongly suggest that the timescales over which the mean climate-change signature will become dominant, relative to natural fluctuations, will vary for individual properties, being most rapid for CO2 (~10 years from present day) to 4 decades for nutrients. We conclude that the strategies used by biota to respond to shifts in environmental heterogeneity may be complex, as they will have to physiologically straddle wide-ranging timescales in the alteration of ocean conditions, including the need to adapt to rapidly rising CO2 and also acclimate to environmental heterogeneity in more slowly changing properties such as warming. © 2016 John Wiley & Sons Ltd.

Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.

2012-09-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon cycle range. These high end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real world climate sensitivity constraints which, if achieved, would lead to reductions on the uppper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present day observables and future changes while the large spread of future projected changes, highlights the ongoing need for such work.

What can we learn about the dynamics of DO-events from studying the high resolution ice core records?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2017-04-01

The causes for and possible predictions of rapid climate changes are poorly understood. The most pronounced changes observed, beside the glacial terminations, are the Dansgaard-Oeschger events. Present day general circulation climate models simulating glacial conditions are not capable of reproducing these rapid shifts. It is thus not known if they are due to bifurcations in the structural stability of the climate or if they are induced by stochastic fluctuations. By analyzing a high resolution ice core record we exclude the bifurcation scenario, which strongly suggests that they are noise induced and thus have very limited predictability. Ref: Peter Ditlevsen, "Tipping points in the climate system", in Nonlinear and Stochastic Climate Dynamics, Cambridge University Press (C. Franzke and T. O'Kane, eds.) (2016) P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, L19703, 2010

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

NASA Astrophysics Data System (ADS)

Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat

2017-11-01

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

Potential groundwater contribution to Amazon evapotranspiration

NASA Astrophysics Data System (ADS)

Fan, Y.; Miguez-Macho, G.

2010-07-01

Climate and land ecosystem models simulate a dry-season vegetation stress in the Amazon forest, but observations show enhanced growth in response to higher radiation under less cloudy skies, indicating an adequate water supply. Proposed mechanisms include larger soil water store and deeper roots in nature and the ability of roots to move water up and down (hydraulic redistribution). Here we assess the importance of the upward soil water flux from the groundwater driven by capillarity. We present a map of water table depth from observations and groundwater modeling, and a map of potential capillary flux these water table depths can sustain. The maps show that the water table beneath the Amazon can be quite shallow in lowlands and river valleys (<5 m in 36% and <10 m in 60% of Amazonia). The water table can potentially sustain a capillary flux of >2.1 mm day-1 to the land surface averaged over Amazonia, but varies from 0.6 to 3.7 mm day-1 across nine study sites. Current models simulate a large-scale reduction in dry-season photosynthesis under today's climate and a possible dieback under projected future climate with a longer dry season, converting the Amazon from a net carbon sink to a source and accelerating warming. The inclusion of groundwater and capillary flux may modify the model results.

Supporting observation campaigns with high resolution modeling

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Voigt, Aiko

2017-04-01

High resolution simulation in support of measurement campaigns offers a promising and emerging way to create large-scale context for small-scale observations of clouds and precipitation processes. As these simulation include the coupling of measured small-scale processes with the circulation, they also help to integrate the research communities from modeling and observations and allow for detailed model evaluations against dedicated observations. In connection with the measurement campaign NARVAL (August 2016 and December 2013) simulations with a grid-spacing of 2.5 km for the tropical Atlantic region (9000x3300 km), with local refinement to 1.2 km for the western part of the domain, were performed using the icosahedral non-hydrostatic (ICON) general circulation model. These simulations are again used to drive large eddy resolving simulations with the same model for selected days in the high definition clouds and precipitation for advancing climate prediction (HD(CP)2) project. The simulations are presented with the focus on selected results showing the benefit for the scientific communities doing atmospheric measurements and numerical modeling of climate and weather. Additionally, an outlook will be given on how similar simulations will support the NAWDEX measurement campaign in the North Atlantic and AC3 measurement campaign in the Arctic.

Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation

NASA Technical Reports Server (NTRS)

Mickley, L. J.; Leibensperger, E. M.; Jacob, D. J.; Rind, D.

2012-01-01

We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences.

The effects of climate change on storm surges around the United Kingdom.

PubMed

Lowe, J A; Gregory, J M

2005-06-15

Coastal flooding is often caused by extreme events, such as storm surges. In this study, improved physical models have been used to simulate the climate system and storm surges, and to predict the effect of increased atmospheric concentrations of greenhouse gases on the surges. In agreement with previous studies, this work indicates that the changes in atmospheric storminess and the higher time-average sea-level predicted for the end of the twenty-first century will lead to changes in the height of water levels measured relative to the present day tide. However, the details of these projections differ somewhat from earlier assessments. Uncertainty in projections of future extreme water levels arise from uncertainty in the amount and timing of future greenhouse gas emissions, uncertainty in the physical models used to simulate the climate system and from the natural variability of the system. The total uncertainty has not yet been reliably quantified and achieving this should be a priority for future research.

Effects of City Expansion on Heat Stress under Climate Change Conditions

PubMed Central

Argüeso, Daniel; Evans, Jason P.; Pitman, Andrew J.; Di Luca, Alejandro

2015-01-01

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990–2009) and future (2040–2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort. PMID:25668390

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

Modelling the interactions between vegetation and climate from the Cretaceous to the Eocene

NASA Astrophysics Data System (ADS)

Loptson, Claire; Lunt, Dan; Francis, Jane

2013-04-01

The climates during the Cretaceous (~144 to 66 Ma) and the early Eocene (~56 to 48 Ma) were much warmer than the present day. Atmospheric CO2 levels for these past climates have a large uncertainty associated with them, but were possibly as high as 2000 to 3000 ppm for the early Eocene (Beerling and Royer, 2011; Lowenstein and Demicco, 2006) and maximum values are thought to range from 800 to 1800 ppm during the Cretaceous (Royer et al., 2012). Current modelling efforts have had great difficulty in replicating the shallow latitudinal temperature gradient indicated by proxy data for these time periods (e.g. Heinemann et al., 2009; Winguth et al., 2010; Shellito et al., 2009). Mechanisms that can result in such a low temperature gradient have not been found (Winguth et al., 2010; Beerling et al., 2011; Sloan and Morrill, 1998), but a contributing factor could be that not all climate feedbacks are included in these models. Vegetation feedbacks have been shown to be especially important (e.g. Otto-Bliesner and Upchurch, 1997; Bonan, 2008) so by including a more accurate representation of vegetation in the climate model, the model-data discrepancies may be reduced. A fully coupled atmosphere-ocean GCM, HadCM3L, coupled to a dynamic global vegetation model (TRIFFID), was used to simulate the climate and the predicted vegetation distributions for and the early Eocene and 12 different time slices representing different ages throughout the Cretaceous at 4x pre-industrial CO2. The only difference in the way these simulations were set up are different boundary conditions that are specific to that time period, e.g. different solar constants and paleogeographies. This allows a direct comparison between the time slices. We present the changes in climate, and therefore vegetation, during the Cretaceous due to changes in these boundary conditions alone, with a focus on Antarctica. Additional Eocene simulations were also carried out with a) fixed globally-uniform vegetation and b) a prescribed vegetation distribution as predicted by the TRIFFID model, but with TRIFFID turned off i.e. the vegetation distribution was fixed, not dynamic. All three Eocene simulations were also run for 2x pre-industrial CO2, allowing the effects of changing CO2 on climate and vegetation to be analysed. We present the effects of different vegetation representations included in a GCM on the early Eocene climate. In addition, climate sensitivity and sensitivity of vegetation to atmospheric CO2 concentration during the early Eocene are investigated. Modelled vegetation types are compared to fossil data to evaluate the performance of TRIFFID for these paleoclimate simulations.

Change in the magnitude and mechanisms of global temperature variability with warming

PubMed Central

Brown, Patrick T.; Ming, Yi; Li, Wenhong; Hill, Spencer A.

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future. PMID:29391875

The Role of Atmospheric Pressure on Surface Thermal Inertia for Early Mars Climate Modeling

NASA Astrophysics Data System (ADS)

Mischna, M.; Piqueux, S.

2017-12-01

On rocky bodies such as Mars, diurnal surface temperatures are controlled by the surface thermal inertia, which is a measure of the ability of the surface to store heat during the day and re-radiate it at night. Thermal inertia is a compound function of the near-surface regolith thermal conductivity, density and specific heat, with the regolith thermal conductivity being strongly controlled by the atmospheric pressure. For Mars, current best maps of global thermal inertia are derived from the Thermal Emission Spectrometer (TES) instrument on the Mars Global Surveyor (MGS) spacecraft using bolometric brightness temperatures of the surface. Thermal inertia is widely used in the atmospheric modeling community to determine surface temperatures and to establish lower boundary conditions for the atmosphere. Infrared radiation emitted from the surface is key in regulating lower atmospheric temperatures and driving overall global circulation. An accurate map of surface thermal inertia is thus required to produce reasonable results of the present-day atmosphere using numerical Mars climate models. Not surprisingly, thermal inertia is also a necessary input into climate models of early Mars, which assume a thicker atmosphere, by as much as one to two orders of magnitude above the present-day 6 mb mean value. Early Mars climate models broadly, but incorrectly, assume the present day thermal inertia surface distribution. Here, we demonstrate that, on early Mars, when pressures were larger than today's, the surface layer thermal inertia was globally higher because of the increased thermal conductivity driven by the higher gas pressure in interstitial pore spaces within the soil. Larger thermal inertia reduces the diurnal range of surface temperature and will affect the size and timing of the modeled seasonal polar ice caps. Additionally, it will globally alter the frequency of when surface temperatures are modeled to exceed the liquid water melting point, and so results may need to be reassessed in light of lower `peak' global temperatures. We shall demonstrate the consequences of using properly calibrated thermal inertia maps for early Mars climate simulations, and propose simplified thermal inertia maps for use in such climate models.

Impacts of global warming on residential heating and cooling degree-days in the United States

PubMed Central

Petri, Yana; Caldeira, Ken

2015-01-01

Climate change is expected to decrease heating demand and increase cooling demand for buildings and affect outdoor thermal comfort. Here, we project changes in residential heating degree-days (HDD) and cooling degree-days (CDD) for the historical (1981–2010) and future (2080–2099) periods in the United States using median results from the Climate Model Intercomparison Project phase 5 (CMIP5) simulations under the Representation Concentration Pathway 8.5 (RCP8.5) scenario. We project future HDD and CDD values by adding CMIP5 projected changes to values based on historical observations of US climate. The sum HDD + CDD is an indicator of locations that are thermally comfortable, with low heating and cooling demand. By the end of the century, station median HDD + CDD will be reduced in the contiguous US, decreasing in the North and increasing in the South. Under the unmitigated RCP8.5 scenario, by the end of this century, in terms of HDD and CDD values considered separately, future New York, NY, is anticipated to become more like present Oklahoma City, OK; Denver, CO, becomes more like Raleigh, NC, and Seattle, WA, becomes more like San Jose, CA. These results serve as an indicator of projected climate change and can help inform decision-making. PMID:26238673

Impacts of global warming on residential heating and cooling degree-days in the United States.

PubMed

Petri, Yana; Caldeira, Ken

2015-08-04

Climate change is expected to decrease heating demand and increase cooling demand for buildings and affect outdoor thermal comfort. Here, we project changes in residential heating degree-days (HDD) and cooling degree-days (CDD) for the historical (1981-2010) and future (2080-2099) periods in the United States using median results from the Climate Model Intercomparison Project phase 5 (CMIP5) simulations under the Representation Concentration Pathway 8.5 (RCP8.5) scenario. We project future HDD and CDD values by adding CMIP5 projected changes to values based on historical observations of US climate. The sum HDD + CDD is an indicator of locations that are thermally comfortable, with low heating and cooling demand. By the end of the century, station median HDD + CDD will be reduced in the contiguous US, decreasing in the North and increasing in the South. Under the unmitigated RCP8.5 scenario, by the end of this century, in terms of HDD and CDD values considered separately, future New York, NY, is anticipated to become more like present Oklahoma City, OK; Denver, CO, becomes more like Raleigh, NC, and Seattle, WA, becomes more like San Jose, CA. These results serve as an indicator of projected climate change and can help inform decision-making.

Modelled non-linear response to climate of Hardangerjøkulen ice cap, southern Norway, since the mid-Holocene

NASA Astrophysics Data System (ADS)

Åkesson, Henning; Nisancioglu, Kerim H.; Giesen, Rianne H.; Morlighem, Mathieu

2016-04-01

Glacier and ice cap volume changes currently amount to half of the total cryospheric contribution to sea-level rise and are projected to remain substantial throughout the 21st century. To simulate glacier behavior on centennial and longer time scales, models rely on simplified dynamics and tunable parameters for processes not well understood. Model calibration is often done using present-day observations, even though the relationship between parameters and parametrized processes may be altered for significantly different glacier states. In this study, we simulate the Hardangerjøkulen ice cap in southern Norway since the mid-Holocene, through the Little Ice Age (LIA) and into the future. We run an ensemble for both calibration and transient experiments, using a two-dimensional ice flow model with mesh refinement. For the Holocene, we apply a simple mass balance forcing based on climate reconstructions. For the LIA until 1962, we use geomorphological evidence and measured outlet glacier positions to find a mass balance history, while we use direct mass balance measurements from 1963 until today. Given a linear climate forcing, we show that Hardangerøkulen grew from ice-free conditions in the mid-Holocene, to its maximum LIA extent in a highly non-linear fashion. We relate this to local bed topography and demonstrate that volume and area of some but not all outlet glaciers, as well as the entire ice cap, become decoupled for several centuries during our simulation of the late Holocene, before co-varying approaching the LIA. Our model is able to simulate most recorded ice cap and outlet glacier changes from the LIA until today. We show that present-day Hardangerøkulen is highly sensitive to mass balance changes, and estimate that the ice cap will melt completely by the year 2100.

An investigation of the Archean climate using the NCAR CCm

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

Jenkins, G.S.

1991-01-01

The Archean (2.5 to 3.8 billion years ago) is of interest climatically, because of the 'Faint-Young Sun Paradox', which can be characterized by the Sun's reduced energy output. This lower energy output leads to a frozen planet if the climate existed as it does today. But, the geologic record shows that water was flowing at the earth's surface 3.8 billion years ago. Energy Balance Models (EBMs) and one-dimensional radiative-convective (1DRC) models predict a frozen planet for this time period, unless large carbon dioxide (CO2) concentrations exist in the Archean atmosphere. The goal is to explore the Archean climate with themore » National Center for Atmospheric Research (NCAR), Community Climate Model (CCM). The search for negative feedbacks to explain the 'Faint-Young Sun Paradox' is the thrust of this study. This study undertakes a series of sensitivity simulations which first explores individual factors that may be important for the Archean. They include rotation rate, lower solar luminosity, and land fraction. Then, these climatic factors along with higher CO2 concentrations are combined into a set of experiments. A faster rotation rate may have existed in the Archean. The faster rotation rate simulations show warmer globally averaged surface temperatures that are caused by a 20 percent decrease in the total cloud fraction. The smaller cloud fraction is brought about by dynamical changes. A global ocean is a possibility for the Archean. A global ocean simulation predicts 4 K increase in global mean surface temperatures compared to the present-day climate control.« less

A Regional Climate Model Evaluation System based on Satellite and other Observations

NASA Astrophysics Data System (ADS)

Lean, P.; Kim, J.; Waliser, D. E.; Hall, A. D.; Mattmann, C. A.; Granger, S. L.; Case, K.; Goodale, C.; Hart, A.; Zimdars, P.; Guan, B.; Molotch, N. P.; Kaki, S.

2010-12-01

Regional climate models are a fundamental tool needed for downscaling global climate simulations and projections, such as those contributing to the Coupled Model Intercomparison Projects (CMIPs) that form the basis of the IPCC Assessment Reports. The regional modeling process provides the means to accommodate higher resolution and a greater complexity of Earth System processes. Evaluation of both the global and regional climate models against observations is essential to identify model weaknesses and to direct future model development efforts focused on reducing the uncertainty associated with climate projections. However, the lack of reliable observational data and the lack of formal tools are among the serious limitations to addressing these objectives. Recent satellite observations are particularly useful as they provide a wealth of information on many different aspects of the climate system, but due to their large volume and the difficulties associated with accessing and using the data, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL / UCLA is developing a model evaluation system to help make satellite observations, in conjunction with in-situ, assimilated, and reanalysis datasets, more readily accessible to the modeling community. The system includes a central database to store multiple datasets in a common format and codes for calculating predefined statistical metrics to assess model performance. This allows the time taken to compare model simulations with satellite observations to be reduced from weeks to days. Early results from the use this new model evaluation system for evaluating regional climate simulations over California/western US regions will be presented.

Role of clouds, aerosols, and aerosol-cloud interaction in 20th century simulations with GISS ModelE2

NASA Astrophysics Data System (ADS)

Nazarenko, L.; Rind, D. H.; Bauer, S.; Del Genio, A. D.

2015-12-01

Simulations of aerosols, clouds and their interaction contribute to the major source of uncertainty in predicting the changing Earth's energy and in estimating future climate. Anthropogenic contribution of aerosols affects the properties of clouds through aerosol indirect effects. Three different versions of NASA GISS global climate model are presented for simulation of the twentieth century climate change. All versions have fully interactive tracers of aerosols and chemistry in both the troposphere and stratosphere. All chemical species are simulated prognostically consistent with atmospheric physics in the model and the emissions of short-lived precursors [Shindell et al., 2006]. One version does not include the aerosol indirect effect on clouds. The other two versions include a parameterization of the interactive first indirect aerosol effect on clouds following Menon et al. [2010]. One of these two models has the Multiconfiguration Aerosol Tracker of Mixing state (MATRIX) that permits detailed treatment of aerosol mixing state, size, and aerosol-cloud activation. The main purpose of this study is evaluation of aerosol-clouds interactions and feedbacks, as well as cloud and aerosol radiative forcings, for the twentieth century climate under different assumptions and parameterizations for aerosol, clouds and their interactions in the climate models. The change of global surface air temperature based on linear trend ranges from +0.8°C to +1.2°C between 1850 and 2012. Water cloud optical thickness increases with increasing temperature in all versions with the largest increase in models with interactive indirect effect of aerosols on clouds, which leads to the total (shortwave and longwave) cloud radiative cooling trend at the top of the atmosphere. Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski (2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem. Phys., 10,4559-4571, doi:10.5194/acp-10-4559-2010. Shindell, D., G. Faluvegi, N. Unger, E. Aguilar, G.A. Schmidt, D.M. Koch, S.E. Bauer, and J.R. Miller (2006), Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI, Atmos. Chem. Phys., 6, 4427-4459.

Circulation pattern-based assessment of projected climate change for a catchment in Spain

NASA Astrophysics Data System (ADS)

Gupta, Hoshin V.; Sapriza-Azuri, Gonzalo; Jódar, Jorge; Carrera, Jesús

2018-01-01

We present an approach for evaluating catchment-scale hydro-meteorological impacts of projected climate change based on the atmospheric circulation patterns (ACPs) of a region. Our approach is motivated by the conjecture that GCMs are especially good at simulating the atmospheric circulation patterns that control moisture transport, and which can be expected to change in response to global warming. In support of this, we show (for the late 20th century) that GCMs provide much better simulations of ACPs than those of precipitation amount for the Upper Guadiana Basin in central Spain. For the same period, four of the twenty GCMs participating in the most recent (5th) IPCC Assessment provide quite accurate representations of the spatial patterns of mean sea level pressure, the frequency distribution of ACP type, the 'number of rainy days per month', and the daily 'probability of rain' (they also reproduce the trend of 'wet day amount', though not the actual magnitudes). A consequent analysis of projected trends and changes in hydro-climatic ACPology between the late 20th and 21st Centuries indicates that (1) actual changes appear to be occurring faster than predicted by the models, and (2) for two greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5) the expected decline in precipitation volume is associated mainly with a few specific ACPs (primarily directional flows from the Atlantic Ocean and Cantabric Sea), and with decreasing probability of rain (linked to increasing temperatures) rather than wet day amount. Our approach is a potentially more insightful alternative for catchment-scale climate impacts assessments than the common approach of statistical downscaling and bias correction.

Assessment of the performance of CORDEX-SA experiments in simulating seasonal mean temperature over the Himalayan region for the present climate: Part I

NASA Astrophysics Data System (ADS)

Nengker, T.; Choudhary, A.; Dimri, A. P.

2018-04-01

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (-6 to -8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found.

South Asia river-flow projections and their implications for water resources

NASA Astrophysics Data System (ADS)

Mathison, C.; Wiltshire, A. J.; Falloon, P.; Challinor, A. J.

2015-12-01

South Asia is a region with a large and rising population, a high dependence on water intense industries, such as agriculture and a highly variable climate. In recent years, fears over the changing Asian summer monsoon (ASM) and rapidly retreating glaciers together with increasing demands for water resources have caused concern over the reliability of water resources and the potential impact on intensely irrigated crops in this region. Despite these concerns, there is a lack of climate simulations with a high enough resolution to capture the complex orography, and water resource analysis is limited by a lack of observations of the water cycle for the region. In this paper we present the first 25 km resolution regional climate projections of river flow for the South Asia region. Two global climate models (GCMs), which represent the ASM reasonably well are downscaled (1960-2100) using a regional climate model (RCM). In the absence of robust observations, ERA-Interim reanalysis is also downscaled providing a constrained estimate of the water balance for the region for comparison against the GCMs (1990-2006). The RCM river flow is routed using a river-routing model to allow analysis of present-day and future river flows through comparison with available river gauge observations. We examine how useful these simulations are for understanding potential changes in water resources for the South Asia region. In general the downscaled GCMs capture the seasonality of the river flows but overestimate the maximum river flows compared to the observations probably due to a positive rainfall bias and a lack of abstraction in the model. The simulations suggest an increasing trend in annual mean river flows for some of the river gauges in this analysis, in some cases almost doubling by the end of the century. The future maximum river-flow rates still occur during the ASM period, with a magnitude in some cases, greater than the present-day natural variability. Increases in river flow could mean additional water resources for irrigation, the largest usage of water in this region, but has implications in terms of inundation risk. These projected increases could be more than countered by changes in demand due to depleted groundwater, increases in domestic use or expansion of water intense industries. Including missing hydrological processes in the model would make these projections more robust but could also change the sign of the projections.

Impacts of peatland forestation on regional climate conditions in Finland

NASA Astrophysics Data System (ADS)

Gao, Yao; Markkanen, Tiina; Backman, Leif; Henttonen, Helena M.; Pietikäinen, Joni-Pekka; Laaksonen, Ari

2014-05-01

Climate response to anthropogenic land cover change happens more locally and occurs on a shorter time scale than the global warming due to increased GHGs. Over the second half of last Century, peatlands were vastly drained in Finland to stimulate forest growth for timber production. In this study, we investigate the biophysical effects of peatland forestation on near-surface climate conditions in Finland. For this, the regional climate model REMO, developed in Max Plank Institute (currently in Climate Service Center, Germany), provides an effective way. Two sets of 15-year climate simulations were done by REMO, using the historic (1920s; The 1st Finnish National Forest Inventory) and present-day (2000s; the 10th Finnish National Forest Inventory) land cover maps, respectively. The simulated surface air temperature and precipitation were then analyzed. In the most intensive peatland forestation area in Finland, the differences in monthly averaged daily mean surface air temperature show a warming effect around 0.2 to 0.3 K in February and March and reach to 0.5 K in April, whereas a slight cooling effect, less than 0.2 K, is found from May till October. Consequently, the selected snow clearance dates in model gridboxes over that area are advanced 0.5 to 4 days in the mean of 15 years. The monthly averaged precipitation only shows small differences, less than 10 mm/month, in a varied pattern in Finland from April to September. Furthermore, a more detailed analysis was conducted on the peatland forestation area with a 23% decrease in peatland and a 15% increase in forest types. 11 day running means of simulated temperature and energy balance terms, as well as snow depth were averaged over 15 years. Results show a positive feedback induced by peatland forestation between the surface air temperature and snow depth in snow melting period. This is because the warmer temperature caused by lower surface albedo due to more forest in snow cover period leads to a quicker and earlier snow melting. Meanwhile, surface albedo is reduced and consequently surface air temperature is increased. Additionally, the maximum difference from individual gridboxes in this area over 15 years of 11 day running means of daily mean surface air temperature reaches 2 K, which is four times as much as the maximum difference of 15-year regional average of that. This illustrates that the spring warming effect from peatland forestation in Finland is highly heterogeneous spatially and temporally.

Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

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

Wan, Hui; Rasch, Philip J.; Zhang, Kai

2014-09-08

This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivitymore » of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.« less

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

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

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

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

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

An observation-based progression modeling approach to spring and autumn deciduous tree phenology

NASA Astrophysics Data System (ADS)

Yu, Rong; Schwartz, Mark D.; Donnelly, Alison; Liang, Liang

2016-03-01

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade ( p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade ( p < 0.02) during the 1970-2012 period; two simulated autumn phenophases were significantly delayed at a rate of 0.37 (mid-leaf coloration) and 0.50 (full-leaf coloration) days/decade ( p < 0.01) during the 1970-2012 period. Consequently, the simulated growing season lengthened at a rate of 0.45 and 2.50 days/decade ( p < =0.001), respectively, during the two periods. Our results further showed the variability of responses to climate between early and late spring phenophases, as well as between leaf coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.

An observation-based progression modeling approach to spring and autumn deciduous tree phenology.

PubMed

Yu, Rong; Schwartz, Mark D; Donnelly, Alison; Liang, Liang

2016-03-01

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade (p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade (p < 0.02) during the 1970-2012 period; two simulated autumn phenophases were significantly delayed at a rate of 0.37 (mid-leaf coloration) and 0.50 (full-leaf coloration) days/decade (p < 0.01) during the 1970-2012 period. Consequently, the simulated growing season lengthened at a rate of 0.45 and 2.50 days/decade (p < =0.001), respectively, during the two periods. Our results further showed the variability of responses to climate between early and late spring phenophases, as well as between leaf coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.

Transient climate-carbon simulations of planetary geoengineering.

PubMed

Matthews, H Damon; Caldeira, Ken

2007-06-12

Geoengineering (the intentional modification of Earth's climate) has been proposed as a means of reducing CO2-induced climate warming while greenhouse gas emissions continue. Most proposals involve managing incoming solar radiation such that future greenhouse gas forcing is counteracted by reduced solar forcing. In this study, we assess the transient climate response to geoengineering under a business-as-usual CO2 emissions scenario by using an intermediate-complexity global climate model that includes an interactive carbon cycle. We find that the climate system responds quickly to artificially reduced insolation; hence, there may be little cost to delaying the deployment of geoengineering strategies until such a time as "dangerous" climate change is imminent. Spatial temperature patterns in the geoengineered simulation are comparable with preindustrial temperatures, although this is not true for precipitation. Carbon sinks in the model increase in response to geoengineering. Because geoengineering acts to mask climate warming, there is a direct CO2-driven increase in carbon uptake without an offsetting temperature-driven suppression of carbon sinks. However, this strengthening of carbon sinks, combined with the potential for rapid climate adjustment to changes in solar forcing, leads to serious consequences should geoengineering fail or be stopped abruptly. Such a scenario could lead to very rapid climate change, with warming rates up to 20 times greater than present-day rates. This warming rebound would be larger and more sustained should climate sensitivity prove to be higher than expected. Thus, employing geoengineering schemes with continued carbon emissions could lead to severe risks for the global climate system.

Forest Management in Earth System Modelling: a Vertically Discretised Canopy Description for ORCHIDEE and Effects on European Climate Since 1750

NASA Astrophysics Data System (ADS)

McGrath, M.; Luyssaert, S.; Naudts, K.; Chen, Y.; Ryder, J.; Otto, J.; Valade, A.

2015-12-01

Forest management has the potential to impact surface physical characteristics to the same degree that changes in land cover do. The impacts of land cover changes on the global climate are well-known. Despite an increasingly detailed understanding of the potential for forest management to affect climate, none of the current generation of Earth system models account for forest management through their land surface modules. We addressed this gap by developing and reparameterizing the ORCHIDEE land surface model to simulate the biogeochemical and biophysical effects of forest management. Through vertical discretization of the forest canopy and corresponding modifications to the energy budget, radiation transfer, and carbon allocation, forest management can now be simulated much more realistically on the global scale. This model was used to explore the effect of forest management on European climate since 1750. Reparameterization was carried out to replace generic forest plant functional types with real tree species, covering the most dominant species across the continent. Historical forest management and land cover maps were created to run the simulations from 1600 until the present day. The model was coupled to the atmospheric model LMDz to explore differences in climate between 1750 and 2010 and attribute those differences to changes in atmospheric carbon dioxide concentrations and concurrent warming, land cover, species composition, and wood extraction. Although Europe's forest are considered a carbon sink in this century, our simulations show the modern forests are still experiencing carbon debt compared to their historical values.

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

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

Thornton, Peter E.; Calvin, Katherine; Jones, Andrew D.

Fossil fuel combustion and land-use change are the first and second largest contributors to industrial-era increases in atmospheric carbon dioxide concentration, which is itself the largest driver of present-day climate change1. Projections of fossil fuel consumption and land-use change are thus fundamental inputs for coupled Earth system models (ESM) used to estimate the physical and biological consequences of future climate system forcing2,3. While empirical datasets are available to inform historical analyses4,5, assessments of future climate change have relied on projections of energy and land use based on energy economic models, constrained using historical and present-day data and forced with assumptionsmore » about future policy, land-use patterns, and socio-economic development trajectories6. Here we show that the influence of biospheric change – the integrated effect of climatic, ecological, and geochemical processes – on land ecosystems has a significant impact on energy, agriculture, and land-use projections for the 21st century. Such feedbacks have been ignored in previous ESM studies of future climate. We find that synchronous exposure of land ecosystem productivity in the economic system to biospheric change as it develops in an ESM results in a 10% reduction of land area used for crop cultivation; increased managed forest area and land carbon; a 15-20% decrease in global crop price; and a 17% reduction in fossil fuel emissions for a low-mid range forcing scenario7. These simulation results demonstrate that biospheric change can significantly alter primary human system forcings to the climate system. This synchronous two-way coupling approach removes inconsistencies in description of climate change between human and biosphere components of the coupled model, mitigating a major source of uncertainty identified in assessments of future climate projections8-10.« less

Introducing the Met Office 2.2-km Europe-wide convection-permitting regional climate simulations

NASA Astrophysics Data System (ADS)

Kendon, Elizabeth J.; Chan, Steven C.; Berthou, Segolene; Fosser, Giorgia; Roberts, Malcolm J.; Fowler, Hayley J.

2017-04-01

The Met Office is currently conducting Europe-wide 2.2-km convection-permitting model (CPM) simulations driven by ERA-Interim reanalysis and present/future-climate GCM simulations. Here, we present the preliminary results of these new European simulations examining daily and sub-daily precipitation outputs in comparison with observations across Europe, 12-km European and 1.5-km UK climate model simulations. As the simulations are not yet complete, we focus on diagnostics that are relatively robust with a limited amount of data; for instance, the diurnal cycle and the probability distribution of daily and sub-daily precipitation intensities. We will also present specific case studies that showcase the benefits of using continental-scale CPM simulations over previously-available small-domain CPM simulations.

Mid-21st century projections of hydroclimate in Western Himalayas and Satluj River basin

NASA Astrophysics Data System (ADS)

Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.

2018-02-01

The Himalayan climate system is sensitive to global warming and climate change. Regional hydrology and the downstream water flow in the rivers of Himalayan origin may change due to variations in snow and glacier melt in the region. This study examines the mid-21st century climate projections over western Himalayas from the Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models under Representative Concentration Pathways (RCP) scenarios (RCP4.5 and RCP8.5). All the global climate models used in the present analysis indicate that the study region would be warmer by mid-century. The temperature trends from all the models studied here are statistically significant at 95% confidence interval. Multi-model ensemble spreads show that there are large differences among the models in their projections of future climate with spread in temperature ranging from about 1.5 °C to 5 °C over various areas of western Himalayas in all the seasons. Spread in precipitation projections lies between 0.3 and 1 mm/day in all the seasons. Major shift in the timing of evaporation maxima and minima is noticed. The GFDL_ESM2G model products have been downscaled to Satluj River basin using the weather research and forecast (WRF) model and impact of climate change on streamflow has been studied. The reduction of precipitation during JJAS is expected to be > 3-6 mm/day in RCP8.5 as compared to present climate. It is expected that precipitation amount shall increase over Satluj basin in future (mid-21st century) The soil and water assessment tool (SWAT) model has been used to simulate the Satluj streamflow for the present and future climate using GFDL_ESM2G precipitation and temperature data as well as the WRF model downscaled data. The computations using the global model data show that total annual discharge from Satluj will be less in future than that in present climate, especially in peak discharge season (JJAS). The SWAT model with downscaled output indicates that during winter and spring, more discharge shall occur in future (RCP8.5) in Satluj River.

Effect of Climate Change on Surface Ozone over North America, Europe, and East Asia

NASA Technical Reports Server (NTRS)

Schnell, Jordan L.; Prather, Michael J.; Josse, Beatrice; Naik, Vaishali; Horowitz, Larry W.; Zeng, Guang; Shindell, Drew T.; Faluvegi, Greg

2016-01-01

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution.

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 considered by the policy makers within a wider range of climate uncertainties.

Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, Canada

NASA Astrophysics Data System (ADS)

Paradis, Daniel; Vigneault, Harold; Lefebvre, René; Savard, Martine M.; Ballard, Jean-Marc; Qian, Budong

2016-03-01

Nitrate (N-NO3) concentration in groundwater, the sole source of potable water in Prince Edward Island (PEI, Canada), currently exceeds the 10 mg L-1 (N-NO3) health threshold for drinking water in 6 % of domestic wells. Increasing climatic and socio-economic pressures on PEI agriculture may further deteriorate groundwater quality. This study assesses how groundwater nitrate concentration could evolve due to the forecasted climate change and its related potential changes in agricultural practices. For this purpose, a tridimensional numerical groundwater flow and mass transport model was developed for the aquifer system of the entire Island (5660 km2). A number of different groundwater flow and mass transport simulations were made to evaluate the potential impact of the projected climate change and agricultural adaptation. According to the simulations for year 2050, N-NO3 concentration would increase due to two main causes: (1) the progressive attainment of steady-state conditions related to present-day nitrogen loadings, and (2) the increase in nitrogen loadings due to changes in agricultural practices provoked by future climatic conditions. The combined effects of equilibration with loadings, climate and agricultural adaptation would lead to a 25 to 32 % increase in N-NO3 concentration over the Island aquifer system. The change in groundwater recharge regime induced by climate change (with current agricultural practices) would only contribute 0 to 6 % of that increase for the various climate scenarios. Moreover, simulated trends in groundwater N-NO3 concentration suggest that an increased number of domestic wells (more than doubling) would exceed the nitrate drinking water criteria. This study underlines the need to develop and apply better agricultural management practices to ensure sustainability of long-term groundwater resources. The simulations also show that observable benefits from positive changes in agricultural practices would be delayed in time due to the slow dynamics of nitrate transport within the aquifer system.

Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, Canada

NASA Astrophysics Data System (ADS)

Paradis, D.; Vigneault, H.; Lefebvre, R.; Savard, M. M.; Ballard, J.-M.; Qian, B.

2015-08-01

Nitrate (N-NO3) concentration in groundwater, the sole source of potable water in Prince Edward Island (PEI, Canada), currently exceeds the 10 mg L-1 (N-NO3) health threshold for drinking water in 6 % of domestic wells. Increasing climatic and socio-economic pressures on PEI agriculture may further deteriorate groundwater quality. This study assesses how groundwater nitrate concentrations could evolve due to the forecasted climate change and its related potential changes in agricultural practices. For this purpose, a tridimensional numerical groundwater flow and mass transport model was developed for the aquifer system of the entire Island (5660 km2). A number of different groundwater flow and mass transport simulations were made to evaluate the potential impact of the projected climate change and agricultural adaptation. According to the simulations for year 2050, N-NO3 concentration would increase due to two main causes: (1) the progressive attainment of steady-state conditions related to present-day nitrogen loadings, and (2) the increase in nitrogen loadings due to changes in agricultural practices provoked by future climatic conditions. The combined effects of equilibration with loadings, climate and agricultural adaptation would lead to a 25 to 32 % increase in N-NO3 concentration over the Island aquifer system. Climate change alone (practices maintained at their current level) would contribute only 0 to 6 % to that increase according to the various climate scenarios. Moreover, simulated trends in groundwater N-NO3 concentration suggest that an increased number of domestic wells (more than doubling) would exceed the nitrate drinking water criteria. This study underlines the need to develop and apply better agricultural management practices to ensure sustainability of long-term groundwater resources. The simulations also show that observable benefits from positive changes in agricultural practices would be delayed in time due to the slow dynamics of nitrate transport within the aquifer system.

The role of bias in simulation of the Indian monsoon and its relationship to predictability

NASA Astrophysics Data System (ADS)

Kelly, P.

2016-12-01

Confidence in future projections of how climate change will affect the Indian monsoon is currently limited by- among other things-model biases. That is, the systematic error in simulating the mean present day climate. An important priority question in seamless prediction involves the role of the mean state. How much of the prediction error in imperfect models stems from a biased mean state (itself a result of many interacting process errors), and how much stems from the flow dependence of processes during an oscillation or variation we are trying to predict? Using simple but effective nudging techniques, we are able to address this question in a clean and incisive framework that teases apart the roles of the mean state vs. transient flow dependence in constraining predictability. The role of bias in model fidelity of simulations of the Indian monsoon is investigated in CAM5, and the relationship to predictability in remote regions in the "free" (non-nudged) domain is explored.

Diagnosing observed characteristics of the wet season across Africa to identify deficiencies in climate model simulations

NASA Astrophysics Data System (ADS)

Dunning, C.; Black, E.; Allan, R. P.

2017-12-01

The seasonality of rainfall over Africa plays a key role in determining socio-economic impacts for agricultural stakeholders, influences energy supply from hydropower, affects the length of the malaria transmission season and impacts surface water supplies. Hence, failure or delays of these rains can lead to significant socio-economic impacts. Diagnosing and interpreting interannual variability and long-term trends in seasonality, and analysing the physical driving mechanisms, requires a robust definition of African precipitation seasonality, applicable to both observational datasets and model simulations. Here we present a methodology for objectively determining the onset and cessation of multiple wet seasons across the whole of Africa. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. Application of this method to observational datasets reveals that over East Africa cessation of the short rains is 5 days earlier in La Nina years, and the failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons over this region. The method is used to examine the representation of the seasonality of African precipitation in CMIP5 model simulations. Overall, atmosphere-only and fully coupled CMIP5 historical simulations represent essential aspects of the seasonal cycle; patterns of seasonal progression of the rainy season are captured, for the most part mean model onset/ cessation dates agree with mean observational dates to within 18 days. However, unlike the atmosphere-only simulations, the coupled simulations do not capture the biannual regime over the southern West African coastline, linked to errors in Gulf of Guinea Sea Surface Temperature. Application to both observational and climate model datasets, and good agreement with agricultural onset methods, indicates the potential applicability of this method to a variety of meteorological and climate impact studies.

Coupled Northern Hemisphere permafrost-ice-sheet evolution over the last glacial cycle

NASA Astrophysics Data System (ADS)

Willeit, M.; Ganopolski, A.

2015-09-01

Permafrost influences a number of processes which are relevant for local and global climate. For example, it is well known that permafrost plays an important role in global carbon and methane cycles. Less is known about the interaction between permafrost and ice sheets. In this study a permafrost module is included in the Earth system model CLIMBER-2, and the coupled Northern Hemisphere (NH) permafrost-ice-sheet evolution over the last glacial cycle is explored. The model performs generally well at reproducing present-day permafrost extent and thickness. Modeled permafrost thickness is sensitive to the values of ground porosity, thermal conductivity and geothermal heat flux. Permafrost extent at the Last Glacial Maximum (LGM) agrees well with reconstructions and previous modeling estimates. Present-day permafrost thickness is far from equilibrium over deep permafrost regions. Over central Siberia and the Arctic Archipelago permafrost is presently up to 200-500 m thicker than it would be at equilibrium. In these areas, present-day permafrost depth strongly depends on the past climate history and simulations indicate that deep permafrost has a memory of surface temperature variations going back to at least 800 ka. Over the last glacial cycle permafrost has a relatively modest impact on simulated NH ice sheet volume except at LGM, when including permafrost increases ice volume by about 15 m sea level equivalent in our model. This is explained by a delayed melting of the ice base from below by the geothermal heat flux when the ice sheet sits on a porous sediment layer and permafrost has to be melted first. Permafrost affects ice sheet dynamics only when ice extends over areas covered by thick sediments, which is the case at LGM.

Estimating sowing and harvest dates based on the Asian summer monsoon

NASA Astrophysics Data System (ADS)

Mathison, Camilla; Deva, Chetan; Falloon, Pete; Challinor, Andrew J.

2018-05-01

Sowing and harvest dates are a significant source of uncertainty within crop models, especially for regions where high-resolution data are unavailable or, as is the case in future climate runs, where no data are available at all. Global datasets are not always able to distinguish when wheat is grown in tropical and subtropical regions, and they are also often coarse in resolution. South Asia is one such region where large spatial variation means higher-resolution datasets are needed, together with greater clarity for the timing of the main wheat growing season. Agriculture in South Asia is closely associated with the dominating climatological phenomenon, the Asian summer monsoon (ASM). Rice and wheat are two highly important crops for the region, with rice being mainly cultivated in the wet season during the summer monsoon months and wheat during the dry winter. We present a method for estimating the crop sowing and harvest dates for rice and wheat using the ASM onset and retreat. The aim of this method is to provide a more accurate alternative to the global datasets of cropping calendars than is currently available and generate more representative inputs for climate impact assessments. We first demonstrate that there is skill in the model prediction of monsoon onset and retreat for two downscaled general circulation models (GCMs) by comparing modelled precipitation with observations. We then calculate and apply sowing and harvest rules for rice and wheat for each simulation to climatological estimates of the monsoon onset and retreat for a present day period. We show that this method reproduces the present day sowing and harvest dates for most parts of India. The application of the method to two future simulations demonstrates that the estimated sowing and harvest dates are successfully modified to ensure that the growing season remains consistent with the internal model climate. The study therefore provides a useful way of modelling potential growing season adaptations to changes in future climate.

Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We apply GENMOM, a coupled atmosphere–ocean climate model, to simulate eight equilibrium time slices at 3000-year intervals for the past 21 000 years forced by changes in Earth–Sun geometry, atmospheric greenhouse gases (GHGs), continental ice sheets, and sea level. Simulated global cooling during the Last Glacial Maximum (LGM) is 3.8 ◦C and the rate of post-glacial warming is in overall agreement with recently published temperature reconstructions. The greatest rate of warming occurs between 15 and 12 ka (2.4 ◦C over land, 0.7 ◦C over oceans, and 1.4 ◦C globally) in response to changes in radiative forcing from the diminished extent of the Northern Hemisphere (NH) ice sheets and increases in GHGs and NH summer insolation. The modeled LGM and 6 ka temperature and precipitation climatologies are generally consistent with proxy reconstructions, the PMIP2 and PMIP3 simulations, and other paleoclimate data–model analyses. The model does not capture the mid-Holocene “thermal maximum” and gradual cooling to preindustrial (PI) global temperature found in the data. Simulated monsoonal precipitation in North Africa peaks between 12 and 9 ka at values ∼ 50 % greater than those of the PI, and Indian monsoonal precipitation peaks at 12 and 9 ka at values ∼ 45 % greater than the PI. GENMOM captures the reconstructed LGM extent of NH and Southern Hemisphere (SH) sea ice. The simulated present-day Antarctica Circumpolar Current (ACC) is ∼ 48 % weaker than the observed (62 versus 119 Sv). The simulated present-day Atlantic Meridional Overturning Circulation (AMOC) of 19.3 ± 1.4 Sv on the Bermuda Rise (33◦ N) is comparable with observed value of 18.7 ± 4.8 Sv. AMOC at 33◦ N is reduced by ∼ 15 % during the LGM, and the largest post-glacial increase (∼ 11 %) occurs during the 15 ka time slice.

Possible future changes in extreme events over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Scott, Jeffery

2013-04-01

In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world's tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations presented in this paper were carried out for two emission scenarios, a "business as usual" scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.

Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

USGS Publications Warehouse

Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-02-24

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.

Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

Geomorphic and Modeling Evidence for a Late Pleistocene Cirque Glacier in Southwest England

NASA Astrophysics Data System (ADS)

Knight, J.; Harrison, S.; Rowan, A. V.

2014-12-01

Several small ice caps have been identified outside of the margins of the last (late Devensian) British ice sheet, but few sites in the uplands of southwest England show evidence for late Devensian niche/cirque glaciers and/or perennial snowbanks. Here we present evidence for the southernmost site yet discovered, in west Penwith, Cornwall. Here, a NE-facing hollow developed on granite bedrock is surrounded by tors with deep bedrock fractures and displaced angular blocks. Bedrock is exposed at the base of the hollow but sediments form a subdued ridge, interpreted as a terminal moraine, at the front of the hollow. The sediments comprise gravelly diamicton containing facetted clasts that are occasionally striated, interbedded with sand lenses. Sediments are deformed by periglacial involutions. We used a 2-D glacier energy balance and iceflow model (Plummer and Phillips, 2003, Quat Sci Rev) to discover if the climatic conditions during the late Devensian could have sustained a cirque glacier at this site. Met Office regional climate data (1981-2010) were used to define mean monthly air temperatures, lapse rate, precipitation, cloudiness and relative humidity, and surface energy fluxes were calculated based on solar position during the present day and last glacial maximum (LGM). We ran a range of different glacier model simulations to test an envelope of late Devensian paleoclimate conditions inferred from other climate proxies. Model results suggest that a cirque glacier could have formed at this site under conditions equivalent to a change in temperature from present-day values of -8.5°C accompanied by a 20% decrease in precipitation, which is consistent with the regional LGM. Response times for these simulations are greater than 500 years, indicating that it is unlikely that such cirque glaciers maintained steady state and were instead short-lived features.

Ship accessibility predictions for the Arctic Ocean based on IPCC CO2 emission scenarios

NASA Astrophysics Data System (ADS)

Oh, Jai-Ho; Woo, Sumin; Yang, Sin-Il

2017-02-01

Changes in the extent of Arctic sea ice, which have resulted from climate change, offer new opportunities to use the Northern Sea Route (NSR) and Northwest Passage (NWP) for shipping. However, choosing to navigate the Arctic Ocean remains challenging due to the limited accessibility of ships and the balance between economic gain and potential risk. As a result, more precise and detailed information on both weather and sea ice change in the Arctic are required. In this study, a high-resolution global AGCM was used to provide detailed information on the extent and thickness of Arctic sea ice. For this simulation, we have simulated the AMIP-type simulation for the present-day climate during 31 years from 1979 to 2009 with observed SST and Sea Ice concentration. For the future climate projection, we have performed the historical climate during 1979-2005 and subsequently the future climate projection during 2010-2099 with mean of four CMIP5 models due to the two Representative Concentration Pathway scenarios (RCP 8.5 and RCP 4.5). First, the AMIP-type simulation was evaluated by comparison with observations from the Hadley Centre sea-ice and Sea Surface Temperature (HadlSST) dataset. The model reflects the maximum (in March) and minimum (in September) sea ice extent and annual cycle. Based on this validation, the future sea ice extents show the decreasing trend for both the maximum and minimum seasons and RCP 8.5 shows more sharply decreasing patterns of sea ice than RCP 4.5. Under both scenarios, ships classified as Polar Class (PC) 3 and Open-Water (OW) were predicted to have the largest and smallest number of ship-accessible days (in any given year) for the NSR and NWP, respectively. Based on the RCP 8.5 scenario, the projections suggest that after 2070, PC3 and PC6 vessels will have year-round access across to the Arctic Ocean. In contrast, OW vessels will continue to have a seasonal handicap, inhibiting their ability to pass through the NSR and NWP.

Climate change indices for Greenland applied directly for other arctic regions - Enhanced and utilized climate information from one high resolution RCM downscaling for Greenland evaluated through pattern scaling and CMIP5

NASA Astrophysics Data System (ADS)

Olesen, M.; Christensen, J. H.; Boberg, F.

2016-12-01

Climate change indices for Greenland applied directly for other arctic regions - Enhanced and utilized climate information from one high resolution RCM downscaling for Greenland evaluated through pattern scaling and CMIP5Climate change affects the Greenlandic society both advantageously and disadvantageously. Changes in temperature and precipitation patterns may result in changes in a number of derived society related climate indices, such as the length of growing season or the number of annual dry days or a combination of the two - indices of substantial importance to society in a climate adaptation context.Detailed climate indices require high resolution downscaling. We have carried out a very high resolution (5 km) simulation with the regional climate model HIRHAM5, forced by the global model EC-Earth. Evaluation of RCM output is usually done with an ensemble of downscaled output with multiple RCM's and GCM's. Here we have introduced and tested a new technique; a translation of the robustness of an ensemble of GCM models from CMIP5 into the specific index from the HIRHAM5 downscaling through a correlation between absolute temperatures and its corresponding index values from the HIRHAM5 output.The procedure is basically conducted in two steps: First, the correlation between temperature and a given index for the HIRHAM5 simulation by a best fit to a second order polynomial is identified. Second, the standard deviation from the CMIP5 simulations is introduced to show the corresponding standard deviation of the index from the HIRHAM5 run. The change of specific climate indices due to global warming will then be possible to evaluate elsewhere corresponding to the change in absolute temperature.Results based on selected indices with focus on the future climate in Greenland calculated for the rcp4.5 and rcp8.5 scenarios will be presented.

Attribution of low precipitation in California during the winter of 2013-2014

NASA Astrophysics Data System (ADS)

Mera, R. J.; Ekwurzel, B.; Rupp, D. E.

2014-12-01

The record-setting drought in the state of California was further aggravated by extreme low precipitation in the winter of 2013-2014 and the associated low snow cover over the Sierra Nevada. Attribution work on the decline in Northern Hemisphere spring snow cover (Rupp et al. 2013) has shown that the decrease was likely the result of combined natural and anthropogenic forcing but not by natural forcing alone. Regional model superensemble simulations of snow water equivalent (SWE) with the Hadley Regional Climate Model (HadRM3P) shows the decline as a statistically-significant, linear trend for the Western US from 1961 to 2010. The present work focuses on attribution of these events by employing a superensemble of regional climate model simulations from the climateprediction.net (CPDN) experiment, which allows for robust statistical analysis of extreme events. Specifically, we compare the decade of the 2000s and the 1960s, which had different levels of heat-trapping gases and forcing from natural variability, among other factors. A linear regression of wet days and number of days with precipitation above 40 mm shows a strong drying pattern for the winter months of December, January, February, March (DJFM), especially for northern California and the Sierra Nevada. A strong warming pattern is also present during the winter months, with the minimum temperatures outpacing maximum temperatures for the Pacific Northwest. We will also investigate how simulations for DJFM 2013-2014, using only natural forcing provided CMIP5 HistoricalNat boundary conditions, compare against the model simulations using observations as boundary conditions. Results from this experiment also highlight the influence of increasing number of simulations on confidence intervals, which significantly reduces the uncertainty of both the change in magnitude of a given event and its corresponding return period.Rupp, David E., Philip W. Mote, Nathaniel L. Bindoff, Peter A. Stott, David A. Robinson, 2013: Detection and Attribution of Observed Changes in Northern Hemisphere Spring Snow Cover. J. Climate, 26, 6904-6914.doi: http://dx.doi.org/10.1175/JCLI-D-12-00563.1

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Consideration of land-use and land-cover changes in the projection of climate extremes over North America by the end of the twenty-first century

NASA Astrophysics Data System (ADS)

Alexandru, Adelina

2018-03-01

Changes in the essential climate extremes indices and surface variables for the end of the twenty-first century are assessed in this study based on two transient climate change simulations, with and without land-use and land-cover changes (LULCC), but identical atmospheric forcing. The two simulations are performed with the 5th generation of the Canadian Regional Climate Model (CRCM5) driven by the Canadian Earth System Model for the (2006-2100)-Representative Concentration Pathway 4.5 (RCP4.5) scenario. For the simulation with LULCC, land-cover data sets are taken from the global change assessment model (GCAM) representing the RCP4.5 scenario for the period 2006-2100. LULCC in RCP4.5 scenario suggest significant reduction in cultivated land (e.g. Canadian Prairies and Mississippi basin) due to afforestation. CRCM5 climate projections imply a general warming by the end of the twenty-first century, especially over the northern regions in winter. CRCM5 projects more warm spell-days per year over most areas of the continent, and implicitly more summer days and tropical nights at the expense of cold-spell, frost and ice days whose number is projected to decrease by up to 40% by the end of the twenty-first century with respect to the baseline period 1971-2000. Most land areas north of 45°N, in all seasons, as well as the southeastern United States in summer, exhibit increases in mean precipitation under the RCP4.5 scenario. In contrast, central parts of the continent in summer and much of Mexico in all seasons show reduced precipitation. In addition, large areas of North America exhibit changes of 10 to 40% (depending on the season and geographical location) in the number of heavy precipitation days. Results also suggest that the biogeophysical effects of LULCC on climate, assessed through differences between the two simulations, lead to warmer regional climates, especially in winter. The investigation of processes leading to this response shows high sensitivity of the results to changes in albedo as a response to LULCC. Overall, at the seasonal scale, results show that intense afforestation may contribute to an additional 25% of projected changes.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Simulating Pliocene warmth and a permanent El Niño-like state: The role of cloud albedo

DOE PAGES

Burls, N. J.; Fedorov, A. V.

2014-09-13

We present that available evidence suggests that during the early Pliocene (4–5 Ma) the mean east-west sea surface temperature (SST) gradient in the equatorial Pacific Ocean was significantly smaller than today, possibly reaching only 1–2°C. The meridional SST gradients were also substantially weaker, implying an expanded ocean warm pool in low latitudes. Subsequent global cooling led to the establishment of the stronger, modern temperature gradients. Given our understanding of the physical processes that maintain the present-day cold tongue in the east, warm pool in the west and hence sharp temperature contrasts, determining the key factors that maintained early Pliocene climatemore » still presents a challenge for climate theories and models. This study demonstrates how different cloud properties could provide a solution. We show that a reduction in the meridional gradient in cloud albedo can sustain reduced meridional and zonal SST gradients, an expanded warm pool and warmer thermal stratification in the ocean, and weaker Hadley and Walker circulations in the atmosphere. Having conducted a range of hypothetical modified cloud albedo experiments, we arrive at our Pliocene simulation, which shows good agreement with proxy SST data from major equatorial and coastal upwelling regions, the tropical warm pool, middle and high latitudes, and available subsurface temperature data. As suggested by the observations, the simulated Pliocene-like climate sustains a robust El Niño-Southern Oscillation despite the reduced mean east-west SST gradient. In conclusion, our results demonstrate that cloud albedo changes may be a critical element of Pliocene climate and that simulating the meridional SST gradient correctly is central to replicating the geographical patterns of Pliocene warmth.« less

Numerical Study of the Effect of Urbanization on the Climate of Desert Cities

NASA Astrophysics Data System (ADS)

Kamal, Samy

This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For each city, the land-use maps of 1985 and 2010 from Landsat satellite observation, and a projected land-use map for 2030, are used to represent the past, present, and future. An additional set of simulations for Las Vegas, the largest of the five cities, uses the NLCD 1992 and 2006 land-use maps and an idealized historical land-use map with no urban coverage for 1900. The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization. The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.

Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies

NASA Astrophysics Data System (ADS)

Shellito, Cindy J.; Sloan, Lisa C.

2006-02-01

Models that allow vegetation to respond to and interact with climate provide a unique method for addressing questions regarding feedbacks between the ecosystem and climate in pre-Quaternary time periods. In this paper, we consider how Dynamic Global Vegetation Models (DGVMs), which have been developed for simulations with present day climate, can be used for paleoclimate studies. We begin with a series of tests in the NCAR Land Surface Model (LSM)-DGVM with Eocene geography to examine (1) the effect of removing C 4 grasses from the available plant functional types in the model; (2) model sensitivity to a change in soil texture; and (3), model sensitivity to a change in the value of pCO 2 used in the photosynthetic rate equations. The tests were designed to highlight some of the challenges of using these models and prompt discussion of possible improvements. We discuss how lack of detail in model boundary conditions, uncertainties in the application of modern plant functional types to paleo-flora simulations, and inaccuracies in the model climatology used to drive the DGVM can affect interpretation of model results. However, we also review a number of DGVM features that can facilitate understanding of past climates and offer suggestions for improving paleo-DGVM studies.

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 British Antarctic Survey thermomechanically coupled ice sheet model (BASISM) to test the extent to which equilibrium state ice sheets in the Northern Hemisphere are GCM dependent. Initial results which do not use GCM-specific topography suggest that employing different GCM climatologies with only small differences in surface air temperature and precipitation has a dramatic effect on the resultant Greenland ice sheet, where the end-member ice sheets vary from near modern to almost zero ice volume. As an extension of this analysis, we will also present results using a second ice sheet model (Glimmer), with a view to testing the degree to which end-member ice sheets are ice sheet model dependent, something which has not previously been addressed. Initially, BASISM and Glimmer will be internally optimised for performance, but we will also present a comparison where BASISM will be configured to the Glimmer model setup in a further test of ice sheet model dependency.

A Regional-Scale Evaluation on Environmental Stability Conditions for Convective Rain under Climate Change from Super-High-Resolution GCM Simulations

NASA Astrophysics Data System (ADS)

Takemi, T.; Nomura, S.; Oku, Y.; Ishikawa, H.

2011-12-01

Understanding and forecasting of convective rain due to intense thunderstorms, which develop under conditions both with and without significant synoptic-scale and/or mesoscale forcings, are critical in dealing with disaster prevention/mitigation and developing urban planning appropriate for disaster management. Thunderstorms rapidly develop even during the daytimes of fair weather conditions without any external forcings, and sometimes become strong enough to induce local-scale meteorological disasters such as torrential rain, flush flooding, high winds, and tornadoes/gusts. With the growing interests in climate change, future changes in the behavior of such convectively generated extreme events have gained scientific and societal interests. This study conducted the regional-scale evaluations on the environmental stability conditions for convective rain that develops under synoptically undisturbed, summertime conditions by using the outputs of super-high-resolution AGCM simulations, at a 20-km resolution, for the present, the near-future, and the future climates under global warming with IPCC A1B emission scenario. The GCM, MRI-AGCM3.2S, was developed by Meteorological Research Institute of Japan Meteorological Agency under the KAKUSHIN program funded by the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The climate simulation outputs that were used in this study corresponded to three 25-year periods: 1980-2004 for the present climate; 2020-2044 for the near-future climate; and 2075-2099 for the future climate. The Kanto Plain that includes the Tokyo metropolitan area was chosen as the study area, since the Tokyo metropolitan area is one of the largest metropolises in the world and is vulnerable to extreme weather events. Therefore, one of the purposes of this study was to examine how regional-scale evaluations are performed from the super-high-resolution GCM outputs. After verifying the usefulness of the GCM present-climate outputs with observations and operational mesoscale analyses, we examined, as another purpose of this study, the future changes in the environmental stability for convective rain. To diagnose the environmental conditions, some of the commonly used stability parameters and indices were examined. In the future climates, temperature lapse rate decreased in the lower troposphere, while water vapor mixing ratio increased throughout the deep troposphere. The changes in the temperature and moisture profiles resulted in the increase in both precipitable water vapor and convective available potential energy. These projected changes will be enhanced with the future period. Furthermore, the statistical analyses for the differences of the stability parameters between no-rain and rain days under the synoptically undisturbed condition in each simulated climate period indicated that the environmental conditions in terms of the stability parameters that distinguish no-rain and rain events are basically unchanged between the present and the future climates. This result suggests that the environmental characteristics favorable for afternoon rain events in the synoptically undisturbed environments will not change under global warming.

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Rain, Brains and Climate Change: improving understanding of regional precipitation with medical registration techniques (Invited)

NASA Astrophysics Data System (ADS)

Levy, A.; Ingram, W.; Allen, M. R.; Jenkinson, M.; Lambert, F. H.; Huntingford, C.

2013-12-01

Precipitation is one of the most important climate variables, but is extremely difficult for general circulation models (GCMs) to simulate accurately. Not only do GCMs disagree on projected and past changes, but they also struggle to get the mean present day distribution of precipitation correct. Some of this disagreement in changes, though, is due to errors in location in the GCMs' mean climate. For example, if the GCMs disagree about the location of the South Asian monsoon, they will disagree in their projections when compared locally, even if they all simulate an intensification of this feature. We have therefore implemented techniques to remove biases of location from GCMs' mean climates. Initially, we adapted medical registration software designed for the analysis of brain scans, using it to transform each GCM's mean climate onto observations. These transformations (or ';warps') were then applied to each GCM's projected changes under an extreme climate change scenario (1% CO2 experiment). We found that both the inter-model range and standard deviation were decreased by 15%, with many regions of the globe receiving a more than 50% reduction [Levy et al. 2013, GRL]. We have now developed a technique tailored to the spatial (longitudinal and latitudinal) and seasonal warping of precipitation fields, which is able to correct precipitation fields much more accurately, as well as providing the option to conserve total global rainfall upon warping. As well as allowing more confident projections of future climate change, this technique can be expected to improve the power and accuracy of the detection and attribution of past changes in precipitation. We have now begun investigating this application, and preliminary results will be presented here.

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

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

Past and Future Climate Change Impacts on Mountain Forests on the Olympic Peninsula (Washington, USA)

NASA Astrophysics Data System (ADS)

Schwörer, C.; Fisher, D. M.; Gavin, D. G.; Temperli, C.; Bartlein, P. J.

2015-12-01

Mountain forest composition and distribution is strongly affected by temperature and is expected to shift to higher elevations with climate change. However, warmer winters will also lead to an upward shift of the snowline and a decrease in snowpack at lower and intermediate elevations. In the mountain ranges of Western North America, snowpack plays an important role in providing additional moisture during the dry summer months. It is therefore unclear if the projected climate change will lead to a rise of subalpine forest due to a longer growing season or a contraction due to drought stress. Since forest succession processes take place over decades and centuries we use LandClim, a dynamic vegetation model, to assess the impact of climate change on mountain forests on the Olympic Peninsula (Washington, USA). As a reality check we first simulate vegetation dynamics since the last Ice Age and compare model output with paleobotanical data from five natural archives that span the topographic and climatic gradients on the Peninsula. LandClim produces realistic present-day species compositions with respect to elevation and precipitation gradients. Moreover, the simulations of forest dynamics for the last 16,000 years generally agree with the pollen and macrofossil data. We then simulated mountain forests under future climate projections. As a result, our model indicates drastic changes in species composition with a replacement of mountain hemlock (Tsuga mertensiana) by more drought-resistant species such as subalpine fir (Abies lasiocarpa). On the drier, eastern side of the Peninsula, the model even suggests a lowering of timberline due to insufficient moisture availability in shallow alpine soils. Our results have important implications for ecosystem managers and stress the urgency of climate change mitigation.

Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth

NASA Astrophysics Data System (ADS)

van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.

2014-03-01

We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the integrated forecasting system (IFS) model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which likely reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The methane lifetime is 7% higher in EC-Earth, but remains well within the range reported in the literature. We evaluate the model by comparing the simulated climatologies of surface carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.

Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Shiferaw, A. S.; Tadesse, T.; Oglesby, R. J.; Rowe, C. M.

2017-12-01

The precipitation extremes were generated over the Greater Horn of Africa (GHA) using the Regional Climate Models (RCMs) simulations from the Coordinated Regional Downscaling Experiment (CORDEX). To assess how well the RCM simulations are capturing the historical observed precipitation extremes, they were compared with the precipitation extremes derived from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2). The result shows that RCM simulations have reasonably captured observed patterns of the precipitation extremes (i.e., the pattern correlation is greater than 0.5). However, significant overestimations or underestimations were observed over some localized areas in the region. The study then assessed the projected changes in these precipitation extremes during 2069-2098 and compared to the 1976-2005 period that were both derived from the RCM simulations. Projected changes in total annual precipitation (PRCPTOT), annual number of heavy (>10mm) and very heavy (>20mm) precipitation days by 2069-2098 show a general north-south pattern with a decrease over southern-half and increase over the northern-half of GHA. These changes are often greatest over parts of Somalia, Eritrea, Ethiopian highlands and southern Tanzania. Maximum 1 and 5-day total precipitation in a year and "Simple Daily Precipitation Intensity Index" (ratio of PRCPTOT to rainy days) are projected to increase over majority of GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer but heavier rainy days in the future. Changes in annual sum of daily precipitation above 95th and 99th percentile are not statistically significant except Eritrea and northwestern Sudan/Somalia. Projected changes in consecutive dry days (CDD) suggest longer periods of dryness over majority of GHA. Among these areas, a substantial increases in CDD are located over southern Tanzania and Ethiopian highlands.

Projections of rising heat stress over the western Maritime Continent from dynamically downscaled climate simulations

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Kang, Suchul; Eltahir, Elfatih A. B.

2018-06-01

This study assesses the future changes in heat stress in response to different emission scenarios over the western Maritime Continent. To better resolve the region-specific changes and to enhance the performance in simulating extreme events, the MIT Regional Climate Model with a 12-km horizontal resolution is used for the dynamical downscaling of three carefully selected CMIP5 global projections forced by two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Daily maximum wet-bulb temperature (TWmax), which includes the effect of humidity, is examined to describe heat stress as regulated by future changes in temperature and humidity. An ensemble of projections reveals robust pattern in which a large increase in temperature is accompanied by a reduction in relative humidity but a significant increase in wet-bulb temperature. This increase in TWmax is relatively smaller over flat and coastal regions than that over mountainous region. However, the flat and coastal regions characterized by warm and humid present-day climate will be at risk even under modest increase in TWmax. The regional extent exposed to higher TWmax and the number of days on which TWmax exceeds its threshold value are projected to be much higher in RCP8.5 scenario than those in RCP4.5 scenario, thus highlighting the importance of controlling greenhouse gas emissions to reduce the adverse impacts on human health and heat-related mortality.

Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation Events

NASA Astrophysics Data System (ADS)

Ban, N.; Schmidli, J.; Schar, C.

2014-12-01

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

Towards quantifying uncertainty in predictions of Amazon 'dieback'.

PubMed

Huntingford, Chris; Fisher, Rosie A; Mercado, Lina; Booth, Ben B B; Sitch, Stephen; Harris, Phil P; Cox, Peter M; Jones, Chris D; Betts, Richard A; Malhi, Yadvinder; Harris, Glen R; Collins, Mat; Moorcroft, Paul

2008-05-27

Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the representation of rooting depth.

Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

NASA Astrophysics Data System (ADS)

Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian

2016-11-01

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.

Reduced ENSO Variability at the LGM Revealed by an Isotope-enabled Earth System Model

NASA Astrophysics Data System (ADS)

Zhu, J.; Liu, Z.; Otto-Bliesner, B. L.; Brady, E. C.; Noone, D.; Zhang, J.; Tomas, R. A.; Jahn, A.; Nusbaumer, J. M.; Wong, T. E.

2016-12-01

El Nino-Southern Oscillation (ENSO) is the most important climate variability at interannual timescale, greatly affecting the weather and climate worldwide. Studying the ENSO at the Last Glacial Maximum (LGM, 21 kyrs before present) can help us better understand its dynamics and improve its projections under anthropogenic global warming. However, both numerical simulations and paleoclimate reconstructions show contradicting results among themselves, e.g., using the Individual Foraminifera Analysis (IFA) approach, some paleo-records suggest an amplified ENSO at the LGM relative to present day; while others indicate a weakened ENSO. These contradictions are hard to explore using traditional climate models due to the indirect nature of model-data comparison: numerical models usually simulate variations in climate state variables (e.g., temperature); while reconstructions can only use proxies (e.g., water isotopes) to infer changes in these state variables. Here we employ the recently developed isotope-enabled Community Earth System Model (iCESM) to study the ENSO strength at the LGM and attempt to provide a consistent picture between climate model and different reconstructions. We find that ENSO at the LGM is about 30% weaker than that of the preindustrial in iCESM, primarily attributable to the weakened atmosphere-ocean coupled feedbacks in a colder climate with a deeper thermocline. With the capability of simulating water isotopes, our model demonstrates that total variance recorded by the IFA water-isotope records in the eastern equatorial Pacific (e.g., Core CD21-30) could actually increase because of an intensified annual cycle, instead of an amplified ENSO. Furthermore, our isotope-enabled simulations suggest that caution should be applied when interpreting the subsurface IFA water-isotope records (e.g., Cores CD38-17P and MD02-2529) due to the wide spread of habitat depth of thermocline-dwelling foraminifera and their possible migration with temporally varying thermocline, which could largely filter out the ENSO signal. Therefore, by realizing these complications, we argue that the weakened ENSO in our model is within the data uncertainty.

Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

PubMed

Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

2017-06-01

Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

Assessment of Folsom Lake Watershed response to historical and potential future climate scenarios

USGS Publications Warehouse

Carpenter, Theresa M.; Georgakakos, Konstantine P.

2000-01-01

An integrated forecast-control system was designed to allow the profitable use of ensemble forecasts for the operational management of multi-purpose reservoirs. The system ingests large-scale climate model monthly precipitation through the adjustment of the marginal distribution of reservoir-catchment precipitation to reflect occurrence of monthly climate precipitation amounts in the extreme terciles of their distribution. Generation of ensemble reservoir inflow forecasts is then accomplished with due account for atmospheric- forcing and hydrologic- model uncertainties. These ensemble forecasts are ingested by the decision component of the integrated system, which generates non- inferior trade-off surfaces and, given management preferences, estimates of reservoir- management benefits over given periods. In collaboration with the Bureau of Reclamation and the California Nevada River Forecast Center, the integrated system is applied to Folsom Lake in California to evaluate the benefits for flood control, hydroelectric energy production, and low flow augmentation. In addition to retrospective studies involving the historical period 1964-1993, system simulations were performed for the future period 2001-2030, under a control (constant future greenhouse-gas concentrations assumed at the present levels) and a greenhouse-gas- increase (1-% per annum increase assumed) scenario. The present paper presents and validates ensemble 30-day reservoir- inflow forecasts under a variety of situations. Corresponding reservoir management results are presented in Yao and Georgakakos, A., this issue. Principle conclusions of this paper are that the integrated system provides reliable ensemble inflow volume forecasts at the 5-% confidence level for the majority of the deciles of forecast frequency, and that the use of climate model simulations is beneficial mainly during high flow periods. It is also found that, for future periods with potential sharp climatic increases of precipitation amount and to maintain good reliability levels, operational ensemble inflow forecasting should involve atmospheric forcing from appropriate climatic periods.

Surface ozone seasonality under global change: Influence from dry deposition and isoprene emissions at northern mid-latitudes

NASA Astrophysics Data System (ADS)

Clifton, O.; Paulot, F.; Fiore, A. M.; Horowitz, L. W.; Malyshev, S.; Shevliakova, E.; Correa, G. J. P.; Lin, M.

2017-12-01

Identifying the contributions of nonlinear chemistry and transport to observed surface ozone seasonal cycles over land using global models relies on an accurate representation of ozone uptake by vegetation (dry deposition). It is well established that in the absence of ozone precursor emission changes, a warming climate will increase surface ozone in polluted regions, and that a rise in temperature-dependent isoprene emissions would exacerbate this "climate penalty". However, the influence of changes in ozone dry deposition, expected to evolve with climate and land use, is often overlooked in air quality projections. With a new scheme that represents dry deposition within the NOAA GFDL dynamic vegetation land model (LM3) coupled to the NOAA GFDL atmospheric chemistry-climate model (AM3), we simulate the impact of 21st century climate and land use on ozone dry deposition and isoprene emissions. This dry deposition parameterization is a version of the Wesely scheme, but uses parameters explicitly calculated by LM3 that respond to climate and land use (e.g., stomatal conductance, canopy interception of water, leaf area index). The parameterization includes a nonstomatal deposition dependence on humidity. We evaluate climatological present-day seasonal cycles of ozone deposition velocities and abundances with those observed at northern mid-latitude sites. With a set of 2010s and 2090s decadal simulations under a high climate warming scenario (RCP8.5) and a sensitivity simulation with well-mixed greenhouse gases following RCP8.5 but air pollutants held at 2010 levels (RCP8.5_WMGG), we examine changes in surface ozone seasonal cycles. We build on our previous findings, which indicate that strong reductions in anthropogenic NOx emissions under RCP8.5 cause the surface ozone seasonal cycle over the NE USA to reverse, shifting from a summer peak at present to a winter peak by 2100. Under RCP8.5_WMGG, we parse the separate effects of climate and land use on ozone dry deposition vs. isoprene emissions to quantify the impact of each process on surface ozone seasonal cycles and compare to the changes induced by declining anthropogenic NOx emissions (RCP8.5).

A Last Glacial Maximum world-ocean simulation at eddy-permitting resolution - Part 1: Experimental design and basic evaluation

NASA Astrophysics Data System (ADS)

Ballarotta, M.; Brodeau, L.; Brandefelt, J.; Lundberg, P.; Döös, K.

2013-01-01

Most state-of-the-art climate models include a coarsely resolved oceanic component, which has difficulties in capturing detailed dynamics, and therefore eddy-permitting/eddy-resolving simulations have been developed to reproduce the observed World Ocean. In this study, an eddy-permitting numerical experiment is conducted to simulate the global ocean state for a period of the Last Glacial Maximum (LGM, ~ 26 500 to 19 000 yr ago) and to investigate the improvements due to taking into account these higher spatial scales. The ocean general circulation model is forced by a 49-yr sample of LGM atmospheric fields constructed from a quasi-equilibrated climate-model simulation. The initial state and the bottom boundary condition conform to the Paleoclimate Modelling Intercomparison Project (PMIP) recommendations. Before evaluating the model efficiency in representing the paleo-proxy reconstruction of the surface state, the LGM experiment is in this first part of the investigation, compared with a present-day eddy-permitting hindcast simulation as well as with the available PMIP results. It is shown that the LGM eddy-permitting simulation is consistent with the quasi-equilibrated climate-model simulation, but large discrepancies are found with the PMIP model analyses, probably due to the different equilibration states. The strongest meridional gradients of the sea-surface temperature are located near 40° N and S, this due to particularly large North-Atlantic and Southern-Ocean sea-ice covers. These also modify the locations of the convection sites (where deep-water forms) and most of the LGM Conveyor Belt circulation consequently takes place in a thinner layer than today. Despite some discrepancies with other LGM simulations, a glacial state is captured and the eddy-permitting simulation undertaken here yielded a useful set of data for comparisons with paleo-proxy reconstructions.

Webinar Presentation: Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty

EPA Pesticide Factsheets

This presentation, Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty, was given at the STAR Black Carbon 2016 Webinar Series: Changing Chemistry over Time held on Oct. 31, 2016.

The effects of atmospheric cloud radiative forcing on climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1989-01-01

In order to isolate the effects of atmospheric cloud radiative forcing (ACRF) on climate, the general circulation of an ocean-covered earth called 'Seaworld' was simulated using the Colorado State University GCM. Most current climate models, however, do not include an interactive ocean. The key simplifications in 'Seaworld' are the fixed boundary temperature with no land points, the lack of mountains and the zonal uniformity of the boundary conditions. Two 90-day 'perpetual July' simulations were performed and analyzed the last sixty days of each. The first run included all the model's physical parameterizations, while the second omitted the effects of clouds in both the solar and terrestrial radiation parameterizations. Fixed and identical boundary temperatures were set for the two runs, and resulted in differences revealing the direct and indirect effects of the ACRF on the large-scale circulation and the parameterized hydrologic processes.

A Systems Approach to Climate, Water and Diarrhea in Hubli-Dharward, India

NASA Astrophysics Data System (ADS)

Mellor, J. E.; Zimmerman, J.

2014-12-01

Although evidence suggests that climate change will negatively impact water resources and hence diarrheal disease rates in the developing world, there is uncertainty surrounding prior studies. This is due to the complexity of the pathways by which climate impacts diarrhea rates making it difficult to develop interventions. Therefore, our goal was to develop a mechanistic systems approach that incorporates the complex climate, human, engineered and water systems to relate climate change to diarrhea rates under future climate scenarios.To do this, we developed an agent-based model (ABM). Our agents are households and children living in Hubli-Dharward, India. The model was informed with 15 months of weather, water quality, ethnographic and diarrhea incidence data. The model's front end is a stochastic weather simulator incorporating 15 global climate models to simulate rainfall and temperature. The water quality available to agents (residents) on a model "day" is a function of the simulated day's weather and is fully validated with field data. As with the field data, as the ambient temperature increases or it rains, the quality of water available to residents in the model deteriorates. The propensity for an resident to get diarrhea is calculated with an integrated Quantitative Microbial Risk Assessment model with uncertainty simulated with a bootstrap method. Other factors include hand-washing, improved water sources, household water treatment and improved sanitation.The benefits of our approach are as follows: Our mechanistic method allows us to develop scientifically derived adaptation strategies. We can quantitatively link climate scenarios with diarrhea incidence over long time periods. We can explore the complex climate and water system dynamics, rank risk factor importance, examine a broad range of scenarios and identify tipping points. Our approach is modular and expandable such that new datasets can be integrated to study climate impacts on a larger scale. Our results indicate that climate change will have a serious effect on diarrhea incidence in the region. However, adaptation strategies including more reliable water supplies and household water treatment can mitigate these impacts.

How to reduce long-term drift in present-day and deep-time simulations?

NASA Astrophysics Data System (ADS)

Brunetti, Maura; Vérard, Christian

2018-06-01

Climate models are often affected by long-term drift that is revealed by the evolution of global variables such as the ocean temperature or the surface air temperature. This spurious trend reduces the fidelity to initial conditions and has a great influence on the equilibrium climate after long simulation times. Useful insight on the nature of the climate drift can be obtained using two global metrics, i.e. the energy imbalance at the top of the atmosphere and at the ocean surface. The former is an indicator of the limitations within a given climate model, at the level of both numerical implementation and physical parameterisations, while the latter is an indicator of the goodness of the tuning procedure. Using the MIT general circulation model, we construct different configurations with various degree of complexity (i.e. different parameterisations for the bulk cloud albedo, inclusion or not of friction heating, different bathymetry configurations) to which we apply the same tuning procedure in order to obtain control runs for fixed external forcing where the climate drift is minimised. We find that the interplay between tuning procedure and different configurations of the same climate model provides crucial information on the stability of the control runs and on the goodness of a given parameterisation. This approach is particularly relevant for constructing good-quality control runs of the geological past where huge uncertainties are found in both initial and boundary conditions. We will focus on robust results that can be generally applied to other climate models.

Multi-year global climatic effects of atmospheric dust from large bolide impacts

NASA Technical Reports Server (NTRS)

Thompson, Starley L.

1988-01-01

The global climatic effects of dust generated by the impact of a 10 km-diameter bolide was simulated using a one-dimensional (vertical only) globally-averaged climate model by Pollack et al. The goal of the simulation is to examine the regional climate effects, including the possibility of coastal refugia, generated by a global dust cloud in a model having realistic geographic resolution. The climate model assumes the instantaneous appearance of a global stratospheric dust cloud with initial optical depth of 10,000. The time history of optical depth decreases according to the detailed calculations of Pollack et al., reaching an optical depth of unity at day 160, and subsequently decreasing with an e-folding time of 1 year. The simulation is carried out for three years in order to examine the atmospheric effects and recovery over several seasons. The simulation does not include any effects of NOx, CO2, or wildfire smoke injections that may accompany the creation of the dust cloud. The global distribution of surface temperature changes, freezing events, precipitation and soil moisture effects and sea ice increases will be discussed.

The role of ice shelves in the Holocene evolution of the Antarctic ice sheet

NASA Astrophysics Data System (ADS)

Bernales, Jorge; Rogozhina, Irina; Thomas, Maik

2014-05-01

Using the continental-scale ice sheet-shelf model SICOPOLIS (Greve, 1997 [1]; Sato and Greve, 2012 [2]), we assess the influence of ice shelves on the Holocene evolution and present-day geometry of the Antarctic ice sheet. We have designed a series of paleoclimate simulations driven by a time-evolved climate forcing that couples the surface temperature record from the Vostok ice core with precipitation pattern using an empirical relation of Dahl-Jensen et al., (1998) [3]. Our numerical experiments show that the geometry of ice shelves is determined by the evolution of climate and ocean conditions over time scales of 15 to 25 kyr. This implies that the initial configuration of ice shelves at the Last Glacial Maximum (LGM, about 21 kyr before present) has a significant effect on the modelled Early Holocene volume of ice shelves (up to 20%) that gradually diminishes to a negligible level for the present-day ice shelf configuration. Thus, the present-day geometry of the Antarctic ice shelves can be attained even if an ice-shelf-free initial condition is chosen at the LGM. However, the grounded ice volume, thickness and dynamic states are found to be sensitive to the ice shelf dynamics over a longer history spanning several tens of thousands of years. A presence of extensive marine ice at the LGM, supported by sediment core reconstructions (e.g. Naish et al., 2009 [4]), has a clear buttressing effect on the grounded ice that remains significant over a period of 30 to 50 kyr. If ice-shelf-free conditions are prescribed at the LGM, the modelled Early Holocene and present-day grounded ice volumes are underestimated by up to 10%, as opposed to simulations incorporating ice shelf dynamics over longer periods. The use of ice-shelf-free LGM conditions thus results in 50 to over 200 meters thinner ice sheet across much of East Antarctica. References [1] Greve, R. (1997). Application of a polythermal three-dimensional ice sheet model to the Greenland ice sheet: response to steady-state and transient climate scenarios. Journal of Climate, 10(5), 901-918. [2] Sato, T., and Greve, R. (2012). Sensitivity experiments for the Antarctic ice sheet with varied sub-ice-shelf melting rates. Annals of Glaciology, 53(60), 221-228. [3] Dahl-Jensen, D., Mosegaard, K., Gundestrup, N., Clow, G. D., Johnsen, S. J., Hansen, A. W., and Balling, N. (1998). Past temperatures directly from the Greenland ice sheet. Science, 282(5387), 268-271. [4] Naish, T., Powell, R., Levy, R., Wilson, G., Scherer, R., Talarico, F., ... and Schmitt, D. (2009). Obliquity-paced Pliocene West Antarctic ice sheet oscillations. Nature, 458(7236), 322-328.

A comparison of climate simulations for the last glacial maximum with three different versions of the ECHAM model and implications for summer-green tree refugia

NASA Astrophysics Data System (ADS)

Arpe, K.; Leroy, S. A. G.; Mikolajewicz, U.

2011-02-01

Model simulations of the last glacial maximum (21 ± 2 ka) with the ECHAM3 T42 atmosphere-only, ECHAM5-MPIOM T31 atmosphere-ocean coupled and ECHAM5 T106 atmosphere-only models are compared. The topography, land-sea mask and glacier distribution for the ECHAM5 simulations were taken from the Paleoclimate Modelling Intercomparison Project Phase II (PMIP2) data set while for ECHAM3 they were taken from PMIP1. The ECHAM5-MPIOM T31 model produced its own sea surface temperatures (SST) while the ECHAM5 T106 simulations were forced at the boundaries by this coupled model SSTs corrected from their present-day biases and the ECHAM3 T42 model was forced with prescribed SSTs provided by Climate/Long-Range Investigation, Mapping, and Prediction project (CLIMAP). The SSTs in the ECHAM5-MPIOM simulation for the last glacial maximum (LGM) were much warmer in the northern Atlantic than those suggested by CLIMAP or Overview of Glacial Atlantic Ocean Mapping (GLAMAP) while the SSTs were cooler everywhere else. This had a clear effect on the temperatures over Europe, warmer for winters in western Europe and cooler for eastern Europe than the simulation with CLIMAP SSTs. Considerable differences in the general circulation patterns were found in the different simulations. A ridge over western Europe for the present climate during winter in the 500 hPa height field remains in both ECHAM5 simulations for the LGM, more so in the T106 version, while the ECHAM3 CLIMAP-SST simulation provided a trough which is consistent with cooler temperatures over western Europe. The zonal wind between 30° W and 10° E shows a southward shift of the polar and subtropical jets in the simulations for the LGM, least obvious in the ECHAM5 T31 one, and an extremely strong polar jet for the ECHAM3 CLIMAP-SST run. The latter can probably be assigned to the much stronger north-south gradient in the CLIMAP SSTs. The southward shift of the polar jet during the LGM is supported by palaeo-data. Cyclone tracks in winter represented by high precipitation are characterised over Europe for the present by a main branch from the British Isles to Norway and a secondary branch towards the Mediterranean Sea, observed and simulated. For the LGM the different models show very different solutions: the ECHAM3 CLIMAP-SST simulation shows just one track going eastward from the British Isles into central Europe, while the ECHAM5 T106 simulation still has two branches but during the LGM the main one goes to the Mediterranean Sea, with enhanced precipitation in the Levant. This agrees with an observed high stand of the Dead Sea during the LGM. For summer the ECHAM5 T106 simulation provides much more precipitation for the present over Europe than the other simulations, thus agreeing with estimates by the Global Precipitation Climatology Project (GPCP). Also during the LGM this model makes Europe less arid than the other simulations. In many respects the ECHAM5 T106 simulation for the present is more realistic than the ECHAM5 T31 coupled simulation and the older ECHAM3 T42 simulation, when comparing them with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis or the GPCP precipitation data. For validating the model data for the LGM, pollen, wood and charcoal analyses were compared with possible summer-green tree growth from model estimates using summer precipitation, minimum winter temperatures and growing degree days (above 5 °C). The ECHAM5 T106 simulation suggests for more sites with findings of palaeo-data, likely tree growth during the LGM than the other simulations, especially over western Europe. The clear message especially from the ECHAM5 T106 simulation is that warm-loving summer-green trees could have survived mainly in Spain but also in Greece in agreement with findings of pollen or charcoal. Southern Italy is also suggested but this could not be validated because of absence of palaeo-data. Previous climate simulations of the LGM have suggested less cold and more humid climate than that reconstructed from pollen findings. Our model results do agree more or less with those of other models but we do not find a contradiction with palaeo-data because we use the pollen data directly without an intermediate reconstruction of temperatures and precipitation from the pollen spectra.

Reconstructions of Fire Activity in North America and Europe over the Past 250 Years: A comparison of the Global Charcoal Database with Historical Records

NASA Astrophysics Data System (ADS)

Magi, B. I.; Marlon, J. R.; Mouillot, F.; Daniau, A. L.; Bartlein, P. J.; Schaefer, A.

2017-12-01

Fire is intertwined with climate variability and human activities in terms of both its causes and consequences, and the most complete understanding will require a multidisciplinary approach. The focus in this study is to compare data-based records of variability in climate and human activities, with fire and land cover change records over the past 250 years in North America and Europe. The past 250 years is a critical period for contextualizing the present-day impact of human activities on climate. Data are from the Global Charcoal Database and from historical reconstructions of past burning. The GCD is comprised of sediment records of charcoal accumulation rates collected around the world by dozens of researchers, and facilitated by the PAGES Global Paleofire Working Group. The historical reconstruction extends back to 1750 CE is based on literature and government records when available, and completed with non-charcoal proxies including tree ring scars or storylines when data are missing. The key data sets are independent records, and the methods and results are independent of any climate or fire-model simulations. Results are presented for Europe, and subsets of North America. Analysis of fire trends from GCD and the historical reconstruction shows broad agreement, with some regional variations as expected. Western USA and North America in general show the best agreement, with departures in the GCD and historical reconstruction fire trends in the present day that may reflect limits in the data itself. Eastern North America shows agreement with an increase in fire from 1750 to 1900, and a strong decreasing trend thereafter. We present ideas for why the trends agree and disagree relative to historical events, and to the sequence of land-cover change in the regions of interest. Together with careful consideration of uncertainties in the data, these results can be used to constrain Earth System Model simulations of both past fire, which explicitly incorporate historical fire emissions, and the pathways of future fire on a warmer planet.

Regional variability of the frequency distribution of daily precipitation and the synoptic characteristics of heavy precipitation events in present and future climate simulations

NASA Astrophysics Data System (ADS)

DeAngelis, Anthony M.

Changes in the characteristics of daily precipitation in response to global warming may have serious impacts on human life and property. An analysis of precipitation in climate models is performed to evaluate how well the models simulate the present climate and how precipitation may change in the future. Models participating in phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) have substantial biases in their simulation of heavy precipitation intensity over parts of North America during the 20th century. Despite these biases, the large-scale atmospheric circulation accompanying heavy precipitation is either simulated realistically or the strength of the circulation is overestimated. The biases are not related to the large-scale flow in a simple way, pointing toward the importance of other model deficiencies, such as coarse horizontal resolution and convective parameterizations, for the accurate simulation of intense precipitation. Although the models may not sufficiently simulate the intensity of precipitation, their realistic portrayal of the large-scale circulation suggests that projections of future precipitation may be reliable. In the CMIP5 ensemble, the distribution of daily precipitation is projected to undergo substantial changes in response to future atmospheric warming. The regional distribution of these changes was investigated, revealing that dry days and days with heavy-extreme precipitation are projected to increase at the expense of light-moderate precipitation over much of the middle and low latitudes. Such projections have serious implications for future impacts from flood and drought events. In other places, changes in the daily precipitation distribution are characterized by a shift toward either wetter or drier conditions in the future, with heavy-extreme precipitation projected to increase in all but the driest subtropical subsidence regions. Further analysis shows that increases in heavy precipitation in midlatitudes are largely explained by thermodynamics, including increases in atmospheric water vapor. However, in low latitudes and northern high latitudes, changes in vertical velocity accompanying heavy precipitation are also important. The strength of the large-scale atmospheric circulation is projected to change in accordance with vertical velocity in many places, though the circulation patterns, and therefore physical mechanisms that generate heavy precipitation, may remain the same.

Evaluating the effects of historical land cover change on summertime weather and climate in New Jersey: Land cover and surface energy budget changes

USGS Publications Warehouse

Wichansky, P.S.; Steyaert, L.T.; Walko, R.L.; Waever, C.P.

2008-01-01

The 19th-century agrarian landscape of New Jersey (NJ) and the surrounding region has been extensively transformed to the present-day land cover by urbanization, reforestation, and localized areas of deforestation. This study used a mesoscale atmospheric numerical model to investigate the sensitivity of the warm season climate of NJ to these land cover changes. Reconstructed 1880s-era and present-day land cover data sets were used as surface boundary conditions for a set of simulations performed with the Regional Atmospheric Modeling System (RAMS). Three-member ensembles with historical and present-day land cover were compared to examine the sensitivity of surface air and dew point temperatures, rainfall, and the individual components of the surface energy budget to these land cover changes. Mean temperatures for the present-day landscape were 0.3-0.6??C warmer than for the historical landscape over a considerable portion of NJ and the surrounding region, with daily maximum temperatures at least 1.0??C warmer over some of the highly urbanized locations. Reforested regions, however, were slightly cooler. Dew point temperatures decreased by 0.3-0.6??C, suggesting drier, less humid near-surface air for the present-day landscape. Surface warming was generally associated with repartitioning of net radiation from latent to sensible heat flux, and conversely for cooling. While urbanization was accompanied by strong surface albedo decreases and increases in net shortwave radiation, reforestation and potential changes in forest composition have generally increased albedos and also enhanced landscape heterogeneity. The increased deciduousness of forests may have further reduced net downward longwave radiation. Copyright 2008 by the American Geophysical Union.

Predicting future threats to the long-term survival of Gila Trout using a high-resolution simulation of climate change

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

Kennedy, Thomas L.; Gutzler, David S.; Leung, Lai R.

2008-11-20

Regional climates are a major factor in determining the distribution of many species. Anthropogenic inputs of greenhouse gases into the atmosphere have been predicted to cause rapid climatic changes in the next 50-100 years. Species such as the Gila Trout (Onchorhynchus gilae) that have small ranges, limited dispersal capabilities, and narrow physiological tolerances will become increasingly susceptible to extinction as their climate envelope changes. This study uses a regional climate change simulation (Leung et al. 2004) to determine changes in the climate envelope for Gila Trout, which is sensitive to maximum temperature, associated with a plausible scenario for greenhouse gasmore » increases. The model predicts approximately a 2° C increase in temperature and a doubling by the mid 21st Century in the annual number of days during which temperature exceeds 37°C, and a 25% increase in the number of days above 32°C, across the current geographical range of Gila Trout. At the same time summer rainfall decreases by more than 20%. These climate changes would reduce their available habitat by decreasing the size of their climate envelope. Warmer temperatures coupled with a decrease in summer precipitation would also tend to increase the intensity and frequency of forest fires that are a major threat to their survival. The climate envelope approach utilized here could be used to assess climate change threats to other rare species with limited ranges and dispersal capabilities.« less

Reference aquaplanet climate in the Community Atmosphere Model, Version 5

DOE PAGES

Medeiros, Brian; Williamson, David L.; Olson, Jerry G.

2016-03-18

In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, includingmore » an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.« less

Life history and spatial traits predict extinction risk due to climate change

NASA Astrophysics Data System (ADS)

Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

2014-03-01

There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

Topographical effects of climate dataset and their impacts on the estimation of regional net primary productivity

NASA Astrophysics Data System (ADS)

Sun, L. Qing; Feng, Feng X.

2014-11-01

In this study, we first built and compared two different climate datasets for Wuling mountainous area in 2010, one of which considered topographical effects during the ANUSPLIN interpolation was referred as terrain-based climate dataset, while the other one did not was called ordinary climate dataset. Then, we quantified the topographical effects of climatic inputs on NPP estimation by inputting two different climate datasets to the same ecosystem model, the Boreal Ecosystem Productivity Simulator (BEPS), to evaluate the importance of considering relief when estimating NPP. Finally, we found the primary contributing variables to the topographical effects through a series of experiments given an overall accuracy of the model output for NPP. The results showed that: (1) The terrain-based climate dataset presented more reliable topographic information and had closer agreements with the station dataset than the ordinary climate dataset at successive time series of 365 days in terms of the daily mean values. (2) On average, ordinary climate dataset underestimated NPP by 12.5% compared with terrain-based climate dataset over the whole study area. (3) The primary climate variables contributing to the topographical effects of climatic inputs for Wuling mountainous area were temperatures, which suggest that it is necessary to correct temperature differences for estimating NPP accurately in such a complex terrain.

Effect of climate variability and change on winter haze over eastern China in recent decades

NASA Astrophysics Data System (ADS)

Liao, Hong; Yang, Yang

2017-04-01

In recent years, eastern China has frequently experienced persistent and severe winter haze pollution episodes with high aerosol concentrations, which have affected half of the 1.3 billion people in China. In this work, the increases in wintertime aerosol concentrations and severe haze events in eastern China over 1985-2015 were quantified by using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database, observed PM2.5 concentrations from the network of China National Environmental Monitoring Centre (CNEMC), and simulated PM2.5 concentrations from the Goddard Earth-Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days (defined as days with atmospheric visibility less than 10 km and relative humidity less than 80%) averaged over eastern China (105-122.5°E, 20-45°N) increased from 21 days in 1980 to 42 days in 2014. Observed severe haze days (defined as days with PM2.5 >150 μg m-3) occurred mainly over Northern China. Considering variations in both anthropogenic emissions and meteorological parameters, the GEOS-Chem model simulated an increasing trend in wintertime surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m-3 decade-1 over eastern China in the past decades. Sensitivity studies showed that changes in anthropogenic emissions and in climate contributed 87% and 17% to this increasing trend, respectively. Wintertime severe haze events over eastern China showed large interannual variations, driven by climate variability. Process analyses were performed to identify the key meteorological parameters that determined the interannual variations of wintertime severe haze events.

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model

PubMed Central

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J.; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H.; Molina, Mario J.

2014-01-01

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol–climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by −2.5 and +1.3 W m−2, respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors’ knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale. PMID:24733923

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model.

PubMed

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H; Molina, Mario J

2014-05-13

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

Interactions of arctic clouds, radiation, and sea ice in present-day and future climates

NASA Astrophysics Data System (ADS)

Burt, Melissa Ann

The Arctic climate system involves complex interactions among the atmosphere, land surface, and the sea-ice-covered Arctic Ocean. Observed changes in the Arctic have emerged and projected climate trends are of significant concern. Surface warming over the last few decades is nearly double that of the entire Earth. Reduced sea-ice extent and volume, changes to ecosystems, and melting permafrost are some examples of noticeable changes in the region. This work is aimed at improving our understanding of how Arctic clouds interact with, and influence, the surface budget, how clouds influence the distribution of sea ice, and the role of downwelling longwave radiation (DLR) in climate change. In the first half of this study, we explore the roles of sea-ice thickness and downwelling longwave radiation in Arctic amplification. As the Arctic sea ice thins and ultimately disappears in a warming climate, its insulating power decreases. This causes the surface air temperature to approach the temperature of the relatively warm ocean water below the ice. The resulting increases in air temperature, water vapor and cloudiness lead to an increase in the surface downwelling longwave radiation, which enables a further thinning of the ice. This positive ice-insulation feedback operates mainly in the autumn and winter. A climate-change simulation with the Community Earth System Model shows that, averaged over the year, the increase in Arctic DLR is three times stronger than the increase in Arctic absorbed solar radiation at the surface. The warming of the surface air over the Arctic Ocean during fall and winter creates a strong thermal contrast with the colder surrounding continents. Sea-level pressure falls over the Arctic Ocean and the high-latitude circulation reorganizes into a shallow "winter monsoon." The resulting increase in surface wind speed promotes stronger surface evaporation and higher humidity over portions of the Arctic Ocean, thus reinforcing the ice-insulation feedback. In the second half of this study, we explore the effects of super-parameterization on the Arctic climate by evaluating a number of key atmospheric characteristics that strongly influence the regional and global climate. One aspect in particular that we examine is the occurrence of Arctic weather states. Observations show that during winter the Arctic exhibits two preferred and persistent states --- a radiatively clear and an opaquely cloudy state. These distinct regimes are influenced by the phase of the clouds and affect the surface radiative fluxes. We explore the radiative and microphysical effects of these Arctic clouds and the influence on these regimes in two present-day climate simulations. We compare simulations performed with the Community Earth System Model, and its super-parameterized counterpart (SP-CESM). We find that the SP-CESM is able to better reproduce both of the preferred winter states, compared to CESM, and has an overall more realistic representation of the Arctic climate.

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

NASA Astrophysics Data System (ADS)

Butchart, Neal; Anstey, James A.; Hamilton, Kevin; Osprey, Scott; McLandress, Charles; Bushell, Andrew C.; Kawatani, Yoshio; Kim, Young-Ha; Lott, Francois; Scinocca, John; Stockdale, Timothy N.; Andrews, Martin; Bellprat, Omar; Braesicke, Peter; Cagnazzo, Chiara; Chen, Chih-Chieh; Chun, Hye-Yeong; Dobrynin, Mikhail; Garcia, Rolando R.; Garcia-Serrano, Javier; Gray, Lesley J.; Holt, Laura; Kerzenmacher, Tobias; Naoe, Hiroaki; Pohlmann, Holger; Richter, Jadwiga H.; Scaife, Adam A.; Schenzinger, Verena; Serva, Federico; Versick, Stefan; Watanabe, Shingo; Yoshida, Kohei; Yukimoto, Seiji

2018-03-01

The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.

Atmospheric blocking in the Climate SPHINX simulations: the role of orography and resolution

NASA Astrophysics Data System (ADS)

Davini, Paolo; Corti, Susanna; D'Andrea, Fabio; Riviere, Gwendal; von Hardenberg, Jost

2017-04-01

The representation of atmospheric blocking in numerical simulations, especially over the Euro-Atlantic region, still represents a main concern for the climate modelling community. We here discuss the Northern Hemisphere winter atmospheric blocking representation in a set of 30-year simulations which has been performed in the framework of the PRACE project "Climate SPHINX". Simulations were run using the EC-Earth Global Climate Model with several ensemble members at 5 different horizontal resolutions (ranging from 125 km to 16 km). Results show that the negative bias in blocking frequency over Europe becomes negligible at resolutions of about 40 km and finer. However, the blocking duration is still underestimated by 1-2 days, suggesting that the correct blocking frequencies are achieved with an overestimation of the number of blocking onsets. The reasons leading to such improvements are then discussed, highlighting the role of orography in shaping the Atlantic jet stream: at higher resolution the jet is weaker and less penetrating over Europe, favoring the breaking of synoptic Rossby waves over the Atlantic stationary ridge and thus increasing the simulated blocking frequency.

Future change in seasonal march of snow water equivalent due to global climate change

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

2012-04-01

Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

A possible impact of cooling over the Tibetan Plateau on the mid-Holocene East Asian monsoon climate

NASA Astrophysics Data System (ADS)

Jin, Liya; Wang, Huijun; Chen, Fahu; Jiang, Dabang

2006-12-01

By using a 9-level global atmospheric general circulation model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, the authors investigated the response of the East Asian monsoon climate to changes both in orbital forcing and the snow and glaciers over the Tibetan Plateau at the mid-Holocene, about 600 calendar years before the present (6 kyr BP). With the Earth’s orbital parameters appropriate for the mid-Holocene, the IAP9L-AGCM computed warmer and wetter conditions in boreal summer than for the present day. Under the precondition of continental snow and glacier cover existing over part of the Tibetan Plateau at the mid-Holocene, the authors examined the regional climate response to the Tibetan Plateau cooling. The simulations indicated that climate changes in South Asia and parts of central Asia as well as in East Asia are sensitive to the Tibetan Plateau cooling at the mid-Holocene, showing a significant decrease in precipitation in northern India, northern China and southern Mongolia and an increase in Southeast Asia during boreal summer. The latter seems to correspond to the weakening, southeastward shift of the Asian summer monsoon system resulting from reduced heat contrast between the Eurasian continent and the Pacific and Indian Oceans when a cooling over the Tibetan Plateau was imposed. The simulation results suggest that the snow and glacier environment over the Tibetan Plateau is an important factor for mid-Holocene climate change in the areas highly influenced by the Asian monsoon.

Modeling Insights into Deuterium Excess as an Indicator of Water Vapor Source Conditions

NASA Technical Reports Server (NTRS)

Lewis, Sophie C.; Legrande, Allegra Nicole; Kelley, Maxwell; Schmidt, Gavin A.

2013-01-01

Deuterium excess (d) is interpreted in conventional paleoclimate reconstructions as a tracer of oceanic source region conditions, such as temperature, where precipitation originates. Previous studies have adopted co-isotopic approaches to estimate past changes in both site and oceanic source temperatures for ice core sites using empirical relationships derived from conceptual distillation models, particularly Mixed Cloud Isotopic Models (MCIMs). However, the relationship between d and oceanic surface conditions remains unclear in past contexts. We investigate this climate-isotope relationship for sites in Greenland and Antarctica using multiple simulations of the water isotope-enabled Goddard Institute for Space Studies (GISS) ModelE-R general circulation model and apply a novel suite of model vapor source distribution (VSD) tracers to assess d as a proxy for source temperature variability under a range of climatic conditions. Simulated average source temperatures determined by the VSDs are compared to synthetic source temperature estimates calculated using MCIM equations linking d to source region conditions. We show that although deuterium excess is generally a faithful tracer of source temperatures as estimated by the MCIM approach, large discrepancies in the isotope-climate relationship occur around Greenland during the Last Glacial Maximum simulation, when precipitation seasonality and moisture source regions were notably different from present. This identified sensitivity in d as a source temperature proxy suggests that quantitative climate reconstructions from deuterium excess should be treated with caution for some sites when boundary conditions are significantly different from the present day. Also, the exclusion of the influence of humidity and other evaporative source changes in MCIM regressions may be a limitation of quantifying source temperature fluctuations from deuterium excess in some instances.

Comparison of the impacts of urban development and climate change on exposing European cities to pluvial flooding

NASA Astrophysics Data System (ADS)

Skougaard Kaspersen, Per; Høegh Ravn, Nanna; Arnbjerg-Nielsen, Karsten; Madsen, Henrik; Drews, Martin

2017-08-01

The economic and human consequences of extreme precipitation and the related flooding of urban areas have increased rapidly over the past decades. Some of the key factors that affect the risks to urban areas include climate change, the densification of assets within cities and the general expansion of urban areas. In this paper, we examine and compare quantitatively the impact of climate change and recent urban development patterns on the exposure of four European cities to pluvial flooding. In particular, we investigate the degree to which pluvial floods of varying severity and in different geographical locations are influenced to the same extent by changes in urban land cover and climate change. We have selected the European cities of Odense, Vienna, Strasbourg and Nice for analyses to represent different climatic conditions, trends in urban development and topographical characteristics. We develop and apply a combined remote-sensing and flood-modelling approach to simulate the extent of pluvial flooding for a range of extreme precipitation events for historical (1984) and present-day (2014) urban land cover and for two climate-change scenarios (i.e. representative concentration pathways, RCP 4.5 and RCP 8.5). Changes in urban land cover are estimated using Landsat satellite imagery for the period 1984-2014. We combine the remote-sensing analyses with regionally downscaled estimates of precipitation extremes of current and expected future climate to enable 2-D overland flow simulations and flood-hazard assessments. The individual and combined impacts of urban development and climate change are quantified by examining the variations in flooding between the different simulations along with the corresponding uncertainties. In addition, two different assumptions are examined with regards to the development of the capacity of the urban drainage system in response to urban development and climate change. In the stationary approach, the capacity resembles present-day design, while it is updated in the evolutionary approach to correspond to changes in imperviousness and precipitation intensities due to urban development and climate change respectively. For all four cities, we find an increase in flood exposure corresponding to an observed absolute growth in impervious surfaces of 7-12 % during the past 30 years of urban development. Similarly, we find that climate change increases exposure to pluvial flooding under both the RCP 4.5 and RCP 8.5 scenarios. The relative importance of urban development and climate change on flood exposure varies considerably between the cities. For Odense, the impact of urban development is comparable to that of climate change under an RCP 8.5 scenario (2081-2100), while for Vienna and Strasbourg it is comparable to the impacts of an RCP 4.5 scenario. For Nice, climate change dominates urban development as the primary driver of changes in exposure to flooding. The variation between geographical locations is caused by differences in soil infiltration properties, historical trends in urban development and the projected regional impacts of climate change on extreme precipitation. Developing the capacity of the urban drainage system in relation to urban development is found to be an effective adaptation measure as it fully compensates for the increase in run-off caused by additional sealed surfaces. On the other hand, updating the drainage system according to changes in precipitation intensities caused by climate change only marginally reduces flooding for the most extreme events.

Experimental Results of Fractionation of HDO and H2O with simulated Martian Dust: Implications for the interpretation of past climate on Mars

NASA Astrophysics Data System (ADS)

Moores, J. E.; Smith, P.; Brown, R.; Lauretta, D.; Boynton, W.

2009-05-01

Climate change on Mars has been greatly debated in recent years. This has been motivated by the results from the Mars Reconnaissance Orbiter, Phoenix Lander and ground-based spectroscopic studies which have found mounting evidence that not only may Mars have had a wet and warm past, but those conditions inclement to life may also have been present more recently. On Mars, this is largely a story of water transport and, as on the Earth, isotopic analysis presents a key to understanding and decoding the Martian paleoclimate. For Mars, the major fractionation observed is in HDO, analogous to the Oxygen-18 cycle on Earth, and observations have shown that the D/H ratio of the planet is enriched by a factor of 5 to 6 from comparable terrestrial values. The conventional explanation is that a great deal of water has been lost to space over geologic time. However, previous studies have not taken into account the ability of present-day Mars to fractionate water as it moves from the polar caps to the polar layered deposits through the atmosphere, potentially masking any climate signal which may exist. In this presentation, we shall report on a series of Mars analogue experiments completed at the relevant ranges of pressure and temperature. Two different scenarios were simulated: the sublimation of dusty water ice and the sublimation of clean water ice through a simulated regolith/dust lag. In both cases, we have found that the system is dominated by adsorption of water. However, the simulant dust (JSC-1) appears to be an extremely efficient vehicle for fractionating water at cold temperatures, as different desorption rates have been recorded for HDO and H2O. This, when coupled with the relatively small amount of water exchanging today implies heavy fractionations in the current Mars system without requiring significant water losses to space.

Tourism climate and thermal comfort in Sun Moon Lake, Taiwan.

PubMed

Lin, Tzu-Ping; Matzarakis, Andreas

2008-03-01

Bioclimate conditions at Sun Moon Lake, one of Taiwan's most popular tourist destinations, are presented. Existing tourism-related climate is typically based on mean monthly conditions of air temperature and precipitation and excludes the thermal perception of tourists. This study presents a relatively more detailed analysis of tourism climate by using a modified thermal comfort range for both Taiwan and Western/Middle European conditions, presented by frequency analysis of 10-day intervals. Furthermore, an integrated approach (climate tourism information scheme) is applied to present the frequencies of each facet under particular criteria for each 10-day interval, generating a time-series of climate data with temporal resolution for tourists and tourism authorities.

Tourism climate and thermal comfort in Sun Moon Lake, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Tzu-Ping; Matzarakis, Andreas

2008-03-01

Bioclimate conditions at Sun Moon Lake, one of Taiwan’s most popular tourist destinations, are presented. Existing tourism-related climate is typically based on mean monthly conditions of air temperature and precipitation and excludes the thermal perception of tourists. This study presents a relatively more detailed analysis of tourism climate by using a modified thermal comfort range for both Taiwan and Western/Middle European conditions, presented by frequency analysis of 10-day intervals. Furthermore, an integrated approach (climate tourism information scheme) is applied to present the frequencies of each facet under particular criteria for each 10-day interval, generating a time-series of climate data with temporal resolution for tourists and tourism authorities.

Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Li, Gen; Xie, Shang-Ping; He, Chao; Chen, Zesheng

2017-10-01

The agrarian-based socioeconomic livelihood of densely populated South Asian countries is vulnerable to modest changes in Indian summer monsoon (ISM) rainfall. How the ISM rainfall will evolve is a question of broad scientific and socioeconomic importance. In response to increased greenhouse gas (GHG) forcing, climate models commonly project an increase in ISM rainfall. This wetter ISM projection, however, does not consider large model errors in both the mean state and ocean warming pattern. Here we identify a relationship between biases in simulated present climate and future ISM projections in a multi-model ensemble: models with excessive present-day precipitation over the tropical western Pacific tend to project a larger increase in ISM rainfall under GHG forcing because of too strong a negative cloud-radiation feedback on sea surface temperature. The excessive negative feedback suppresses the local ocean surface warming, strengthening ISM rainfall projections via atmospheric circulation. We calibrate the ISM rainfall projections using this `present-future relationship’ and observed western Pacific precipitation. The correction reduces by about 50% of the projected rainfall increase over the broad ISM region. Our study identifies an improved simulation of western Pacific convection as a priority for reliable ISM projections.

Projection of the change in future extremes over Japan using a cloud-resolving model: (2) Precipitation Extremes and the results of the NHM-1km experiments

NASA Astrophysics Data System (ADS)

Kanada, S.; Nakano, M.; Nakamura, M.; Hayashi, S.; Kato, T.; Kurihara, K.; Sasaki, H.; Uchiyama, T.; Aranami, K.; Honda, Y.; Kitoh, A.

2008-12-01

In order to study changes in the regional climate in the vicinity of Japan during the summer rainy season due to global warming, experiments by a semi-cloud resolving non-hydrostatic model with a horizontal resolution of 5km (NHM-5km) have been conducted from June to October by nesting within the results of the 10-year time-integrated experiments using a hydrostatic atmospheric general circulation model with a horizontal grid of 20 km (AGCM-20km: TL959L60) for the present and future up to the year 2100. A non-hydrostatic model developed by the Japan Meteorological Agency (JMA) (JMA-NHM; Saito et al. 2001, 2006) was adopted. Detailed descriptions of the NHM-5km are shown by the poster of Nakano et al. Our results show that rainy days over most of the Japanese Islands will decrease in June and July and increase in August and September in the future climate. Especially, remarkable increases in intense precipitations such as larger than 150 - 300 mm/day are projected from the present to future climate. The 90th percentiles of regional largest values among maximum daily precipitations (R-MDPs) grow 156 to 207 mm/day in the present and future climates, respectively. It is well-known that the horizontal distribution of precipitation, especially the heavy rainfall in the vicinity of Japan, much depends on the topography. Therefore, higher resolution experiments by a cloud-resolving model with a horizontal resolution of 1km (NHM-1km) are one-way nested within the results of NHM-5km. The basic frame and design of the NHM-1km is the same as those of the NHM-5km, but the topography is finer and no cumulus parameterization is used in the NHM-1km experiments. The NHM-1km, which treats the convection and cloud microphysics explicitly, can represent not only horizontal distributions of rainfall in detail but also the 3-dimensional structures of meso-beta-scale convective systems (MCSs). Because of the limitation of computation resources, only heavy rainfall events that rank in top 10 % of all rainfall events are selected for the NHM-1km experiments (Heavy rainfall events are defined by R-MDPs > 156 and 207 mm/day for the present and future climates, respectively, from the results of the NHM-5km). Tentative comparisons between the results of the NHM-1km and NHM-1km experiments reveal that the NHM-1km can re-produce more detailed and realistic horizontal distributions of rainfall in many cases. (This study is supported by the Ministry of Education, Culture, Sports, Science and Technology under the framework of the KAKUSHIN program. Numerical simulations are performed in the Earth Simulator)

Air pollution control and decreasing new particle formation lead to strong climate warming

NASA Astrophysics Data System (ADS)

Makkonen, R.; Asmi, A.; Kerminen, V.-M.; Boy, M.; Arneth, A.; Hari, P.; Kulmala, M.

2011-09-01

The number of cloud droplets determines several climatically relevant cloud properties. A major cause for the high uncertainty in the indirect aerosol forcing is the availability of cloud condensation nuclei (CCN), which in turn is highly sensitive to atmospheric new particle formation. Here we present the effect of new particle formation on anthropogenic aerosol forcing in present-day (year 2000) and future (year 2100) conditions. The total aerosol forcing (-1.61 W m-2 in year 2000) is simulated to be greatly reduced in the future, to -0.23 W m-2, mainly due to decrease in SO2 emissions and resulting decrease in new particle formation. With the total aerosol forcing decreasing in response to air pollution control measures taking effect, warming from increased greenhouse gas concentrations can potentially increase at a very rapid rate.

Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; McQuade, Scott

2014-01-01

The goal of climate informatics, an emerging discipline, is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the field's remaining challenges. Given the impact of climate change, understanding the climate system is an international priority. The goal of climate informatics is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the remaining challenges.

Contributions of Uncertainty in Droplet Nucleation to the Indirect Effect in Global Models

NASA Astrophysics Data System (ADS)

Rothenberg, D. A.; Wang, C.; Avramov, A.

2016-12-01

Anthropogenic aerosol perturbations to clouds and climate (the indirect effect, or AIE) contribute significant uncertainty towards understanding contemporary climate change. Despite refinements over the past two decades, modern global aerosol-climate models widely disagree on the magnitude of AIE, and wholly disagree with satellite estimates. Part of the spread in estimates of AIE arises from a lack of constraints on what exactly comprised the pre-industrial atmospheric aerosol burden, but another component is attributable to inter-model differences in simulating the chain of aerosol-cloud-precipitation processes which ultimately produce the indirect effect. Thus, one way to help constrain AIE is to thoroughly investigate the differences in aerosol-cloud processes and interactions occurring in these models. We have configured one model, the CESM/MARC, with a suite of parameterizations affecting droplet activation. Each configuration produces similar climatologies with respect to precipitation and cloud macrophysics, but shows different sensitivies to aerosol perturbation - up to 1 W/m^2 differences in AIE. Regional differences in simulated aerosol-cloud interactions, especially in marine regions with little anthropogenic pollution, contribute to the spread in these AIE estimates. The baseline pre-industrial droplet number concentration in marine regions dominated by natural aerosol strongly predicts the magnitude of each model's AIE, suggesting that targeted observations of cloud microphysical properties across different cloud regimes and their sensitivity to aerosol influences could help provide firm constraints and targets for models. Additionally, we have performed supplemental fully-coupled (atmosphere/ocean) simulations with each model configuration, allowing the model to relax to equilibrium following a change in aerosol emissions. These simulations allow us to assess the slower-timescale responses to aerosol perturbations. The spread in fast model responses (which produce the noted changes in indirect effect or forcing) gives rise to large differences in the equilibrium climate state of each configuration. We show that these changes in equilibrium climate state have implications for AIE estimates from model configurations tuned to the present-day climate.

Future changes in Asian summer monsoon precipitation extremes as inferred from 20-km AGCM simulations

NASA Astrophysics Data System (ADS)

Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung

2018-04-01

This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further exacerbate the precipitation extremes, whereas those in the Baiu region lead to weaker changes of these extremes.

Future impacts of global warming and reforestation on drought patterns over West Africa

NASA Astrophysics Data System (ADS)

Diasso, Ulrich; Abiodun, Babatunde J.

2017-07-01

This study investigates how a large-scale reforestation in Savanna (8-12°N, 20°W-20°E) could affect drought patterns over West Africa in the future (2031-2060) under the RCP4.5 scenario. Simulations from two regional climate models (RegCM4 and WRF) were analyzed for the study. The study first evaluated the performance of both RCMs in simulating the present-day climate and then applied the models to investigate the future impacts of global warming and reforestation on the drought patterns. The simulated and observed droughts were characterized with the Standardized Precipitation and Evapotranspiration Index (SPEI), and the drought patterns were classified using a Self-organizing Map (SOM) technique. The models capture essential features in the seasonal rainfall and temperature fields (including the Saharan Heat Low), but struggle to reproduce the onset and retreat of the West African Monsoon as observed. Both RCMs project a warmer climate (about 1-2 °C) over West Africa in the future. They do not reach a consensus on future change in rainfall, but they agree on a future increase in frequency of severe droughts (by about 2 to 9 events per decade) over the region. They show that reforestation over the Savanna could reduce the future warming by 0.1 to 0.8 °C and increase the precipitation by 0.8 to 1.2 mm per day. However, the impact of reforestation on the frequency of severe droughts is twofold. While reforestation decreases the droughts frequency (by about 1-2 events per decade) over the Savanna and Guinea coast, it increases droughts frequency (by 1 event per decade) over the Sahel, especially in July to September. The results of this study have application in using reforestation to mitigate impacts of climate change in West Africa.

Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

NASA Astrophysics Data System (ADS)

Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

2015-01-01

In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30 day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

Climate-simulated raceway pond culturing: quantifying the maximum achievable annual biomass productivity of Chlorella sorokiniana in the contiguous USA

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

Huesemann, M.; Chavis, A.; Edmundson, S.

Chlorella sorokiniana (DOE 1412) emerged as one of the most promising microalgae strains from the NAABB consortium project, with a remarkable doubling time under optimal conditions of 2.57 hr-1. However, its maximum achievable annual biomass productivity in outdoor ponds in the contiguous United States remained unknown. In order to address this knowledge gap, this alga was cultured in indoor LED-lighted and temperature-controlled raceways in nutrient replete freshwater (BG-11) medium at pH 7 under conditions simulating the daily sunlight intensity and water temperature fluctuations during three seasons in Southern Florida, an optimal outdoor pond culture location for this organism identified bymore » biomass growth modeling. Prior strain characterization indicated that the average maximum specific growth rate (µmax) at 36 ºC declined continuously with pH, with µmax corresponding to 5.92, 5.83, 4.89, and 4.21 day-1 at pH 6, 7, 8, and 9, respectively. In addition, the maximum specific growth rate declined nearly linearly with increasing salinity until no growth was observed above 35 g/L NaCl. In the climate-simulated culturing studies, the volumetric ash-free dry weight-based biomass productivities during the linear growth phase were 57, 69, and 97 mg/L-day for 30-year average light and temperature simulations for January (winter), March (spring), and July (summer), respectively, which corresponds to average areal productivities of 11.6, 14.1, and 19.9 g/m2-day at a constant pond depth of 20.5 cm. The photosynthetic efficiencies (PAR) in the three climate-simulated pond culturing experiments ranged from 4.1 to 5.1%. The annual biomass productivity was estimated as ca. 15 g/m2-day, nearly double the U.S. Department of Energy (DOE) 2015 State of Technology annual cultivation productivity of 8.5 g/m2-day, but this is still significantly below the projected 2022 target of ca. 25 g/m2-day (U.S. DOE, 2016) for economic microalgal biofuel production, indicating the need for additional research in strain biology and system engineering.« less

Dynamical Downscaling of Climate Change over the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Wang, Y.; Zhang, C.; Hamilton, K. P.; Lauer, A.

2015-12-01

The pseudo-global-warming (PGW) method was applied to the Hawaii Regional Climate Model (HRCM) to dynamically downscale the projected climate in the late 21st century over the Hawaiian Islands. The initial and boundary conditions were adopted from MERRA reanalysis and NOAA SST data for the present-day simulations. The global warming increments constructed from the CMIP3 multi-model ensemble mean were added to the reanalysis and SST data to perform the future climate simulations. We found that the Hawaiian Islands are vulnerable to global warming effects and the changes are diverse due to the varied topography. The windward side will have more clouds and receive more rainfall. The increase of the moisture in the boundary layer makes the major contribution. On the contrary, the leeward side will have less clouds and rainfall. The clouds and rain can slightly slow down the warming trend over the windward side. The temperature increases almost linearly with the terrain height. Cloud base and top heights will slightly decline in response to the slightly lower trade wind inversion base height, while the trade wind occurrence frequency will increase by about 8% in the future. More extreme rainfall events will occur in the warming climate over the Hawaiian Islands. And the snow cover on the top of Mauna Kea and Mauna Loa will nearly disappear in the future winter.

A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae)

USGS Publications Warehouse

Ludwig, Antoinette; Ginsberg, Howard; Hickling, Graham J.; Ogden, Nicholas H.

2016-01-01

The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick.

A Dynamic Population Model to Investigate Effects of Climate and Climate-Independent Factors on the Lifecycle of Amblyomma americanum (Acari: Ixodidae).

PubMed

Ludwig, Antoinette; Ginsberg, Howard S; Hickling, Graham J; Ogden, Nicholas H

2016-01-01

The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick. © Crown copyright 2015.

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

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

Unger, N.; Harper, K.; Zheng, Y.

2013-10-22

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball- Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the ratemore » of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R 2 = 64-96 %) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr -1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.« less

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

NASA Technical Reports Server (NTRS)

Unger, N.; Harper, K.; Zeng, Y.; Kiang, N. Y.; Alienov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.;

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-10-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar-Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Photosynthesis-dependent isoprene emission from leaf to planet in a global carbon-chemistry-climate model

NASA Astrophysics Data System (ADS)

Unger, N.; Harper, K.; Zheng, Y.; Kiang, N. Y.; Aleinov, I.; Arneth, A.; Schurgers, G.; Amelynck, C.; Goldstein, A.; Guenther, A.; Heinesch, B.; Hewitt, C. N.; Karl, T.; Laffineur, Q.; Langford, B.; McKinney, K. A.; Misztal, P.; Potosnak, M.; Rinne, J.; Pressley, S.; Schoon, N.; Serça, D.

2013-07-01

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball-Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2= 64-96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 Tg C yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Response of carbon fluxes and climate to orbital forcing changes in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Jochum, M.; Peacock, S.; Moore, J. K.; Lindsay, K. T.

2009-12-01

A global general circulation model coupled to an ocean ecosystem model is used to quantify the response of carbon fluxes and climate to changes in orbital forcing. Compared to the present-day simulation, the simulation with the Earth's orbital parameters from 115,000 years ago features significantly cooler northern high latitudes, but only moderately cooler southern high latitudes. This asymmetry is explained by a 30% reduction of the strength of the Atlantic Meridional Overturning Circulation that is caused by an increased Arctic sea-ice export and a resulting freshening of the North Atlantic. The strong northern high-latitude cooling and the direct insolation induced tropical warming lead to global shifts in precipitation and winds to the order of 10-20%. These climate shifts lead to regional differences in air-sea carbon fluxes of the same order. However, the differences in global net carbon fluxes are insignificant. This surprising result is due to several effects, two of which stand out: Firstly, colder sea surface temperature leads to a more effective solubility pump but also to increased sea-ice concentration which blocks air-sea exchange; and secondly, the weakening of Southern Ocean winds, which is predicted by some idealized studies, is small compared to its interannual variability.

Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

NASA Astrophysics Data System (ADS)

Joetzjer, E.; Delire, C.; Douville, H.; Ciais, P.; Decharme, B.; Fisher, R.; Christoffersen, B.; Calvet, J. C.; da Costa, A. C. L.; Ferreira, L. V.; Meir, P.

2014-08-01

While a majority of Global Climate Models project dryer and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC Land Surface Model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent ThroughFall Exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different Water Stress Function (WSF) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentration, the increased Water Use Efficiency (WUE) mitigates the ISBACC's sensitivity to drought. While one of the proposed WSF formulation improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

Climate-induced changes in river water temperature in North Iberian Peninsula

NASA Astrophysics Data System (ADS)

Soto, Benedicto

2017-06-01

This study evaluates the effects of climate change on the thermal regime of 12 rivers in the Northern Iberian Peninsula by using a non-linear regression model that employs air temperature as the only input variable. Prediction of future air temperature was obtained from five regional climate models (RCMs) under emission scenario Special Report on Emissions Scenarios A1B. Prior to simulation of water temperature, air temperature was bias-corrected (B-C) by means of variance scaling (VS) method. This procedure allows an improvement of fit between observed and estimated air temperature for all climate models. The simulation of water temperature for the period 1990-2100 shows an increasing trend, which is higher for the period of June-August (summer) and September-November (autumn) (0.0275 and 0.0281 °C/year) than that of winter (December-February) and spring (March-May) (0.0181 and 0.0218 °C/year). In the high air temperature range, daily water temperature is projected to increase on average by 2.2-3.1 °C for 2061-2090 relative to 1961-1990. During the coldest days, the increment of water temperature would range between 1.0 and 1.7 °C. In fact, employing the numbers of days that water temperature exceeded the upper incipient lethal temperature (UILT) for brown trout (24.7 °C) has been noted that this threshold is exceeded 14.5 days per year in 2061-2090 while in 1961-1990, this values was exceeded 2.6 days per year of mean and 3.6 days per year in observation period (2000-2014).

An Iberian climatology of solar radiation obtained from WRF regional climate simulations for 1950-2010 period

NASA Astrophysics Data System (ADS)

Perdigão, João; Salgado, Rui; Magarreiro, Clarisse; Soares, Pedro M. M.; Costa, Maria João; Dasari, Hari Prasad

2017-12-01

The mesoscale Weather Research and Forecasting (WRF) Model is used over the Iberian Peninsula to generate 60 years (1950-2010) of climate data, at 5 km resolution, in order to evaluate and characterize the incident shortwave downward radiation at the surface (SW ↓), in present climate. The simulated values of SW ↓ in the period 2000-2009 were compared with data measured in Spanish and Portuguese meteorological stations before and a statistical BIAS correction was applied using data from Clouds and the Earth's Radiant Energy System (CERES), on board four different satellites. The spatial and temporal comparison between WRF results and observations show a good agreement for the analyzed period, although the model overestimates observations. This overestimation has a mean normalized bias of about 7% after BIAS correction (or 17% for original WRF output). Additionally, the present simulation was confronted against another previously validated WRF simulation performed with different resolution and set of parametrizations, showing comparable results. WRF adequately reproduces the observational features of SW ↓ with correlation coefficients above 0.8 in annual and seasonal basis. 60 years of simulated SW ↓ over the Iberian Peninsula were produced, which showed annual mean values that range from 130 W/m2, in the northern regions, to a maximum of around 230 W/m2 in the southeast of the Iberian Peninsula (IP). SW ↓ over IP shows a positive gradient from north to south and from west to east, with local effects influenced by topography and distance to the coast. The analysis of the simulated cloud fraction indicates that clear sky days are found in > 30% of the period at the southern area of IP, particularly in the Algarve (Portugal) and Andalusia (Spain), and this value increases significantly in the summer season for values above 80%.

Late Quaternary glacier sensitivity to temperature and precipitation distribution in the Southern Alps of New Zealand

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

Ann V. Rowan; Simon H. Brocklehurst; David M. Schultz

2014-05-01

Glaciers respond to climate variations and leave geomorphic evidence that represents an important terrestrial paleoclimate record. However, the accuracy of paleoclimate reconstructions from glacial geology is limited by the challenge of representing mountain meteorology in numerical models. Precipitation is usually treated in a simple manner and yet represents difficult-to-characterize variables such as amount, distribution, and phase. Furthermore, precipitation distributions during a glacial probably differed from present-day interglacial patterns. We applied two models to investigate glacier sensitivity to temperature and precipitation in the eastern Southern Alps of New Zealand. A 2-D model was used to quantify variations in the length ofmore » the reconstructed glaciers resulting from plausible precipitation distributions compared to variations in length resulting from change in mean annual air temperature and precipitation amount. A 1-D model was used to quantify variations in length resulting from interannual climate variability. Assuming that present-day interglacial values represent precipitation distributions during the last glacial, a range of plausible present-day precipitation distributions resulted in uncertainty in the Last Glacial Maximum length of the Pukaki Glacier of 17.1?km (24%) and the Rakaia Glacier of 9.3?km (25%), corresponding to a 0.5°C difference in temperature. Smaller changes in glacier length resulted from a 50% decrease in precipitation amount from present-day values (-14% and -18%) and from a 50% increase in precipitation amount (5% and 9%). Our results demonstrate that precipitation distribution can produce considerable variation in simulated glacier extents and that reconstructions of paleoglaciers should include this uncertainty.« less

SIMULATING REGIONAL-SCALE AIR QUALITY WITH DYNAMIC CHANGES IN REGIONAL CLIMATE AND CHEMICAL BOUNDARY CONDITIONS

EPA Science Inventory

This poster compares air quality modeling simulations under current climate and a future (approximately 2050) climate scenario. Differences in predicted ozone episodes and daily average PM_2.5 concentrations are presented, along with vertical ozone profiles. Modeling ...

Can climate models be tuned to simulate the global mean absolute temperature correctly?

NASA Astrophysics Data System (ADS)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

Climate Variability In The Euro-atlantic Sector As Simulated By Echam4

NASA Astrophysics Data System (ADS)

Menezes, I.; Corte-Real, J.; Ramos, A.; Conde, F.

The atmosphere is a fundamental component of the climate system and its influence in local and global climates results from its composition, structure and motion. The best available tools to simulate future climates are coupled atmosphere-ocean general circulation models (AOGCMs), ECHAM4 (T42 L19)[1] being a very relevant exam- ple of such a model due to its elaborated parametrizations of physical processes. The purpose of this work is twofold : (1) to assess the ability of ECHAM4 in reproducing the reference climate of 1961-1990, over the Euro-Atlantic sector (29N-71N; 67W- 59E) in terms of mean sea level pressure, surface temperature and total precipitation; (2) to evaluate the expected changes of the same climate elements in a warmer world. To attain the first goal the ECHAMSs control run output is compared with observed data obtained from the Climatic Research Unit (CRU data set)[2-5]; to achieve the second objective, the modelSs control run is compared with its transient run forced by greenhouse gases. In both cases, comparisons are made in terms of mean values, variability in space and time and extremes. References [1] E. Roeckner, K. Arpe, L. Bengtsson, M. Christoph, M. Claussen, L. Dümenil, M. Esch, M. Giorgetta, U. Schlese, and U. Schulzweida, 1996: The atmospheric gen- eral circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institut für Meteorologie, Report No. 218, Hamburg, Germany, 90 pp. [2] M. Hulme, D. Conway, P.D. Jones, T. Jiang, E.M. Barrow, and C. Turney (1995), Construction of a 1961-90 European climatology for climate change impacts and mod- elling applications, Int. J. Climatol., 15, 1333-1363. [3] M. Hulme (1994), The cost of climate data U a European experience, Weather, 49, 168-175. [4] M. Hulme, and M.G. New (1997), Dependence of large-scale precipitation clima- tologies on temporal and spatial sampling, J. Climate, 10, 1099-1113. 1 [5] C.J. Willmot, S.M. Robeson and M.J. Janis (1996), Comparison of approaches for estimating time-averaged precipitation using data from the United States, Int. J. Cli- matol., 16, 1103-1115. 2

Irrigation mitigates against heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Fischer, Erich; Visser, Auke; Hirsch, Annette L.; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I.

2017-04-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use gridded observations and ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on hot extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Finally we find that present-day irrigation is partly masking GHG-induced warming of extreme temperatures, with particularly strong effects in South Asia. Our results overall underline that irrigation substantially reduces our exposure to hot temperature extremes and highlight the need to account for irrigation in future climate projections.

Atmospheric Rivers Induced Heavy Precipitation and Flooding in the Western U.S. Simulated by the WRF Regional Climate Model

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

Leung, Lai R.; Qian, Yun

2009-02-12

Twenty years of regional climate simulated by the Weather Research and Forecasting model for North America has been analyzed to study the influence of the atmospheric rivers and the role of the land surface on heavy precipitation and flooding in the western U.S. Compared to observations, the simulation realistically captured the 95th percentile extreme precipitation, mean precipitation intensity, as well as the mean precipitation and temperature anomalies of all the atmospheric river events between 1980-1999. Contrasting the 1986 President Day and 1997 New Year Day atmospheric river events, differences in atmospheric stability are found to have an influence on themore » spatial distribution of precipitation in the Coastal Range of northern California. Although both cases yield similar amounts of heavy precipitation, the 1997 case was found to produce more runoff compared to the 1986 case. Antecedent soil moisture, the ratio of snowfall to total precipitation (which depends on temperature), and existing snowpack all seem to play a role, leading to a higher runoff to precipitation ratio simulated for the 1997 case. This study underscores the importance of characterizing or simulating atmospheric rivers and the land surface conditions for predicting floods, and for assessing the potential impacts of climate change on heavy precipitation and flooding in the western U.S.« less

Fog and rain in the Amazon

PubMed Central

Anber, Usama; Gentine, Pierre; Wang, Shuguang; Sobel, Adam H.

2015-01-01

The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget. These results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents. PMID:26324902

Fog and rain in the Amazon

DOE PAGES

Anber, Usama; Gentine, Pierre; Wang, Shuguang; ...

2015-08-31

The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget.more » Finally, these results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.« less

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

Anber, Usama; Gentine, Pierre; Wang, Shuguang

The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget.more » Finally, these results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.« less

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

NASA Astrophysics Data System (ADS)

Rothenberg, Daniel; Avramov, Alexander; Wang, Chien

2018-06-01

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

Superensemble of a Regional Climate Model for the Western US using Climateprediction.net

NASA Astrophysics Data System (ADS)

Mote, P.; Salahuddin, A.; Allen, M.; Jones, R.

2010-12-01

For over a decade, a citizen science experiment called climateprediction.net organized by Oxford University has used computer time contributed by over 80,000 volunteers around the world to create superensembles of global climate simulations. A new climateprediction.net experiment built by the UK Meteorological Office and Oxford, and released in late summer 2010, brings these computing resources to bear on regional climate modeling for the Western US, western Europe, and southern Africa. For the western US, the spatial resolution of 25km permits important topological features -- mountain ranges and valleys -- to be resolved and to influence simulated climate, which consequently includes many important observed features of climate like the fact that California’s Central Valley is hottest at the north and south ends in summer, and cooler in the middle owing to the maritime influence that leaks through the gap in the coast range in the San Francisco area. We designed the output variables to satisfy both research needs and societal and environmental impacts needs. These include atmospheric circulation on regional and global scales, surface fluxes of energy, and hydrologic variables; extremes of temperature, precipitation, and wind; and derived quantities like frost days and number of consecutive dry days. Early results from pre-release beta testing suggest that the simulated fields compare favorably with available observations, and that the model performs as well in the distributed computing environment as on a dedicated high-performance machine. The advantages of a superensemble in interpreting regional climate change will permit an unprecedented combination of statistical completeness and spatial resolution.

Scaling a Convection-Resolving RCM to Near-Global Scales

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Chadha, T.; Kwasniewski, G.; Hoefler, T.; Lapillonne, X.; Lüthi, D.; Osuna, C.; Schar, C.; Schulthess, T. C.; Vogt, H.

2017-12-01

In the recent years, first decade-long kilometer-scale resolution RCM simulations have been performed on continental-scale computational domains. However, the size of the planet Earth is still an order of magnitude larger and thus the computational implications of performing global climate simulations at this resolution are challenging. We explore the gap between the currently established RCM simulations and global simulations by scaling the GPU accelerated version of the COSMO model to a near-global computational domain. To this end, the evolution of an idealized moist baroclinic wave has been simulated over the course of 10 days with a grid spacing of up to 930 m. The computational mesh employs 36'000 x 16'001 x 60 grid points and covers 98.4% of the planet's surface. The code shows perfect weak scaling up to 4'888 Nodes of the Piz Daint supercomputer and yields 0.043 simulated years per day (SYPD) which is approximately one seventh of the 0.2-0.3 SYPD required to conduct AMIP-type simulations. However, at half the resolution (1.9 km) we've observed 0.23 SYPD. Besides formation of frontal precipitating systems containing embedded explicitly-resolved convective motions, the simulations reveal a secondary instability that leads to cut-off warm-core cyclonic vortices in the cyclone's core, once the grid spacing is refined to the kilometer scale. The explicit representation of embedded moist convection and the representation of the previously unresolved instabilities exhibit a physically different behavior in comparison to coarser-resolution simulations. The study demonstrates that global climate simulations using kilometer-scale resolution are imminent and serves as a baseline benchmark for global climate model applications and future exascale supercomputing systems.

Dynamically downscaling predictions for deciduous tree leaf emergence in California under current and future climate.

PubMed

Medvigy, David; Kim, Seung Hee; Kim, Jinwon; Kafatos, Menas C

2016-07-01

Models that predict the timing of deciduous tree leaf emergence are typically very sensitive to temperature. However, many temperature data products, including those from climate models, have been developed at a very coarse spatial resolution. Such coarse-resolution temperature products can lead to highly biased predictions of leaf emergence. This study investigates how dynamical downscaling of climate models impacts simulations of deciduous tree leaf emergence in California. Models for leaf emergence are forced with temperatures simulated by a general circulation model (GCM) at ~200-km resolution for 1981-2000 and 2031-2050 conditions. GCM simulations are then dynamically downscaled to 32- and 8-km resolution, and leaf emergence is again simulated. For 1981-2000, the regional average leaf emergence date is 30.8 days earlier in 32-km simulations than in ~200-km simulations. Differences between the 32 and 8 km simulations are small and mostly local. The impact of downscaling from 200 to 8 km is ~15 % smaller in 2031-2050 than in 1981-2000, indicating that the impacts of downscaling are unlikely to be stationary.

How much rainfall sustained a Green Sahara during the mid-Holocene?

NASA Astrophysics Data System (ADS)

Hopcroft, Peter; Valdes, Paul; Harper, Anna

2016-04-01

The present-day Sahara desert has periodically transformed to an area of lakes and vegetation during the Quaternary in response to orbitally-induced changes in the monsoon circulation. Coupled atmosphere-ocean general circulation model simulations of the mid-Holocene generally underestimate the required monsoon shift, casting doubt on the fidelity of these models. However, the climatic regime that characterised this period remains unclear. To address this, we applied an ensemble of dynamic vegetation model simulations using two different models: JULES (Joint UK Land Environment Simulator) a comprehensive land surface model, and LPJ (Lund-Potsdam-Jena model) a widely used dynamic vegetation model. The simulations are forced with a number of idealized climate scenarios, in which an observational climatology is progressively altered with imposed anomalies of precipitation and other related variables, including cloud cover and humidity. The applied anomalies are based on an ensemble of general circulation model simulations, and include seasonal variations but are spatially uniform across the region. When perturbing precipitation alone, a significant increase of at least 700mm/year is required to produce model simulations with non-negligible vegetation coverage in the Sahara region. Changes in related variables including cloud cover, surface radiation fluxes and humidity are found to be important in the models, as they modify the water balance and so affect plant growth. Including anomalies in all of these variables together reduces the precipitation change required for a Green Sahara compared to the case of increasing precipitation alone. We assess whether the precipitation changes implied by these vegetation model simulations are consistent with reconstructions for the mid-Holocene from pollen samples. Further, Earth System models predict precipitation increases that are significantly smaller than that inferred from these vegetation model simulations. Understanding this difference presents an ongoing challenge.

Projections of Rapidly Rising Temperatures over Africa Under Low Mitigation

NASA Technical Reports Server (NTRS)

Engelbrecht, Francois; Adegoke, Jimmy; Bopape, Mary-Jane; Naidoo, Mogesh; Garland, Rebecca; Thatcher, Marcus; McGregor, John; Katzfe, Jack; Werner, Micha; Ichoku, Charles;

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

NASA Technical Reports Server (NTRS)

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua

2015-01-01

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

RACORO continental boundary layer cloud investigations. 3. Separation of parameterization biases in single-column model CAM5 simulations of shallow cumulus

DOE PAGES

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; ...

2015-06-19

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only amore » relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.« less

Increased flood risks in the Sacramento-San Joaquin Valleys, CA, under climate change

NASA Astrophysics Data System (ADS)

Das, T.; Hidalgo-Leon, H.; Dettinger, M.; Cayan, D.

2008-12-01

Natural calamities like floods cause immense damages to human society globally, and California is no exception. A simulation analysis of flood generation in the western Sierra Nevada of California was carried out on simulated by the Variable Infiltration Capacity (VIC) hydrologic model under prescribed changes in precipitation (+10 percent) and temperature (+3oC and +5oC) to evaluate likely changes in 3-day flood- frequency curves under climate change. An additional experiment was carried out where snow production was artificially turned off in VIC. All these experiments showed larger flood magnitudes from California's Northern Sierra Nevada (NSN) and Southern Sierra Nevada (SSN), but the changes (for floods larger than the historical 20-year floods) were significant (at 90 percent confidence level) only in the SSN for severe warming cases. Another analysis using downscaled daily precipitation and temperature projections from three General Circulation Models (CNRM CM3, GFDL CM2.1 and NCAR PCM1) and emission scenario A2 as input to VIC yielded a general increase in the 3-days annual maximum flows under climate change. The increases are significant (at 90 percent confidence level) in the SSN for the period 2051-2099 with all the three climate models analyzed. In the NSN the increases are significant only with the CNRM CM3 model. In general, the frequency of floods increases or stayed same under the projected future climates, and some of the projected floods were unprecedentedly large when compared to historical simulations.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-05

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

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.

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.

Development of a Simple Framework to Assess Hydrological Extremes using Solely Climate Data

NASA Astrophysics Data System (ADS)

Foulon, E.; Gagnon, P.; Rousseau, A. N.

2014-12-01

Extreme flow conditions such as droughts and floods are in general the direct consequences of short- to long-term weather/climate anomalies. For example, in southern Quebec, Canada, winter and summer 7-day low flows are due to summer and fall precipitations. Which prompts the question: is it possible to assess future extreme flow conditions from meteorological/climate indices or should we rely on the classical approach of using outputs of climate models as input to a hydrological model? The objective of this study is to assess six hydrological indices describing extreme flows at the watershed scale (Qmax, Qmin;7d, Qmin;30d for two seasons: winter and summer) using local climate indices without relying on the aforementioned classical approach. To establish the relationship between climate and hydrological indices, daily precipitations, minimum and maximum temperatures from 89 climate projections are used as inputs to a distributed hydrological model. River flows are simulated at the outlet of the Yamaska and Bécancour watersheds in Québec for the 1961-2100 periods. To identify the best predictors, hydrological indices are extracted from the flow series, and climate indices are computed for different time intervals (from a day up to four years). The difference between four-month, cumulative, climatic demand (P-ETP) explains 69% of the 7-day summer low flow during the calibration process. For both watersheds, preliminary findings indicate that the selected indices explain, on average, 38 and 60% of the variability of high- and low-flow indices, respectively. Overall, the results clearly illustrate that the change in the hydrological indices can be detected through the concurrent trends in the climate indices. The use of many climate projections ensures the relationships are not simulation-dependent and shows summer events are particularly at risk with increasing high flows and decreasing low flows. The development of a simple predictive tool to assess the impact of climate change on flows represents one of the major spin-off benefits of this study and may prooveto be useful to municipalities concerned with source water and flood management. Future work includes development of additional climate indices and application of the framework to more watersheds.

The New England Climate Adaptation Project: Enhancing Local Readiness to Adapt to Climate Change through Role-Play Simulations

NASA Astrophysics Data System (ADS)

Rumore, D.; Kirshen, P. H.; Susskind, L.

2014-12-01

Despite scientific consensus that the climate is changing, local efforts to prepare for and manage climate change risks remain limited. How we can raise concern about climate change risks and enhance local readiness to adapt to climate change's effects? In this presentation, we will share the lessons learned from the New England Climate Adaptation Project (NECAP), a participatory action research project that tested science-based role-play simulations as a tool for educating the public about climate change risks and simulating collective risk management efforts. NECAP was a 2-year effort involving the Massachusetts Institute of Technology, the Consensus Building Institute, the National Estuarine Research Reserve System, and four coastal New England municipalities. During 2012-2013, the NECAP team produced downscaled climate change projections, a summary risk assessment, and a stakeholder assessment for each partner community. Working with local partners, we used these assessments to create a tailored, science-based role-play simulation for each site. Through a series of workshops in 2013, NECAP engaged between 115-170 diverse stakeholders and members of the public in each partner municipality in playing the simulation and a follow up conversation about local climate change risks and possible adaptation strategies. Data were collected through before-and-after surveys administered to all workshop participants, follow-up interviews with 25 percent of workshop participants, public opinion polls conducted before and after our intervention, and meetings with public officials. This presentation will report our research findings and explain how science-based role-play simulations can be used to help communicate local climate change risks and enhance local readiness to adapt.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-06-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall, the day-to-day variability is crucial for the risk of flooding, national water supply, and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the AR-5 of the Intergovernmental Panel on Climate Change, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. The relative increase by the period 2071-2100 with respect to the control period 1871-1900 ranges from 13% to 50% under the strongest scenario (Representative Concentration Pathways, RCP-8.5), in the 10 models with the most realistic monsoon climatology; and 13% to 85% when all the 20 models are considered. The spread across models reduces when variability increase per degree of global warming is considered, which is independent of the scenario in most models, and is 8% ± 4%/K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

NASA Astrophysics Data System (ADS)

Belušić, Andreina; Prtenjak, Maja Telišman; Güttler, Ivan; Ban, Nikolina; Leutwyler, David; Schär, Christoph

2018-06-01

Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

NASA Technical Reports Server (NTRS)

Redemann, Jens

2018-01-01

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Detailed climate-change projections for urban land-use change and green-house gas increases for Belgium with COSMO-CLM coupled to TERRA_URB

NASA Astrophysics Data System (ADS)

Wouters, Hendrik; Vanden Broucke, Sam; van Lipzig, Nicole; Demuzere, Matthias

2016-04-01

Recent research clearly show that climate modelling at high resolution - which resolve the deep convection, the detailed orography and land-use including urbanization - leads to better modelling performance with respect to temperatures, the boundary-layer, clouds and precipitation. The increasing computational power enables the climate research community to address climate-change projections with higher accuracy and much more detail. In the framework of the CORDEX.be project aiming for coherent high-resolution micro-ensemble projections for Belgium employing different GCMs and RCMs, the KU Leuven contributes by means of the downscaling of EC-EARTH global climate model projections (provided by the Royal Meteorological Institute of the Netherlands) to the Belgian domain. The downscaling is obtained with regional climate simulations at 12.5km resolution over Europe (CORDEX-EU domain) and at 2.8km resolution over Belgium (CORDEX.be domain) using COSMO-CLM coupled to urban land-surface parametrization TERRA_URB. This is done for the present-day (1975-2005) and future (2040 → 2070 and 2070 → 2100). In these high-resolution runs, both GHG changes (in accordance to RCP8.5) and urban land-use changes (in accordance to a business-as-usual urban expansion scenario) are taken into account. Based on these simulations, it is shown how climate-change statistics are modified when going from coarse resolution modelling to high-resolution modelling. The climate-change statistics of particular interest are the changes in number of extreme precipitation events and extreme heat waves in cities. Hereby, it is futher investigated for the robustness of the signal change between the course and high-resolution and whether a (statistical) translation is possible. The different simulations also allow to address the relative impact and synergy between the urban expansion and increased GHG on the climate-change statistics. Hereby, it is investigated for which climate-change statistics the urban heat island and urban expansion is relevant, and to what extent the urban expansion can be included in the coarse-to-high resolution translation.

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 extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Tropical cyclones in a stabilized 1.5 and 2 degree warmer world.

NASA Astrophysics Data System (ADS)

Wehner, M. F.; Stone, D. A.; Loring, B.; Krishnan, H.

2017-12-01

We present an ensemble of very high resolution global climate model simulations of a stabilized 1.5oC and 2oC warmer climate as envisioned by the Paris COP21 agreement. The resolution of this global climate model (25km) permits simulated tropical cyclones up to Category Five on the Saffir-Simpson scale Projected changes in tropical cyclones are significant. Tropical cyclones in the two stabilization scenarios are less frequent but more intense than in simulations of the present. Output data from these simulations is freely available to all interested parties and should prove a useful resource to those interested in studying the impacts of stabilized global warming.

Abrupt cooling over the North Atlantic in modern climate models

PubMed Central

Sgubin, Giovanni; Swingedouw, Didier; Drijfhout, Sybren; Mary, Yannick; Bennabi, Amine

2017-01-01

Observations over the 20th century evidence no long-term warming in the subpolar North Atlantic (SPG). This region even experienced a rapid cooling around 1970, raising a debate over its potential reoccurrence. Here we assess the risk of future abrupt SPG cooling in 40 climate models from the fifth Coupled Model Intercomparison Project (CMIP5). Contrary to the long-term SPG warming trend evidenced by most of the models, 17.5% of the models (7/40) project a rapid SPG cooling, consistent with a collapse of the local deep-ocean convection. Uncertainty in projections is associated with the models' varying capability in simulating the present-day SPG stratification, whose realistic reproduction appears a necessary condition for the onset of a convection collapse. This event occurs in 45.5% of the 11 models best able to simulate the observed SPG stratification. Thus, due to systematic model biases, the CMIP5 ensemble as a whole underestimates the chance of future abrupt SPG cooling, entailing crucial implications for observation and adaptation policy. PMID:28198383

Characterization of extreme sea level at the European coast

NASA Astrophysics Data System (ADS)

Elizalde, Alberto; Jorda, Gabriel; Mathis, Moritz; Mikolajewicz, Uwe

2015-04-01

Extreme high sea levels arise as a combination of storm surges and particular high tides events. Future climate simulations not only project changes in the atmospheric circulation, which induces changes in the wind conditions, but also an increase in the global mean sea level by thermal expansion and ice melting. Such changes increase the risk of coastal flooding, which represents a possible hazard for human activities. Therefore, it is important to investigate the pattern of sea level variability and long-term trends at coastal areas. In order to analyze further extreme sea level events at the European coast in the future climate projections, a new setup for the global ocean model MPIOM coupled with the regional atmosphere model REMO is prepared. The MPIOM irregular grid has enhanced resolution in the European region to resolve the North and the Mediterranean Seas (up to 11 x 11 km at the North Sea). The ocean model includes as well the full luni-solar ephemeridic tidal potential for tides simulation. To simulate the air-sea interaction, the regional atmospheric model REMO is interactively coupled to the ocean model over Europe. Such region corresponds to the EuroCORDEX domain with a 50 x 50 km resolution. Besides the standard fluxes of heat, mass (freshwater), momentum and turbulent energy input, the ocean model is also forced with sea level pressure, in order to be able to capture the full variation of sea level. The hydrological budget within the study domain is closed using a hydrological discharge model. With this model, simulations for present climate and future climate scenarios are carried out to study transient changes on the sea level and extreme events. As a first step, two simulations (coupled and uncoupled ocean) driven by reanalysis data (ERA40) have been conducted. They are used as reference runs to evaluate the climate projection simulations. For selected locations at the coast side, time series of sea level are separated on its different components: tides, short time atmospheric process influence (1-30 days), seasonal cycle and interannual variability. Every sea level component is statistically compared with data from local tide gauges.

Evaluating the effects of historical land cover change on summertime weather and climate in New Jersey

NASA Astrophysics Data System (ADS)

Wichansky, Paul Stuart

The 19th-century agrarian landscape of New Jersey (NJ) and the surrounding region has been extensively transformed to the present-day land cover by urbanization, reforestation, and localized areas of deforestation. This study used a mesoscale atmospheric numerical model to investigate the sensitivity of the warm season climate of NJ to these land cover changes. Reconstructed 1880s-era and present-day land cover datasets were used as surface boundary conditions for a set of simulations performed with the Regional Atmospheric Modeling System (RAMS). Three-member ensembles with historical and present-day land cover were compared to examine the sensitivity of surface air and dewpoint temperatures, rainfall, the individual components of the surface energy budget, horizontal and vertical winds, and the vertical profiles of temperature and humidity to these land cover changes. Mean temperatures for the present-day landscape were 0.3-0.6°C warmer than for the historical landscape over a considerable portion of NJ and the surrounding region, with daily maximum temperatures at least 1.0°C warmer over some of the highly urbanized locations. Reforested regions in the present-day landscape, however, showed a slight cooling. Surface warming was generally associated with repartitioning of net radiation from latent to sensible heat flux, and conversely for cooling. Reduced evapotranspiration from much of the present-day land surface led to dewpoint temperature decreases of 0.3-0.6°C. While urbanization was accompanied by strong surface albedo decreases and increases in net shortwave radiation, reforestation and potential changes in forest composition have generally increased albedos and also enhanced landscape heterogeneity. The increased deciduousness of forests may have further reduced net downward longwave radiation. These land cover changes have modified boundary-layer dynamics by increasing low-level convergence and upper-level divergence in the interior of NJ, especially where sensible heat fluxes have increased for the present-day landscape, hence enhancing uplift in the mid-troposphere. The mesoscale circulations that developed in the present-day ensemble were also more effective at lifting available moisture to higher levels of the boundary layer, lowering dewpoints near the surface but increasing them aloft. Likewise, the sea breeze in coastal areas of NJ in the present-day ensemble had stronger uplift during the afternoon and enhanced moisture transport to higher levels.

Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza; Gregoire, Lauren; Kageyama, Masa; Roche, Didier; Valdes, Paul; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-04-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21-9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will concentrate on shorter durations around specific events to allow the more computationally expensive models to take part. Ivanovic, R. F., Gregoire, L. J., Kageyama, M., Roche, D. M., Valdes, P. J., Burke, A., Drummond, R., Peltier, W. R., and Tarasov, L.: Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev. Discuss., 8, 9045-9102, doi:10.5194/gmdd-8-9045-2015, 2015.

Climate and Ocean Circulation During "The Boring Billion" Simulated by CCSM3

NASA Astrophysics Data System (ADS)

Liu, P.; Hu, Y.; Liu, Y.

2017-12-01

The Boring Billion is referred to the era between approximately 1.8 and 0.8 billion years ago. Geological evidence suggests that no dramatic climate changes in the billions of years, at least in terms of permanent glaciation. The atmospheric oxygen maintained at a relatively low level without significant perturbations. Life had a certain degree of evolution with a quite gentle pace. Relative to the Great Oxidation Event occurred previously, and the Snowball Earth Event and Cambrian Explosion occurred afterwards, this billion years was calm in all aspects so it's often referred to as "the Boring Billion". Why were both the climate and oxygen concentration so stable, and how the anoxic condition in the deep ocean maintained are the questions that motivated our research. We use the Atmosphere Ocean General Circulation Model CCSM3 in this study. The climate of the Boring Billion is simulated for two distinct continental configurations reconstructed for 1540 Ma and 1420 Ma, with continental fragments concentrating towards the North Pole and equator, respectively. The solar constant is set to be 10% weaker than that of the present day. The results show that when the concentration of CO2 is 20 times the present atmospheric level (PAL), the global mean surface temperatures are 19 ° C and 20 ° C for the 1540 Ma and 1420 Ma continental configuration, respectively. Large scale permanent glaciers cannot develop in such a warm climate even for the continents at the polar region. The largest mixed-layer depth in the high-latitude ocean is approximately 1200 m and meridional overturning circulation can reach depth of 3000 m with strength of 40 Sv for both continental configuration. This implies that the material and energy exchange between shallow and deep ocean, as well as atmosphere and ocean, is efficient. When CO2 concentration is reduced to 10 PAL, 5 PAL or 2.5 PAL, global average temperature becomes 16 ° C, 13 ° C and 2 ° C respectively, and permanent glaciers start to form at the polar regions. Therefore, our simulations suggest that the CO2 concentration had to be close to or higher than 20 PAL in order for the simulated climate to be consistent with the observations. Moreover, the oceans were not dynamically stratified, to maintain an anoxic deep ocean biogeochemical processes which are not included in the model have to be invoked.

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Water-balance wodel of a wetland on the Fort Berthold Reservation, North Dakota

USGS Publications Warehouse

Vining, Kevin C.

2007-01-01

A numerical water-balance model was developed to simulate the responses of a wetland on the Fort Berthold Reservation, North Dakota, to historical and possible extreme hydrological inputs and to changes in hydrological inputs that might occur if a proposed refinery is built on the reservation. Results from model simulations indicated that the study wetland would likely contain water during most historical and extreme-precipitation events with the addition of maximum potential discharges of 0.6 acre-foot per day from proposed refinery holding ponds. Extended periods with little precipitation and above-normal temperatures may result in the wetland becoming nearly dry, especially if potential holding-pond discharges are near zero. Daily simulations based on the historical-enhanced climate data set for May and June 2005, which included holding-pond discharges of 0.6 acre-foot per day, indicated that the study-wetland maximum simulated water volume was about 16.2 acre-feet and the maximum simulated water level was about 1.2 feet at the outlet culvert. Daily simulations based on the extreme summer data set, created to represent an extreme event with excessive June precipitation and holding-pond discharges of 0.6 acre-foot per day, indicated that the study-wetland maximum simulated water volume was about 38.6 acre-feet and the maximum simulated water level was about 2.6 feet at the outlet culvert. A simulation performed using the extreme winter climate data set and an outlet culvert blocked with snow and ice resulted in the greatest simulated wetland water volume of about 132 acre-feet and the greatest simulated water level, which would have been about 6.2 feet at the outlet culvert, but water was not likely to overflow an adjacent highway.

The Construction of 3-d Neutral Density for Arbitrary Data Sets

NASA Astrophysics Data System (ADS)

Riha, S.; McDougall, T. J.; Barker, P. M.

2014-12-01

The Neutral Density variable allows inference of water pathways from thermodynamic properties in the global ocean, and is therefore an essential component of global ocean circulation analysis. The widely used algorithm for the computation of Neutral Density yields accurate results for data sets which are close to the observed climatological ocean. Long-term numerical climate simulations, however, often generate a significant drift from present-day climate, which renders the existing algorithm inaccurate. To remedy this problem, new algorithms which operate on arbitrary data have been developed, which may potentially be used to compute Neutral Density during runtime of a numerical model.We review existing approaches for the construction of Neutral Density in arbitrary data sets, detail their algorithmic structure, and present an analysis of the computational cost for implementations on a single-CPU computer. We discuss possible strategies for the implementation in state-of-the-art numerical models, with a focus on distributed computing environments.

Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

2016-04-01

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

Glacial Inception in north-east Canada: The Role of Topography and Clouds

NASA Astrophysics Data System (ADS)

Birch, Leah; Tziperman, Eli; Cronin, Timothy

2016-04-01

Over the past 0.8 million years, ice ages have dominated Earth's climate on a 100 thousand year cycle. Interglacials were brief, sometimes lasting only a few thousand years, leading to the next inception. Currently, state-of-the-art global climate models (GCMs) are incapable of simulating the transition of Earth's climate from interglacial to glaciated. We hypothesize that this failure may be related to their coarse spatial resolution, which does not allow resolving the topography of inception areas, and their parameterized representation of clouds and atmospheric convection. To better understand the small scale topographic and cloud processes mis-represented by GCMs, we run the Weather Research and Forecasting model (WRF), which is a regional, cloud-resolving atmospheric model capable of a realistic simulation of the regional mountain climate and therefore of surface ice and snow mass balance. We focus our study on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred at 115kya. We examine the sensitivity of mountain glaciers to Milankovitch Forcing, topography, and meteorology, while observing impacts of a cloud resolving model. We first verify WRF's ability to simulate present day climate in the region surrounding the Penny Ice Cap, and then investigate how a GCM-like biased representation of topography affects sensitivity of this mountain glacier to Milankovitch forcing. Our results show the possibility of ice cap growth on an initially snow-free landscape with realistic topography and insolation values from the last glacial inception. Whereas, smoothed topography as seen in GCMs has a negative surface mass balance, even with the relevant orbital parameter configuration. We also explore the surface mass balance feedbacks from an initially ice-covered Baffin Island and discuss the role of clouds and convection.

Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth

NASA Astrophysics Data System (ADS)

van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.; Williams, A. G.; Chambers, S. D.

2014-10-01

We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the IFS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The atmospheric lifetime of methane in EC-Earth is 9.4 years, which is 7% longer than the lifetime obtained with ERA-Interim but remains well within the range reported in the literature. We further evaluate the model by comparing the simulated climatologies of surface radon-222 and carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.

How does dynamical downscaling affect model biases and future projections of explosive extratropical cyclones along North America's Atlantic coast?

NASA Astrophysics Data System (ADS)

Seiler, C.; Zwiers, F. W.; Hodges, K. I.; Scinocca, J. F.

2018-01-01

Explosive extratropical cyclones (EETCs) are rapidly intensifying low pressure systems that generate severe weather along North America's Atlantic coast. Global climate models (GCMs) tend to simulate too few EETCs, perhaps partly due to their coarse horizontal resolution and poorly resolved moist diabatic processes. This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America's Atlantic coast. A regional climate model (CanRCM4) is forced with the CanESM2 GCM for the periods 1981 to 2000 and 2081 to 2100. EETCs are tracked from relative vorticity using an objective feature tracking algorithm. CanESM2 simulates 38% fewer EETC tracks compared to reanalysis data, which is consistent with a negative Eady growth rate bias (-0.1 day^{-1}). Downscaling CanESM2 with CanRCM4 increases EETC frequency by one third, which reduces the frequency bias to -22%, and increases maximum EETC precipitation by 22%. Anthropogenic greenhouse gas forcing is projected to decrease EETC frequency (-15%, -18%) and Eady growth rate (-0.2 day^{-1}, -0.2 day^{-1}), and increase maximum EETC precipitation (46%, 52%) in CanESM2 and CanRCM4, respectively. The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate. The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant. Further bias reductions could be achieved by addressing processes that lead to an underestimation of lower tropospheric meridional temperature gradients.

Role of Climate Change in Global Predictions of Future Tropospheric Ozone and Aerosols

NASA Technical Reports Server (NTRS)

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

2006-01-01

A unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies general circulation model II is applied to simulate an equilibrium CO2-forced climate in the year 2100 to examine the effects of climate change on global distributions of tropospheric ozone and sulfate, nitrate, ammonium, black carbon, primary organic carbon, secondary organic carbon, sea salt, and mineral dust aerosols. The year 2100 CO2 concentration as well as the anthropogenic emissions of ozone precursors and aerosols/aerosol precursors are based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) A2. Year 2100 global O3 and aerosol burdens predicted with changes in both climate and emissions are generally 5-20% lower than those simulated with changes in emissions alone; as exceptions, the nitrate burden is 38% lower, and the secondary organic aerosol burden is 17% higher. Although the CO2-driven climate change alone is predicted to reduce the global O3 concentrations over or near populated and biomass burning areas because of slower transport, enhanced biogenic hydrocarbon emissions, decomposition of peroxyacetyl nitrate at higher temperatures, and the increase of O3 production by increased water vapor at high NOx levels. The warmer climate influences aerosol burdens by increasing aerosol wet deposition, altering climate-sensitive emissions, and shifting aerosol thermodynamic equilibrium. Climate change affects the estimates of the year 2100 direct radiative forcing as a result of the climate-induced changes in burdens and different climatological conditions; with full gas-aerosol coupling and accounting for ozone and direct radiative forcings by the O2, sulfate, nitrate, black carbon, and organic carbon are predicted to be +0.93, -0.72, -1.0, +1.26, and -0.56 W m(exp -2), respectively, using present-day climate and year 2100 emissions, while they are predicted to be +0.76, -0.72, 0.74, +0.97, and -0.58 W m(exp -2), respectively, with year 2100 climate and emissions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Impact of preindustrial to present-day changes in short-lived pollutant emissions on atmospheric composition and climate forcing

NASA Astrophysics Data System (ADS)

Naik, Vaishali; Horowitz, Larry W.; Fiore, Arlene M.; Ginoux, Paul; Mao, Jingqiu; Aghedo, Adetutu M.; Levy, Hiram

2013-07-01

We describe and evaluate atmospheric chemistry in the newly developed Geophysical Fluid Dynamics Laboratory chemistry-climate model (GFDL AM3) and apply it to investigate the net impact of preindustrial (PI) to present (PD) changes in short-lived pollutant emissions (ozone precursors, sulfur dioxide, and carbonaceous aerosols) and methane concentration on atmospheric composition and climate forcing. The inclusion of online troposphere-stratosphere interactions, gas-aerosol chemistry, and aerosol-cloud interactions (including direct and indirect aerosol radiative effects) in AM3 enables a more complete representation of interactions among short-lived species, and thus their net climate impact, than was considered in previous climate assessments. The base AM3 simulation, driven with observed sea surface temperature (SST) and sea ice cover (SIC) over the period 1981-2007, generally reproduces the observed mean magnitude, spatial distribution, and seasonal cycle of tropospheric ozone and carbon monoxide. The global mean aerosol optical depth in our base simulation is within 5% of satellite measurements over the 1982-2006 time period. We conduct a pair of simulations in which only the short-lived pollutant emissions and methane concentrations are changed from PI (1860) to PD (2000) levels (i.e., SST, SIC, greenhouse gases, and ozone-depleting substances are held at PD levels). From the PI to PD, we find that changes in short-lived pollutant emissions and methane have caused the tropospheric ozone burden to increase by 39% and the global burdens of sulfate, black carbon, and organic carbon to increase by factors of 3, 2.4, and 1.4, respectively. Tropospheric hydroxyl concentration decreases by 7%, showing that increases in OH sinks (methane, carbon monoxide, nonmethane volatile organic compounds, and sulfur dioxide) dominate over sources (ozone and nitrogen oxides) in the model. Combined changes in tropospheric ozone and aerosols cause a net negative top-of-the-atmosphere radiative forcing perturbation (-1.05 W m-2) indicating that the negative forcing (direct plus indirect) from aerosol changes dominates over the positive forcing due to ozone increases, thus masking nearly half of the PI to PD positive forcing from long-lived greenhouse gases globally, consistent with other current generation chemistry-climate models.

The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

PubMed Central

Triviño, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas; Araújo, Miguel B.

2011-01-01

Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. PMID:22216263

Equilibrium and Effective Climate Sensitivity

NASA Astrophysics Data System (ADS)

Rugenstein, M.; Bloch-Johnson, J.

2016-12-01

Atmosphere-ocean general circulation models, as well as the real world, take thousands of years to equilibrate to CO2 induced radiative perturbations. Equilibrium climate sensitivity - a fully equilibrated 2xCO2 perturbation - has been used for decades as a benchmark in model intercomparisons, as a test of our understanding of the climate system and paleo proxies, and to predict or project future climate change. Computational costs and limited time lead to the widespread practice of extrapolating equilibrium conditions from just a few decades of coupled simulations. The most common workaround is the "effective climate sensitivity" - defined through an extrapolation of a 150 year abrupt2xCO2 simulation, including the assumption of linear climate feedbacks. The definitions of effective and equilibrium climate sensitivity are often mixed up and used equivalently, and it is argued that "transient climate sensitivity" is the more relevant measure for predicting the next decades. We present an ongoing model intercomparison, the "LongRunMIP", to study century and millennia time scales of AOGCM equilibration and the linearity assumptions around feedback analysis. As a true ensemble of opportunity, there is no protocol and the only condition to participate is a coupled model simulation of any stabilizing scenario simulating more than 1000 years. Many of the submitted simulations took several years to conduct. As of July 2016 the contribution comprises 27 scenario simulations of 13 different models originating from 7 modeling centers, each between 1000 and 6000 years. To contribute, please contact the authors as soon as possible We present preliminary results, discussing differences between effective and equilibrium climate sensitivity, the usefulness of transient climate sensitivity, extrapolation methods, and the state of the coupled climate system close to equilibrium. Caption for the Figure below: Evolution of temperature anomaly and radiative imbalance of 22 simulations with 12 models (color indicates the model). 20 year moving average.

Early and late hot extremes, and elongation of the warm period over Greece

NASA Astrophysics Data System (ADS)

Founda, Dimitra; Giannakopoulos, Christos; Pierros, Fragiskos

2017-04-01

The eastern Mediterranean has been assigned as one of the most responsive areas in climate change, mainly with respect to the occurrence of warmer and drier conditions. In Greece in particular, observations suggest prominent increases in the summer air temperature which in some areas amount to approximately 1 0C/decade since the mid 1970s, while Regional Climate Models simulate further increases in the near and distant future. These changes are coupled with simultaneous increase in the occurrence of hot extremes. In addition to changes in the frequency and intensity of hot extrems, timing of occurrence is also of special interest. Early heat waves in particular, have been found to increase thermal risk in humans. The study explores variations and trends in timing, namely the date of first and last occurrence of hot extremes within the year, and subsequently the hot extremes period (season), defined as the time interval (number of days) between first and last hot extremes occurrence, over Greece. A case study for the area of Athens covering a longer than 100-years period (1897-2015) was conducted first, which will be extended to other Greek areas. Several heat related climatic indices were used, based either on predefined temperature thresholds such as 'tropical days' (daily maximum air temperature, Tmax >30 0C), 'tropical nights' (daily minimum air temperature, Tmin >20 0C), 'hot days' (Tmax >35 0C), or on local climate statistics such as days with Tmax (or Tmin) > 95th percentile. The analysis revealed significant changes in the period of hot extremes and specifically elongation of the period, attributed to early rather than late hot extremes occurrence. An earlier shift of the first tropical day and the first tropical night occurrence by approximately 2 days/decade was found over the study period. An overall elongation of the 'hot days' season by 2.6 days/decade was also observed, which is more prominent since the early 1980s. Over the last three decades, earlier shift of occurrence of days with Tmax > 37 0C and Tmin > 26 0C (corresponding to the 95th percentiles of summer Tmax and Tmin respectively for Athens) was striking, amounting to 8 days/decade. Our findings for the hot extremes period will be used to validate respective simulations of Regional Climate Models downscaled over the areas of interest.

RCP4.5: A Pathway for Stabilization of Radiative Forcing by 2100

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

Thomson, Allison M.; Calvin, Katherine V.; Smith, Steven J.

2011-07-29

Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes radiative forcing at 4.5 W m{sup -2} in the year 2100 without ever exceeding that value. Simulated with the Global Change Assessment Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover in a global economic framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate historical emissions and land cover information common to the RCP process and follows a cost-minimizing pathway to reach the target radiative forcing. The imperative to limit emissions in order to reach this target drives changes in the energy system, includingmore » shifts to electricity, to lower emissions energy technologies and to the deployment of carbon capture and geologic storage technology. In addition, the RCP4.5 emissions price also applies to land use emissions; as a result, forest lands expand from their present day extent. The simulated future emissions and land use were downscaled from the regional simulation to a grid to facilitate transfer to climate models. While there are many alternative pathways to achieve a radiative forcing level of 4.5 W m{sup -2}, the application of the RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing.« less

Producing physically consistent and bias free extreme precipitation events over the Switzerland: Bridging gaps between meteorology and impact models

NASA Astrophysics Data System (ADS)

José Gómez-Navarro, Juan; Raible, Christoph C.; Blumer, Sandro; Martius, Olivia; Felder, Guido

2016-04-01

Extreme precipitation episodes, although rare, are natural phenomena that can threat human activities, especially in areas densely populated such as Switzerland. Their relevance demands the design of public policies that protect public assets and private property. Therefore, increasing the current understanding of such exceptional situations is required, i.e. the climatic characterisation of their triggering circumstances, severity, frequency, and spatial distribution. Such increased knowledge shall eventually lead us to produce more reliable projections about the behaviour of these events under ongoing climate change. Unfortunately, the study of extreme situations is hampered by the short instrumental record, which precludes a proper characterization of events with return period exceeding few decades. This study proposes a new approach that allows studying storms based on a synthetic, but physically consistent database of weather situations obtained from a long climate simulation. Our starting point is a 500-yr control simulation carried out with the Community Earth System Model (CESM). In a second step, this dataset is dynamically downscaled with the Weather Research and Forecasting model (WRF) to a final resolution of 2 km over the Alpine area. However, downscaling the full CESM simulation at such high resolution is infeasible nowadays. Hence, a number of case studies are previously selected. This selection is carried out examining the precipitation averaged in an area encompassing Switzerland in the ESM. Using a hydrological criterion, precipitation is accumulated in several temporal windows: 1 day, 2 days, 3 days, 5 days and 10 days. The 4 most extreme events in each category and season are selected, leading to a total of 336 days to be simulated. The simulated events are affected by systematic biases that have to be accounted before this data set can be used as input in hydrological models. Thus, quantile mapping is used to remove such biases. For this task, a 20-yr high-resolution control simulation is carried out. The extreme events belong to this distribution, and can be mapped onto the distribution of precipitation obtained from a gridded product of precipitation provided by MeteoSwiss. This procedure yields bias-free extreme precipitation events which serve as input by hydrological models that eventually produce a simulated, yet physically consistent flooding event. Thereby, the proposed methodology guarantees consistency with the underlying physics of extreme events, and reproduces plausible impacts of up to one-in-five-centuries situations.

Modeling a complex system of multipurpose reservoirs under prospective scenarios (hydrology, water uses, water management): the case of the Durance River basin (South Eastern France, 12 800 km2)

NASA Astrophysics Data System (ADS)

Monteil, Céline; Hendrickx, Frédéric; Samie, René; Sauquet, Eric

2015-04-01

The Durance River and its main tributary, the Verdon River, are two major rivers located in the Southern part of France. Three large dams (Serre-Ponçon, Castillon and Sainte-Croix) were built on their streams during the second half of the 20th century for multiple purposes. Stored water is used for hydropower, recreational, industry, drinking water and irrigation. Flows are partly diverted to feed areas outside the basin. On average 30 plants located in the Durance and Verdon valleys currently produce a total of 600 million kWh per year, equal to the annual residential consumption of a city with over 2.5 million inhabitants. The Southern part of France has been recently affected by severe droughts (2003, 2007 and 2011) and the rules for water allocation and reservoir management are now questioned particularly in the light of global change. The objective of the research project named "R²D²-2050" was to assess water availability and risks of water shortage in the mid-21st century by taking into account changes in both climate and water management. Therefore, a multi-model multi-scenario approach was considered to simulate regional climate, water resources and water demands under present-day (over the 1980-2009 baseline period) and under future conditions (over the 2036-2065 period). In addition, a model of water management was developed to simulate reservoir operating rules of the three dams. This model was calibrated to simulate water released from reservoir under constraints imposed by current day water allocation rules (e.g. downstream water requirements for irrigation, minimum water levels in the reservoirs during summer time for recreational purposes). Four territorial socio-economic scenarios were also elaborated with the help of stake holders to project water needs in the 2050s for the areas supplied with water from the Durance River basin. Results suggest an increase of the average air temperature with consequences on snow accumulation, snowmelt processes but also evapotranspiration process. However changes in total precipitation are highly uncertain. The six tested rainfall-runoff models project reduced flows, especially in the spring and summer seasons. Depending on the socio-economic scenarios and the area, the downstream total water needs could decrease or remain stable. Considering the present day constraints, these changes would lead to a decrease in energy production (mainly due to reduced annual inflows) and to less flexibility for hydropower management during winter peak energy demand. Results of the R²D² 2050 project suggest also that the downscaling methods still fail to reproduce some crucial aspects of the climate at regional scale. Unexpected biases are propagated along the chain of models. The key issue to simulate accurately reservoir operations under present and future climate conditions is the filling curves that depict the balance between water supply and demand. Probabilistic filling curves were calibrated here to meet the constraint on water level in summer objective nine years over ten. A large proportion of regional climates generated over the baseline period lead to unrealistic curves, pointing out higher levels of requirement in models output to assess global change impacts on water management systems like on the Durance River basin.

A Climate Statistics Tool and Data Repository

NASA Astrophysics Data System (ADS)

Wang, J.; Kotamarthi, V. R.; Kuiper, J. A.; Orr, A.

2017-12-01

Researchers at Argonne National Laboratory and collaborating organizations have generated regional scale, dynamically downscaled climate model output using Weather Research and Forecasting (WRF) version 3.3.1 at a 12km horizontal spatial resolution over much of North America. The WRF model is driven by boundary conditions obtained from three independent global scale climate models and two different future greenhouse gas emission scenarios, named representative concentration pathways (RCPs). The repository of results has a temporal resolution of three hours for all the simulations, includes more than 50 variables, is stored in Network Common Data Form (NetCDF) files, and the data volume is nearly 600Tb. A condensed 800Gb set of NetCDF files were made for selected variables most useful for climate-related planning, including daily precipitation, relative humidity, solar radiation, maximum temperature, minimum temperature, and wind. The WRF model simulations are conducted for three 10-year time periods (1995-2004, 2045-2054, and 2085-2094), and two future scenarios RCP4.5 and RCP8.5). An open-source tool was coded using Python 2.7.8 and ESRI ArcGIS 10.3.1 programming libraries to parse the NetCDF files, compute summary statistics, and output results as GIS layers. Eight sets of summary statistics were generated as examples for the contiguous U.S. states and much of Alaska, including number of days over 90°F, number of days with a heat index over 90°F, heat waves, monthly and annual precipitation, drought, extreme precipitation, multi-model averages, and model bias. This paper will provide an overview of the project to generate the main and condensed data repositories, describe the Python tool and how to use it, present the GIS results of the computed examples, and discuss some of the ways they can be used for planning. The condensed climate data, Python tool, computed GIS results, and documentation of the work are shared on the Internet.

Sensitivity of Historical Simulation of the Permafrost to Different Atmospheric Forcing Data Sets from 1979 to 2009

NASA Astrophysics Data System (ADS)

Guo, Donglin; Wang, Huijun; Wang, Aihui

2017-11-01

Numerical simulation is of great importance to the investigation of changes in frozen ground on large spatial and long temporal scales. Previous studies have focused on the impacts of improvements in the model for the simulation of frozen ground. Here the sensitivities of permafrost simulation to different atmospheric forcing data sets are examined using the Community Land Model, version 4.5 (CLM4.5), in combination with three sets of newly developed and reanalysis-based atmospheric forcing data sets (NOAA Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-I), and NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA)). All three simulations were run from 1979 to 2009 at a resolution of 0.5° × 0.5° and validated with what is considered to be the best available permafrost observations (soil temperature, active layer thickness, and permafrost extent). Results show that the use of reanalysis-based atmospheric forcing data set reproduces the variations in soil temperature and active layer thickness but produces evident biases in their climatologies. Overall, the simulations based on the CFSR and ERA-I data sets give more reasonable results than the simulation based on the MERRA data set, particularly for the present-day permafrost extent and the change in active layer thickness. The three simulations produce ranges for the present-day climatology (permafrost area: 11.31-13.57 × 106 km2; active layer thickness: 1.10-1.26 m) and for recent changes (permafrost area: -5.8% to -9.0%; active layer thickness: 9.9%-20.2%). The differences in air temperature increase, snow depth, and permafrost thermal conditions in these simulations contribute to the differences in simulated results.

Hydroclimatic trends in simulations over the CORDEX North America region

NASA Astrophysics Data System (ADS)

Arritt, Raymond; Groisman, Pavel; Daniel, Ariele; Schillerberg, Tayler

2015-04-01

An increase in the occurrence of heavy precipitation has been one of the most pronounced climate change signals for the central United States. We study this trend by using the RegCM4 regional climate model to dynamically downscale CMIP5 global projections for 1950-2099 over the CORDEX North America domain. We examine the robustness of the results by driving the regional model with two different global models, by performing simulations at both 50 km and 25 km grid spacing, and by using different convective parameterizations in RegCM4. The global models sample the range of climate sensitivity in CMIP5: HadGEM2-ES has the highest equilibrium climate sensitivity of the CMIP5 models, while GFDL-ESM2M has one of the lowest sensitivities. RegCM4 results show increases in heavy precipitation (> 50 mm/day) over the central United States for the period 1951-2005 similar to observed trends. This trend is predicted to accelerate so that by the end of the 21st century incidence of heavy precipitation increases by a factor of 2 to 3. The trend is robust in that it is produced regardless of the driving global model or the configuration of the regional model. Results also show a modest increase in the number of dry days and a marked increase in the number of long runs of dry days (16 or more consecutive dry days). The combination of heavier events and longer runs of dry days has implications for sectors such as agriculture and water quality. This research was sponsored by USDA NIFA under the Earth System Modeling program and as part of a regional collaborative project.

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 model reproduces the observed increase in Atlantic hurricane activity (numbers, Accumulated Cyclone Energy (ACE), Power Dissipation Index (PDI), etc.) over the period 1980-2006 fairly realistically, and also simulates ENSO-related interannual variations in hurricane counts. Annual simulated hurricane counts from a two-member ensemble correlate with observed counts at r=0.86. However, the model does not simulate hurricanes as intense as those observed, with minimum central pressures of 937 hPa (category 4) and maximum surface winds of 47 m/s (category 2) being the most intense simulated so far in these experiments. To explore possible impacts of future climate warming on Atlantic hurricane activity, we are re-running the 1980- 2006 seasons, keeping the interannual to multidecadal variations unchanged, but altering the August-October mean climate according to changes simulated by an 18-member ensemble of AR4 climate models (years 2080- 2099, A1B emission scenario). The warmer climate state features higher Atlantic SSTs, and also increased vertical wind shear across the Caribbean (Vecchi and Soden, GRL 2007). A key assumption of this approach is that the 18-model ensemble-mean climate change is the best available projection of future climate change in the Atlantic. Some of the 18 global models show little increase in wind shear, or even a decrease, and thus there will be considerable uncertainty associated with the hurricane frequency results, which will require further exploration. Results from our simulations will be presented at the meeting.

Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data

NASA Astrophysics Data System (ADS)

Collins, W. D.; Wehner, M. F.; Prabhat, M.; Kurth, T.; Satish, N.; Mitliagkas, I.; Zhang, J.; Racah, E.; Patwary, M.; Sundaram, N.; Dubey, P.

2017-12-01

Anthropogenically-forced climate changes in the number and character of extreme storms have the potential to significantly impact human and natural systems. Current high-performance computing enables multidecadal simulations with global climate models at resolutions of 25km or finer. Such high-resolution simulations are demonstrably superior in simulating extreme storms such as tropical cyclones than the coarser simulations available in the Coupled Model Intercomparison Project (CMIP5) and provide the capability to more credibly project future changes in extreme storm statistics and properties. The identification and tracking of storms in the voluminous model output is very challenging as it is impractical to manually identify storms due to the enormous size of the datasets, and therefore automated procedures are used. Traditionally, these procedures are based on a multi-variate set of physical conditions based on known properties of the class of storms in question. In recent years, we have successfully demonstrated that Deep Learning produces state of the art results for pattern detection in climate data. We have developed supervised and semi-supervised convolutional architectures for detecting and localizing tropical cyclones, extra-tropical cyclones and atmospheric rivers in simulation data. One of the primary challenges in the applicability of Deep Learning to climate data is in the expensive training phase. Typical networks may take days to converge on 10GB-sized datasets, while the climate science community has ready access to O(10 TB)-O(PB) sized datasets. In this work, we present the most scalable implementation of Deep Learning to date. We successfully scale a unified, semi-supervised convolutional architecture on all of the Cori Phase II supercomputer at NERSC. We use IntelCaffe, MKL and MLSL libraries. We have optimized single node MKL libraries to obtain 1-4 TF on single KNL nodes. We have developed a novel hybrid parameter update strategy to improve scaling to 9600 KNL nodes (600,000 cores). We obtain 15PF performance over the course of the training run; setting a new watermark for the HPC and Deep Learning communities. This talk will share insights on how to obtain this extreme level of performance, current gaps/challenges and implications for the climate science community.

Inhomogeneities detection in annual precipitation time series in Portugal using direct sequential simulation

NASA Astrophysics Data System (ADS)

Caineta, Júlio; Ribeiro, Sara; Costa, Ana Cristina; Henriques, Roberto; Soares, Amílcar

2014-05-01

Climate data homogenisation is of major importance in monitoring climate change, the validation of weather forecasting, general circulation and regional atmospheric models, modelling of erosion, drought monitoring, among other studies of hydrological and environmental impacts. This happens because non-climate factors can cause time series discontinuities which may hide the true climatic signal and patterns, thus potentially bias the conclusions of those studies. In the last two decades, many methods have been developed to identify and remove these inhomogeneities. One of those is based on geostatistical simulation (DSS - direct sequential simulation), where local probability density functions (pdf) are calculated at candidate monitoring stations, using spatial and temporal neighbouring observations, and then are used for detection of inhomogeneities. This approach has been previously applied to detect inhomogeneities in four precipitation series (wet day count) from a network with 66 monitoring stations located in the southern region of Portugal (1980-2001). This study revealed promising results and the potential advantages of geostatistical techniques for inhomogeneities detection in climate time series. This work extends the case study presented before and investigates the application of the geostatistical stochastic approach to ten precipitation series that were previously classified as inhomogeneous by one of six absolute homogeneity tests (Mann-Kendall test, Wald-Wolfowitz runs test, Von Neumann ratio test, Standard normal homogeneity test (SNHT) for a single break, Pettit test, and Buishand range test). Moreover, a sensibility analysis is implemented to investigate the number of simulated realisations that should be used to accurately infer the local pdfs. Accordingly, the number of simulations per iteration is increased from 50 to 500, which resulted in a more representative local pdf. A set of default and recommended settings is provided, which will help other users to implement this method. The need of user intervention is reduced to a minimum through the usage of a cross-platform script. Finally, as in the previous study, the results are compared with those from the SNHT, Pettit and Buishand range tests, which were applied to composite (ratio) reference series. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").

Assessment of CMIP5 historical simulations of rainfall over Southeast Asia

NASA Astrophysics Data System (ADS)

Raghavan, Srivatsan V.; Liu, Jiandong; Nguyen, Ngoc Son; Vu, Minh Tue; Liong, Shie-Yui

2018-05-01

We present preliminary analyses of the historical (1986-2005) climate simulations of a ten-member subset of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) global climate models over Southeast Asia. The objective of this study was to evaluate the general circulation models' performance in simulating the mean state of climate over this less-studied climate vulnerable region, with a focus on precipitation. Results indicate that most of the models are unable to reproduce the observed state of climate over Southeast Asia. Though the multi-model ensemble mean is a better representation of the observations, the uncertainties in the individual models are far high. There is no particular model that performed well in simulating the historical climate of Southeast Asia. There seems to be no significant influence of the spatial resolutions of the models on the quality of simulation, despite the view that higher resolution models fare better. The study results emphasize on careful consideration of models for impact studies and the need to improve the next generation of models in their ability to simulate regional climates better.

A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

NASA Astrophysics Data System (ADS)

Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie

2017-11-01

There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study highlights the point that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.

Global Air Quality and Climate Impacts of Mitigating Short-lived Climate Pollution in China

NASA Astrophysics Data System (ADS)

Harper, K.; Unger, N.; Heyes, C.; Kiesewetter, G.; Klimont, Z.; Schoepp, W.; Wagner, F.

2014-12-01

China is a major emitter of harmful air pollutants, including the short-lived climate pollutants (SLCPs) and their precursors. Implementation of pollution control technologies provides a mechanism for simultaneously protecting human and ecosystem health and achieving near-term climate co-benefits; however, predicting the outcomes of technical and policy interventions is challenging because the SLCPs participate in both climate warming and cooling and share many common emission sources. Here, we present the results of a combined regional integrated assessment and global climate modeling study aimed at quantifying the near-term climate and air quality co-benefits of selective control of Chinese air pollution emissions. Results from IIASA's Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) integrated assessment model indicate that methane emission reductions make up > 75% of possible CO2-equivalent emission reductions of the SLCPs and their precursors in China in 2030. A multi-pollutant emission reduction scenario incorporating the 2030 Chinese pollution control measures with the highest potential for future climate impact is applied to the NASA ModelE2 - Yale Interactive Terrestrial Biosphere (NASA ModelE2-YIBs) global carbon - chemistry - climate model to assess the regional and long-range impacts of Chinese SLCP mitigation measures. Using model simulations that incorporate dynamic methane emissions and photosynthesis-dependent isoprene emissions, we quantify the impacts of Chinese reductions of the short-lived air pollutants on radiative forcing and on surface ozone and particulate air pollution. Present-day modeled methane mole fractions are evaluated against SCIAMACHY methane columns and NOAA ESRL/GMD surface flask measurements.

Mean and extreme temperatures in a warming climate: EURO CORDEX and WRF regional climate high-resolution projections for Portugal

NASA Astrophysics Data System (ADS)

Cardoso, Rita M.; Soares, Pedro M. M.; Lima, Daniela C. A.; Miranda, Pedro M. A.

2018-02-01

Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8.5. An additional WRF simulation with even higher resolution (9 km) for RCP8.5 scenario is also examined. All simulations for the historical period (1971-2000) are evaluated against the available station observations and the EURO-CORDEX model results are ranked in order to build multi-model ensembles. In present climate models are able to reproduce the main topography/coast related temperature gradients. Although there are discernible differences between models, most present a cold bias. The multi-model ensembles improve the overall representation of the temperature. The ensembles project a significant increase of the maximum and minimum temperatures in all seasons and scenarios. Maximum increments of 8 °C in summer and autumn and between 2 and 4 °C in winter and spring are projected in RCP8.5. The temperature distributions for all models show a significant increase in the upper tails of the PDFs. In RCP8.5 more than half of the extended summer (MJJAS) has maximum temperatures exceeding the historical 90th percentile and, on average, 60 tropical nights are projected for the end of the century, whilst there are only 7 tropical nights in the historical period. Conversely, the number of cold days almost disappears. The yearly average number of heat waves increases by seven to ninefold by 2100 and the most frequent length rises from 5 to 22 days throughout the twenty-first century. 5% of the longest events will last for more than one month. The amplitude is overwhelming larger, reaching values which are not observed in the historical period. More than half of the heat waves will be stronger than the extreme heat wave of 2003 by the end of the century. The future heatwaves will also enclose larger areas, approximately 100 events in the 2071-2100 period (more than 3 per year) will cover the whole country. The RCP4.5 scenario has in general smaller magnitudes.

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.

Comparisons Between TIME-GCM/MERRA Simulations and LEO Satellite Observations

NASA Astrophysics Data System (ADS)

Hagan, M. E.; Haeusler, K.; Forbes, J. M.; Zhang, X.; Doornbos, E.; Bruinsma, S.; Lu, G.

2014-12-01

We report on yearlong National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM) simulations where we utilize the recently developed lower boundary condition based on 3-hourly MERRA (Modern-Era Retrospective Analysis for Research and Application) reanalysis data to account for tropospheric waves and tides propagating upward into the model domain. The solar and geomagnetic forcing is based on prevailing geophysical conditions. The simulations show a strong day-to-day variability in the upper thermospheric neutral temperature tidal fields, which is smoothed out quickly when averaging is applied over several days, e.g. up to 50% DE3 amplitude reduction for a 10-day average. This is an important result with respect to tidal diagnostics from satellite observations where averaging over multiple days is inevitable. In order to assess TIME-GCM performance we compare the simulations with measurements from the Gravity field and steady-state Ocean Circulation Explorer (GOCE), Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellites.

Consequences of 1.5 °C and 2 °C global warming levels for temperature and precipitation changes over Central Africa

NASA Astrophysics Data System (ADS)

Pokam Mba, Wilfried; Longandjo, Georges-Noel T.; Moufouma-Okia, Wilfran; Bell, Jean-Pierre; James, Rachel; Vondou, Derbetini A.; Haensler, Andreas; Fotso-Nguemo, Thierry C.; Merlin Guenang, Guy; Djiotang Tchotchou, Angennes Lucie; Kamsu-Tamo, Pierre H.; Takong, Ridick R.; Nikulin, Grigory; Lennard, Christopher J.; Dosio, Alessandro

2018-05-01

Discriminating climate impacts between 1.5 °C and 2 °C warming levels is particularly important for Central Africa, a vulnerable region where multiple biophysical, political, and socioeconomic stresses interact to constrain the region’s adaptive capacity. This study uses an ensemble of 25 transient Regional Climate Model (RCM) simulations from the CORDEX initiative, forced with the Representative Concentration Pathway (RCP) 8.5, to investigate the potential temperature and precipitation changes in Central Africa corresponding to 1.5 °C and 2 °C global warming levels. Global climate model simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to drive the RCMs and determine timing of the targeted global warming levels. The regional warming differs over Central Africa between 1.5 °C and 2 °C global warming levels. Whilst there are large uncertainties associated with projections at 1.5 °C and 2 °C, the 0.5 °C increase in global temperature is associated with larger regional warming response. Compared to changes in temperature, changes in precipitation are more heterogeneous and climate model simulations indicate a lack of consensus across the region, though there is a tendency towards decreasing seasonal precipitation in March–May, and a reduction of consecutive wet days. As a drought indicator, a significant increase in consecutive dry days was found. Consistent changes of maximum 5 day rainfall are also detected between 1.5 °C vs. 2 °C global warming levels.

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Kim, Daehyun; Ahn, Min-Seop; Kang, In-Sik; Del Genio, Anthony D.

2015-01-01

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Ice sheet climate modeling: past achievements, ongoing challenges, and future endeavors

NASA Astrophysics Data System (ADS)

Lenaerts, J.

2017-12-01

Fluctuations in surface mass balance (SMB) mask out a substantial portion of contemporary Greenland and Antarctic ice sheet mass loss. That implies that we need accurate, consistent, and long-term SMB time series to isolate the mass loss signal. This in turn requires understanding of the processes driving SMB, and how they interplay. The primary controls on present-day ice sheet SMB are snowfall, which is regulated by large-scale atmospheric variability, and surface meltwater production at the ice sheet's edges, which is a complex result of atmosphere-surface interactions. Additionally, wind-driven snow redistribution and sublimation are large SMB contributors on the downslope areas of the ice sheets. Climate models provide an integrated framework to simulate all these individual ice sheet components. Recent developments in RACMO2, a regional climate model bound by atmospheric reanalyses, have focused on enhancing horizontal resolution, including blowing snow, snow albedo, and meltwater processes. Including these physics not only enhanced our understanding of the ice sheet climate system, but also enabled to obtain increasingly accurate estimates of ice sheet SMB. However, regional models are not suitable to capture the mutual interactions between ice sheet and the remainder of the global climate system in transient climates. To take that next step, global climate models are essential. In this talk, I will highlight our present work on improving ice sheet climate in the Community Earth System Model (CESM). In particular, we focus on an improved representation of polar firn, ice sheet clouds, and precipitation. For this exercise, we extensively use field observations, remote sensing data, as well as RACMO2. Next, I will highlight how CESM is used to enhance our understanding of ice sheet SMB, its drivers, and past and present changes.

Sensitivity of the Atmospheric Response to Warm Pool El Nino Events to Modeled SSTs and Future Climate Forcings

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Garfinkel, Chaim I.; Newman, Paul A.; Oman, Luke D.

2013-01-01

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. Under present-day climate conditions, WPEN events generate poleward propagating wavetrains and enhance midlatitude planetary wave activity, weakening the stratospheric polar vortices. The late 21st century extratropical atmospheric response to WPEN events is investigated using the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM), version 2. GEOSCCM simulations are forced by projected late 21st century concentrations of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) and by SSTs and sea ice concentrations from an existing ocean-atmosphere simulation. Despite known ocean-atmosphere model biases, the prescribed SST fields represent a best estimate of the structure of late 21st century WPEN events. The future Arctic vortex response is qualitatively similar to that observed in recent decades but is weaker in late winter. This response reflects the weaker SST forcing in the Nino 3.4 region and subsequently weaker Northern Hemisphere tropospheric teleconnections. The Antarctic stratosphere does not respond to WPEN events in a future climate, reflecting a change in tropospheric teleconnections: The meridional wavetrain weakens while a more zonal wavetrain originates near Australia. Sensitivity simulations show that a strong poleward wavetrain response to WPEN requires a strengthening and southeastward extension of the South Pacific Convergence Zone; this feature is not captured by the late 21st century modeled SSTs. Expected future increases in GHGs and decreases in ODSs do not affect the polar stratospheric responses to WPEN.

Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Falloon, Pete; Ito, Akihiko; Smallman, T. Luke; Williams, Mathew

2018-02-01

Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) business as usual emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095-2099) compared to 2001-2005, which is 2-3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y-1. Using REA also leads to a 45-68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Climate mitigation and the future of tropical landscapes.

PubMed

Thomson, Allison M; Calvin, Katherine V; Chini, Louise P; Hurtt, George; Edmonds, James A; Bond-Lamberty, Ben; Frolking, Steve; Wise, Marshall A; Janetos, Anthony C

2010-11-16

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m(-2) (approximately 526 ppm CO(2)) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

A Prototype Two-Decade Fully-Coupled Fine-Resolution CCSM Simulation

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

McClean, Julie L.; Bader, David C; Bryan, Frank O.

2011-01-01

A fully coupled global simulation using the Community Climate System Model (CCSM) was configured using grid resolutions of 0.1{sup o} for the ocean and sea-ice, and 0.25{sup o} for the atmosphere and land, and was run under present-day greenhouse gas conditions for 20 years. It represents one of the first efforts to simulate the planetary system at such high horizontal resolution. The climatology of the circulation of the atmosphere and the upper ocean were compared with observational data and reanalysis products to identify persistent mean climate biases. Intensified and contracted polar vortices, and too cold sea surface temperatures (SSTs) inmore » the subpolar and mid-latitude Northern Hemisphere were the dominant biases produced by the model. Intense category 4 cyclones formed spontaneously in the tropical North Pacific. A case study of the ocean response to one such event shows the realistic formation of a cold SST wake, mixed layer deepening, and warming below the mixed layer. Too many tropical cyclones formed in the North Pacific however, due to too high SSTs in the tropical eastern Pacific. In the North Atlantic anomalously low SSTs lead to a dearth of hurricanes. Agulhas eddy pathways are more realistic than in equivalent stand-alone ocean simulations forced with atmospheric reanalysis.« less

Decadal climate simulations using the Climate Forecast System (CFS) coupled to the SSiB2 land surface model

NASA Astrophysics Data System (ADS)

De Sales, F.; Xue, Y.; Marx, L.; Ek, M. B.

2016-12-01

The Simplified Simple Biophysical version 2 (SSiB2) model was implemented in the NCEP Climate Forecast System (CFS) for two 30-yr simulations. One simulation was initialized from CFS reanalysis data (EXP1), and the other from a 10-yr spin-up run (EXP2), in which the ocean model was allowed to run freely while the atmosphere and land surface were maintained constant to adjust inconsistencies in the initial conditions. EXP2 also includes an update in the SSiB2's average soil water potential calculation. The material presented highlights the model's performance in predicting spatial and temporal variability of monthly precipitation and surface temperature and aims at determining the optimum configuration for longer simulations. In general, the model is able to reproduce the main features of large-scale precipitation, with spatial correlation (scorr) and RMSE of 0.8 and 1.4 mm day-1, respectively. A split ITCZ pattern is observed in the Pacific and Indian oceans, which results in dry biases along the equator and wet-bias bands to its north and south. Positive biases are also observed in the Atlantic ITCZ. The model generates consistent surface temperature climatology (scorr > 0.9, RMSE= 2.3°C). Warm biases are observed especially over southern Asia during summer. Both experiments produce similar precipitation climatology patterns with similar biases. EXP2, however, improves the temperature simulation by reducing the global bias by 48% and 26% during boreal winter and summer, respectively; and improves the temperature decadal variability for many areas. Moreover, EXP2 generates a better continental surface air warming trend. In the attempt to improve the precipitation decadal variability in the simulations, remotely-sensed LAI and vegetation cover fraction have been implemented in the CFS/SSiB2 to substitute the look-up table originally used in EXP1 and 2. The satellite vegetation data has been processed into global monthly maps which are continuous updated throughout the simulation. Results from this experiment will also be presented.

Return periods of losses associated with European windstorm series in a changing climate

NASA Astrophysics Data System (ADS)

Karremann, Melanie K.; Pinto, Joaquim G.; Reyers, Mark; Klawa, Matthias

2015-04-01

During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series affecting Europe are quantified based on potential losses using empirical models. Moreover, possible future changes of clustering and return periods of European storm series with high potential losses are quantified. Historical storm series are identified using 40 winters of NCEP reanalysis data (1973/1974 - 2012/2013). Time series of top events (1, 2 or 5 year return levels) are used to assess return periods of storm series both empirically and theoretically. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Additionally, 800 winters of ECHAM5/MPI-OM1 general circulation model simulations for present (SRES scenario 20C: years 1960- 2000) and future (SRES scenario A1B: years 2060- 2100) climate conditions are investigated. Clustering is identified for most countries in Europe, and estimated return periods are similar for reanalysis and present day simulations. Future changes of return periods are estimated for fixed return levels and fixed loss index thresholds. For the former, shorter return periods are found for Western Europe, but changes are small and spatially heterogeneous. For the latter, which combines the effects of clustering and event ranking shifts, shorter return periods are found everywhere except for Mediterranean countries. These changes are generally not statistically significant between recent and future climate. However, the return periods for the fixed loss index approach are mostly beyond the range of preindustrial natural climate variability. This is not true for fixed return levels. The quantification of losses associated with storm series permits a more adequate windstorm risk assessment in a changing climate.

High-resolution spatial distribution of temperature over Berlin simulated by the mesoscale model METRAS and comparison with measured data

NASA Astrophysics Data System (ADS)

Sodoudi, Sahar; Schäfer, Kerstin; Grawe, David; Petrik, Ronny; Heinke Schlünzen, K.

2014-05-01

The world's population is projected to increase in the next decades especially in urban areas. Additionally, the living conditions are affected largely by the local urban climate. The urban climate is a complex local system which might change differently than the regional climate. Studying the spatial distribution of air temperature and urban heat island intensity is one of the major concerns in the climate change scenarios. Due to the expected higher frequency of heat waves in the future and the related heat stress, high resolution distribution of air temperature is an important key for urban planning and development. In this study the non-hydrostatic Mesoscale Transport and Fluid Model (METRAS) developed at the University of Hamburg is used to simulate the air temperature for the urban area of Berlin. The forcing data have been derived from the ECMWF reanalysis data. We have used three nested domains (resolution of 4 km, 1 km, 200 m) to simulate the temperature in Berlin. Evaluation of these mesoscale model results is challenging for urban areas, due to the sparse and heterogeneous distribution of meteorological stations and the heterogeneous land cover in urban areas. The Meteorological Institute of the Free University of Berlin organized six measurement campaigns in 2012. Measurements were taken at 31 different routes through Berlin using mobile measurement systems. In comparison with data from permanent weather stations the mobile measurements show a general overestimation of temperature and underestimation of relative humidity values. This may be the result of the different land cover types and places, where the mobile measurements and the stationary measurements were taken. The highly resolved (200 m) simulated air temperature from METRAS has been verified for three different selected summer days in 2012 with different pressure patterns over Berlin. For the model evaluation, the data from the measuring campaign and 34 permanent stations have been used. The results show that METRAS overestimated the cloud water and rain water content on the first two selected days. The air temperature on the first two days has been underestimated by the model due to the reduced incoming radiation, and the strength of the urban heat island has not been reproduced. The mean absolute error is higher during the day time and especially in the city center. The last selected day is a sunny day with light wind from the Northwest. On this day the diurnal temperature variation is well reproduced by the model, although METRAS predicts short showers for several small areas during the afternoon. The showers do not lead to a temperature decrease over the whole city. The mean absolute error is much smaller in comparison with the other days. The temperature peak and the urban heat island are well consistent with observations. The mean absolute error is smaller in the city center and larger over the green areas. The spatial distribution of simulated temperature is in a good agreement with the measurements.

Impact of climate change on mercury concentrations and deposition in the eastern United States.

PubMed

Megaritis, Athanasios G; Murphy, Benjamin N; Racherla, Pavan N; Adams, Peter J; Pandis, Spyros N

2014-07-15

The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. Copyright © 2014 Elsevier B.V. All rights reserved.

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

PubMed

Mendlik, Thomas; Gobiet, Andreas

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

Atmosphere Assessment for MARS Science Laboratory Entry, Descent and Landing Operations

NASA Technical Reports Server (NTRS)

Cianciolo, Alicia D.; Cantor, Bruce; Barnes, Jeff; Tyler, Daniel, Jr.; Rafkin, Scot; Chen, Allen; Kass, David; Mischna, Michael; Vasavada, Ashwin R.

2013-01-01

On August 6, 2012, the Mars Science Laboratory rover, Curiosity, successfully landed on the surface of Mars. The Entry, Descent and Landing (EDL) sequence was designed using atmospheric conditions estimated from mesoscale numerical models. The models, developed by two independent organizations (Oregon State University and the Southwest Research Institute), were validated against observations at Mars from three prior years. In the weeks and days before entry, the MSL "Council of Atmospheres" (CoA), a group of atmospheric scientists and modelers, instrument experts and EDL simulation engineers, evaluated the latest Mars data from orbiting assets including the Mars Reconnaissance Orbiter's Mars Color Imager (MARCI) and Mars Climate Sounder (MCS), as well as Mars Odyssey's Thermal Emission Imaging System (THEMIS). The observations were compared to the mesoscale models developed for EDL performance simulation to determine if a spacecraft parameter update was necessary prior to entry. This paper summarizes the daily atmosphere observations and comparison to the performance simulation atmosphere models. Options to modify the atmosphere model in the simulation to compensate for atmosphere effects are also presented. Finally, a summary of the CoA decisions and recommendations to the MSL project in the days leading up to EDL is provided.

Response of air-sea carbon fluxes and climate to orbital forcing changes in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Jochum, M.; Peacock, S.; Moore, K.; Lindsay, K.

2010-07-01

A global general circulation model coupled to an ocean ecosystem model is used to quantify the response of carbon fluxes and climate to changes in orbital forcing. Compared to the present-day simulation, the simulation with the Earth's orbital parameters from 115,000 years ago features significantly cooler northern high latitudes but only moderately cooler southern high latitudes. This asymmetry is explained by a 30% reduction of the strength of the Atlantic Meridional Overturning Circulation that is caused by an increased Arctic sea ice export and a resulting freshening of the North Atlantic. The strong northern high-latitude cooling and the direct insolation induced tropical warming lead to global shifts in precipitation and winds to the order of 10%-20%. These climate shifts lead to regional differences in air-sea carbon fluxes of the same order. However, the differences in global net air-sea carbon fluxes are small, which is due to several effects, two of which stand out: first, colder sea surface temperature leads to a more effective solubility pump but also to increased sea ice concentration which blocks air-sea exchange, and second, the weakening of Southern Ocean winds that is predicted by some idealized studies occurs only in part of the basin, and is compensated by stronger winds in other parts.

Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

NASA Astrophysics Data System (ADS)

Joetzjer, E.; Delire, C.; Douville, H.; Ciais, P.; Decharme, B.; Fisher, R.; Christoffersen, B.; Calvet, J. C.; da Costa, A. C. L.; Ferreira, L. V.; Meir, P.

2014-12-01

While a majority of global climate models project drier and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC (Interaction Soil-Biosphere-Atmosphere Carbon Cycle) land surface model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent throughfall exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different water stress functions (WSFs) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentrations, the increased water-use efficiency (WUE) mitigates the sensitivity of ISBACC to drought. While one of the proposed WSF formulations improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 4. Water Resources

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

Thomson, Allison M.; Brown, Robert A.; Rosenberg, Norman J.

Global warming will impact the hydrologic cycle by increasing the capacity of the atmosphere to hold moisture. Anticipated impacts are generally increased evaporation at low latitudes and increased precipitation at middle and high latitudes. The impacts on specific regions will depend on changes in weather patterns and are certain to be complex. Here we apply a suite of 12 potential climate change scenarios that could occur over the next century as atmospheric CO2 concentrations reach double the pre-industrial level to the Hydrologic Unit Model of the United States (HUMUS) to simulate water supply in the conterminous United States. In Partmore » 4 we examine the sufficiency of this water supply to meet changing demands of irrigated agriculture. General Circulation Models (GCMs) used to simulate climate disagree on whether the US as a whole and its constituent regions will receive more or less precipitation as global warming occurs. The changes in water yield driven by changes in climate will likely be most consequential in the semi-arid western parts of the country where water yield is currently scarce and the resource is intensively managed. Changes of greater than +/-50% with respect to present day water yield are projected in parts of the Midwest and Southwest US. Interannual variability is likely to increase with reduced water yield but decrease with wetter conditions.« less

WRF-Cordex simulations for Europe: mean and extreme precipitation for present and future climates

NASA Astrophysics Data System (ADS)

Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.

2013-04-01

The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.

Climate change effects on landslides in southern B.C.

NASA Astrophysics Data System (ADS)

Jakob, M.

2009-04-01

Two mechanisms that contribute to the temporal occurrence of landslides in coastal British Columbia are ante¬cedent rainfall and short-term intense rainfall. These two quantities can be extracted from the precipitation regimes simulated by climate models. This makes such models an attractive tool for use in the investigation of the effect of global warming on landslide fre¬quencies. In order to provide some measure of the reliability of models used to address the landslide question, the present-day simulation of the antecedent precipitation and short- term rainfall using the daily data from the Canadian Centre for Climate Modelling and Analysis model (CGCM) is compared to observations along the south coast of British Colum¬bia. This evaluation showed that the model was reasonably successful in simulating sta¬tistics of the antecedent rainfall but was less successful in simulating the short-term rainfall. The monthly mean precipitation data from an ensemble of 19 of the world's global climate models were available to study potential changes in landslide frequencies with global warming. Most of the models were used to produce simulations with three scenar¬ios with different levels of prescribed greenhouse gas concentrations during the twenty-first century. The changes in the antecedent precipitation were computed from the resulting monthly and seasonal means. In order to deal with models' suspected difficulties in sim¬ulating the short-term precipitation and lack of daily data, a statistical procedure was used to relate the short-term precipitation to the monthly means. The qualitative model results agree reasonably well, and when averaged over all models and the three scenarios, the change in the antecedent precipitation is predicted to be about 10% and the change in the short-term precipitation about 6%. Because the antecedent precipitation and the short-term precipitation contribute to the occurrence of landslides, the results of this study support the prediction of increased landslide frequency along the British Columbia south coast during the twenty-first century.

On the uncertainty of phenological responses to climate change and its implication for terrestrial biosphere models

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-01-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate systems through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Land surface models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we analyzed the Harvard Forest phenology record to investigate and characterize the sources of uncertainty in phenological forecasts and the subsequent impacts on model forecasts of carbon and water cycling in the future. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species with 12 phenological models of different complexity to predict leaf bud-burst. The evaluation of different phenological models indicated support for spring warming models with photoperiod limitations and, though to a lesser extent, to chilling models based on the alternating model structure. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% CI: 2.4 day century-1 for scenario B1 and 4.5 day century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 day century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied somewhat among models (±7.7 day century-1 for A1fi, ±3.6 day century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 day °C-1 and 5.2 day °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated carbon and water fluxes using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of the seasonality of processes, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and evapotranspiration (ET) of 9.6% and 2.9% respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, uncertainties related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-06-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate system through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Terrestrial biosphere models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we used the Harvard Forest phenology record to investigate and characterize sources of uncertainty in predicting phenology, and the subsequent impacts on model forecasts of carbon and water cycling. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species, with 12 leaf bud-burst models that varied in complexity. Akaike's Information Criterion indicated support for spring warming models with photoperiod limitations and, to a lesser extent, models that included chilling requirements. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% Confidence Interval - CI: 2.4 days century-1 for scenario B1 and 4.5 days century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 days century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied among models (±7.7 days century-1 for A1fi, ±3.6 days century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 days °C-1 and 5.2 days °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO2 uptake and evapotranspiration (ET) using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios (i.e. driver) represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Climate change reduces the capacity of northern peatlands to absorb the atmospheric carbon dioxide: The different responses of bogs and fens

NASA Astrophysics Data System (ADS)

Wu, Jianghua; Roulet, Nigel T.

2014-10-01

The carbon (C) storage of northern peatlands is equivalent to ~34-46% of the ~795 T g C currently held in the atmosphere as CO2. Most studies report that northern peatlands are a sink of between 20 and 60 g CO2-C m-2 yr-1. Since peatland hydrology and biogeochemistry are very closely related to climate, there is concern whether northern peatlands will continue to function as C sinks with climate change. We used a coupled land surface scheme and peatland C model, called CLASS3W-MWM, to examine the sensitivity of peatland C to climate change. Based on the data available to constrain our model, we simulated the C dynamics of the Mer Bleue (MB) bog in eastern Canada and the Degerö Stormyr (DS) poor fen in northern Sweden for four Intergovernmental Panel on Climate Change (IPCC) climate change scenarios, i.e., A1B, A2, B1, and Commit, over four time periods, i.e., present day, 2030, 2060, and 2100. When the simulated future C fluxes were compared to the baseline fluxes under the present climate conditions, we found that fens were much more sensitive to climate change than bogs. Gross primary production (GPP) at MB significantly increased by 4-44% up to 2100 for all scenarios except Commit. GPP at DS significantly decreased by 34-39% for A1B and A2, and slightly increased by 6-10% for B1 and Commit. Total ecosystem respiration (TER) significantly increased by 7-57% for MB and 4-34% for DS up to 2100 for all scenarios except Commit. Net ecosystem production (NEP), therefore, significantly decreased. The bog, however, was still a C sink up to 2100, though much reduced, but the fen switched to a C source for A1B and A2 scenarios. Additional experiments where we climatically transplanted the study peatlands or forced vegetation changes when the fen became too dry showed similar but less dramatic results as the standard runs. Our results indicate that northern peatlands should be included in the C-coupled climate model to fully understand the response of C cycling in terrestrial ecosystems to climate change and to reduce the uncertainties for projecting the future climate.

Describing the direct and indirect radiative effects of atmospheric aerosols over Europe by using coupled meteorology-chemistry simulations: a contribution from the AQMEII-Phase II exercise

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Balzarini, Alessandra; Baró, Rocío; Curci, Gabriele; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Langer, Matthias; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Tuccella, Paolo; Werhahn, Johannes; Zabkar, Rahela

2014-05-01

The study of the response of the aerosol levels in the atmosphere to a changing climate and how this affects the radiative budget of the Earth (direct, semi-direct and indirect effects) is an essential topic to build confidence on climate science, since these feedbacks involve the largest uncertainties nowadays. Air quality-climate interactions (AQCI) are, therefore, a key, but uncertain contributor to the anthropogenic forcing that remains poorly understood. To build confidence in the AQCI studies, regional-scale integrated meteorology-atmospheric chemistry models (i.e., models with on-line chemistry) that include detailed treatment of aerosol life cycle and aerosol impacts on radiation (direct effects) and clouds (indirect effects) are in demand. In this context, the main objective of this contribution is the study and definition of the uncertainties in the climate-chemistry-aerosol-cloud-radiation system associated to the direct radiative forcing and the indirect effect caused by aerosols over Europe, using an ensemble of fully-coupled meteorology-chemistry model simulations with the WRF-Chem model run under the umbrella of AQMEII-Phase 2 international initiative. Simulations were performed for Europe for the entire year 2010. According to the common simulation strategy, the year was simulated as a sequence of 2-day time slices. For better comparability, the seven groups applied the same grid spacing of 23 km and shared common processing of initial and boundary conditions as well as anthropogenic and fire emissions. With exception of a simulation with different cloud microphysics, identical physics options were chosen while the chemistry options were varied. Two model set-ups will be considered here: one sub-ensemble of simulations not taking into account any aerosol feedbacks (the baseline case) and another sub-ensemble of simulations which differs from the former by the inclusion of aerosol-radiation feedback. The existing differences for meteorological variables (mainly 2-m temperature and precipitation) and air quality levels (mainly ozone an PM10) between both sub-ensembles of WRF-Chem simulations have been characterized. In the case of ozone and PM10, an increase in solar radiation and temperature has generally resulted in an enhanced photochemical activity and therefore a negative feedback (areas with low aerosol concentrations present more than 50 W m-2 higher global radiation for cloudy conditions). However, simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions strongly depend on the model configuration and the meteorological situation. These results will help providing improved science-based foundations to better assess the impacts of climate variability, support the development of effective climate change policies and optimize private decision-making.

Impact du réchauffement climatique sur le cycle hydrologique

NASA Astrophysics Data System (ADS)

Planton, Serge; Déqué, Michel; Douville, Hervé; Spagnoli, Bruno

2005-02-01

At the planetary scale, the models consistently simulate an intensification of the hydrological cycle in a future climate, warmer than the present-day one. However, this intensification might be accompanied by its slowing down due to an increase of the residence time of water vapour in the atmosphere. The impact of climate change on extreme events is even more difficult to evaluate, as results are dependent on methods, emission scenarios and, above all, on models. However, the increase of extreme winter precipitation over northern Europe is a common feature of these evaluations. The hydrological cycle, through the geographical distribution of continental surface humidity, seems to play a key role on the possibility to detect the warming in France. To cite this article: S. Planton et al., C. R. Geoscience 337 (2005).

Disruption of the European climate seasonal clock in a warming world

NASA Astrophysics Data System (ADS)

Cattiaux, J.; Cassou, C.

2015-12-01

Strength and inland penetration of the oceanic westerly flow over Europe control a large part of the temperature variability over most of the continent. Reduced westerlies, linked to high-pressure anomalies over Scandinavia, induce cold conditions in winter and warm conditions in summer. Here we propose to define the onset of these two seasons as the calendar day where the daily circulation/temperature relationship over Western Europe switches sign. According to this meteorologically-based metrics assessed from several observational datasets, we provide robust evidence for an earlier summer onset by ~10 days between the 1960s and 2000s. Results from model ensemble simulations dedicated to detection-attribution show that this calendar advance is incompatible with the sole internal climate variability and can be attributed to anthropogenic forcings. Late winter snow disappearance over Eastern Europe affects cold air intrusion to the West when easterlies blow, and is mainly responsible for the observed present-day and near-future summer advance. Our findings agree with phenological-based trends (earlier spring events) reported for many living species over Europe, for which they provide a novel dynamical interpretation beyond the traditionally evoked global warming effect. Based on business-as-usual scenario, a seasonal shift of ~25 days is expected by 2100 for summer onset, while no clear signal arises for winter onset.

The Impact of Warm Pool El Nino Events on Antarctic Ozone

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Newman, P. A.; Song, In-Sun; Frith, Stacey M.

2011-01-01

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific in austral spring and summer. Previous work found an enhancement in planetary wave activity in the South Pacific in austral spring, and a warming of 3-5 K in the Antarctic lower stratosphere during austral summer, in WPEN events as compared with ENSO neutral. In this presentation, we show that weakening of the Antarctic vortex during WPEN affects the structure and magnitude of high-latitude total ozone. We use total ozone data from TOMS and OMI, as well as station data from Argentina and Antarctica, to identify shifts in the longitudinal location of the springtime ozone minimum from its climatological position. In addition, we examine the sensitivity of the WPEN-related ozone response to the phase of the quasi-biennial oscillation (QBO). We then compare the observed response to WPEN events with Goddard Earth Observing System chemistry-climate model, version 2 (GEOS V2 CCM) simulations. Two, 50-year time-slice simulations are forced by annually repeating SST and sea ice climatologies, one set representing observed WPEN events and the second set representing neutral ENSO events, in a present-day climate. By comparing the two simulations, we isolate the impact of WPEN events on lower stratospheric ozone, and furthermore, examine the sensitivity of the WPEN ozone response to the phase of the QBO.

Projected Impacts of 21st Century Climate Change on Potential Habitat for Vegetation and Forest Types in Russia

NASA Astrophysics Data System (ADS)

Soja, A. J.; Tchebakova, N. M.; Parfenova, E. I.; Cantin, A.; Conard, S. G.

2015-12-01

Global GCMs have demonstrated profound potential for projections to affect the distribution of terrestrial ecosystems and individual species at all hierarchical levels. We modeled progression of potential Russian ecotones and forest-forming species as the climate changes. Large-scale bioclimatic models were developed to predict Russian zonal vegetation (RuBCliM) and forest types (ForCliM) from three bioclimatic indices (1) growing degree-days above 5 degrees C; (2) negative degree-days below 0 C ; and (3) an annual moisture index (ratio of growing degree days to annual precipitation). The presence or absence of continuous permafrost was explicitly included in the models as limiting the forests and tree species distribution. All simulations to predict vegetation change across Russia were run by coupling our bioclimatic models with bioclimatic indices and the permafrost distribution for the baseline period and for the future 2020, 2050 and 2100 simulated by 3 GCMs (CGCM3.1, HadCM3 and IPSLCM4) and 3 climate change scenarios (A1B, A2 and B1). Under these climate scenarios, it is projected the zonobiomes will shift far northward to reach equilibrium with the change in climate. Under the warmer and drier projected future climate, about half of Russia would be suitable for the forest-steppe ecotone and grasslands, rather than for forests. Water stress tolerant light-needled taiga would have an increased advantage over water-loving dark-needled taiga. Permafrost-tolerant L. dahurica taiga would remain the dominant forest across permafrost. Increases in severe fire weather would lead to increases in large, high-severity fires, especially at boundaries between forest ecotones, which can be expected to facilitate a more rapid progression of vegetation towards a new equilibrium with the climate. Adaptation to climate change may be facilitated by: assisting migration of forests by seed transfers to establish genotypes that may be more ecologically suited as climate changes; and the introduction of suitable agricultural crops that may be potentially adapted to a warmer climate in the expected steppe and forest-steppe.

Quantifying the role of climate variability on extreme total water level impacts: An application of a full simulation model to Ocean Beach, California

NASA Astrophysics Data System (ADS)

Serafin, K.; Ruggiero, P.; Stockdon, H. F.; Barnard, P.; Long, J.

2014-12-01

Many coastal communities worldwide are vulnerable to flooding and erosion driven by extreme total water levels (TWL), potentially dangerous events produced by the combination of large waves, high tides, and high non-tidal residuals. The West coast of the United States provides an especially challenging environment to model these processes due to its complex geological setting combined with uncertain forecasts for sea level rise (SLR), changes in storminess, and possible changes in the frequency of major El Niños. Our research therefore aims to develop an appropriate methodology to assess present-day and future storm-induced coastal hazards along the entire U.S. West coast, filling this information gap. We present the application of this framework in a pilot study at Ocean Beach, California, a National Park site within the Golden Gate National Recreation Area where existing event-scale coastal change data can be used for model calibration and verification. We use a probabilistic, full simulation TWL model (TWL-FSM; Serafin and Ruggiero, in press) that captures the seasonal and interannual climatic variability in extremes using functions of regional climate indices, such as the Multivariate ENSO index (MEI), to represent atmospheric patterns related to the El Niño-Southern Oscillation (ENSO). In order to characterize the effect of climate variability on TWL components, we refine the TWL-FSM by splitting non-tidal residuals into low (monthly mean sea level anomalies) and high frequency (storm surge) components. We also develop synthetic climate indices using Markov sequences to reproduce the autocorrelated nature of ENSO behavior. With the refined TWL-FSM, we simulate each TWL component, resulting in synthetic TWL records providing robust estimates of extreme return level events (e.g., the 100-yr event) and the ability to examine the relative contribution of each TWL component to these extreme events. Extreme return levels are then used to drive storm impact models to examine the probability of coastal change (Stockdon et al., 2013) and thus, the vulnerability to storm-induced coastal hazards that Ocean Beach faces. Future climate variability is easily incorporated into this framework, allowing us to quantify how an evolving climate will alter future extreme TWLs and their related coastal impacts.

Transient climate simulations of the deglaciation 21-9 thousand years before present (version 1) - PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-07-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.

Stream nitrate responses to hydrological forcing and climate change in northern forests of the USA (Invited)

NASA Astrophysics Data System (ADS)

Sebestyen, S. D.; Campbell, J. L.; Shanley, J. B.; Pourmokhtarian, A.; Driscoll, C. T.; Boyer, E. W.

2009-12-01

There is a need to understand how climate variability and change affect nutrient delivery to surface waters. We analyzed long-term records of hydrochemical data to explore how the forms, concentrations, and loadings of nitrogen in forest streams throughout the northern USA vary with catchment wetness. We considered projected changes in growing season length and precipitation patterns to simulate future climate scenarios and to assess how stream nitrate loading responds to hydrological forcing under different climate change scenarios. At the Sleepers River Research Watershed in northeastern Vermont, model results suggest that stream nutrient loadings over the next century will respond to hydrological forcing during climate change that affects the amount of water that flows through the landscape. For example, growing season stream water yield (+20%) and nitrate loadings (+57%) increase in response to greater amounts of precipitation (+28%) during a warmer climate with a longer growing season (+43 days). We further explore these findings by presenting model results from a biogeochemical process model (PnET-BGC) to separate changes that are due to biogeochemical cycling and the effects of hydrological forcing. Our findings suggest that nitrogen cycling and transport will intensify during anthropogenic climate forcing, thereby affecting the timing and magnitude of annual stream nutrient loadings in northern forests of the USA.

Future local and remote influences on Mediterranean ozone air quality and climate forcing

NASA Astrophysics Data System (ADS)

Arnold, S.; Val Martin, M.; Heald, C. L.; Lamarque, J.; Tilmes, S.; Emmons, L. K.

2012-12-01

The Mediterranean region is expected to display large increases in population over the coming decades, and to exhibit strong sensitivity to projected climate change, with increasing frequency of extreme summer temperatures and decreases in precipitation. Understanding of how these changes will affect atmospheric composition in the region is limited. The eastern Mediterranean basin has been shown to exhibit a pronounced summertime local maximum in tropospheric ozone, which impacts both local air quality and the atmospheric radiation balance. The Mediterranean troposphere is influenced by a diverse range of sources, including contributions from inter-continental import, in addition to local anthropogenic and biogenic sources. In summer, the region is subject to import of pollution from Northern Europe in the boundary layer and lower troposphere, from North American sources in the large-scale westerly flow of the free mid and upper-troposphere, as well as import of pollution lofted in the Asian monsoon and carried west to the eastern Mediterranean in anticyclonic flow in the upper troposphere over north Africa. Future atmospheric composition in the Mediterranean is likely to be sensitive to projected changes in emissions from these different sources, as well as changes in transport patterns and dry deposition fluxes under future climate conditions. We use the NCAR Community Earth System Model (CESM) to simulate climate and atmospheric composition for the 2050s, based on greenhouse gas abundances, trace gas and aerosol emissions and land cover and use from two representative concentration pathway (RCP) scenarios (RCP4.5 & RCP8.5), designed for use by the IPCC Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments. By comparing these simulations with a present-day scenario, we investigate the effects of predicted changes in climate and emissions on air quality and climate forcing over the Mediterranean region. The simulations suggest decreases in boundary layer ozone and sulfate aerosol throughout the tropospheric column over the Mediterranean under both RCP scenarios, and an increase in ozone of up to 14 ppbv between 5-10km. This ozone increase is coincident with an increase in easterly import of ozone precursors in upper tropospheric outflow from Asian monsoon convection. We present a breakdown of contributions to the projected ozone changes from changes in emissions and from climate-driven changes. We estimate the implications of the predicted changes in tropospheric composition for Mediterranean air quality and climate in 2050, and the consequences for the effectiveness of European policies aimed at protecting the region's climate and public health.

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

DOE PAGES

Monier, Erwan; Xu, Liyi; Snyder, Richard

2016-04-26

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios,more » climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations-although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Lastly, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.« less

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

NASA Astrophysics Data System (ADS)

Monier, Erwan; Xu, Liyi; Snyder, Richard

2016-05-01

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios, climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations—although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Finally, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.

Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

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

Monier, Erwan; Xu, Liyi; Snyder, Richard

Scientific challenges exist on how to extract information from the wide range of projected impacts simulated by crop models driven by climate ensembles. A stronger focus is required to understand and identify the mechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections of five metrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start of field operations). We use a large ensemble of climate simulations by the MIT IGSM-CAM integrated assessment model that accounts for the uncertainty associated with different emissions scenarios,more » climate sensitivities, and representations of natural variability. By the end of the century, the US is projected to experience fewer frosts, a longer growing season, more heat stress and an earlier start of field operations-although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shown not to be robust. We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). The wide range of our projections compares well the CMIP5 multi-model ensemble, especially for temperature-related indices. This suggests that using a single climate model that accounts for key sources of uncertainty can provide an efficient and complementary framework to the more common approach of multi-model ensembles. We also show that greenhouse gas mitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility for multiple cropping). A major benefit of climate mitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This has major implications considering that any significant climate change impacts on crop yield would result in nation-wide changes in the agriculture sector. Lastly, we argue that the analysis of agro-climate indices should more often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.« less

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

Holocene biome shifts in the East Asian monsoon margin region

NASA Astrophysics Data System (ADS)

Dallmeyer, Anne; Claussen, Martin; Ni, Jian; Wang, Yongbo; Cao, Xianyong; Herzschuh, Ulrike

2013-04-01

East Asia is affected by three major atmospheric circulation systems determining the regional climate and vegetation distribution: The moisture advected by the Indian and East Asian monsoon support the growing of forest in large parts of Eastern China. The influence of the monsoon gets weaker further on the continent yielding a transition of forest to steppe and of steppe to desert in Central East Asia (e.g. Inner Mongolia) where the dry westerly winds prevail. Particularly in these transition zones, vegetation is supposed to be very sensitive to climate change and strong feedbacks are expected in case of climate and vegetation shifts due to large environmental changes (Feng et al., 2006). During mid-Holocene, cyclic variations in the Earth's orbit around the sun led to an enhancement of the Asian monsoon system probably causing strong shifts in the biome distribution. According to reconstructions, the steppe-forest margin moved to the northwest by about 500km (Yu et al., 2000) and the desert area in China and Inner Mongolia was substantially reduced compared to today (Feng et al., 2006). However, in the complex environment of Asia, the locally limited reconstructions may not portray the general vegetation change. To get a systematic overview on the spatial pattern of biome shifts in the Asian monsoon - westerly wind transition zone since mid-Holocene, we use the diagnostic vegetation model BIOME4 and force this model with climate anomalies from different transient Holocene climate simulations performed in coupled atmosphere-ocean-vegetation models. The main aims of this study are to a) get a consistent ensemble of possible changes in biome distribution since the mid-Holocene b) test the robustness of the simulated vegetation changes and quantify the differences between the models, and c) allow for a better comparison of simulated and reconstructed vegetation changes. Preliminary results confirm the general trend seen in the reconstructions. The simulations reveal an expansion of forest for most models and a substantially reduced desert fraction in the transition zone during mid-Holocene. However, the amplitude of the signal and the trend varies for the different climate models. At mid-Holocene, the desert-steppe margin is located further west by approx. 6° in the ensemble mean ranging from 1° to 10° in the different simulations. The forest biomes extend further north-westward by approx. 2° in the ensemble mean ranging from 0° to 4°. In some simulations, the biome distribution shows a strong variability during the last 6000 years and a strong increase of desert starting 500 years before present. In other simulations the biome distribution stays relatively constant until 4500 years before present, afterwards the desert border gradually moves eastward to its present-day position. References: Feng, Z.-D., An, C.B., and Wang, H.B.: Holocene climatic and environmental changes in the arid and semi-arid areas of China: a review. The Holocene 16(1), 119-130, 2006. Yu, G., Chen, X., Ni, J., Cheddadi, R., Guiot, J., Han, H., Harrison, S.P., Huang, C., Ke, M., Kong, Z., Li, S., Li, W., Liew, P., Liu, G., Liu, J., Liu, Q., Liu, K.-B., Prentice, I.C., Qui, W., Ren, G., Song, C., Sugita, S., Sun, X., Tang, L., Van Campo, E., Xia, Y., Xu, Q., Yan, S., Yang, X., Zhao, J., and Zheng, Z.: Palaeovegetation of China: a pollen date-based synthesis for the mid-Holocene and last glacial maximum. J. Biogeogr., 27, 635-664, 2000.

GCM simulations of volcanic aerosol forcing. I - Climate changes induced by steady-state perturbations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Rind, David; Lacis, Andrew; Hansen, James E.; Sato, Makiko; Ruedy, Reto

1993-01-01

The response of the climate system to a temporally and spatially constant amount of volcanic particles is simulated using a general circulation model (GCM). The optical depth of the aerosols is chosen so as to produce approximately the same amount of forcing as results from doubling the present CO2 content of the atmosphere and from the boundary conditions associated with the peak of the last ice age. The climate changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. The simulations indicate that a significant cooling of the troposphere and surface can occur at times of closely spaced multiple sulfur-rich volcanic explosions that span time scales of decades to centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature.

Simulation of Changes in the Near-Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

NASA Astrophysics Data System (ADS)

Guo, Donglin; Wang, Aihui; Li, Duo; Hua, Wei

2018-03-01

Change in the near-surface soil freeze/thaw cycle is critical for assessments of hydrological activity, ecosystems, and climate change. Previous studies investigated the near-surface soil freeze/thaw cycle change mostly based on in situ observations and satellite monitoring. Here numerical simulation method is tested to estimate the long-term change in the near-surface soil freeze/thaw cycle in response to recent climate warming for its application to predictions. Four simulations are performed at 0.5° × 0.5° resolution from 1979 to 2009 using the Community Land Model version 4.5, each driven by one of the four atmospheric forcing data sets (i.e., one default Climate Research Unit-National Centers for Environmental Prediction [CRUNCEP] and three newly developed Modern Era Retrospective-Analysis for Research and Applications, Climate Forecast System Reanalysis, and European Centre for Medium-Range Weather Forecasts Reanalysis Interim). The observations from 299 weather stations in both Russia and China are employed to validate the simulated results. The results show that all simulations reasonably reproduce the observed variations in the ground temperature, the freeze start and end dates, and the freeze duration (the correlation coefficients range from 0.47 to 0.99, and the Nash-Sutcliffe efficiencies range from 0.19 to 0.98). Part of the simulations also exactly simulate the trends of the ground temperature, the freeze start and end dates, and the freeze duration. Of the four simulations, the results from the simulation using the CRUNCEP data set show the best overall agreement with the in situ observations, indicating that the CRUNCEP data set could be preferentially considered as the basic atmospheric forcing data set for future prediction. The simulated area-averaged annual freeze duration shortened by 8.03 days on average from 1979 to 2009, with an uncertainty (one standard deviation) of 0.67 days caused by the different atmospheric forcing data sets. These results address the performance of numerical model in simulating the long-term changes in the near-surface soil freeze/thaw cycle and the role of different atmospheric forcing data sets in the simulation, which are useful for the prediction of future freeze/thaw dynamics.

Latest research related to climate change analysis with applications in impact studies over the territory of Serbia

NASA Astrophysics Data System (ADS)

Vukovic, Ana; Vujadinovic, Mirjam; Djurdjevic, Vladimir; Cvetkovic, Bojan; Djordjevic, Marija; Ruml, Mirjana; Rankovic-Vasic, Zorica; Przic, Zoran; Stojicic, Djurdja; Krzic, Aleksandra; Rajkovic, Borivoj

2015-04-01

Serbia is a country with relatively small scale terrain features with economy mostly based on local landowners' agricultural production. Climate change analysis must be downscaled accordingly, to recognize climatological features of the farmlands. Climate model simulations and impact studies significantly contribute to the future strategic planning in economic development and therefore impact analysis must be approached with high level of confidence. This paper includes research related to climate change and impacts in Serbia resulted from cooperative work of the modeling and user community. Dynamical downscaling of climate projections for the 21st century with multi-model approach and statistical bias correction are done in order to prepare model results for impact studies. Presented results are from simulations performed using regional EBU-POM model, which is forced with A1B and A2 SRES/IPCC (2007) with comparative analysis with other regional models and from the latest high resolution NMMB simulations forced with RCP8.5 IPCC scenario (2012). Application of bias correction of the model results is necessary when calculated indices are not linearly dependent on the model results and delta approach in presenting results with respect to present climate simulations is insufficient. This is most important during the summer over the north part of the country where model bias produce much higher temperatures and less precipitation, which is known as "summer drying problem" and is common in regional models' simulations over the Pannonian valley. Some of the results, which are already observed in present climate, like higher temperatures and disturbance in the precipitation pattern, lead to present and future advancement of the start of the vegetation period toward earlier dates, associated with an increased risk of the late spring frost, extended vegetation period, disturbed preparation for the rest period, increased duration and frequency of the draught periods, etc. Based on the projected climate changes an application is proposed of the ensemble seasonal forecasts for early preparation in case of upcoming unfavorable weather conditions. This paper was realized as a part of the projects "Studying climate change and its influence on the environment: impacts, adaptation and mitigation" (43007) and "Assessment of climate change impacts on water resources in Serbia" (37005) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011-2015.

Testing a Weather Generator for Downscaling Climate Change Projections over Switzerland

NASA Astrophysics Data System (ADS)

Keller, Denise E.; Fischer, Andreas M.; Liniger, Mark A.; Appenzeller, Christof; Knutti, Reto

2016-04-01

Climate information provided by global or regional climate models (RCMs) are often too coarse and prone to substantial biases, making it impossible to directly use daily time-series of the RCMs for local assessments and in climate impact models. Hence, statistical downscaling becomes necessary. For the Swiss National Climate Change Initiative (CH2011), a delta-change approach was used to provide daily climate projections at the local scale. This data have the main limitations that changes in variability, extremes and in the temporal structure, such as changes in the wet day frequency, are not reproduced. The latter is a considerable downside of the delta-change approach for many impact applications. In this regard, stochastic weather generators (WGs) are an appealing technique that allow the simulation of multiple realizations of synthetic weather sequences consistent with the locally observed weather statistics and its future changes. Here, we analyse a Richardson-type weather generator (WG) as an alternative method to downscale daily precipitation, minimum and maximum temperature. The WG is calibrated for 26 Swiss stations and the reference period 1980-2009. It is perturbed with change factors derived from 12 RCMs (ENSEMBLES) to represent the climate of 2070-2099 assuming the SRES A1B emission scenario. The WG can be run in multi-site mode, making it especially attractive for impact-modelers that rely on a realistic spatial structure in downscaled time-series. The results from the WG are benchmarked against the original delta-change approach that applies mean additive or multiplicative adjustments to the observations. According to both downscaling methods, the results reveal area-wide mean temperature increases and a precipitation decrease in summer, consistent with earlier studies. For the summer drying, the WG indicates primarily a decrease in wet-day frequency and correspondingly an increase in mean dry spell length by around 18% - 40% at low-elevation stations. By construction, these potential changes cannot be represented by a delta-change approach. In winter, both methods project a shortening of the frost period (-30 to -60 days) and a decrease of snow days (-20% to -100%). The WG demonstrates though, that almost present-day conditions in snow-days could still occur in the future. As expected, both methods have difficulties in representing extremes. If users focus on changes in temporal sequences and need a large number of future realizations that are spatially consistent, it is recommended to use data from a WG instead of a delta-change approach.

An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol

NASA Astrophysics Data System (ADS)

Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M.

2017-12-01

In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is discussed.

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.; Suarez, Max J.

2000-01-01

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which 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. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. 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 action).

Estimating the human influence on Hurricanes Harvey, Irma and Maria

NASA Astrophysics Data System (ADS)

Wehner, M. F.; Patricola, C. M.; Risser, M. D.

2017-12-01

Attribution of the human-induced climate change influence on the physical characteristics of individual extreme weather events has become an advanced science over the past decade. However, it is only recently that such quantification of anthropogenic influences on event magnitudes and probability of occurrence could be applied to very extreme storms such as hurricanes. We present results from two different classes of attribution studies for the impactful Atlantic hurricanes of 2017. The first is an analysis of the record rainfall amounts during Hurricane Harvey in the Houston, Texas area. We analyzed observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of ENSO. We found that human-induced climate change likely increased Hurricane Harvey's total rainfall by at least 19%, and likely increased the chances of the observed rainfall by a factor of at least 3.5. This suggests that changes exceeded Clausius-Clapeyron scaling, motivating attribution studies using dynamical climate models. The second analysis consists of two sets of hindcast simulations of Hurricanes Harvey, Irma, and Maria using the Weather Research and Forecasting model (WRF) at 4.5 km resolution. The first uses realistic boundary and initial conditions and present-day greenhouse gas forcings while the second uses perturbed conditions and pre-industrial greenhouse has forcings to simulate counterfactual storms without anthropogenic influences. These simulations quantify the fraction of Harvey's precipitation attributable to human activities and test the super Clausius-Clapeyron scaling suggested by the observational analysis. We will further quantify the human influence on intensity for Harvey, Irma, and Maria.

Water and nitrogen management effects on semiarid sorghum production and soil trace gas flux under future climate.

PubMed

Duval, Benjamin D; Ghimire, Rajan; Hartman, Melannie D; Marsalis, Mark A

2018-01-01

External inputs to agricultural systems can overcome latent soil and climate constraints on production, while contributing to greenhouse gas emissions from fertilizer and water management inefficiencies. Proper crop selection for a given region can lessen the need for irrigation and timing of N fertilizer application with crop N demand can potentially reduce N2O emissions and increase N use efficiency while reducing residual soil N and N leaching. However, increased variability in precipitation is an expectation of climate change and makes predicting biomass and gas flux responses to management more challenging. We used the DayCent model to test hypotheses about input intensity controls on sorghum (Sorghum bicolor (L.) Moench) productivity and greenhouse gas emissions in the southwestern United States under future climate. Sorghum had been previously parameterized for DayCent, but an inverse-modeling via parameter estimation method significantly improved model validation to field data. Aboveground production and N2O flux were more responsive to N additions than irrigation, but simulations with future climate produced lower values for sorghum than current climate. We found positive interactions between irrigation at increased N application for N2O and CO2 fluxes. Extremes in sorghum production under future climate were a function of biomass accumulation trajectories related to daily soil water and mineral N. Root C inputs correlated with soil organic C pools, but overall soil C declined at the decadal scale under current weather while modest gains were simulated under future weather. Scaling biomass and N2O fluxes by unit N and water input revealed that sorghum can be productive without irrigation, and the effect of irrigating crops is difficult to forecast when precipitation is variable within the growing season. These simulation results demonstrate the importance of understanding sorghum production and greenhouse gas emissions at daily scales when assessing annual and decadal-scale management decisions' effects on aspects of arid and semiarid agroecosystem biogeochemistry.

Multimodel comparison of the ionosphere variability during the 2009 sudden stratosphere warming

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Fang, T.-W.; Jin, H.; Sassi, F.; Schmidt, H.; Chau, J. L.; Siddiqui, T. A.; Goncharenko, L.

2016-07-01

A comparison of different model simulations of the ionosphere variability during the 2009 sudden stratosphere warming (SSW) is presented. The focus is on the equatorial and low-latitude ionosphere simulated by the Ground-to-topside model of the Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Model plus Global Ionosphere Plasmasphere (WAM+GIP), and Whole Atmosphere Community Climate Model eXtended version plus Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (WACCMX+TIMEGCM). The simulations are compared with observations of the equatorial vertical plasma drift in the American and Indian longitude sectors, zonal mean F region peak density (NmF2) from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, and ground-based Global Positioning System (GPS) total electron content (TEC) at 75°W. The model simulations all reproduce the observed morning enhancement and afternoon decrease in the vertical plasma drift, as well as the progression of the anomalies toward later local times over the course of several days. However, notable discrepancies among the simulations are seen in terms of the magnitude of the drift perturbations, and rate of the local time shift. Comparison of the electron densities further reveals that although many of the broad features of the ionosphere variability are captured by the simulations, there are significant differences among the different model simulations, as well as between the simulations and observations. Additional simulations are performed where the neutral atmospheres from four different whole atmosphere models (GAIA, HAMMONIA (Hamburg Model of the Neutral and Ionized Atmosphere), WAM, and WACCMX) provide the lower atmospheric forcing in the TIME-GCM. These simulations demonstrate that different neutral atmospheres, in particular, differences in the solar migrating semidiurnal tide, are partly responsible for the differences in the simulated ionosphere variability in GAIA, WAM+GIP, and WACCMX+TIMEGCM.

Impact of a drier Early-Mid-Holocene climate upon Amazonian forests.

PubMed

Mayle, Francis E; Power, Mitchell J

2008-05-27

This paper uses a palaeoecological approach to examine the impact of drier climatic conditions of the Early-Mid-Holocene (ca 8000-4000 years ago) upon Amazonia's forests and their fire regimes. Palaeovegetation (pollen data) and palaeofire (charcoal) records are synthesized from 20 sites within the present tropical forest biome, and the underlying causes of any emergent patterns or changes are explored by reference to independent palaeoclimate data and present-day patterns of precipitation, forest cover and fire activity across Amazonia. During the Early-Mid-Holocene, Andean cloud forest taxa were replaced by lowland tree taxa as the cloud base rose while lowland ecotonal areas, which are presently covered by evergreen rainforest, were instead dominated by savannahs and/or semi-deciduous dry forests. Elsewhere in the Amazon Basin there is considerable spatial and temporal variation in patterns of vegetation disturbance and fire, which probably reflects the complex heterogeneous patterns in precipitation and seasonality across the basin, and the interactions between climate change, drought- and fire susceptibility of the forests, and Palaeo-Indian land use. Our analysis shows that the forest biome in most parts of Amazonia appears to have been remarkably resilient to climatic conditions significantly drier than those of today, despite widespread evidence of forest burning. Only in ecotonal areas is there evidence of biome replacement in the Holocene. From this palaeoecological perspective, we argue against the Amazon forest 'dieback' scenario simulated for the future.

Mid-Western US heavy summer-precipitation in regional and global climate models: the impact on model skill and consensus through an analogue lens

NASA Astrophysics Data System (ADS)

Gao, Xiang; Schlosser, C. Adam

2018-04-01

Regional climate models (RCMs) can simulate heavy precipitation more accurately than general circulation models (GCMs) through more realistic representation of topography and mesoscale processes. Analogue methods of downscaling, which identify the large-scale atmospheric conditions associated with heavy precipitation, can also produce more accurate and precise heavy precipitation frequency in GCMs than the simulated precipitation. In this study, we examine the performances of the analogue method versus direct simulation, when applied to RCM and GCM simulations, in detecting present-day and future changes in summer (JJA) heavy precipitation over the Midwestern United States. We find analogue methods are comparable to MERRA-2 and its bias-corrected precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events, all significantly improving upon MERRA precipitation. For the late twentieth-century heavy precipitation frequency, RCM precipitation improves upon the corresponding driving GCM with greater accuracy yet comparable inter-model discrepancies, while both RCM- and GCM-based analogue results outperform their model-simulated precipitation counterparts in terms of accuracy and model consensus. For the projected trends in heavy precipitation frequency through the mid twenty-first century, analogue method also manifests its superiority to direct simulation with reduced intermodel disparities, while the RCM-based analogue and simulated precipitation do not demonstrate a salient improvement (in model consensus) over the GCM-based assessment. However, a number of caveats preclude any overall judgement, and further work—over any region of interest—should include a larger sample of GCMs and RCMs as well as ensemble simulations to comprehensively account for internal variability.

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

Different sensitivities of snowpacks to warming in Mediterranean climate mountain areas

NASA Astrophysics Data System (ADS)

López-Moreno, J. I.; Gascoin, S.; Herrero, J.; Sproles, E. A.; Pons, M.; Alonso-González, E.; Hanich, L.; Boudhar, A.; Musselman, K. N.; Molotch, N. P.; Sickman, J.; Pomeroy, J.

2017-07-01

In this study we quantified the sensitivity of snow to climate warming in selected mountain sites having a Mediterranean climate, including the Pyrenees in Spain and Andorra, the Sierra Nevada in Spain and California (USA), the Atlas in Morocco, and the Andes in Chile. Meteorological observations from high elevations were used to simulate the snow energy and mass balance (SEMB) and calculate its sensitivity to climate. Very different climate sensitivities were evident amongst the various sites. For example, reductions of 9%-19% and 6-28 days in the mean snow water equivalent (SWE) and snow duration, respectively, were found per °C increase. Simulated changes in precipitation (±20%) did not affect the sensitivities. The Andes and Atlas Mountains have a shallow and cold snowpack, and net radiation dominates the SEMB; and explains their relatively low sensitivity to climate warming. The Pyrenees and USA Sierra Nevada have a deeper and warmer snowpack, and sensible heat flux is more important in the SEMB; this explains the much greater sensitivities of these regions. Differences in sensitivity help explain why, in regions where climate models project relatively greater temperature increases and drier conditions by 2050 (such as the Spanish Sierra Nevada and the Moroccan Atlas Mountains), the decline in snow accumulation and duration is similar to other sites (such as the Pyrenees and the USA Sierra Nevada), where models project stable precipitation and more attenuated warming. The snowpack in the Andes (Chile) exhibited the lowest sensitivity to warming, and is expected to undergo only moderate change (a decrease of <12% in mean SWE, and a reduction of < 7 days in snow duration under RCP 4.5). Snow accumulation and duration in the other regions are projected to decrease substantially (a minimum of 40% in mean SWE and 15 days in snow duration) by 2050.

On the identification of a Pliocene time slice for data–model comparison

USGS Publications Warehouse

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception.

On the identification of a Pliocene time slice for data–model comparison

PubMed Central

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception. PMID:24043865

Implementation of Tritium in the Lmdz-Iso General Circulation Model: First Promising Results for the Study of the Relationships Between Stratospheric Air Inputs into the Lower Troposphere in Polar Regions, Water Cycle and Climate

NASA Astrophysics Data System (ADS)

Cauquoin, A.; Jean Baptiste, P.; Risi, C. M.; Fourre, E.; Landais, A.

2014-12-01

Understanding the links between climate and water cycle is essential in the current context of global warming. The water isotopic composition, quantified as δD, δ18O or δ17O, has a great potential to trace the organization of present-day hydrological cycle. When recorded in various archives as tree rings, sediments, ice cores, they have also been largely used to reconstruct the past evolution of climate and water. The Antarctic cap is extremely sensitive to climate change. Moreover, this region is under the influence of exchanges between the troposphere and the stratosphere because of the presence of the polar vortex. Tritium (3H) has been shown to be an appropriate tracer for the intrusion of stratospheric air masses into the lower troposphere. Natural tritium is mainly produced by the interaction of cosmic radiations with the upper atmosphere. This tritium enters the hydrological cycle in the form of tritiated water molecules (HTO) and has a radioactive half-life of 4500±8 days. In an approach combining data and model, we have first implemented tritium in the coupled Laboratoire de Météorologie Dynamique Zoom (LMDZ) Atmospheric General Circulation Model developed at IPSL [Risi et al., 2010]: LMDZ-iso. The implementation of natural tritium uses the same model architecture as for the other water isotopes, after a correct description of associated cosmogenic production terms [Masarik and Beer, 2009]. The model is used in a configuration dedicated to the simulation of the stratosphere, with 39 layers. In this presentation, we will focus on the modeling of spatial and temporal natural variations of tritium content in precipitation. The model is validated against a compilation of available data for natural tritium. We show that the continental and latitudinal effects are well reproduced by the model and that simulated seasonal variations of the tritium content of precipitation are coherent with our current knowledge of troposphere-stratosphere exchanges. Masarik and Beer (2009) J. Geophys. Res., 114, D11103. Risi et al. (2010) J. Geophys. Res., 115, D12118.

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Projected Changes on the Global Surface Wave Drift Climate towards the END of the Twenty-First Century

NASA Astrophysics Data System (ADS)

Carrasco, Ana; Semedo, Alvaro; Behrens, Arno; Weisse, Ralf; Breivik, Øyvind; Saetra, Øyvind; Håkon Christensen, Kai

2016-04-01

The global wave-induced current (the Stokes Drift - SD) is an important feature of the ocean surface, with mean values close to 10 cm/s along the extra-tropical storm tracks in both hemispheres. Besides the horizontal displacement of large volumes of water the SD also plays an important role in the ocean mix-layer turbulence structure, particularly in stormy or high wind speed areas. The role of the wave-induced currents in the ocean mix-layer and in the sea surface temperature (SST) is currently a hot topic of air-sea interaction research, from forecast to climate ranges. The SD is mostly driven by wind sea waves and highly sensitive to changes in the overlaying wind speed and direction. The impact of climate change in the global wave-induced current climate will be presented. The wave model WAM has been forced by the global climate model (GCM) ECHAM5 wind speed (at 10 m height) and ice, for present-day and potential future climate conditions towards the end of the end of the twenty-first century, represented by the Intergovernmental Panel for Climate Change (IPCC) CMIP3 (Coupled Model Inter-comparison Project phase 3) A1B greenhouse gas emission scenario (usually referred to as a ''medium-high emissions'' scenario). Several wave parameters were stored as output in the WAM model simulations, including the wave spectra. The 6 hourly and 0.5°×0.5°, temporal and space resolution, wave spectra were used to compute the SD global climate of two 32-yr periods, representative of the end of the twentieth (1959-1990) and twenty-first (1969-2100) centuries. Comparisons of the present climate run with the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-40 reanalysis are used to assess the capability of the WAM-ECHAM5 runs to produce realistic SD results. This study is part of the WRCP-JCOMM COWCLIP (Coordinated Ocean Wave Climate Project) effort.

Hydrological and biogeochemical constraints on terrestrial carbon cycle feedbacks

NASA Astrophysics Data System (ADS)

Mystakidis, Stefanos; Seneviratne, Sonia I.; Gruber, Nicolas; Davin, Edouard L.

2017-01-01

The feedbacks between climate, atmospheric CO2 concentration and the terrestrial carbon cycle are a major source of uncertainty in future climate projections with Earth systems models. Here, we use observation-based estimates of the interannual variations in evapotranspiration (ET), net biome productivity (NBP), as well as the present-day sensitivity of NBP to climate variations, to constrain globally the terrestrial carbon cycle feedbacks as simulated by models that participated in the fifth phase of the coupled model intercomparison project (CMIP5). The constraints result in a ca. 40% lower response of NBP to climate change and a ca. 30% reduction in the strength of the CO2 fertilization effect relative to the unconstrained multi-model mean. While the unconstrained CMIP5 models suggest an increase in the cumulative terrestrial carbon storage (477 PgC) in response to an idealized scenario of 1%/year atmospheric CO2 increase, the constraints imply a ca. 19% smaller change. Overall, the applied emerging constraint approach offers a possibility to reduce uncertainties in the projections of the terrestrial carbon cycle, which is a key determinant of the future trajectory of atmospheric CO2 concentration and resulting climate change.

Climate change jeopardizes the persistence of freshwater zooplankton by reducing both habitat suitability and demographic resilience.

PubMed

Pinceel, Tom; Buschke, Falko; Weckx, Margo; Brendonck, Luc; Vanschoenwinkel, Bram

2018-01-24

Higher temperatures and increased environmental variability under climate change could jeopardize the persistence of species. Organisms that rely on short windows of rainfall to complete their life-cycles, like desert annual plants or temporary pool animals, may be particularly at risk. Although some could tolerate environmental changes by building-up banks of propagules (seeds or eggs) that buffer against catastrophes, climate change will threaten this resilience mechanism if higher temperatures reduce propagule survival. Using a crustacean model species from temporary waters, we quantified experimentally the survival and dormancy of propagules under anticipated climate change and used these demographic parameters to simulate long term population dynamics. By exposing propagules to present-day and projected daily temperature cycles in an 8 month laboratory experiment, we showed how increased temperatures reduce survival rates in the propagule bank. Integrating these reduced survival rates into population models demonstrated the inability of the bank to maintain populations; thereby exacerbating extinction risk caused by shortened growing seasons. Overall, our study demonstrates that climate change could threaten the persistence of populations by both reducing habitat suitability and eroding life-history strategies that support demographic resilience.

Evaluating the Appropriateness of Downscaled Climate Information for Projecting Risks of Salmonella.

PubMed

Guentchev, Galina S; Rood, Richard B; Ammann, Caspar M; Barsugli, Joseph J; Ebi, Kristie; Berrocal, Veronica; O'Neill, Marie S; Gronlund, Carina J; Vigh, Jonathan L; Koziol, Ben; Cinquini, Luca

2016-02-29

Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts. This study presents an evaluation of temperature-based heat indices for the Washington D.C. area derived from statistically downscaled GCM simulations for 1971-2000--a necessary step in establishing the credibility of these data. The indices approximate high weekly mean temperatures linked previously to occurrences of Salmonella infections. Due to bias-correction, included in the Asynchronous Regional Regression Model (ARRM) and the Bias Correction Constructed Analogs (BCCA) downscaling methods, the observed 30-year means of the heat indices were reproduced reasonably well. In April and May, however, some of the statistically downscaled data misrepresent the increase in the number of hot days towards the summer months. This study demonstrates the dependence of the outcomes to the selection of downscaled climate data and the potential for misinterpretation of future estimates of Salmonella infections.

Interactions between tectonics, climate and vegetation during the Cretaceous. A context for the diversification of Angiosperms.

NASA Astrophysics Data System (ADS)

Sepulchre, Pierre; Chaboureau, Anne-Claire; Donnadieu, Yannick; Franc, Alain; Ladant, Jean-Baptiste

2017-04-01

It has long been thought that the Angiosperms diversification occurred within a context of warmer-than-present and equable climate during the Cretaceous. However, during the last decade, the view of a uniformely warm Cretaceous climate has been challenged both by paleoclimate proxies and numerical simulations. Among the processes likely affecting climate during this time, atmospheric pCO2 and tectonics appear to be pivotal to drive temperature and precipitation changes, while the feedbacks from vegetation cover changes on the hydrological cycles remain to be explored. Here we attempt to provide a review of the main studies exploring climate-vegetation interactions during the Cretaceous. Then we present climate simulations aiming at quantifying the impact of landmasses redistribution on climate and vegetation distribution from 225 Ma to 70 Ma. In our simulations, the Pangea breakup triggers the decrease of arid belts from the Triassic to the Cretaceous and a subsequent onset of humid conditions during the late Cretaceous. Positioning angiosperm-bearing fossil sites on our paleo-bioclimatic maps confirm that the rise of flowering plants occured within a context of changing climate. With additional simulations in which we modified physiological parameterizations of the vegetation, we explore the combined impact of paleogeography and shift to angiosperms-dominated land surfaces on climate at the regional and global scales. This gives us the opportunity to test earlier ideas that the angiosperms takeover could have benefited from a positive feedback induced by their particular transpiration capacities.

Simulating adaptive wood harvest in a changing climate

NASA Astrophysics Data System (ADS)

Yousefpour, Rasoul; Nabel, Julia; Pongratz, Julia

2016-04-01

The world's forest experience substantial carbon exchange fluxes between land and atmosphere. Large carbon sinks occur in response to changes in environmental conditions (such as climate change and increased atmospheric CO2 concentrations), removing about one quarter of current anthropogenic CO2-emissions. Large sinks also occur due to regrowth of forest on areas of agricultural abandonment or forest management. Forest management, on the other hand, also leads to substantial amounts of carbon being eventually released to the atmosphere. Both sinks and sources attributable to forests are therefore dependent on the intensity of management. Forest management in turn depends on the availability of resources, which is influenced by environmental conditions and sustainability of management systems applied. Estimating future carbon fluxes therefore requires accounting for the interaction of environmental conditions, forest growth, and management. However, this interaction is not fully captured by current modeling approaches: Earth system models depict in detail interactions between climate, the carbon cycle, and vegetation growth, but use prescribed information on management. Resource needs and land management, however, are simulated by Integrated Assessment Models that typically only have coarse representations of the influence of environmental changes on vegetation growth and are typically based on the demand for wood driven by regional population growth and energy needs. Here we present a study that provides the link between environmental conditions, forest growth and management. We extend the land component JSBACH of the Max Planck Institute's Earth system model (MPI-ESM) to simulate potential wood harvest in response to altered growth conditions and thus as adaptive to changing climate and CO2 conditions. We apply the altered model to estimate potential wood harvest for future climates (representative concentration pathways, RCPs) for the management scenario of "sustained yields" (SY), i.e. that wood harvest is not allowed to reduce wood carbon stocks below their present-day average state. We find that the potentials for SY range from about 420 to 610 PgC cumulatively until 2100 depending on assumed future climate (RCPs 2.6, 4.5 or 8.5). They are thus substantially higher than the harvest prescribed in the context of the same RCPs for the coupled model intercomparison project (CMIP5), which ranged from about 130 to 210 PgC. The underlying drivers of the higher potentials of SY as compared to the RCP harvest are in all scenarios foremost avoided natural mortality, followed by avoided losses due to fire and windbreak. Further, usage of the increase in forest carbon stocks simulated with time under RCP harvest plays a large role in the first decades of the 21st century. The potential wood harvest that we simulate accounting for environmental changes does not include considerations on biodiversity and other ecosystem services or technical feasibility. However, the substantially higher simulated harvest from SY as compared to that prescribed from the RCPs and the difference found between climate scenarios highlights the need to account for effects of environmental changes on vegetation growth also in socio-economic models and thus the need for a consistent representation of climate-landuse interactions.

GIS and crop simulation modelling applications in climate change research

USDA-ARS?s Scientific Manuscript database

The challenges that climate change presents humanity require an unprecedented ability to predict the responses of crops to environment and management. Geographic information systems (GIS) and crop simulation models are two powerful and highly complementary tools that are increasingly used for such p...

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Climate change and watershed mercury export: a multiple projection and model analysis

USGS Publications Warehouse

Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

2013-01-01

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

Pathways to 1.5 °C and 2 °C warming based on observational and geological constraints

NASA Astrophysics Data System (ADS)

Goodwin, Philip; Katavouta, Anna; Roussenov, Vassil M.; Foster, Gavin L.; Rohling, Eelco J.; Williams, Richard G.

2018-02-01

To restrict global warming to below the agreed targets requires limiting carbon emissions, the principal driver of anthropogenic warming. However, there is significant uncertainty in projecting the amount of carbon that can be emitted, in part due to the limited number of Earth system model simulations and their discrepancies with present-day observations. Here we demonstrate a novel approach to reduce the uncertainty of climate projections; using theory and geological evidence we generate a very large ensemble (3 × 104) of projections that closely match records for nine key climate metrics, which include warming and ocean heat content. Our analysis narrows the uncertainty in surface-warming projections and reduces the range in equilibrium climate sensitivity. We find that a warming target of 1.5 °C above the pre-industrial level requires the total emitted carbon from the start of year 2017 to be less than 195-205 PgC (in over 66% of the simulations), whereas a warming target of 2 °C is only likely if the emitted carbon remains less than 395-455 PgC. At the current emission rates, these warming targets are reached in 17-18 years and 35-41 years, respectively, so that there is a limited window to develop a more carbon-efficient future.

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 of over 35 days per year. Results show significant projected decreases in mean annual, spring and summer precipitation amounts by mid-century. The projected decreases are largest for summer, with "likely" reductions ranging from 0% to 20%. The frequencies of heavy precipitation events show notable increases (approximately 20%) during the winter and autumn months. The number of extended dry periods is projected to increase substantially during autumn and summer. Regional variations of projected precipitation change remain statistically elusive. The energy content of the wind is projected to significantly decrease for the future spring, summer and autumn months. Projected increases for winter were found to be statistically insignificant. The projected decreases were largest for summer, with "likely" values ranging from 3% to 15%. Results suggest that the tracks of intense storms are projected to extend further south over Ireland relative to those in the reference simulation. As extreme storm events are rare, the storm-tracking research needs to be extended. Future work will focus on analysing a larger ensemble, thus allowing a robust statistical analysis of extreme storm track projections.

Dynamic simulation and numerical analysis of hurricane storm surge under sea level rise with geomorphologic changes along the northern Gulf of Mexico

USGS Publications Warehouse

Bilskie, Matthew V.; Hagen, S.C.; Alizad, K.A.; Medeiros, S.C.; Passeri, Davina L.; Needham, H.F.; Cox, A.

2016-01-01

This work outlines a dynamic modeling framework to examine the effects of global climate change, and sea level rise (SLR) in particular, on tropical cyclone-driven storm surge inundation. The methodology, applied across the northern Gulf of Mexico, adapts a present day large-domain, high resolution, tide, wind-wave, and hurricane storm surge model to characterize the potential outlook of the coastal landscape under four SLR scenarios for the year 2100. The modifications include shoreline and barrier island morphology, marsh migration, and land use land cover change. Hydrodynamics of 10 historic hurricanes were simulated through each of the five model configurations (present day and four SLR scenarios). Under SLR, the total inundated land area increased by 87% and developed and agricultural lands by 138% and 189%, respectively. Peak surge increased by as much as 1 m above the applied SLR in some areas, and other regions were subject to a reduction in peak surge, with respect to the applied SLR, indicating a nonlinear response. Analysis of time-series water surface elevation suggests the interaction between SLR and storm surge is nonlinear in time; SLR increased the time of inundation and caused an earlier arrival of the peak surge, which cannot be addressed using a static (“bathtub”) modeling framework. This work supports the paradigm shift to using a dynamic modeling framework to examine the effects of global climate change on coastal inundation. The outcomes have broad implications and ultimately support a better holistic understanding of the coastal system and aid restoration and long-term coastal sustainability.

The impact of Southern Ocean gateways on the Cenozoic climate evolution

NASA Astrophysics Data System (ADS)

von der Heydt, Anna; Viebahn, Jan; Dijkstra, Henk

2016-04-01

During the Cenozoic period, which covers the last 65 Million (Ma) years, Earth's climate has undergone a major long-term transition from warm "greenhouse" to colder "icehouse" conditions with extensive ice sheets in the polar regions of both hemispheres. On the very long term the gradual cooling may be seen as response to the overall slowly decreasing atmospheric CO2-concentration due to weathering processes in the Earth System, however, continental geometry has changed considerably over this period and the long-term gradual trend was interrupted, by several rapid transitions as well as periods where temperature and greenhouse gas concentrations seem to be decoupled. The Eocene-Oligocene boundary (˜34 Ma, E/O) and mid-Miocene climatic transition (˜13 Ma, MCT) reflect major phases of Antarctic ice sheet build-up and global climate cooling, while Northern Hemisphere ice sheets developed much later, most likely at the Pliocene-Pleistocene transition (˜2.7Ma). Thresholds in atmospheric CO2-concentration together with feedback mechanisms related to land ice formation are now among the favoured mechanisms of these climatic transitions, while the long-proposed ocean circulation changes caused by opening of tectonic gateways seem to play a less direct role. The opening of the Southern Ocean gateways, notably the Drake Passage and the Tasman Gateway as well as the northward movement of Australia over this long time period, however, has eventually led to the development of today's strongest ocean current, the Antarctic Circumpolar Current (ACC), playing a major role in the transport properties of the global ocean circulation. The overall state of the global ocean circulation, therefore, preconditions the climate system to dramatic events such as major ice sheet formation. Here, we present results of a state-of-the art global climate model (CESM) under various continental configurations: (i) present day geometry, (ii) present day geometry with a closed Drake Passage and (iii) a recently developed late Eocene continental configuration. Between the different configurations we find significant differences in heat transport as well as sea surface and deep ocean temperatures around the Antarctic continent. By decomposing the heat transport with respect to different ocean circulation regimes, we reveal the dominant physical processes responsible for the heat transport changes. Moreover, we compare the fully coupled system with the corresponding ocean-only simulations in order to further analyze the interplay between the ocean gateways, sea-ice and atmospheric feedbacks. Finally, for the ocean-only simulations we also compare eddy-resolving spatial resolution with non-eddying resolution to quantify the relevance of resolved mesoscale turbulence on the changes in ocean circulation regimes induced by gateway openings. In conclusion, we demonstrate that for deciphering the different mechanisms active in the steps of the Cenozoic greenhouse-to-icehouse transition detailed analyses of the pathways of heat in the different climate subsystems are crucial in order to clearly identify the physical processes at work.

Multiple Climate States of Habitable Exoplanets: The Role of Obliquity and Irradiance

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

Kilic, C.; Raible, C. C.; Stocker, T. F., E-mail: stocker@climate.unibe.ch

Stable, steady climate states on an Earth-size planet with no continents are determined as a function of the tilt of the planet’s rotation axis (obliquity) and stellar irradiance. Using a general circulation model of the atmosphere coupled to a slab ocean and a thermodynamic sea ice model, two states, the Aquaplanet and the Cryoplanet, are found for high and low stellar irradiance, respectively. In addition, four stable states with seasonally and perennially open water are discovered if comprehensively exploring a parameter space of obliquity from 0° to 90° and stellar irradiance from 70% to 135% of the present-day solar constant.more » Within 11% of today’s solar irradiance, we find a rich structure of stable states that extends the area of habitability considerably. For the same set of parameters, different stable states result if simulations are initialized from an aquaplanet or a cryoplanet state. This demonstrates the possibility of multiple equilibria, hysteresis, and potentially rapid climate change in response to small changes in the orbital parameters. The dynamics of the atmosphere of an aquaplanet or a cryoplanet state is investigated for similar values of obliquity and stellar irradiance. The atmospheric circulation substantially differs in the two states owing to the relative strength of the primary drivers of the meridional transport of heat and momentum. At 90° obliquity and present-day solar constant, the atmospheric dynamics of an Aquaplanet state and one with an equatorial ice cover is analyzed.« less

Multiple Climate States of Habitable Exoplanets: The Role of Obliquity and Irradiance

NASA Astrophysics Data System (ADS)

Kilic, C.; Raible, C. C.; Stocker, T. F.

2017-08-01

Stable, steady climate states on an Earth-size planet with no continents are determined as a function of the tilt of the planet’s rotation axis (obliquity) and stellar irradiance. Using a general circulation model of the atmosphere coupled to a slab ocean and a thermodynamic sea ice model, two states, the Aquaplanet and the Cryoplanet, are found for high and low stellar irradiance, respectively. In addition, four stable states with seasonally and perennially open water are discovered if comprehensively exploring a parameter space of obliquity from 0° to 90° and stellar irradiance from 70% to 135% of the present-day solar constant. Within 11% of today’s solar irradiance, we find a rich structure of stable states that extends the area of habitability considerably. For the same set of parameters, different stable states result if simulations are initialized from an aquaplanet or a cryoplanet state. This demonstrates the possibility of multiple equilibria, hysteresis, and potentially rapid climate change in response to small changes in the orbital parameters. The dynamics of the atmosphere of an aquaplanet or a cryoplanet state is investigated for similar values of obliquity and stellar irradiance. The atmospheric circulation substantially differs in the two states owing to the relative strength of the primary drivers of the meridional transport of heat and momentum. At 90° obliquity and present-day solar constant, the atmospheric dynamics of an Aquaplanet state and one with an equatorial ice cover is analyzed.

Warming ancient Mars with water clouds

NASA Astrophysics Data System (ADS)

Hartwick, V.; Toon, B.

2017-12-01

High clouds in the present day Mars atmosphere nucleate on interplanetary dust particles (IDPs) that burn up on entry into the Mars atmosphere. Clouds form when superstaturated water vapor condenses on suspended aerosols. Radiatively active water ice clouds may play a crucial role in warming the early Mars climate. Urata and Toon (2011) simulate a stable warm paleo-climate for Mars if clouds form high in the atmosphere and if particles are sufficiently large (r > 10 μm). The annual fluence of micrometeoroids at Mars was larger early on in the evolution of our solar system. Additionally, the water vapor budget throughout the middle and high atmosphere was likely heightened . Both factors should contribute to enhanced nucleation and growth of water ice cloud particles at high altitudes. Here, we use the MarsCAM-CARMA general circulation model (GCM) to examine the radiative impact of high altitude water ice clouds on the early Mars climate and as a possible solution to the faint young sun problem for Mars.

A Transient Initialization Routine of the Community Ice Sheet Model for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

van der Laan, Larissa; van den Broeke, Michiel; Noël, Brice; van de Wal, Roderik

2017-04-01

The Community Ice Sheet Model (CISM) is to be applied in future simulations of the Greenland Ice Sheet under a range of climate change scenarios, determining the sensitivity of the ice sheet to individual climatic forcings. In order to achieve reliable results regarding ice sheet stability and assess the probability of future occurrence of tipping points, a realistic initial ice sheet geometry is essential. The current work describes and evaluates the development of a transient initialization routine, using NGRIP 18O isotope data to create a temperature anomaly field. Based on the latter, surface mass balance components runoff and precipitation are perturbed for the past 125k years. The precipitation and runoff fields originate from a downscaled 1 km resolution version of the regional climate model RACMO2.3 for the period 1961-1990. The result of the initialization routine is a present-day ice sheet with a transient memory of the last glacial-interglacial cycle, which will serve as the future runs' initial condition.

Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios.

PubMed

Muñoz-Mas, R; Lopez-Nicolas, A; Martínez-Capel, F; Pulido-Velazquez, M

2016-02-15

The impact of climate change on the habitat suitability for large brown trout (Salmo trutta L.) was studied in a segment of the Cabriel River (Iberian Peninsula). The future flow and water temperature patterns were simulated at a daily time step with M5 models' trees (NSE of 0.78 and 0.97 respectively) for two short-term scenarios (2011-2040) under the representative concentration pathways (RCP 4.5 and 8.5). An ensemble of five strongly regularized machine learning techniques (generalized additive models, multilayer perceptron ensembles, random forests, support vector machines and fuzzy rule base systems) was used to model the microhabitat suitability (depth, velocity and substrate) during summertime and to evaluate several flows simulated with River2D©. The simulated flow rate and water temperature were combined with the microhabitat assessment to infer bivariate habitat duration curves (BHDCs) under historical conditions and climate change scenarios using either the weighted usable area (WUA) or the Boolean-based suitable area (SA). The forecasts for both scenarios jointly predicted a significant reduction in the flow rate and an increase in water temperature (mean rate of change of ca. -25% and +4% respectively). The five techniques converged on the modelled suitability and habitat preferences; large brown trout selected relatively high flow velocity, large depth and coarse substrate. However, the model developed with support vector machines presented a significantly trimmed output range (max.: 0.38), and thus its predictions were banned from the WUA-based analyses. The BHDCs based on the WUA and the SA broadly matched, indicating an increase in the number of days with less suitable habitat available (WUA and SA) and/or with higher water temperature (trout will endure impoverished environmental conditions ca. 82% of the days). Finally, our results suggested the potential extirpation of the species from the study site during short time spans. Copyright © 2015 Elsevier B.V. All rights reserved.

Wave inhibition by sea ice enables trans-Atlantic ice rafting of debris during Heinrich Events

NASA Astrophysics Data System (ADS)

Wagner, T. J. W.; Dell, R.; Eisenman, I.; Keeling, R. F.; Padman, L.; Severinghaus, J. P.

2017-12-01

The thickness of the ice-rafted debris (IRD) layers that signal Heinrich Events declines far more gradually with distance from the iceberg sources than would be expected based on present-day iceberg trajectories. Here we model icebergs as passive Lagrangian tracers driven by ocean currents, winds, and sea surface temperatures. The icebergs are released in a comprehensive climate model simulation of the last glacial maximum (LGM), as well as a simulation of the modern climate. The two simulated climates result in qualitatively similar distributions of iceberg meltwater and hence debris, with the colder temperatures of the LGM having only a relatively small effect on meltwater spread. In both scenarios, meltwater flux falls off rapidly with zonal distance from the source, in contrast with the more uniform spread of IRD in sediment cores. In order to address this discrepancy, we propose a physical mechanism that could have prolonged the lifetime of icebergs during Heinrich events. The mechanism involves a surface layer of cold and fresh meltwater formed from, and retained around, densely packed armadas of icebergs. This leads to wintertime sea ice formation even in relatively low latitudes. The sea ice in turn shields the icebergs from wave erosion, which is the main source of iceberg ablation. We find that allowing sea ice to form around all icebergs during four months each winter causes the model to approximately agree with the distribution of IRD in sediment cores.

Global atmospheric particle formation from CERN CLOUD measurements.

PubMed

Dunne, Eimear M; Gordon, Hamish; Kürten, Andreas; Almeida, João; Duplissy, Jonathan; Williamson, Christina; Ortega, Ismael K; Pringle, Kirsty J; Adamov, Alexey; Baltensperger, Urs; Barmet, Peter; Benduhn, Francois; Bianchi, Federico; Breitenlechner, Martin; Clarke, Antony; Curtius, Joachim; Dommen, Josef; Donahue, Neil M; Ehrhart, Sebastian; Flagan, Richard C; Franchin, Alessandro; Guida, Roberto; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Jokinen, Tuija; Kangasluoma, Juha; Kirkby, Jasper; Kulmala, Markku; Kupc, Agnieszka; Lawler, Michael J; Lehtipalo, Katrianne; Makhmutov, Vladimir; Mann, Graham; Mathot, Serge; Merikanto, Joonas; Miettinen, Pasi; Nenes, Athanasios; Onnela, Antti; Rap, Alexandru; Reddington, Carly L S; Riccobono, Francesco; Richards, Nigel A D; Rissanen, Matti P; Rondo, Linda; Sarnela, Nina; Schobesberger, Siegfried; Sengupta, Kamalika; Simon, Mario; Sipilä, Mikko; Smith, James N; Stozkhov, Yuri; Tomé, Antonio; Tröstl, Jasmin; Wagner, Paul E; Wimmer, Daniela; Winkler, Paul M; Worsnop, Douglas R; Carslaw, Kenneth S

2016-12-02

Fundamental questions remain about the origin of newly formed atmospheric aerosol particles because data from laboratory measurements have been insufficient to build global models. In contrast, gas-phase chemistry models have been based on laboratory kinetics measurements for decades. We built a global model of aerosol formation by using extensive laboratory measurements of rates of nucleation involving sulfuric acid, ammonia, ions, and organic compounds conducted in the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber. The simulations and a comparison with atmospheric observations show that nearly all nucleation throughout the present-day atmosphere involves ammonia or biogenic organic compounds, in addition to sulfuric acid. A considerable fraction of nucleation involves ions, but the relatively weak dependence on ion concentrations indicates that for the processes studied, variations in cosmic ray intensity do not appreciably affect climate through nucleation in the present-day atmosphere. Copyright © 2016, American Association for the Advancement of Science.

Uncertainties in Isoprene Photochemistry and Emissions: Implications for the Oxidative Capacity of Past and Present Atmospheres and for Climate Forcing Agents

NASA Technical Reports Server (NTRS)

Achakulwisut, P.; Mickley, L. J.; Murray, Lee; Tai, A.P.K.; Kaplan, J.O.; Alexander, B.

2015-01-01

Current understanding of the factors controlling biogenic isoprene emissions and of the fate of isoprene oxidation products in the atmosphere has been evolving rapidly. We use a climate-biosphere-chemistry modeling framework to evaluate the sensitivity of estimates of the tropospheric oxidative capacity to uncertainties in isoprene emissions and photochemistry. Our work focuses on trends across two time horizons: from the Last Glacial Maximum (LGM, 21 000 years BP) to the preindustrial (1770s); and from the preindustrial to the present day (1990s). We find that different oxidants have different sensitivities to the uncertainties tested in this study, with OH being the most sensitive: changes in the global mean OH levels for the LGM-to-preindustrial transition range between -29 and +7, and those for the preindustrial-to-present day transition range between -8 and +17, across our simulations. Our results suggest that the observed glacial-interglacial variability in atmospheric methane concentrations is predominantly driven by changes in methane sources as opposed to changes in OH, the primary methane sink. However, the magnitudes of change are subject to uncertainties in the past isoprene global burdens, as are estimates of the change in the global burden of secondary organic aerosol (SOA) relative to the preindustrial. We show that the linear relationship between tropospheric mean OH and tropospheric mean ozone photolysis rates, water vapor, and total emissions of NOx and reactive carbon first reported in Murray et al. (2014) does not hold across all periods with the new isoprene photochemistry mechanism. Our results demonstrate that inadequacies in our understanding of present-day OH and its controlling factors must be addressed in order to improve model estimates of the oxidative capacity of past and present atmospheres.

Use of North American and European air quality networks to evaluate global chemistry-climate modeling of surface ozone

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

Schnell, J. L.; Prather, M. J.; Josse, B.

Here we test the current generation of global chemistry–climate models in their ability to simulate observed, present-day surface ozone. Models are evaluated against hourly surface ozone from 4217 stations in North America and Europe that are averaged over 1° × 1° grid cells, allowing commensurate model–measurement comparison. Models are generally biased high during all hours of the day and in all regions. Most models simulate the shape of regional summertime diurnal and annual cycles well, correctly matching the timing of hourly (~ 15:00 local time (LT)) and monthly (mid-June) peak surface ozone abundance. The amplitude of these cycles is lessmore » successfully matched. The observed summertime diurnal range (~ 25 ppb) is underestimated in all regions by about 7 ppb, and the observed seasonal range (~ 21 ppb) is underestimated by about 5 ppb except in the most polluted regions, where it is overestimated by about 5 ppb. The models generally match the pattern of the observed summertime ozone enhancement, but they overestimate its magnitude in most regions. Most models capture the observed distribution of extreme episode sizes, correctly showing that about 80 % of individual extreme events occur in large-scale, multi-day episodes of more than 100 grid cells. The models also match the observed linear relationship between episode size and a measure of episode intensity, which shows increases in ozone abundance by up to 6 ppb for larger-sized episodes. Lastly, we conclude that the skill of the models evaluated here provides confidence in their projections of future surface ozone.« less

Use of North American and European air quality networks to evaluate global chemistry-climate modeling of surface ozone

DOE PAGES

Schnell, J. L.; Prather, M. J.; Josse, B.; ...

2015-09-25

Here we test the current generation of global chemistry–climate models in their ability to simulate observed, present-day surface ozone. Models are evaluated against hourly surface ozone from 4217 stations in North America and Europe that are averaged over 1° × 1° grid cells, allowing commensurate model–measurement comparison. Models are generally biased high during all hours of the day and in all regions. Most models simulate the shape of regional summertime diurnal and annual cycles well, correctly matching the timing of hourly (~ 15:00 local time (LT)) and monthly (mid-June) peak surface ozone abundance. The amplitude of these cycles is lessmore » successfully matched. The observed summertime diurnal range (~ 25 ppb) is underestimated in all regions by about 7 ppb, and the observed seasonal range (~ 21 ppb) is underestimated by about 5 ppb except in the most polluted regions, where it is overestimated by about 5 ppb. The models generally match the pattern of the observed summertime ozone enhancement, but they overestimate its magnitude in most regions. Most models capture the observed distribution of extreme episode sizes, correctly showing that about 80 % of individual extreme events occur in large-scale, multi-day episodes of more than 100 grid cells. The models also match the observed linear relationship between episode size and a measure of episode intensity, which shows increases in ozone abundance by up to 6 ppb for larger-sized episodes. Lastly, we conclude that the skill of the models evaluated here provides confidence in their projections of future surface ozone.« less

Climate sensitivity of Tibetan Plateau glaciers - past and future implications

NASA Astrophysics Data System (ADS)

Heyman, Jakob; Hubbard, Alun; Stroeven, Arjen P.; Harbor, Jonathan M.

2013-04-01

The Tibetan Plateau is one of the most extensively glaciated, non-Polar regions of the world, and its mountain glaciers are the primary source of melt water for several of the largest Asian rivers. During glacial cycles, Tibetan Plateau glaciers advanced and retreated multiple times, but remained restricted to the highest mountain areas as valley glaciers and ice caps. Because glacier extent is dominantly controlled by climate, the past extent of Tibetan glaciers provide information on regional climate. Here we present a study analyzing the past maximum extents of glaciers on the Tibetan Plateau with the output of a 3D glacier model, in an effort to quantify Tibetan Plateau climate. We have mapped present-day glaciers and glacial landforms deposited by formerly more extensive glaciers in eight mountain regions across the Tibetan Plateau, allowing us to define present-day and past maximum glacier outlines. Using a high-resolution (250 m) higher-order glacier model calibrated against present-day glacier extents, we have quantified the climate perturbations required to expand present-day glaciers to their past maximum extents. We find that a modest cooling of at most 6°C for a few thousand years is enough to attain past maximum extents, even with 25-75% precipitation reduction. This evidence for limited cooling indicates that the temperature of the Tibetan Plateau remained relatively stable over Quaternary glacial cycles. Given the significant sensitivity to temperature change, the expectation is perhaps that a future warmer climate might result in intense glacier reduction. We have tested this hypothesis and modeled the future glacier development for the three mountain regions with the largest present-day glacier cover using a projected warming of 2.8 to 6.2°C within 100 years (envelope limits from IPCC). These scenarios result in dramatic glacier reductions, including 24-100% ice volume loss after 100 years and 77-100% ice volume loss after 300 years.

GCM Simulations of Titan's Paleoclimate

NASA Astrophysics Data System (ADS)

Lora, Juan M.; Lunine, Jonathan; Russell, Joellen; Hayes, Alexander

2014-11-01

The hemispheric asymmetry observed in the distribution of Titan's lakes and seas has been suggested to be the result of asymmetric seasonal forcing, where a relative moistening of the north occurs in the current epoch due to its longer and less intense summers. General circulation models (GCMs) of present-day Titan have also shown that the atmosphere transports methane away from the equator. In this work, we use a Titan GCM to investigate the effects that changes in Titan's effective orbital parameters have had on its climate in recent geologic history. The simulations show that the climate is relatively insensitive to changes in orbital parameters, with persistently dry low latitudes and wet polar regions. The amount of surface methane that builds up over either pole depends on the insolation distribution, confirming the influence of orbital forcing on the distribution of surface liquids. The evolution of the orbital forcing implies that the surface reservoir must be transported on timescales of ~30 kyr, in which case the asymmetry reverses with a period of ~125 kyr. Otherwise, the orbital forcing is insufficient for generating the observed dichotomy.

Climate Change Signals in the EURO-CORDEX Simulations

NASA Astrophysics Data System (ADS)

Jacob, Daniela; Preuschmann, Swantje

2014-05-01

A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. Within this presentation, the first results on climate change signals based on simulations with a horizontal resolution of 12.5 km for the new emission scenarios RCP4.5 and RCP8.5 will be presented. The new EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The presentation is based on the results of the Paper JACOB et al. (2013). We concentrated on the statistical analysis of robustness and significance of the climate change signals for mean annual and seasonal temperature, total annual and seasonal precipitation, heavy precipitation, heat waves and dry spells, by using daily data for three time periods: 1971-2000, 2021-2050 and 2071-2100. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities. The analysis of projected changes in the 95th percentile of the mean length of dry spells shows similar patterns for all scenarios. The climate projections from the new ensemble indicate a reduced northwards shift of Mediterranean drying evolution and slightly stronger mean precipitation increases over most of Europe. Within the high-resolution simulations in the EURO-CORDEX changes of the pattern for heavy precipitation events are clearly visible. (Jacob2013) Jacob, D.; Petersen, J.; Eggert, B.; Alias, A.; Christensen, O. B.; Bouwer, L.; Braun, A.; Colette, A.; Déqué, M.; Georgievski, G.; Georgopoulou, E.; Gobiet, A.; Menut, L.; Nikulin, G.; Haensler, A.; Hempelmann, N.; Jones, C.; Keuler, K.; Kovats, S.; Kröner, N.; Kotlarski, S.; Kriegsmann, A.; Martin, E.; Meijgaard, E.; Moseley, C.; Pfeifer, S.; Preuschmann, S.; Radermacher, C.; Radtke, K.; Rechid, D.; Rounsevell, M.; Samuelsson, P.; Somot, S.; Soussana, J.-F.; Teichmann, C.; Valentini, R.; Vautard, R.; Weber, B. & Yiou, P.( 2013): EURO-CORDEX: new high-resolution climate change projections for European impact research Regional Environmental Change, Springer Berlin Heidelberg, 2013, 1-16.

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.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models

NASA Astrophysics Data System (ADS)

Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M.

2011-03-01

Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models.

Assessing modeled Greenland surface mass balance in the GISS Model E2 and its sensitivity to surface albedo

NASA Astrophysics Data System (ADS)

Alexander, Patrick; LeGrande, Allegra N.; Koenig, Lora S.; Tedesco, Marco; Moustafa, Samiah E.; Ivanoff, Alvaro; Fischer, Robert P.; Fettweis, Xavier

2016-04-01

The surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) plays an important role in global sea level change. Regional Climate Models (RCMs) such as the Modèle Atmosphérique Régionale (MAR) have been employed at high spatial resolution with relatively complex physics to simulate ice sheet SMB. Global climate models (GCMs) incorporate less sophisticated physical schemes and provide outputs at a lower spatial resolution, but have the advantage of modeling the interaction between different components of the earth's oceans, climate, and land surface at a global scale. Improving the ability of GCMs to represent ice sheet SMB is important for making predictions of future changes in global sea level. With the ultimate goal of improving SMB simulated by the Goddard Institute for Space Studies (GISS) Model E2 GCM, we compare simulated GrIS SMB against the outputs of the MAR model and radar-derived estimates of snow accumulation. In order to reproduce present-day climate variability in the Model E2 simulation, winds are constrained to match the reanalysis datasets used to force MAR at the lateral boundaries. We conduct a preliminary assessment of the sensitivity of the simulated Model E2 SMB to surface albedo, a parameter that is known to strongly influence SMB. Model E2 albedo is set to a fixed value of 0.8 over the entire ice sheet in the initial configuration of the model (control case). We adjust this fixed value in an ensemble of simulations over a range of 0.4 to 0.8 (roughly the range of observed summer GrIS albedo values) to examine the sensitivity of ice-sheet-wide SMB to albedo. We prescribe albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 v6 to examine the impact of a more realistic spatial and temporal variations in albedo. An age-dependent snow albedo parameterization is applied, and its impact on SMB relative to observations and the RCM is assessed.

NCAR CCM2 simulation of the modern Antarctic climate

NASA Technical Reports Server (NTRS)

Tzeng, Ren-Yow; Bromwich, David H.; Parish, Thomas R.; Chen, Biao

1994-01-01

The National Center for Atmospheric Research (NCAR) community climate model version 2 (CCM2) simulation of the circumpolar trough, surface air temperature, the polar vortex, cloudiness, winds, and atmospheric moisture and energy budgets are examined to validate the model's representation of the present-day Antarctic climate. The results show that the CCM2 can well simulate many important climate features over Antarctica, such as the location and intensity of the circumpolar trough, the coreless winter over the plateau, the intensity and horizontal distribution of the surface inversion, the speed and streamline pattern of the katabatic winds, the double jet stream feature over the southern Indian and Pacific oceans, and the arid climate over the continent. However, there are also some serious errors in the model. Some are due to old problems but some are caused by the new parameterizations in the model. The model errors over high southern latitudes can be summarized as follows: The circumpolar trough, the polar vertex, and the westerlies in midlatitudes are too strong; the semiannual cycle of the circumpolar trough is distorted compared to the observations; the low centers of the circumpolar trough and the troughs in the middle and upper troposphere are shifted eastward by 15 deg - 40 deg longitude; the surface temperatures are too cold over the plateau in summer and over the coastline in winter; the polar tropopause continues to have a cold bias; and the cloudiness is too high over the continent. These biases are induced by two major factors: (1) the cloud optical properties in tropical and middle latitudes, which cause the eastward shift of troughs and surface low centers and the error in the semiannual cycle, and (2) the cold bias of the surface air temperature, which is attributed to the oversimulation of cloudiness over the continent, especially during summer, and the uniform 2-m-thick sea ice. The constant thickness of sea ice suppresses the energy flux from the ocean to the atmosphere and hence reduces the air temperature near the coast during winter. Finally, although the simulated Antarctic climate still suffers these biases, the overall performance of the CCM2 is much better than that of the CCM1-T42. Therefore the CCM2 is good enough to be used for climate change studies, especially over Antarctica.

Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Lin, Zhaohui; Rhoades, Alan M.; Ullrich, Paul A.; Zarzycki, Colin M.; Lu, Zheng; Rahimi-Esfarjani, Stefan R.

2017-10-01

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10-40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

Fewer rainy days and more extreme rainfall by the end of the century in Southern Africa

NASA Astrophysics Data System (ADS)

Pohl, Benjamin; Macron, Clémence; Monerie, Paul-Arthur

2017-04-01

Future changes in the structure of daily rainfall, especially the number of rainy days and the intensity of extreme events, are likely to induce major impacts on rain-fed agriculture in the tropics. In Africa this issue is of primary importance, but the agreement between climate models to simulate such descriptors of rainfall is generally poor. Here, we show that the climate models used for the fifth assessment report of IPCC simulate a marked decrease in the number of rainy days, together with a strong increase in the rainfall amounts during the 1% wettest days, by the end of the 21st century over Southern Africa. These combined changes lead to an apparent stability of seasonal totals, but are likely to alter the quality of the rainy season. These evolutions are due to the superposition of slowly-changing moisture fluxes, mainly supported by increased hygrometric capacity associated with global warming, and unchanged short-term atmospheric configurations in which extreme events are embedded. This could cause enhanced floods or droughts, stronger soil erosion and nutriment loss, questioning the sustainability of food security for the 300 million people currently living in Africa south of the Equator.

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

Medeiros, Brian; Williamson, David L.; Olson, Jerry G.

In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, includingmore » an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.« less

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

NASA Astrophysics Data System (ADS)

Keller, Michael; Kröner, Nico; Fuhrer, Oliver; Lüthi, Daniel; Schmidli, Juerg; Stengel, Martin; Stöckli, Reto; Schär, Christoph

2018-04-01

Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM) and 2 km grid spacing (convection-resolving model, CRM) are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW) using a vertically uniform warming and the other with vertically dependent warming (VW) that enables changes in lapse rate. The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.

Regional projections of North Indian climate for adaptation studies.

PubMed

Mathison, Camilla; Wiltshire, Andrew; Dimri, A P; Falloon, Pete; Jacob, Daniela; Kumar, Pankaj; Moors, Eddy; Ridley, Jeff; Siderius, Christian; Stoffel, Markus; Yasunari, T

2013-12-01

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes. Copyright © 2012 Elsevier B.V. All rights reserved.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

NASA Astrophysics Data System (ADS)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

Climate impact on airborne particulate matter concentrations in California using seven year analysis periods

NASA Astrophysics Data System (ADS)

Mahmud, A.; Hixson, M.; Hu, J.; Zhao, Z.; Chen, S.-H.; Kleeman, M. J.

2010-11-01

The effect of global climate change on the annual average concentration of fine particulate matter (PM2.5) in California was studied using a climate-air quality modeling system composed of global through regional models. Output from the NCAR/DOE Parallel Climate Model (PCM) generated under the "business as usual" global emissions scenario was downscaled using the Weather Research and Forecasting (WRF) model followed by air quality simulations using the UCD/CIT airshed model. The system represents major atmospheric processes acting on gas and particle phase species including meteorological effects on emissions, advection, dispersion, chemical reaction rates, gas-particle conversion, and dry/wet deposition. The air quality simulations were carried out for the entire state of California with a resolution of 8-km for the years 2000-2006 (present climate with present emissions) and 2047-2053 (future climate with present emissions). Each of these 7-year analysis periods was analyzed using a total of 1008 simulated days to span a climatologically relevant time period with a practical computational burden. The 7-year windows were chosen to properly account for annual variability with the added benefit that the air quality predictions under the present climate could be compared to actual measurements. The climate-air quality modeling system successfully predicted the spatial pattern of present climate PM2.5 concentrations in California but the absolute magnitude of the annual average PM2.5 concentrations were under-predicted by ~4-39% in the major air basins. The majority of this under-prediction was caused by excess ventilation predicted by PCM-WRF that should be present to the same degree in the current and future time periods so that the net bias introduced into the comparison is minimized. Surface temperature, relative humidity (RH), rain rate, and wind speed were predicted to increase in the future climate while the ultra violet (UV) radiation was predicted to decrease in major urban areas in the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB). These changes lead to a predicted decrease in PM2.5 mass concentrations of ~0.3-0.7 μg m-3 in the southern portion of the SJV and ~0.3-1.1 μg m-3 along coastal regions of California including the heavily populated San Francisco Bay Area and the SoCAB surrounding Los Angeles. Annual average PM2.5 concentrations were predicted to increase at certain locations within the SJV and the Sacramento Valley (SV) due to the effects of climate change, but a corresponding analysis of the annual variability showed that these predictions are not statistically significant (i.e. the choice of a different 7-year period could produce a different outcome for these regions). Overall, virtually no region in California outside of coastal + central Los Angeles, and a small region around the port of Oakland in the San Francisco Bay Area experienced a statistically significant change in annual average PM2.5 concentrations due to the effects of climate change in the present~study. The present study employs the highest spatial resolution (8 km) and the longest analysis windows (7 years) of any climate-air quality analysis conducted for California to date, but the results still have some degree of uncertainty. Most significantly, GCM calculations have inherent uncertainty that is not fully represented in the current study since a single GCM was used as the starting point for all calculations. The PCM results used in the current study predicted greater wintertime increases in air temperature over the Pacific Ocean than over land, further motivating comparison to other GCM results. Ensembles of GCM results are usually employed to build confidence in climate calculations. The current results provide a first data-point for the climate-air quality analysis that simultaneously employ the fine spatial resolution and long time scales needed to capture the behavior of climate-PM2.5 interactions in California. Future downscaling studies should follow up with a full ensemble of GCMs as their starting point, and include aerosol feedback effects on local meteorology.

Legacy effects of simulated short-term climate change on ammonia oxidisers, denitrifiers, and nitrous oxide emissions in an acid soil.

PubMed

Xu, Xiaoya; Liu, Xiaorui; Li, Yong; Ran, Yu; Liu, Yapeng; Zhang, Qichun; Li, Zheng; He, Yan; Xu, Jianming; Di, Hongjie

2017-04-01

Although the effect of simulated climate change on nitrous oxide (N 2 O) emissions and on associated microbial communities has been reported, it is not well understood if these effects are short-lived or long-lasting. Here, we conducted a field study to determine the interactive effects of simulated warmer and drier conditions on nitrifier and denitrifier communities and N 2 O emissions in an acidic soil and the longevity of the effects. A warmer (+2.3 °C) and drier climate (-7.4% soil moisture content) was created with greenhouses. The variation of microbial population abundance and community structure of ammonia-oxidizing archaea (AOA), bacteria (AOB), and denitrifiers (nirK/S, nosZ) were determined using real-time PCR and high-throughput sequencing. The results showed that the simulated warmer and drier conditions under the greenhouse following urea application significantly increased N 2 O emissions. There was also a moderate legacy effect on the N 2 O emissions when the greenhouses were removed in the urea treatment, although this effect only lasted a short period of time (about 60 days). The simulated climate change conditions changed the composition of AOA with the species affiliated to marine group 1.1a-associated lineage increasing significantly. The abundance of all the functional denitrifier genes decreased significantly under the simulated climate change conditions and the legacy effect, after the removal of greenhouses, significantly increased the abundance of AOB, AOA (mainly the species affiliated to marine group 1.1a-associated lineage), and nirK and nosZ genes in the urea-treated soil. In general, the effect of the simulated climate change was short-lived, with the denitrifier communities being able to return to ambient levels after a period of adaptation to ambient conditions. Therefore, the legacy effect of simulated short-time climate change conditions on the ammonia oxidizer and denitrifier communities and N 2 O emissions were temporary and once the conditions were removed, the microbial communities were able to adapt to the ambient conditions.

A flexible climate model for use in integrated assessments

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Stone, P. H.

Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100-150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties.

Toward Improving Predictability of Extreme Hydrometeorological Events: the Use of Multi-scale Climate Modeling in the Northern High Plains

NASA Astrophysics Data System (ADS)

Munoz-Arriola, F.; Torres-Alavez, J.; Mohamad Abadi, A.; Walko, R. L.

2014-12-01

Our goal is to investigate possible sources of predictability of hydrometeorological extreme events in the Northern High Plains. Hydrometeorological extreme events are considered the most costly natural phenomena. Water deficits and surpluses highlight how the water-climate interdependence becomes crucial in areas where single activities drive economies such as Agriculture in the NHP. Nonetheless we recognize the Water-Climate interdependence and the regulatory role that human activities play, we still grapple to identify what sources of predictability could be added to flood and drought forecasts. To identify the benefit of multi-scale climate modeling and the role of initial conditions on flood and drought predictability on the NHP, we use the Ocean Land Atmospheric Model (OLAM). OLAM is characterized by a dynamic core with a global geodesic grid with hexagonal (and variably refined) mesh cells and a finite volume discretization of the full compressible Navier Stokes equations, a cut-grid cell method for topography (that reduces error in computational gradient computation and anomalous vertical dispersion). Our hypothesis is that wet conditions will drive OLAM's simulations of precipitation to wetter conditions affecting both flood forecast and drought forecast. To test this hypothesis we simulate precipitation during identified historical flood events followed by drought events in the NHP (i.e. 2011-2012 years). We initialized OLAM with CFS-data 1-10 days previous to a flooding event (as initial conditions) to explore (1) short-term and high-resolution and (2) long-term and coarse-resolution simulations of flood and drought events, respectively. While floods are assessed during a maximum of 15-days refined-mesh simulations, drought is evaluated during the following 15 months. Simulated precipitation will be compared with the Sub-continental Observation Dataset, a gridded 1/16th degree resolution data obtained from climatological stations in Canada, US, and Mexico. This in-progress research will ultimately contribute to integrate OLAM and VIC models and improve predictability of extreme hydrometeorological events.

Sugar beet growth in a changing climate: past, present and future trends in southwest Germany

NASA Astrophysics Data System (ADS)

Kremer, Pascal; Fuchs, Hans-Joachim; Lang, Christian

2017-04-01

In the study, single factors and their impact on sugar beet cultivation against the background of past and projected climate change are being analyzed. The database consists of climate data by the German Weather Service and 1x1 km interpolated INTERMET raster data. Impact models were run to assess possible future trends using climate projection data of the REgional MOdel (REMO), emission scenario A1B, Run 1, data stream 2 for Germany, daily resolution, without bias correction, 10x10 km raster (n=150) (MPI on behalf of UBA 2006). Compared periods were: B:1971 2000; K:2021-2050; L:2071-2100. Agronomic data were collected from the field books of regional trials from 1974 2014 (n=448). Moreover, a business survey of regional farmers was carried out and evaluated. Impact models to predict timing for sowing, the date of field emergence and row closure, were derived from these data. The ontogenesis was simulated using a linear, temperature-based leaf-growth model. Sowing shifted forward by 7,3 days in regional field trials from 1974 2014. Progress-oriented, risk-tolerant farmers start sowing 10-14 days earlier compared to 1980. Recently, sowing is being conducted on average on 21 March in southwest Germany. For period K, 17 March, and for period L, 2 March is being projected as the average future sowing date while the same late frost risk applies compared to present climatic conditions. Shifting forward the sowing date with spring warming and, thus, exploiting the associated yield potential is the most promising agronomic adaptation strategy to the projected climate change on the farm level. In connection to earlier sowing, the field emergence tendentially shifted forward by 14 days in the field trials. Assuming sowing on 15 March, projection results show an advance of field emergence form 7 April in period B to 3 April in period L. Row closure in field trials in average shifted forward by 19,6 days. For period L, 29 May and thus, an earlier row closure of 9 days compared to K, is being projected. In period L, 20-leaf-stage is being projected 7,8 days, and 40-leaf-stage 11,2 days earlier compared to period K. All previously mentioned trends positively influence the yield potential of sugar beets due to the increasing use efficiency of photosynthetically active radiation. Running a correlation analysis, the height of the yield variance reconnaissance ratio of the main weather-related growth factors, temperature and precipitation, was determined. During the main growth phase from June-September, the precipitation sum explains 76%, the daily average temperature sum from April-October in the range of 3°C-19°C explains 64% of the yield variance of Mainz from 1991-2012. For both parameters, a decrease is being projected for the second half of the 21st century, which would influence the regional yield potential negatively. Summarizing, climate change had positive as well as negative impacts on regional sugar beet cultivation. Based on the REMO data, past trends continue prospectively. Due to that, it is important to fully use positive effects for yield formation. Furthermore, adaption to negative climatic changes and research are crucial to guarantee a high-yielding, sustainable sugar beet growth in future.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

Short-term Climate Simulations of African Easterly Waves with a Global Mesoscale Model

NASA Astrophysics Data System (ADS)

Shen, B. W.

2015-12-01

Recent high-resolution global model simulations ( Shen et al., 2010a, 2010b, 2012; 2013), which were conducted to examine the role of multiscale processes associated with tropical waves in the predictability of mesoscale tropical cyclones (TCs), suggested that a large-scale system (e.g., tropical waves) can provide determinism on the prediction of TC genesis, making it possible to extend the lead time of genesis predictions. Selected cases include the relationship between (i) TC Nargis (2008) and an Equatorial Rossby wave; (ii) Hurricane Helene (2006) and an intensifying African Easterly Wave (AEW); (iii) Twin TCs (2002) and a mixed Rossby-gravity wave during an active phase of the Madden Julian Oscillation (MJO); (iv) Hurricane Sandy (2012) and tropical waves during an active phase of the MJO. In this talk, thirty-day simulations with different model configurations are presented to examine the model's ability to simulate AEWs and MJOs and their association with tropical cyclogenesis. I will first discuss the simulations of the initiation and propagation of 6 consecutive AEWs in late August 2006 and the mean state of the African easterly jet (AEJ) over both Africa and downstream in the tropical Atlantic. By comparing our simulations with NCEP analysis and satellite data (e.g., TRMM), it is shown that the statistical characteristics of individual AEWs are realistically simulated with larger errors in the 5th and th AEWs. Results from the sensitivity experiments suggest the following: 1) accurate representations of non-linear interactions between the atmosphere and land processes are crucial for improving the simulations of the AEWs and the AEJ; 2) improved simulations of an individual AEW and its interaction with local environments (e.g., the Guinea Highlands) could provide determinism for hurricane formation downstream. Of interest is the potential to extend the lead time for predicting hurricane formation (e.g., a lead time of up to 22 days) as the 4th AEW is realistically simulated; 3) however, the dependence of AEW simulations on accurate dynamic and surface initial conditions and boundary conditions poses a challenge in simulating their modulation on hurricane activity. In addition to the simulations of AEWs, I will also present the 30-day simulations of selected MJO cases.

The Jena Diversity Model: Towards a Richer Representation of the Terrestrial Biosphere for Earth System Modelling

NASA Astrophysics Data System (ADS)

Pavlick, R.; Reu, B.; Bohn, K.; Dyke, J.; Kleidon, A.

2010-12-01

The terrestrial biosphere is a complex, self-organizing system which is continually both adapting to and altering its global environment. It also exhibits a vast diversity of vegetation forms and functioning. However, the terrestrial biosphere components within current state-of-the-art Earth System Models abstract this diversity in to a handful of relatively static plant functional types. These coarse and static representations of functional diversity might contribute to overly pessimistic projections regarding terrestrial ecosystem responses to scenarios of global change (e.g. Amazonian and boreal forest diebacks). In the Jena Diversity (JeDi) model, we introduce a new approach to vegetation modelling with a richer representation of functional diversity, based not on plant functional types, but on unavoidable plant ecophysiological trade-offs, which we hypothesize should be more stable in time. The JeDi model tests a large number of plant growth strategies. Each growth strategy is simulated using a set of randomly generated parameter values, which characterize its functioning in terms of carbon allocation, ecophysiology, and phenology, which are then linked to the growing conditions at the land surface. The model is constructed in such a way that these parameters inherently lead to ecophysiological trade-offs, which determine whether a growth strategy is able to survive and reproduce under the prevalent climatic conditions. Kleidon and Mooney (2000) demonstrated that this approach is capable of reproducing the geographic distribution of species richness. More recently, we have shown the JeDi model can explain other biogeographical phenomena including the present-day global pattern of biomes (Reu et al., accepted), ecosystem evenness (Kleidon et al. 2009), and possible mechanisms for biome shifts and biodiversity changes under scenarios of global warming (Reu et al., submitted). We have also evaluated the simulated biogeochemical fluxes from JeDi against a variety of site, field, and satellite observations (Pavlick et al., submitted) following a protocol established by the Carbon-Land Model Intercomparison Project (Randerson et al. 2009). We found that the global patterns of biogeochemical fluxes and land surface properties are reasonably well simulated using this bottom-up trade-off approach and compare favorably with other state of the art terrestrial biosphere models. Here, we present some results from JeDi simulations, wherein we varied the modelled functional diversity to quantify its impact on terrestrial biogeochemical fluxes under both present-day conditions and projected scenarios of global change. We also present results from a set of simulations wherein we vary the ability of the modelled ecosystems to adapt through changes in functional composition, leading to different projection responses of the carbon cycle to global warming. This plant functional tradeoff approach sets the foundation for many applications, including exploring the emergence and climatic impacts of major vegetation transitions throughout the last 400 million years as well as quantifying the significance of preserving functional diversity to hedge against uncertain climates in the future.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach.

PubMed

Taylor, Lyla L; Banwart, Steve A; Valdes, Paul J; Leake, Jonathan R; Beerling, David J

2012-02-19

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO(2)) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean-atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal-geosphere interactions at the global scale, which constitutes a first step towards developing 'next-generation' geochemical models.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach

PubMed Central

Taylor, Lyla L.; Banwart, Steve A.; Valdes, Paul J.; Leake, Jonathan R.; Beerling, David J.

2012-01-01

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO2) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean–atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal–geosphere interactions at the global scale, which constitutes a first step towards developing ‘next-generation’ geochemical models. PMID:22232768

Multiphase, multicomponent parameter estimation for liquid and vapor fluxes in deep arid systems using hydrologic data and natural environmental tracers

USGS Publications Warehouse

Kwicklis, Edward M.; Wolfsberg, Andrew V.; Stauffer, Philip H.; Walvoord, Michelle Ann; Sully, Michael J.

2006-01-01

Multiphase, multicomponent numerical models of long-term unsaturated-zone liquid and vapor movement were created for a thick alluvial basin at the Nevada Test Site to predict present-day liquid and vapor fluxes. The numerical models are based on recently developed conceptual models of unsaturated-zone moisture movement in thick alluvium that explain present-day water potential and tracer profiles in terms of major climate and vegetation transitions that have occurred during the past 10 000 yr or more. The numerical models were calibrated using borehole hydrologic and environmental tracer data available from a low-level radioactive waste management site located in a former nuclear weapons testing area. The environmental tracer data used in the model calibration includes tracers that migrate in both the liquid and vapor phases (??D, ??18O) and tracers that migrate solely as dissolved solutes (Cl), thus enabling the estimation of some gas-phase as well as liquid-phase transport parameters. Parameter uncertainties and correlations identified during model calibration were used to generate parameter combinations for a set of Monte Carlo simulations to more fully characterize the uncertainty in liquid and vapor fluxes. The calculated background liquid and vapor fluxes decrease as the estimated time since the transition to the present-day arid climate increases. However, on the whole, the estimated fluxes display relatively little variability because correlations among parameters tend to create parameter sets for which changes in some parameters offset the effects of others in the set. Independent estimates on the timing since the climate transition established from packrat midden data were essential for constraining the model calibration results. The study demonstrates the utility of environmental tracer data in developing numerical models of liquid- and gas-phase moisture movement and the importance of considering parameter correlations when using Monte Carlo analysis to characterize the uncertainty in moisture fluxes. ?? Soil Science Society of America.

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

Integrated assessment of climate change impact on surface runoff contamination by pesticides.

PubMed

Gagnon, Patrick; Sheedy, Claudia; Rousseau, Alain N; Bourgeois, Gaétan; Chouinard, Gérald

2016-07-01

Pesticide transport by surface runoff depends on climate, agricultural practices, topography, soil characteristics, crop type, and pest phenology. To accurately assess the impact of climate change, these factors must be accounted for in a single framework by integrating their interaction and uncertainty. This article presents the development and application of a framework to assess the impact of climate change on pesticide transport by surface runoff in southern Québec (Canada) for the 1981-2040 period. The crop enemies investigated were: weeds for corn (Zea mays); and for apple orchard (Malus pumila), 3 insect pests (codling moth [Cydia pomonella], plum curculio [Conotrachelus nenuphar], and apple maggot [Rhagoletis pomonella]), 2 diseases (apple scab [Venturia inaequalis], and fire blight [Erwinia amylovora]). A total of 23 climate simulations, 19 sites, and 11 active ingredients were considered. The relationship between climate and phenology was accounted for by bioclimatic models of the Computer Centre for Agricultural Pest Forecasting (CIPRA) software. Exported loads of pesticides were evaluated at the edge-of-field scale using the Pesticide Root Zone Model (PRZM), simulating both hydrology and chemical transport. A stochastic model was developed to account for PRZM parameter uncertainty. Results of this study indicate that for the 2011-2040 period, application dates would be advanced from 3 to 7 days on average with respect to the 1981-2010 period. However, the impact of climate change on maximum daily rainfall during the application window is not statistically significant, mainly due to the high variability of extreme rainfall events. Hence, for the studied sites and crop enemies considered, climate change impact on pesticide transported in surface runoff is not statistically significant throughout the 2011-2040 period. Integr Environ Assess Managem 2016;12:559-571. © Her Majesty the Queen in Right of Canada 2015; Published 2015 SETAC. © Her Majesty the Queen in Right of Canada 2015; Published 2015 SETAC.

Changes in flowering phenology of woody plants in North China

NASA Astrophysics Data System (ADS)

Dai, Junhu

2016-04-01

Over the past several decades, abundant evidences proved that the first flowering date of plants in northern hemisphere became earlier in response to climate warming. However, the existing results about impact of climate change on flowering duration are controversial. In this study, we studied temporal trends in first flowering date (FFD), end of flowering date (EFD) and flowering duration (FD) of 94 woody plants from 1963 to 2014 at three stations (Harbin, Beijing and Xi'an) in North China. Meanwhile, we analyzed the relationship between length of flowering periods and temperature using two phenological models (including regression model and growing degree day model). At all stations, more than 90% of observed species showed earlier flowering over time from 1963 to 2014. The average trends in FFD were 1.33, 1.77 and 3.01 days decade-1 at Harbin, Beijing and Xi'an, respectively. During the same period, EFD also became earlier by a mean rate of 2.19, 1.39 and 2.00 days decade-1, respectively. Regarding FD, a significant shortening of FD was observed at Harbin (-0.86 days decade-1), but FD extended by 0.37 and 1.01 days decade-1 at Beijing and Xi'an, respectively. At interspecific level, the plant species with longer FD tend to have stronger trends of FD extension. Through regression analyses, we found more than 85% of time series revealed a significant negative relationship between FFD (or EFD) and preseason temperature. The regression model could simulate the interannual changes in FFD and EFD with the mean goodness of fit (R2) ranging from 0.38 to 0.67, but failed to simulate the FD accurately, as R2 ranging from 0.09 to 0.18. Regarding to FFD and EFD, the growing degree day model could improved R2 of simuation, but also could not simulate FD accurately. Therefore, we concluded that the FFD and EFD advanced notably in recent six decades as a result of climate warming, but the direction of FD changes depended on locations and the species involved. In addition, the conventional phenological models could not explain most parts of interannual variance in FD, partly due superposition of errors caused by simultaneously simulating FFD and EFD. Therefore, the mechanism of FD changes and more drivers of FD such as soil moisture and light need to be further studied.

Modelling the enigmatic Late Pliocene Glacial Event - Marine Isotope Stage M2

USGS Publications Warehouse

Dolan, Aisling M.; Haywood, Alan M.; Hunter, Stephen J.; Tindall, Julia C.; Dowsett, Harry J.; Hill, Daniel J.; Pickering, Steven J.

2015-01-01

The Pliocene Epoch (5.2 to 2.58 Ma) has often been targeted to investigate the nature of warm climates. However, climate records for the Pliocene exhibit significant variability and show intervals that apparently experienced a cooler than modern climate. Marine Isotope Stage (MIS) M2 (~ 3.3 Ma) is a globally recognisable cooling event that disturbs an otherwise relatively (compared to present-day) warm background climate state. It remains unclear whether this event corresponds to significant ice sheet build-up in the Northern and Southern Hemisphere. Estimates of sea level for this interval vary, and range from modern values to estimates of 65 m sea level fall with respect to present day. Here we implement plausible M2 ice sheet configurations into a coupled atmosphere–ocean climate model to test the hypothesis that larger-than-modern ice sheet configurations may have existed at M2. Climate model results are compared with proxy climate data available for M2 to assess the plausibility of each ice sheet configuration. Whilst the outcomes of our data/model comparisons are not in all cases straight forward to interpret, there is little indication that results from model simulations in which significant ice masses have been prescribed in the Northern Hemisphere are incompatible with proxy data from the North Atlantic, Northeast Arctic Russia, North Africa and the Southern Ocean. Therefore, our model results do not preclude the possibility of the existence of larger ice masses during M2 in the Northern or Southern Hemisphere. Specifically they are not able to discount the possibility of significant ice masses in the Northern Hemisphere during the M2 event, consistent with a global sea-level fall of between 40 m and 60 m. This study highlights the general need for more focused and coordinated data generation in the future to improve the coverage and consistency in proxy records for M2, which will allow these and future M2 sensitivity tests to be interrogated further.

Modeling the effects of land use and climate change on riverine smallmouth bass

USGS Publications Warehouse

Peterson, J.T.; Kwak, T.J.

1999-01-01

Anthropogenic changes in temperature and stream flow, associated with watershed land use and climate change, are critical influences on the distribution and abundance of riverine fishes. To project the effects of changing land use and climate, we modeled a smallmouth bass (Micropterus dolomieu) population in a midwestern USA, large river- floodplain ecosystem under historical (1915-1925), present (1977-1990), and future (2060, influenced by climate change) temperature and flow regimes. The age-structured model included parameters for temperature and river discharge during critical seasonal periods, fish population dynamics, and fishing harvest. Model relationships were developed from empirical field data collected over a 13-yr period. Sensitivity analyses indicated that discharge during the spawning/rearing period had a greater effect on adult density and fishing yield than did spawning/rearing temperature or winter discharge. Simulations for 100 years projected a 139% greater mean fish density under a historical flow regime (64.9 fish/ha) than that estimated for the present (27.1 fish/ha) with a sustainable fishing harvest under both flow regimes. Simulations under future climate-change-induced temperature and flow regimes with present land use projected a 69% decrease in mean fish density (8.5 fish/ha) from present and an unstable population that went extinct during 56% of the simulations. However, when simulated under a future climate-altered temperature and flow regime with historical land use, the population increased by 66% (45.0 fish/ha) from present and sustained a harvest. Our findings suggest that land-use changes may be a greater detriment to riverine fishes than projected climate change and that the combined effects of both factors may lead to local species extinction. However, the negative effects of increased temperature and precipitation associated with future global warming could be mitigated by river channel, floodplain, and watershed restoration.

Climate change and larval transport in the ocean: fractional effects from physical and physiological factors.

PubMed

Kendall, Matthew S; Poti, Matt; Karnauskas, Kristopher B

2016-04-01

Changes in larval import, export, and self-seeding will affect the resilience of coral reef ecosystems. Climate change will alter the ocean currents that transport larvae and also increase sea surface temperatures (SST), hastening development, and shortening larval durations. Here, we use transport simulations to estimate future larval connectivity due to: (1) physical transport of larvae from altered circulation alone, and (2) the combined effects of altered currents plus physiological response to warming. Virtual larvae from islands throughout Micronesia were moved according to present-day and future ocean circulation models. The Hybrid Coordinate Ocean Model (HYCOM) spanning 2004-2012 represented present-day currents. For future currents, we altered HYCOM using analysis from the National Center for Atmospheric Research Community Earth System Model, version 1-Biogeochemistry, Representative Concentration Pathway 8.5 experiment. Based on the NCAR model, regional SST is estimated to rise 2.74 °C which corresponds to a ~17% decline in larval duration for some taxa. This reduction was the basis for a separate set of simulations. Results predict an increase in self-seeding in 100 years such that 62-76% of islands experienced increased self-seeding, there was an average domainwide increase of ~1-3% points in self-seeding, and increases of up to 25% points for several individual islands. When changed currents alone were considered, approximately half (i.e., random) of all island pairs experienced decreased connectivity but when reduced PLD was added as an effect, ~65% of connections were weakened. Orientation of archipelagos relative to currents determined the directional bias in connectivity changes. There was no universal relationship between climate change and connectivity applicable to all taxa and settings. Islands that presently export large numbers of larvae but that also maintain or enhance this role into the future should be the focus of conservation measures that promote long-term resilience of larval supply. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Effect of climate-driven changes in species composition on regional emission capacities of biogenic compounds

NASA Astrophysics Data System (ADS)

Schurgers, G.; Arneth, A.; Hickler, T.

2011-11-01

Regional or global modeling studies of dynamic vegetation often represent vegetation by large functional units (plant functional types (PFTs)). For simulation of biogenic volatile organic compounds (BVOC) in these models, emission capacities, which give the emission under standardized conditions, are provided as an average value for a PFT. These emission capacities thus hide the known heterogeneity in emission characteristics that are not straightforwardly related to functional characteristics of plants. Here we study the effects of the aggregation of species-level information on emission characteristics at PFT level. The roles of temporal and spatial variability are assessed for Europe by comparing simulations that represent vegetation by dominant tree species on the one hand and by plant functional types on the other. We compare a number of time slices between the Last Glacial Maximum (21,000 years ago) and the present day to quantify the effects of dynamically changing vegetation on BVOC emissions. Spatial heterogeneity of emission factors is studied with present-day simulations. We show that isoprene and monoterpene emissions are of similar magnitude in Europe when the simulation represents dominant European tree species, which indicates that simulations applying typical global-scale emission capacities for PFTs tend to overestimate isoprene and underestimate monoterpene emissions. Moreover, both spatial and temporal variability affect emission capacities considerably, and by aggregating these to PFT level averages, one loses the information on local heterogeneity. Given the reactive nature of these compounds, accounting for spatial and temporal heterogeneity can be important for studies of their fate in the atmosphere.

Potential contribution of groundwater to dry-season ET in the Amazon

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Fan, Ying

2010-05-01

Climate and land ecosystem models simulate vegetation stress in the Amazon forest in the dry season, but observations show enhanced growth in response to higher radiation under less cloudy skies indicating an adequate water supply. The question is: how does the vegetation obtain sufficient water, and what is missing in the models? Shallow model soil and rooting depth is a factor; the ability of roots to move water up and down (hydraulic redistribution) may be another, but another cause may lie in the buffering effect of the groundwater found in nature but absent in models. We present observational and modeling evidence that the vast groundwater store, consequence of high annual rainfall combined with poor drainage in the Amazon, may provide a stable source for dry-season photosynthesis. The water table beneath the Amazon is sufficiently shallow (38% area <5m and 63% area <10m deep) as to contribute >2mm/day to dry-season evapotranspiration, a non-negligible portion of tower-observed flux of 3-4mm/day, the latter including canopy-interception loss and open-water evaporation. This may have important implications to our understanding of Amazonia ecosystem response and feedback to climate change. Current models, lacking groundwater, predict a significant reduction in dry-season photosynthesis under current climate and large-scale dieback under projected future climate converting the Amazon from a net carbon sink to a net source and accelerating warming. If groundwater is considered in the models, the magnitude of the responses and feedbacks may be reduced.

Climate change and watershed mercury export: a multiple projection and model analysis.

PubMed

Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

2013-09-01

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.

Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States

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

Leung, Lai R.; Qian, Yun; Bian, Xindi

To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (1995-2015) and three future (2040-2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper focuses on analyses of regional simulations in the Columbia River and Sacramento-San Joaquin River Basins. Results based on the regional simulations show that by mid-century, the average regional warming ofmore » 1-2.5oC strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack is about 70%. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation is found to increase by 5 to 15 mm/day (15-20%) along the Cascades and the Sierra. The warming results in increased rainfall over snowfall and reduced snow accumulation (or earlier snowmelt) during the cold season. In the Columbia River Basin, these changes are accompanied by more frequent rain-on-snow events. Overall, they induce higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Such changes could have serious impacts on water resources and agriculture in the western U.S. Changes in surface water and energy budgets in the Columbia River and Sacramento-San Joaquin basins are driven mainly by changes in surface temperature, which are statistically significant at the 0.95 confidence level. Changes in precipitation, however, are spatially incoherent and not statistically significant except for the drying trend during summer.« less

Challenges in the development of very high resolution Earth System Models for climate science

NASA Astrophysics Data System (ADS)

Rasch, Philip J.; Xie, Shaocheng; Ma, Po-Lun; Lin, Wuyin; Wan, Hui; Qian, Yun

2017-04-01

The authors represent the 20+ members of the ACME atmosphere development team. The US Department of Energy (DOE) has, like many other organizations around the world, identified the need for an Earth System Model capable of rapid completion of decade to century length simulations at very high (vertical and horizontal) resolution with good climate fidelity. Two years ago DOE initiated a multi-institution effort called ACME (Accelerated Climate Modeling for Energy) to meet this an extraordinary challenge, targeting a model eventually capable of running at 10-25km horizontal and 20-400m vertical resolution through the troposphere on exascale computational platforms at speeds sufficient to complete 5+ simulated years per day. I will outline the challenges our team has encountered in development of the atmosphere component of this model, and the strategies we have been using for tuning and debugging a model that we can barely afford to run on today's computational platforms. These strategies include: 1) evaluation at lower resolutions; 2) ensembles of short simulations to explore parameter space, and perform rough tuning and evaluation; 3) use of regionally refined versions of the model for probing high resolution model behavior at less expense; 4) use of "auto-tuning" methodologies for model tuning; and 5) brute force long climate simulations.

Most robust estimate of the Transient Climate Response yet?

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Venema, Victor; Schurer, Andrew

2017-04-01

Estimates of the Transient Climate Response often lack a coherent hemispheric or otherwise spatio-temporal representation. In the light of recent work that highlights the importance of inhomogeneous forcing considerations (Shindell et al 2014; Marvel et al 2015) and tas/tos-related inaccuracies (Richardson et al. 2016), here we present results from a well-tested two-box response model that takes these effects carefully into account. All external forcing data are updated based on latest emission estimates as well as recent TSI and volcanic AOD estimates. So are observed GMST data which include data for the entire year of 2016. Hence we also provide one of the first TCR estimates taking the latest El Nino into account. We demonstrate that short-term climate variability is not going to change the TCR estimate beyond very minor fluctuations. The method is therefore shown to be robust within surprisingly small uncertainty estimates. Using PMIP3 and an extended ensemble of HadCM3 simulations (Euro500; Schurer et al. 2014) GCM simulations for the pre-industrial period, we test the fast and slow response time constants that are tailored for observational data (Ripdal 2012). We also test the hemispheric response as well as the response over land and ocean separately. The TCR/ECS ratio is taken from a selected sub-set of CMIP5 simulations. The selection criteria is the best spatiotemporal match over 4 different time periods between 1860 and 2010. We will argue that this procedure should also be standard procedure to estimate ECS from observations, rather than relying on OHC estimates only. Finally, the demonstrate that PMIP3-type simulations that are initialised at least a century before 1850 (as is the standard initialisation for CMIP5-type simulations) are to be preferred. Remaining long-term radiative imbalance due to strong volcanic eruptions (e.g. Gleckler et al. 2006) tend to make CMIP5-type simulations slightly more sensitive to forcing, which leads to detectable stronger warming up until recent day.

Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England

NASA Astrophysics Data System (ADS)

Brenner, Simon; Coxon, Gemma; Howden, Nicholas J. K.; Freer, Jim; Hartmann, Andreas

2018-02-01

Chalk aquifers are an important source of drinking water in the UK. Due to their properties, they are particularly vulnerable to groundwater-related hazards like floods and droughts. Understanding and predicting groundwater levels is therefore important for effective and safe water management. Chalk is known for its high porosity and, due to its dissolvability, exposed to karstification and strong subsurface heterogeneity. To cope with the karstic heterogeneity and limited data availability, specialised modelling approaches are required that balance model complexity and data availability. In this study, we present a novel approach to evaluate simulated groundwater level frequencies derived from a semi-distributed karst model that represents subsurface heterogeneity by distribution functions. Simulated groundwater storages are transferred into groundwater levels using evidence from different observations wells. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. Firstly, we evaluate the performance of the model when simulating groundwater level time series using a spilt sample test and parameter identifiability analysis. Secondly, we apply a split sample test to the simulated groundwater level percentiles to explore the performance in predicting groundwater level exceedances. We show that the model provides robust simulations of discharge and groundwater levels at three observation wells at a test site in a chalk-dominated catchment in south-western England. The second split sample test also indicates that the percentile approach is able to reliably predict groundwater level exceedances across all considered timescales up to their 75th percentile. However, when looking at the 90th percentile, it only provides acceptable predictions for long time periods and it fails when the 95th percentile of groundwater exceedance levels is considered. By modifying the historic forcings of our model according to expected future climate changes, we create simple climate scenarios and we show that the projected climate changes may lead to generally lower groundwater levels and a reduction of exceedances of high groundwater level percentiles.

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0)contribution to CMIP6

DOE PAGES

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; ...

2016-10-18

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of futuremore » climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.« less

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

2016-10-01

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

Sensitivity of Hurricane Storm Surge to Land Cover and Topography Under Various Sea Level Rise Scenarios Along the Mississippi Coast

NASA Astrophysics Data System (ADS)

Bilskie, M. V.; Hagen, S. C.; Medeiros, S. C.

2013-12-01

Major Gulf hurricanes have a high probability of impacting the northern Gulf of Mexico, especially coastal Mississippi (Resio, 2007). Due to the wide and flat continental shelf, this area provides near-perfect geometry for high water levels under tropical cyclone conditions. Literature suggests with 'very high confidence that global sea level will rise at least 0.2 m and no more than 2.0 m by 2011' (Donoghue, 2011; Parris et al., 2012). Further, it is recognized that the Mississippi barrier islands are highly susceptible to a westward migration and retreating shoreline. With predictions for less frequent, more intense tropical storms, rising sea levels, and a changing landscape, it is important to understand how these changes may affect inundation extent and flooding due to hurricane storm surge. A state-of-the-art SWAN+ADCIRC hydrodynamic model of coastal Mississippi was utilized to simulate Hurricane Katrina with present day sea level conditions. Using present day as a base scenario, past (1960) and future (2050) sea level changes were simulated. In addition to altering the initial sea state, land use land cover (LULC) was modified for 1960 and 2050 based on historic data and future projections. LULC datasets are used to derive surface roughness characteristics, such as Manning's n, and wind reduction factors. The topography along the barrier islands and near the Pascagoula River, MS was also altered to reflect the 1960 landscape. Storm surge sensitivity to topographic change were addressed by comparing model results between two 1960 storm surge simulations; one with current topography and a second with changes to the barrier islands. In addition, model responses to changes in LULC are compared. The results will be used to gain insight into adapting present day storm surge models for future conditions. References Donoghue, J. (2011). Sea level history of the northern Gulf of Mexico coast and sea level rise scenarios for the near future. Climatic Change, 107(1-2), 17-33. doi: 10.1007/s10584-011-0077-x Parris, A., Bromirski, P., Burkett, V., Cayan, D., Culver, M., Hall, J., . . . Weiss, J. (2012). Global Sea Level Rise Scenarios for the United States National Climate Assessment NOAA Tech Memo OAR CPO-1 (pp. 37). Resio, D. T. (2007). White paper on estimating hurricane inundation probabilities (pp. 125). Vicksburg, MS: U.S. Army Engineering Research and Development Center.

Culture or climate? The relative influences of past processes on the composition of the lowland Congo rainforest.

PubMed

Brncic, Terry M; Willis, Katherine J; Harris, David J; Washington, Richard

2007-02-28

This paper presents the results from a palaeoecological study to establish the impact of prehistoric human activity and climate change on the vegetation and soils of the Goualougo area of the Nouabalé-Ndoki National Park, in the Republic of Congo (Congo-Brazzaville). This is a region that is known from previous work (through evidence of pottery, furnaces and charcoal layers beneath the present day rainforest vegetation) to have had prehistoric settlement dating back to at least 2000 calibrated years before present. In addition, there is climatic evidence to suggest that significant variations in precipitation have occurred in central Africa over the last few millennia. Presently, the region is covered in uninhabited moist semi-evergreen rainforest. Key research questions addressed in this paper include the extent to which the present-day composition of rainforest in this region is as a result of processes of the past (climate change and/or human activity), and the resilience of the rainforest to these perturbations. Statistical analyses of pollen, microscopic charcoal and geochemical data are used to determine the relationship over time between vegetation dynamics and climate change, anthropogenic burning and metal smelting. Significant changes in forest composition are linked to burning and climate change but not metallurgy. The strongest influence on the present day composition appears to be related to the increased anthropogenic burning that started approximately 1000 years ago. Results from this study are discussed in terms of their implications for the present and future management of this globally important forested region.

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.

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

Huesemann, Michael; Dale, T.; Chavis, A.

Two innovative culturing systems, the LED-lighted and temperature-controlled 800 liter indoor raceways at Pacific Northwest National Laboratory (PNNL) and the Phenometrics environmental Photobioreactors™ (ePBRs) were evaluated in terms of their ability to accurately simulate the microalgae growth performance of outdoor cultures subjected to fluctuating sunlight and water temperature conditions. When repeating a 60-day outdoor pond culture experiment (batch and semi-continuous at two dilution rates) conducted in Arizona with the freshwater strain Chlorella sorokiniana DOE 1412 in these two indoor simulators, it was found that ash-free dry weight based biomass growth and productivity in the PNNL climate-simulation ponds was comparatively slightlymore » higher (8–13%) but significantly lower (44%) in the ePBRs. The difference in biomass productivities between the indoor and outdoor ponds was not statistically significant. When the marine Picochlorum soloecismus was cultured in five replicate ePBRs at Los Alamos National Laboratory (LANL) and in duplicate indoor climate-simulation ponds at PNNL, using the same inoculum, medium, culture depth, and light and temperature scripts, the optical density based biomass productivity and the rate of increase in cell counts in the ePBRs was about 35% and 66%, respectively, lower compared than in the indoor ponds. Potential reasons for the divergence in growth performance in these pond simulators, relative to outdoor raceways, are discussed. In conclusion, the PNNL climate-simulation ponds provide reasonably reliable biomass productivity estimates for microalgae strains cultured in outdoor raceways under different climatic conditions.« less

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

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

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

DOE PAGES

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.; ...

2016-08-23

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

Calibration of Daycent biogeochemical model for rice paddies in three agro-ecological zones in Peninsular India to optimize cropping practices and predict GHG emissions

NASA Astrophysics Data System (ADS)

Rajan, S.; Kritee, K.; Keough, C.; Parton, W. J.; Ogle, S. M.

2014-12-01

Rice is a staple for nearly half of the world population with irrigated and rainfed lowland rice accounting for about 80% of the worldwide harvested rice area. Increased atmospheric CO2 and rising temperatures are expected to adversely affect rice yields by the end of the 21st century. In addition, different crop management practices affect methane and nitrous oxide emissions from rice paddies antagonistically warranting a review of crop management practices such that farmers can adapt to the changing climate and also help mitigate climate change. The Daily DayCent is a biogeochemical model that operates on a daily time step, driven by four ecological drivers, i.e. climate, soil, vegetation, and management practices. The model is widely used to simulate daily fluxes of various gases, plant productivity, nutrient availability, and other ecosystem parameters in response to changes in land management and climate. We employed the DayCent model as a tool to optimize rice cropping practices in Peninsular India so as to develop a set of farming recommendations to ensure a triple win (i.e. higher yield, higher profit and lower GHG emissions). We applied the model to simulate both N2O and CH4 emissions, and crop yields from four rice paddies in three different agro-ecological zones under different management practices, and compared them with measured GHG and yield data from these plots. We found that, like all process based models, the biggest constraint in using the model was input data acquisition. Lack of accurate documentation of historic land use and management practices, missing historical daily weather data, and difficulty in obtaining digital records of soil and crop/vegetation parameters related to our experimental plots came in the way of our execution of this model. We will discuss utilization of estimates based on available literature, or knowledge-based values in lieu of missing measured parameters in our simulations with DayCent which could prove to be a solution to overcome data limitations in modeling with DayCent and other process based models for developing regions of the world.

Use of regional climate model output for hydrologic simulations

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.; Wilby, R.L.; Gutowski, W.J.; Leavesley, G.H.; Pan, Z.; Arritt, R.W.; Takle, E.S.

2002-01-01

Daily precipitation and maximum and minimum temperature time series from a regional climate model (RegCM2) configured using the continental United States as a domain and run on a 52-km (approximately) spatial resolution were used as input to a distributed hydrologic model for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango. Colorado; east fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily datasets of precipitation and maximum and minimum temperature were developed from measured data for each basin. These datasets included precipitation and temperature data for all stations (hereafter, All-Sta) located within the area of the RegCM2 output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and All-Sta data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and All-Sta-based simulations of runoff show little skill on a daily basis [Nash-Sutcliffe (NS) values range from 0.05 to 0.37 for RegCM2 and -0.08 to 0.65 for All-Sta]. When the precipitation and temperature biases are corrected in the RegCM2 output and All-Sta data (Bias-RegCM2 and Bias-All, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins (NS values range from 0.41 to 0.66 for RegCM2 and 0.60 to 0.76 for All-Sta). In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from - 0.08 to 0.72). These results indicate that measured data at the coarse resolution of the RegCM2 output can be made appropriate for basin-scale modeling through bias correction (essentially a magnitude correction). However, RegCM2 output, even when bias corrected, does not contain the day-to-day variability present in the All-Sta dataset that is necessary for basin-scale modeling. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

Future changes in precipitation patterns and extremes: a model-based approach

NASA Astrophysics Data System (ADS)

Mitsakis, Evangelos; Stamos, Iraklis; Anastassiadou, Kalliopi; Kammerer, Harald; Kaundinya, Ingo; Kohl, Bernhard; Kapsomenakis, John; Zerefos, Christos; Aifadopoulou, Georfia

2016-04-01

In recent decades, the Earth has experienced abrupt climate changes, including changes of mean precipitation heights as well as precipitation extremes. It is very likely that the abrupt climate changes which are result of the increase of the greenhouse gases (GHG) concentration (IPCC 2007) will continue with an accelerate magnitude in the coming decades. The modern tool used to project the future climate change is General Circulation Models (GCMs). Due to computational resources limitations, the horizontal resolution of present day GCMs is quite low, usually in the order of hundreds of kilometers. In such a crude resolution many local aspects of the climate are unable to be represented. In addition, the topographical input is equally crude, thus excluding important local features of the topographic forcing. For these reasons downscaling methods have been developed, which input the GCM results producing high resolution localized climate information. Dynamical downscaling is achieved using Regional Climate Models (RCMs) that increase the resolution of the GCMs to even less than 10 km. In that direction, future changes in the mean precipitation as well as precipitation extremes due to the anthropogenic climate change over the area of Greece are examined for various emission scenarios in the framework of this paper (e.g. RCP 8.5, SRES A1B, etc.). Regarding Greece, future changes are based on daily precipitation data from 18 Region Climate Models simulations (6 for RCP 8.5 and 12 for SRES A1B). The changes in precipitation extremes are defined by calculating the changes of nine extreme precipitation indices which are divided in three categories: percentile (R75p, R95p, R99p), absolute threshold (Rmax, R10, R20, R50, RX5day) and duration (CDD) indices, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). Taking into account all the results that are discussed explicitly in the following sections we conclude that the mean precipitation as well as the number of moderate rainy days is projected to decrease over Greece especially in the end of 21th century. Nevertheless the frequency as well as the strength of individual extremely high precipitation events will be increased over the largest part of Greece.

Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models

NASA Technical Reports Server (NTRS)

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.;

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R.

2012-01-01

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

Deforestation intensifies hot days

NASA Astrophysics Data System (ADS)

Stoy, Paul C.

2018-05-01

Deforestation often increases land-surface and near-surface temperatures, but climate models struggle to simulate this effect. Research now shows that deforestation has increased the severity of extreme heat in temperate regions of North America and Europe. This points to opportunities to mitigate extreme heat.

Vulnerability of sandy coasts to climate change and anthropic pressures: methodology and preliminary results

NASA Astrophysics Data System (ADS)

Idier, D.; Poumadère, M.; Vinchon, C.; Romieu, E.; Oliveros, C.

2009-04-01

1-INTRODUCTION Climate change is considered in the latest reports of the Intergovernmental Panel on Climate Change IPCC (2007) as unequivocal. Induced vulnerability of the system is defined as "the combination of sensitivity to climatic variations, probability of adverse effects, and adaptive capacity". Substantial methodological challenges remain, in particular estimating the risk of adverse climate change impacts and interpreting relative vulnerability across diverse situations. As stated by the IPCC, the "coastal systems should be considered vulnerable to changes in climate". In these areas, amongst the most serious impacts of sea-level rise (Nicholls, 1996) are erosion and marine inundation. Thus, the coast of metropolitan France, being composed of 31% sandy coasts, is potentially vulnerable, as it has been qualitatively assessed on the pilot coasts of Aquitaine and Languedoc-Roussillon in the RESPONSE project (Vinchon et al., 2008). Within the ANR VULSACO project (VULnerability of SAndy COast to climate change and anthropic pressure), the present day erosion tendencies as well as the potentially future erosion trends are investigated. The main objectives are to: (1) assess indicators of vulnerability to climate change for low-lying linear sandy coastal systems, from the shore to the hinterland, facing undergoing climate change and anthropic pressure until the 2030s; and (2) identify the aggravating or improving effect of human pressure on this vulnerability. This second issue is sometimes considered as a main driver of coastal risks. The methodology proposed in the project considers anthropic adaptation (or not) by putting decision makers in front of potential modifications of the physical system, to study the decision process and the choice of adaptation (or not). The coastal system is defined by its morphology, its physical characteristics and its land use. The time scales will range from short-term (days to weeks, e.g. time scale of extreme events) to medium-term (decades), whereas the space scales range from several tens of meters to several tens of kilometers. The project is based on the study of representative coastal units: 4 sites characterised by low-lying linear sandy beaches but different, representative, hydrodynamic and socio-economic environments. These sites are located in: Mediterranean Sea (Lido of Sète), Atlantic coast (Truc Vert beach and Noirmoutier island) and English channel coast (Est of Dunkerque). Each of these sites is studied following the same methodology, on both the physical and socio-economic dimensions, the aim being to identify vulnerability indicators regarding climate change and anthropic pressure. 2 - METHODOLOGY The work is based on the following methodology, for every site: 1) The compartments of the unit are defined: shoreface, coastline, backshore, hinterland, from a physical and socio-economical point of view. 2) The available data are analysed in order to provide some information on the present trend of the coastal unit, regarding climate change and anthropic pressure, but also to support the model validation. 3) The vulnerability is studied. On one hand, the socio-economic dimension is assessed and, in a risk governance perspective, stake holders are identified and involved. This part of the project combines the study of social perceptions of dangers along with a deliberative workshop. On the other hand, numerical models of the physical behaviour of shoreface and coastline are applied. The selected models cover a time scale from short-term (storm time scale) to long-term (decades). Then, vulnerability can be studied: the vulnerability of coast/beach is defined and studied based on in-situ observations and model results. Most of these models needs some forcing conditions (waves at the boundary of the computational domains for instance). The present day conditions can be potentially modified by climate change. However, the model and literature review on climate change show that the few prediction of wave conditions available for the future deal mainly with the significant wave height, and not so much with the wave direction or period. To compensate this lack of knowledge, a sensitivity study is done to get information on the possible changes within the next decades (2030). It consists in studying the influence of a modification in the characteristics of the present day forcing conditions(like waves) within a reasonable magnitude order. 4) The anthropic pressure is taken into account as a modulator of the physical vulnerability. In each context, participative techniques are used to involve representatives of the main stakeholder groups into decision-making simulations. The scenario of a storm in 2030 is adopted to provide structured interactions during the workshop. Along with socio-economic projections, this simulation relies upon a fictive journal article written on the basis of the model outputs. These methodological choices aim at better understanding how decisions are made by stake holders dealing with risks and scientific uncertainty. Some applied results on the study sites will be presented at the EGU. ACKNOWLEDGEMENTS The VULSACO project is financially supported by the ANR (French National Research Agency) within the Vulnérabilité-Milieux-Climat programm.

Ensemble projection of the sea level rise impact on storm surge and inundation at the coast of Bangladesh

NASA Astrophysics Data System (ADS)

Jisan, Mansur Ali; Bao, Shaowu; Pietrafesa, Leonard J.

2018-01-01

The hydrodynamic model Delft3D is used to study the impact of sea level rise (SLR) on storm surge and inundation in the coastal region of Bangladesh. To study the present-day inundation scenario, the tracks of two known tropical cyclones (TC) were used: Aila (Category 1; 2009) and Sidr (Category 5; 2007). Model results were validated with the available observations. Future inundation scenarios were generated by using the strength of TC Sidr, TC Aila and an ensemble of historical TC tracks but incorporating the effect of SLR. Since future change in storm surge inundation under SLR impact is a probabilistic incident, a probable range of future change in the inundated area was calculated by taking into consideration the uncertainties associated with TC tracks, intensities and landfall timing. The model outputs showed that the inundated area for TC Sidr, which was calculated as 1860 km2, would become 31 % larger than the present-day scenario if a SLR of 0.26 m occurred during the mid-21st-century climate scenario. Similarly to that, an increasing trend was found for the end-21st-century climate scenario. It was found that with a SLR of 0.54 m, the inundated area would become 53 % larger than the present-day case. Along with the inundation area, the impact of SLR was examined for changes in future storm surge level. A significant increase of 14 % was found in storm surge level for the case of TC Sidr at Barisal station if a SLR of 0.26 m occurred in the mid-21st century. Similarly to that, an increase of 29 % was found at storm surge level with a SLR of 0.54 m in this location for the end-21st-century climate scenario. Ensemble projections based on uncertainties of future TC events also showed that, for a change of 0.54 m in SLR, the inundated area would range between 3500 and 3750 km2, whereas for present-day SLR simulations it was found within the range of 1000-1250 km2. These results revealed that even if the future TCs remain at the same strength as at present, the projected changes in SLR will generate more severe threats in terms of surge height and the extent of the inundated area.

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

NASA Astrophysics Data System (ADS)

Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

2015-12-01

Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started in May 2015 and the harvest of this pilot season will be September 2015.

LGM permafrost distribution: how well can the latest PMIP multi-model ensembles reconstruct?

NASA Astrophysics Data System (ADS)

Saito, K.; Sueyoshi, T.; Marchenko, S.; Romanovsky, V.; Otto-Bliesner, B.; Walsh, J.; Bigelow, N.; Hendricks, A.; Yoshikawa, K.

2013-03-01

Global-scale frozen ground distribution during the Last Glacial Maximum (LGM) was reconstructed using multi-model ensembles of global climate models, and then compared with evidence-based knowledge and earlier numerical results. Modeled soil temperatures, taken from Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) simulations, were used to diagnose the subsurface thermal regime and determine underlying frozen ground types for the present-day (pre-industrial; 0 k) and the LGM (21 k). This direct method was then compared to the earlier indirect method, which categorizes the underlying frozen ground type from surface air temperature, applied to both the PMIP2 (phase II) and PMIP3 products. Both direct and indirect diagnoses for 0 k showed strong agreement with the present-day observation-based map, although the soil temperature ensemble showed a higher diversity among the models partly due to varying complexity of the implemented subsurface processes. The area of continuous permafrost estimated by the multi-model analysis was 25.6 million km2 for LGM, in contrast to 12.7 million km2 for the pre-industrial control, whereas seasonally, frozen ground increased from 22.5 million km2 to 32.6 million km2. These changes in area resulted mainly from a cooler climate at LGM, but other factors as well, such as the presence of huge land ice sheets and the consequent expansion of total land area due to sea-level change. LGM permafrost boundaries modeled by the PMIP3 ensemble-improved over those of the PMIP2 due to higher spatial resolutions and improved climatology-also compared better to previous knowledge derived from the geomorphological and geocryological evidences. Combinatorial applications of coupled climate models and detailed stand-alone physical-ecological models for the cold-region terrestrial, paleo-, and modern climates will advance our understanding of the functionality and variability of the frozen ground subsystem in the global eco-climate system.

Future U.S. ozone projections dependence on regional emissions, climate change, long-range transport and differences in modeling design

NASA Astrophysics Data System (ADS)

He, Hao; Liang, Xin-Zhong; Lei, Hang; Wuebbles, Donald J.

2016-03-01

A consistent modeling framework with nested global and regional chemical transport models (CTMs) is used to separate and quantitatively assess the relative contributions to projections of future U.S. ozone pollution from the effects of emissions changes, climate change, long-range transport (LRT) of pollutants, and differences in modeling design. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, a regional CTM's representation of present-day U.S. ozone pollution is notably improved, especially relative to results from the regional CTM with fixed LBCs or from the global CTM alone. This nested system of global and regional CTMs projects substantial surface ozone trends for the 2050's: 6-10 ppb decreases under the 'clean' A1B scenario and ∼15 ppb increases under the 'dirty' A1Fi scenario. Among the total trends of future ozone, regional emissions changes dominate, contributing negative 25-60% in A1B and positive 30-45% in A1Fi. Comparatively, climate change contributes positive 10-30%, while LRT effects through changing chemical LBCs account for positive 15-20% in both scenarios, suggesting introducing dynamic LBCs could influence projections of the U.S. future ozone pollution with a magnitude comparable to effects of climate change alone. The contribution to future ozone projections due to differences in modeling design, including model formulations, emissions treatments, and other factors between the global and the nested regional CTMs, is regionally dependent, ranging from negative 20% to positive 25%. It is shown that the model discrepancies for present-day simulations between global and regional CTMs can propagate into future U.S. ozone projections systematically but nonlinearly, especially in California and the Southeast. Therefore in addition to representations of emissions change and climate change, accurate treatment of LBCs for the regional CTM is essential for projecting the future U.S. ozone pollution.

Impact of climate variability on tropospheric ozone.

PubMed

Grewe, Volker

2007-03-01

A simulation with the climate-chemistry model (CCM) E39/C is presented, which covers both the troposphere and stratosphere dynamics and chemistry during the period 1960 to 1999. Although the CCM, by its nature, is not exactly representing observed day-by-day meteorology, there is an overall model's tendency to correctly reproduce the variability pattern due to an inclusion of realistic external forcings, like observed sea surface temperatures (e.g. El Niño), major volcanic eruption, solar cycle, concentrations of greenhouse gases, and Quasi-Biennial Oscillation. Additionally, climate-chemistry interactions are included, like the impact of ozone, methane, and other species on radiation and dynamics, and the impact of dynamics on emissions (lightning). However, a number of important feedbacks are not yet included (e.g. feedbacks related to biogenic emissions and emissions due to biomass burning). The results show a good representation of the evolution of the stratospheric ozone layer, including the ozone hole, which plays an important role for the simulation of natural variability of tropospheric ozone. Anthropogenic NO(x) emissions are included with a step-wise linear trend for each sector, but no interannual variability is included. The application of a number of diagnostics (e.g. marked ozone tracers) allows the separation of the impact of various processes/emissions on tropospheric ozone and shows that the simulated Northern Hemisphere tropospheric ozone budget is not only dominated by nitrogen oxide emissions and other ozone pre-cursors, but also by changes of the stratospheric ozone budget and its flux into the troposphere, which tends to reduce the simulated positive trend in tropospheric ozone due to emissions from industry and traffic during the late 80s and early 90s. For tropical regions the variability in ozone is dominated by variability in lightning (related to ENSO) and stratosphere-troposphere exchange (related to Northern Hemisphere Stratospheric dynamics and solar activity). Since tropospheric background chemistry is regarded only, the results are quantitatively limited with respect to derived trends. However, the main results are regarded to be robust. Although the horizontal resolution is rather coarse in comparison to regional models, such kind of simulations provide useful and necessary information on the impact of large-scale processes and inter-annual/decadal variations on regional air quality.