Weather and seasonal climate prediction for South America using a multi-model superensemble

NASA Astrophysics Data System (ADS)

Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.

2005-11-01

This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a multi-analysis-multi-model superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent predictions of rainfall for particular synoptic events to forecast day 3. Copyright

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Contacts Change Log Events Calendar Numerical Forecast Systems NCEP Model Analysis and Guidance Page [< Modeling Center NOAA Center for Weather and Climate Prediction (NCWCP) 5830 University Research Court

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Description of the NCAR Community Climate Model (CCM3). Technical note

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

Kiehl, J.T.; Hack, J.J.; Bonan, G.B.

This repor presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Climate Model designated CCM3. The material provides an overview of the major model components, and the way in which they interact as the numerical integration proceeds. This version of the CCM incorporates significant improvements to the physic package, new capabilities such as the incorporation of a slab ocean component, and a number of enhancements to the implementation (e.g., the ability to integrate the model on parallel distributed-memory computational platforms).

Simulating seasonal tropical cyclone intensities at landfall along the South China coast

NASA Astrophysics Data System (ADS)

Lok, Charlie C. F.; Chan, Johnny C. L.

2018-04-01

A numerical method is developed using a regional climate model (RegCM3) and the Weather Forecast and Research (WRF) model to predict seasonal tropical cyclone (TC) intensities at landfall for the South China region. In designing the model system, three sensitivity tests have been performed to identify the optimal choice of the RegCM3 model domain, WRF horizontal resolution and WRF physics packages. Driven from the National Centers for Environmental Prediction Climate Forecast System Reanalysis dataset, the model system can produce a reasonable distribution of TC intensities at landfall on a seasonal scale. Analyses of the model output suggest that the strength and extent of the subtropical ridge in the East China Sea are crucial to simulating TC landfalls in the Guangdong and Hainan provinces. This study demonstrates the potential for predicting TC intensities at landfall on a seasonal basis as well as projecting future climate changes using numerical models.

Software Simplifies the Sharing of Numerical Models

NASA Technical Reports Server (NTRS)

2014-01-01

To ease the sharing of climate models with university students, Goddard Space Flight Center awarded SBIR funding to Reston, Virginia-based Parabon Computation Inc., a company that specializes in cloud computing. The firm developed a software program capable of running climate models over the Internet, and also created an online environment for people to collaborate on developing such models.

Performance evaluation of a non-hydrostatic regional climate model over the Mediterranean/Black Sea area and climate projections for the XXI century

NASA Astrophysics Data System (ADS)

Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia

2013-04-01

In the framework of the Work Package 4 (Developing integrated tools for environmental assessment) of PERSEUS Project, high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes the Mediterranean and Black Seas, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Assessment of temperature and precipitation over Mediterranean Area and Black Sea with non hydrostatic high resolution regional climate model

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Montesarchio, M.; Zollo, A.; Bucchignani, E.

2012-12-01

In the framework of the Italian GEMINA Project (program of expansion and development of the Euro-Mediterranean Center for Climate Change (CMCC), high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes all the Mediterranean Sea, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate patterns but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Contemporary Drought and Future Effects of Climate Change on the Endangered Blunt-Nosed Leopard Lizard, Gambelia sila.

PubMed

Westphal, Michael F; Stewart, Joseph A E; Tennant, Erin N; Butterfield, H Scott; Sinervo, Barry

2016-01-01

Extreme weather events can provide unique opportunities for testing models that predict the effect of climate change. Droughts of increasing severity have been predicted under numerous models, thus contemporary droughts may allow us to test these models prior to the onset of the more extreme effects predicted with a changing climate. In the third year of an ongoing severe drought, surveys failed to detect neonate endangered blunt-nosed leopard lizards in a subset of previously surveyed populations where we expected to see them. By conducting surveys at a large number of sites across the range of the species over a short time span, we were able to establish a strong positive correlation between winter precipitation and the presence of neonate leopard lizards over geographic space. Our results are consistent with those of numerous longitudinal studies and are in accordance with predictive climate change models. We suggest that scientists can take immediate advantage of droughts while they are still in progress to test patterns of occurrence in other drought-sensitive species and thus provide for more robust models of climate change effects on biodiversity.

rpe v5: an emulator for reduced floating-point precision in large numerical simulations

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.

2017-06-01

This paper describes the rpe (reduced-precision emulator) library which has the capability to emulate the use of arbitrary reduced floating-point precision within large numerical models written in Fortran. The rpe software allows model developers to test how reduced floating-point precision affects the result of their simulations without having to make extensive code changes or port the model onto specialized hardware. The software can be used to identify parts of a program that are problematic for numerical precision and to guide changes to the program to allow a stronger reduction in precision.The development of rpe was motivated by the strong demand for more computing power. If numerical precision can be reduced for an application under consideration while still achieving results of acceptable quality, computational cost can be reduced, since a reduction in numerical precision may allow an increase in performance or a reduction in power consumption. For simulations with weather and climate models, savings due to a reduction in precision could be reinvested to allow model simulations at higher spatial resolution or complexity, or to increase the number of ensemble members to improve predictions. rpe was developed with a particular focus on the community of weather and climate modelling, but the software could be used with numerical simulations from other domains.

Implications of Climate Change on the Heat Budget of Lentic Systems Used for Power Station Cooling: Case Study Clinton Lake, Illinois.

PubMed

Quijano, Juan C; Jackson, P Ryan; Santacruz, Santiago; Morales, Viviana M; García, Marcelo H

2016-01-05

We use a numerical model to analyze the impact of climate change-in particular higher air temperatures-on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois

USGS Publications Warehouse

Quijano, Juan C; Jackson, P. Ryan; Santacruz, Santiago; Morales, Viviana M; Garcia, Marcelo H.

2016-01-01

We use a numerical model to analyze the impact of climate change--in particular higher air temperatures--on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

A Numerical Climate Observing Network Design Study

NASA Technical Reports Server (NTRS)

Stammer, Detlef

2003-01-01

This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".

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

Ingmann, P.; Readings, C. J.; Knott, K.

For the post-2000 time-frame two general classes of Earth Observation missions have been identified to address user requirements (see e.g. ESA, 1995), namely Earth Watch and Earth Explorer missions. One of the candidate Earth Explorer Missions selected for Phase A study is the Atmospheric Dynamics Mission which is intended to exploit a Doppler wind lidar, ALADIN, to measure winds in clear air (ESA, 1995 and ESA, 1996). It is being studied as a candidate for flight on the International Space Station (ISS) as an externally attached payload. The primary, long-term objective of the Atmospheric Dynamics Mission is to provide observationsmore » of wind profiles (e.g. radial wind component). Such data would be assimilated into numerical forecasting models leading to an improvement in objective analyses and hence in Numerical Weather Prediction. The mission would also provide data needed to address some of the key concerns of the World Climate Research Programme (WCRP) i.e. quantification of climate variability, validation and improvement of numerical models and process studies relevant to climate change. The newly acquired data would also help realize some of the objectives of the Global Climate Observing System (GCOS)« less

COSP: Satellite simulation software for model assessment

DOE PAGES

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

2011-08-01

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

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

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.

The representation of low-level clouds during the West African monsoon in weather and climate models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and radiation data) and ground-based eye observations of clouds and radiation measurements from weather stations. Our results show that many of the climate models have great difficulties representing the diurnal cycle of winds and clouds, leading to associated errors in radiation. Typical errors include a substantial underestimation of the lowest clouds accompanied by an overestimation of clouds at the top of the monsoon layer, indicating systematic problems in vertical exchange processes, which are also reflected in large errors in jet speed. Consequently, many models show a too flat diurnal cycle in cloudiness. This contribution is part of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project that aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions. The analysis of the capability of state-of-the-art numerical models to represent low-level cloudiness presented here is an important requisite for the planned assessments of the influence of anthropogenic aerosol.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus

DOE PAGES

Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.; ...

2017-04-25

The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The

Simulated Climate Impacts of Mexico City's Historical Urban Expansion

NASA Astrophysics Data System (ADS)

Benson-Lira, Valeria

Urbanization, a direct consequence of land use and land cover change, is responsible for significant modification of local to regional scale climates. It is projected that the greatest urban growth of this century will occur in urban areas in the developing world. In addition, there is a significant research gap in emerging nations concerning this topic. Thus, this research focuses on the assessment of climate impacts related to urbanization on the largest metropolitan area in Latin America: Mexico City. Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.

Response of the pelagic system of the Pacific Ocean off Baja California Peninsula to the projected effects of climate change: insights from a numerical model.

NASA Astrophysics Data System (ADS)

Arellano, B.; Rivas, D.

2015-12-01

The response of the physical and biological dynamics of the Pacific Ocean off Baja California to the projected effects of climate change are studied using numerical simulations. This region is part of the California Current System, which is a highly productive ecosystem due to the seasonal upwelling, supporting all the trophic levels and important fisheries. The response of the ecosystem to the effects of climate change is uncertain and the information generated by models could be useful to predict future conditions. A three-dimensional hydrodinamical model is coupled to a Nitrate-Phytoplankton-Zooplankton-Detritus (NPZD) trophic model, and it is forced by the GFDL 3.0 model outputs. Monthly climatologies of variables such as temperature, nutrients, wind, and ocean circulation patterns during the historical period 1985-2005 are compared to the available observed data in order to assess the model's ability to reproduce the observed patterns. The system's response to a high-emission scenario proposed by the Intergovernmental Panel of Climate Change (IPCC) is also studied. The experiments are carried out using data correspondig to the RCP 6.0 scenario during the period 2006-2050.

Insights from Modeling the Integrated Climate, Biogeochemical Cycles, Human Activities and Their Interactions in the ACME Earth System Model

NASA Astrophysics Data System (ADS)

Leung, L. R.; Thornton, P. E.; Riley, W. J.; Calvin, K. V.

2017-12-01

Towards the goal of understanding the contributions from natural and managed systems to current and future greenhouse gas fluxes and carbon-climate and carbon-CO2 feedbacks, efforts have been underway to improve representations of the terrestrial, river, and human components of the ACME earth system model. Broadly, our efforts include implementation and comparison of approaches to represent the nutrient cycles and nutrient limitations on ecosystem production, extending the river transport model to represent sediment and riverine biogeochemistry, and coupling of human systems such as irrigation, reservoir operations, and energy and land use with the ACME land and river components. Numerical experiments have been designed to understand how terrestrial carbon, nitrogen, and phosphorus cycles regulate climate system feedbacks and the sensitivity of the feedbacks to different model treatments, examine key processes governing sediment and biogeochemistry in the rivers and their role in the carbon cycle, and exploring the impacts of human systems in perturbing the hydrological and carbon cycles and their interactions. This presentation will briefly introduce the ACME modeling approaches and discuss preliminary results and insights from numerical experiments that lay the foundation for improving understanding of the integrated climate-biogeochemistry-human system.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Numerical Issues Associated with Compensating and Competing Processes in Climate Models: an Example from ECHAM-HAM

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

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

2013-06-26

The purpose of this paper is to draw attention to the need for appropriate numerical techniques to represent process interactions in climate models. In two versions of the ECHAM-HAM model, different time integration methods are used to solve the sulfuric acid (H2SO4) gas evolution equation, which lead to substantially different results in the H2SO4 gas concentration and the aerosol nucleation rate. Using convergence tests and sensitivity simulations performed with various time stepping schemes, it is confirmed that numerical errors in the second model version are significantly smaller than those in version one. The use of sequential operator splitting in combinationmore » with long time step is identified as the main reason for the large systematic biases in the old model. The remaining errors in version two in the nucleation rate, related to the competition between condensation and nucleation, have a clear impact on the simulated concentration of cloud condensation nuclei in the lower troposphere. These errors can be significantly reduced by employing an implicit solver that handles production, condensation and nucleation at the same time. Lessons learned in this work underline the need for more caution when treating multi-time-scale problems involving compensating and competing processes, a common occurrence in current climate models.« less

Integrating geological archives and climate models for the mid-Pliocene warm period.

PubMed

Haywood, Alan M; Dowsett, Harry J; Dolan, Aisling M

2016-02-16

The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change.

Integrating geological archives and climate models for the mid-Pliocene warm period

PubMed Central

Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.

2016-01-01

The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change. PMID:26879640

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Contacts Change Log Events Calendar People Numerical Forecast Systems Ensemble and Post Processing Team

The Art and Science of Climate Model Tuning

DOE PAGES

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

2017-03-31

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

The Art and Science of Climate Model Tuning

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

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew

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

Mesoscale numerical modeling of meteorological events in a strong topographic gradient in the northeastern part of Mexico

NASA Astrophysics Data System (ADS)

Pineda-Martinez, Luis F.; Carbajal, Noel

2009-08-01

A series of numerical experiments were carried out to study the effect of meteorological events such as warm and cold air masses on climatic features and variability of a understudied region with strong topographic gradients in the northeastern part of Mexico. We applied the mesoscale model MM5. We investigated the influence of soil moisture availability in the performance of the model under two representative events for winter and summer. The results showed that a better resolution in land use cover improved the agreement among observed and calculated data. The topography induces atmospheric circulation patterns that determine the spatial distribution of climate and seasonal behavior. The numerical experiments reveal regions favorable to forced convection on the eastern side of the mountain chains Eastern Sierra Madre and Sierra de Alvarez. These processes affect the vertical and horizontal structure of the meteorological variables along the topographic gradient.

Global and Arctic climate engineering: numerical model studies.

PubMed

Caldeira, Ken; Wood, Lowell

2008-11-13

We perform numerical simulations of the atmosphere, sea ice and upper ocean to examine possible effects of diminishing incoming solar radiation, insolation, on the climate system. We simulate both global and Arctic climate engineering in idealized scenarios in which insolation is diminished above the top of the atmosphere. We consider the Arctic scenarios because climate change is manifesting most strongly there. Our results indicate that, while such simple insolation modulation is unlikely to perfectly reverse the effects of greenhouse gas warming, over a broad range of measures considering both temperature and water, an engineered high CO2 climate can be made much more similar to the low CO2 climate than would be a high CO2 climate in the absence of such engineering. At high latitudes, there is less sunlight deflected per unit albedo change but climate system feedbacks operate more powerfully there. These two effects largely cancel each other, making the global mean temperature response per unit top-of-atmosphere albedo change relatively insensitive to latitude. Implementing insolation modulation appears to be feasible.

Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors

USGS Publications Warehouse

Fagherazzi, Sergio; Kirwan, Matthew L.; Mudd, Simon M.; Guntenspergen, Glenn R.; Temmerman, Stijn; D'Alpaos, Andrea; van de Koppel, Johan; Rybczyk, John; Reyes, Enrique; Craft, Chris; Clough, Jonathan

2012-01-01

Salt marshes are delicate landforms at the boundary between the sea and land. These ecosystems support a diverse biota that modifies the erosive characteristics of the substrate and mediates sediment transport processes. Here we present a broad overview of recent numerical models that quantify the formation and evolution of salt marshes under different physical and ecological drivers. In particular, we focus on the coupling between geomorphological and ecological processes and on how these feedbacks are included in predictive models of landform evolution. We describe in detail models that simulate fluxes of water, organic matter, and sediments in salt marshes. The interplay between biological and morphological processes often produces a distinct scarp between salt marshes and tidal flats. Numerical models can capture the dynamics of this boundary and the progradation or regression of the marsh in time. Tidal channels are also key features of the marsh landscape, flooding and draining the marsh platform and providing a source of sediments and nutrients to the marsh ecosystem. In recent years, several numerical models have been developed to describe the morphogenesis and long-term dynamics of salt marsh channels. Finally, salt marshes are highly sensitive to the effects of long-term climatic change. We therefore discuss in detail how numerical models have been used to determine salt marsh survival under different scenarios of sea level rise.

Numerical models of salt marsh evolution: Ecological, geomorphic, and climatic factors

USGS Publications Warehouse

Fagherazzi, S.; Kirwan, M.L.; Mudd, S.M.; Guntenspergen, G.R.; Temmerman, S.; D'Alpaos, A.; Van De Koppel, J.; Rybczyk, J.M.; Reyes, E.; Craft, C.; Clough, J.

2012-01-01

Salt marshes are delicate landforms at the boundary between the sea and land. These ecosystems support a diverse biota that modifies the erosive characteristics of the substrate and mediates sediment transport processes. Here we present a broad overview of recent numerical models that quantify the formation and evolution of salt marshes under different physical and ecological drivers. In particular, we focus on the coupling between geomorphological and ecological processes and on how these feedbacks are included in predictive models of landform evolution. We describe in detail models that simulate fluxes of water, organic matter, and sediments in salt marshes. The interplay between biological and morphological processes often produces a distinct scarp between salt marshes and tidal flats. Numerical models can capture the dynamics of this boundary and the progradation or regression of the marsh in time. Tidal channels are also key features of the marsh landscape, flooding and draining the marsh platform and providing a source of sediments and nutrients to the marsh ecosystem. In recent years, several numerical models have been developed to describe the morphogenesis and long-term dynamics of salt marsh channels. Finally, salt marshes are highly sensitive to the effects of long-term climatic change. We therefore discuss in detail how numerical models have been used to determine salt marsh survival under different scenarios of sea level rise. Copyright 2012 by the American Geophysical Union.

Carbon dioxide and climate: a second assessment

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

Not Available

For over a century, concern has been expressed that increases in atmospheric carbon dioxide (CO/sub 2/) concentration could affect global climate by changing the heat balance of the atmosphere and Earth. Observations reveal steadily increasing concentrations of CO/sub 2/, and experiments with numerical climate models indicate that continued increase would eventually produce significant climatic change. Comprehensive assessment of the issue will require projection of future CO/sub 2/ emissions and study of the disposition of this excess carbon in the atmosphere, ocean, and biota; the effect on climate; and the implications for human welfare. This study focuses on one aspect, estimationmore » of the effect on climate of assumed future increases in atmospheric CO/sub 2/. Conclusions are drawn principally from present-day numerical models of the climate system. To address the significant role of the oceans, the study also makes use of observations of the distributions of anthropogenic tracers other than CO/sub 2/. The rapid scientific developments in these areas suggest that periodic reassessments will be warranted. The starting point for the study was a similar 1979 review by a Climate Research Board panel chaired by the late Jule G. Charney. The present study has not found any new results that necessitate substantial revision of the conclusions of the Charney report.« less

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

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

Fox-Rabinovitz, M. S.

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods.

Key Issues for Seamless Integrated Chemistry–Meteorology Modeling

EPA Science Inventory

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can con...

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

Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.

The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The

Weather Forecaster Understanding of Climate Models

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Quantifying alluvial fan sensitivity to climate in Death Valley, California, from field observations and numerical models

NASA Astrophysics Data System (ADS)

Brooke, Sam; Whittaker, Alexander; Armitage, John; D'Arcy, Mitch; Watkins, Stephen

2017-04-01

A quantitative understanding of landscape sensitivity to climate change remains a key challenge in the Earth Sciences. The stream-flow deposits of coupled catchment-fan systems offer one way to decode past changes in external boundary conditions as they comprise simple, closed systems that can be represented effectively by numerical models. Here we combine the collection and analysis of grain size data on well-dated alluvial fan surfaces in Death Valley, USA, with numerical modelling to address the extent to which sediment routing systems record high-frequency, high-magnitude climate change. We compile a new database of Holocene and Late-Pleistocene grain size trends from 11 alluvial fans in Death Valley, capturing high-resolution grain size data ranging from the Recent to 100 kyr in age. We hypothesise the observed changes in average surface grain size and fining rate over time are a record of landscape response to glacial-interglacial climatic forcing. With this data we are in a unique position to test the predictions of landscape evolution models and evaluate the extent to which climate change has influenced the volume and calibre of sediment deposited on alluvial fans. To gain insight into our field data and study area, we employ an appropriately-scaled catchment-fan model that calculates an eroded volumetric sediment budget to be deposited in a subsiding basin according to mass balance where grain size trends are predicted by a self-similarity fining model. We use the model to compare predicted trends in alluvial fan stratigraphy as a function of boundary condition change for a range of model parameters and input grain size distributions. Subsequently, we perturb our model with a plausible glacial-interglacial magnitude precipitation change to estimate the requisite sediment flux needed to generate observed field grain size trends in Death Valley. Modelled fluxes are then compared with independent measurements of sediment supply over time. Our results constitute one of the first attempts to combine the detailed collection of alluvial fan grain size data in time and space with coupled catchment-fan models, affording us the means to evaluate how well field and model data can be reconciled for simple sediment routing systems.

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

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

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less

An online-coupled NWP/ACT model with conserved Lagrangian levels

NASA Astrophysics Data System (ADS)

Sørensen, B.; Kaas, E.; Lauritzen, P. H.

2012-04-01

Numerical weather and climate modelling is under constant development. Semi-implicit semi-Lagrangian (SISL) models have proven to be numerically efficient in both short-range weather forecasts and climate models, due to the ability to use long time steps. Chemical/aerosol feedback mechanism are becoming more and more relevant in NWP as well as climate models, since the biogenic and anthropogenic emissions can have a direct effect on the dynamics and radiative properties of the atmosphere. To include chemical feedback mechanisms in the NWP models, on-line coupling is crucial. In 3D semi-Lagrangian schemes with quasi-Lagrangian vertical coordinates the Lagrangian levels are remapped to Eulerian model levels each time step. This remapping introduces an undesirable tendency to smooth sharp gradients and creates unphysical numerical diffusion in the vertical distribution. A semi-Lagrangian advection method is introduced, it combines an inherently mass conserving 2D semi-Lagrangian scheme, with a SISL scheme employing both hybrid vertical coordinates and a fully Lagrangian vertical coordinate. This minimizes the vertical diffusion and thus potentially improves the simulation of the vertical profiles of moisture, clouds, and chemical constituents. Since the Lagrangian levels suffer from traditional Lagrangian limitations caused by the convergence and divergence of the flow, remappings to the Eulerian model levels are generally still required - but this need only be applied after a number of time steps - unless dynamic remapping methods are used. For this several different remapping methods has been implemented. The combined scheme is mass conserving, consistent, and multi-tracer efficient.

Exploring changes in vertical ice extent along the margin of the East Antarctic Ice Sheet in western Dronning Maud Land - initial results of the MAGIC-DML collaboration

NASA Astrophysics Data System (ADS)

Lifton, N. A.; Newall, J. C.; Fredin, O.; Glasser, N. F.; Fabel, D.; Rogozhina, I.; Bernales, J.; Prange, M.; Sams, S.; Eisen, O.; Hättestrand, C.; Harbor, J.; Stroeven, A. P.

2017-12-01

Numerical ice sheet models constrained by theory and refined by comparisons with observational data are a central component of work to address the interactions between the cryosphere and changing climate, at a wide range of scales. Such models are tested and refined by comparing model predictions of past ice geometries with field-based reconstructions from geological, geomorphological, and ice core data. However, on the East Antarctic Ice sheet, there are few empirical data with which to reconstruct changes in ice sheet geometry in the Dronning Maud Land (DML) region. In addition, there is poor control on the regional climate history of the ice sheet margin, because ice core locations, where detailed reconstructions of climate history exist, are located on high inland domes. This leaves numerical models of regional glaciation history in this near-coastal area largely unconstrained. MAGIC-DML is an ongoing Swedish-US-Norwegian-German-UK collaboration with a focus on improving ice sheet models by combining advances in numerical modeling with filling critical data gaps that exist in our knowledge of the timing and pattern of ice surface changes on the western Dronning Maud Land margin. A combination of geomorphological mapping using remote sensing data, field investigations, cosmogenic nuclide surface exposure dating, and numerical ice-sheet modeling are being used in an iterative manner to produce a comprehensive reconstruction of the glacial history of western Dronning Maud Land. We will present an overview of the project, as well as field observations and preliminary in situ cosmogenic nuclide measurements from the 2016/17 expedition.

Numerical modeling and experimental investigation of the local hydrology of a porous concrete site.

DOT National Transportation Integrated Search

2011-10-01

Although porous pavement use has been accepted as a successful stormwater management practice in warm climates, application in regions with colder climates, like New England, is still under investigation. The Randolph Park and Ride Site, which is the...

Parameter uncertainty in simulations of extreme precipitation and attribution studies.

NASA Astrophysics Data System (ADS)

Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.

2017-12-01

The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

NASA Technical Reports Server (NTRS)

Zobler, L.; Lewis, R.

1988-01-01

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

Simulation of modern climate with the new version of the INM RAS climate model

NASA Astrophysics Data System (ADS)

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

2017-03-01

The INMCM5.0 numerical model of the Earth's climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved.

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

NASA Astrophysics Data System (ADS)

Lade, Steven J.; Donges, Jonathan F.; Fetzer, Ingo; Anderies, John M.; Beer, Christian; Cornell, Sarah E.; Gasser, Thomas; Norberg, Jon; Richardson, Katherine; Rockström, Johan; Steffen, Will

2018-05-01

Changes to climate-carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate-carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate-carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate-carbon feedback; and concentration-carbon feedbacks may be more sensitive to future climate change than climate-carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.

Realistic dust and water cycles in the MarsWRF GCM using coupled two-moment microphysics

NASA Astrophysics Data System (ADS)

Lee, Christopher; Richardson, Mark Ian; Mischna, Michael A.; Newman, Claire E.

2017-10-01

Dust and water ice aerosols significantly complicate the Martian climate system because the evolution of the two aerosol fields is coupled through microphysics and because both aerosols strongly interact with visible and thermal radiation. The combination of strong forcing feedback and coupling has led to various problems in understanding and modeling of the Martian climate: in reconciling cloud abundances at different locations in the atmosphere, in generating a stable dust cycle, and in preventing numerical instability within models.Using a new microphysics model inside the MarsWRF GCM we show that fully coupled simulations produce more realistic simulation of the Martian climate system compared to a dry, dust only simulations. In the coupled simulations, interannual variability and intra-annual variability are increased, strong 'solstitial pause' features are produced in both winter high latitude regions, and dust storm seasons are more varied, with early southern summer (Ls 180) dust storms and/or more than one storm occurring in some seasons.A new microphysics scheme was developed as a part of this work and has been included in the MarsWRF model. The scheme uses split spectral/spatial size distribution numerics with adaptive bin sizes to track particle size evolution. Significantly, this scheme is highly accurate, numerically stable, and is capable of running with time steps commensurate with those of the parent atmospheric model.

Prerequisites for understanding climate-change impacts on northern prairie wetlands

USGS Publications Warehouse

Anteau, Michael J.; Wiltermuth, Mark T.; Post van der Burg, Max; Pearse, Aaron T.

2016-01-01

The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.

Human and climate impact on global riverine water and sediment fluxes - a distributed analysis

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2013-05-01

Understanding riverine water and sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of climate, landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. The intensity and dynamics between man-made and climatic factors vary widely across the globe and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment and water discharge model (WBMsed) to simulate human and climate effect on our planet's large rivers.

The PMIP4 contribution to CMIP6 - Part 1: Overview and over-arching analysis plan

NASA Astrophysics Data System (ADS)

Kageyama, Masa; Braconnot, Pascale; Harrison, Sandy P.; Haywood, Alan M.; Jungclaus, Johann H.; Otto-Bliesner, Bette L.; Peterschmitt, Jean-Yves; Abe-Ouchi, Ayako; Albani, Samuel; Bartlein, Patrick J.; Brierley, Chris; Crucifix, Michel; Dolan, Aisling; Fernandez-Donado, Laura; Fischer, Hubertus; Hopcroft, Peter O.; Ivanovic, Ruza F.; Lambert, Fabrice; Lunt, Daniel J.; Mahowald, Natalie M.; Peltier, W. Richard; Phipps, Steven J.; Roche, Didier M.; Schmidt, Gavin A.; Tarasov, Lev; Valdes, Paul J.; Zhang, Qiong; Zhou, Tianjun

2018-03-01

This paper is the first of a series of four GMD papers on the PMIP4-CMIP6 experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016).The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21 000 years ago (lgm); the Last Interglacial, 127 000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.

Free boundary models for mosquito range movement driven by climate warming.

PubMed

Bao, Wendi; Du, Yihong; Lin, Zhigui; Zhu, Huaiping

2018-03-01

As vectors, mosquitoes transmit numerous mosquito-borne diseases. Among the many factors affecting the distribution and density of mosquitoes, climate change and warming have been increasingly recognized as major ones. In this paper, we make use of three diffusive logistic models with free boundary in one space dimension to explore the impact of climate warming on the movement of mosquito range. First, a general model incorporating temperature change with location and time is introduced. In order to gain insights of the model, a simplified version of the model with the change of temperature depending only on location is analyzed theoretically, for which the dynamical behavior is completely determined and presented. The general model can be modified into a more realistic one of seasonal succession type, to take into account of the seasonal changes of mosquito movements during each year, where the general model applies only for the time period of the warm seasons of the year, and during the cold season, the mosquito range is fixed and the population is assumed to be in a hibernating status. For both the general model and the seasonal succession model, our numerical simulations indicate that the long-time dynamical behavior is qualitatively similar to the simplified model, and the effect of climate warming on the movement of mosquitoes can be easily captured. Moreover, our analysis reveals that hibernating enhances the chances of survival and successful spreading of the mosquitoes, but it slows down the spreading speed.

Numerical Modeling of Rocky Mountain Paleoglaciers - Insights into the Climate of the Last Glacial Maximum and the Subsequent Deglaciation

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2014-12-01

Numerical modeling of paleoglaciers can yield information on the climatic conditions necessary to sustain those glaciers. In this study we apply a coupled 2-d mass/energy balance and flow model (Plummer and Phillips, 2003) to reconstruct local last glacial maximum (LLGM) glaciers and paleoclimate in ten study areas along the crest of the U.S. Rocky Mountains between 33°N and 49°N. In some of the areas, where timing of post-LLGM ice recession is constrained by surface exposure ages on either polished bedrock upvalley from the LLGM moraines or post-LLGM recessional moraines, we use the model to assess magnitudes and rates of climate change during deglaciation. The modeling reveals a complex pattern of LLGM climate. The magnitude of LLGM-to-modern climate change (temperature and/or precipitation change) was greater in both the northern (Montana) Rocky Mountains and southern (New Mexico) Rocky Mountains than in the middle (Wyoming and Colorado) Rocky Mountains. We use temperature depression estimates from global and regional climate models to infer LLGM precipitation from our glacier model results. Our results suggest a reduction of precipitation coupled with strongly depressed temperatures in the north, contrasted with strongly enhanced precipitation and much more modest temperature depression in the south. The middle Rocky Mountains of Colorado and Wyoming appear to have experienced a reduction in precipitation at the LLGM without the strong temperature depression of the northern Rocky Mountains. Preliminary work on modeling of deglaciation in the Sangre de Cristo Range in southern Colorado suggests that approximately half of the LLGM-to-modern climate change took place during the initial ~2400 years of deglaciation. If increasing temperature and changing solar insolation were the sole drivers of this initial deglaciation, then temperature would need to have risen by slightly more than 1°C/ky through this interval to account for the observed rate of ice recession.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

NASA Astrophysics Data System (ADS)

Ray, A. J.; Ojima, D. S.; Morisette, J. T.

2012-12-01

The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in these projects is to provide the connections between climate data and running ecological models, and prototype these for future work. NCPP will develop capacities to provide enhanced climate information at relevant spatial and temporal scales, both for historical climate and projections of future climate, and will work to link expert guidance and understanding of modeling processes and evaluation of modeling with the use of numerical climate data. Translational information thus is a suite of information that aids in translation of numerical climate information into usable knowledge for applications, e.g. ecological response models, hydrologic risk studies. This information includes technical and scientific aspects including, but not limited to: 1) results of objective, quantitative evaluation of climate models & downscaling techniques, 2) guidance on appropriate uses and interpretation, i.e., understanding the advantages and limitations of various downscaling techniques for specific user applications, 3) characterizing and interpreting uncertainty, 4) Descriptions meaningful to applications, e.g. narratives. NCPP believes that translational information is best co-developed between climate scientists and applications scientists, such as the NC-CSC pilot.

Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan.

PubMed

Ahmad, Zulfiqar; Ashraf, Arshad; Fryar, Alan; Akhter, Gulraiz

2011-02-01

The integration of the Geographic Information System (GIS) with groundwater modeling and satellite remote sensing capabilities has provided an efficient way of analyzing and monitoring groundwater behavior and its associated land conditions. A 3-dimensional finite element model (Feflow) has been used for regional groundwater flow modeling of Upper Chaj Doab in Indus Basin, Pakistan. The approach of using GIS techniques that partially fulfill the data requirements and define the parameters of existing hydrologic models was adopted. The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient, and estimation of the groundwater budget of the aquifer. GIS is used for spatial database development, integration with a remote sensing, and numerical groundwater flow modeling capabilities. The thematic layers of soils, land use, hydrology, infrastructure, and climate were developed using GIS. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater flow modeling and integration and presentation of image processing and modeling results. The groundwater flow model was calibrated to simulate future changes in piezometric heads from the period 2006 to 2020. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The model results indicated a significant response in watertable due to external influential factors. The developed model provides an effective tool for evaluating better management options for monitoring future groundwater development in the study area.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

Prediction of daily spring hydrographs for future climatic scenarios based on an integrated numerical modelling approach: Application on a snow-governed semi- arid karst catchment area.

NASA Astrophysics Data System (ADS)

Doummar, J.; Kassem, A.; Gurdak, J. J.

2017-12-01

In the framework of a three-year USAID/NSF- funded PEER Science project, flow in a karst system in Lebanon (Assal Spring; discharge 0.2-2.5 m3/s yearly volume of 22-30 Mm3) dominated by snow and semi arid conditions was simulated using an integrated numerical model (Mike She 2016). The calibrated model (Nash-Sutcliffe coefficient of 0.77) is based on high resolution input data (2014-2017) and detailed catchment characterization. The approach is to assess the influence of various model parameters on recharge signals in the different hydrological karst compartments (Atmosphere, unsaturated zone, and saturated zone) based on an integrated numerical model. These parameters include precipitation intensity and magnitude, temperature, snow-melt parameters, in addition to karst specific spatially distributed features such as fast infiltration points, soil properties and thickness, topographical slopes, Epikarst and thickness of unsaturated zone, and hydraulic conductivity among others. Moreover, the model is currently simulated forward using various scenarios for future climate (Global Climate Models GCM; daily downscaled temperature and precipitation time series for Lebanon 2020-2045) in order to depict the flow rates expected in the future and the effect of climate change on hydrographs recession coefficients, discharge maxima and minima, and total spring discharge volume . Additionally, a sensitivity analysis of individual or coupled major parameters allows quantifying their impact on recharge or indirectly on the vulnerability of the system (soil thickness, soil and rock hydraulic conductivity appear to be amongst the highly sensitive parameters). This study particularly unravels the normalized single effect of rain magnitude and intensity, snow, and temperature change on the flow rate (e.g., a change of temperature of 3° on the catchment yields a Residual Mean Square Error RMSE of 0.15 m3/s in the spring discharge and a 16% error in the total annual volume with respect to the calibrated model). Finally, such a study can allow decision makers to implement best informed management practices, especially in complex karst systems, to overcome impacts of climate change on water resources.

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.

Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem

Treesearch

J.A. O' Donnell; J.W. Harden; A.D. McGuire; V.E. Romanovsky

2011-01-01

In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil...

Test Driven Development of a Parameterized Ice Sheet Component

NASA Astrophysics Data System (ADS)

Clune, T.

2011-12-01

Test driven development (TDD) is a software development methodology that offers many advantages over traditional approaches including reduced development and maintenance costs, improved reliability, and superior design quality. Although TDD is widely accepted in many software communities, the suitability to scientific software is largely undemonstrated and warrants a degree of skepticism. Indeed, numerical algorithms pose several challenges to unit testing in general, and TDD in particular. Among these challenges are the need to have simple, non-redundant closed-form expressions to compare against the results obtained from the implementation as well as realistic error estimates. The necessity for serial and parallel performance raises additional concerns for many scientific applicaitons. In previous work I demonstrated that TDD performed well for the development of a relatively simple numerical model that simulates the growth of snowflakes, but the results were anecdotal and of limited relevance to far more complex software components typical of climate models. This investigation has now been extended by successfully applying TDD to the implementation of a substantial portion of a new parameterized ice sheet component within a full climate model. After a brief introduction to TDD, I will present techniques that address some of the obstacles encountered with numerical algorithms. I will conclude with some quantitative and qualitative comparisons against climate components developed in a more traditional manner.

Biogenic organic emissions, air quality and climate

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2015-12-01

Living organisms produce copious amounts of a diverse array of metabolites including many volatile organic compounds that are released into the atmosphere. These compounds participate in numerous chemical reactions that influence the atmospheric abundance of important air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. The production and release of these organics are strongly influenced by environmental conditions including air pollution, temperature, solar radiation, and water availability and they are highly sensitive to stress and extreme events. As a result, releases of biogenic organics to the atmosphere have an impact on, and are sensitive to, air quality and climate leading to potential feedback couplings. Their role in linking air quality and climate is conceptually clear but an accurate quantitative representation is needed for predictive models. Progress towards this goal will be presented including numerical model development and assessments of the predictive capability of the Model of Emission of Gases and Aerosols from Nature (MEGAN). Recent studies of processes controlling the magnitude and variations in biogenic organic emissions will be described and observations of their impact on atmospheric composition will be shown. Recent advances and priorities for future research will be discussed including laboratory process studies, long-term measurements, multi-scale regional studies, global satellite observations, and the development of a next generation model for simulating land-atmosphere chemical exchange.

Numerical modeling of Drangajökull Ice Cap, NW Iceland

NASA Astrophysics Data System (ADS)

Anderson, Leif S.; Jarosch, Alexander H.; Flowers, Gwenn E.; Aðalgeirsdóttir, Guðfinna; Magnússon, Eyjólfur; Pálsson, Finnur; Muñoz-Cobo Belart, Joaquín; Þorsteinsson, Þorsteinn; Jóhannesson, Tómas; Sigurðsson, Oddur; Harning, David; Miller, Gifford H.; Geirsdóttir, Áslaug

2016-04-01

Over the past century the Arctic has warmed twice as fast as the global average. This discrepancy is likely due to feedbacks inherent to the Arctic climate system. These Arctic climate feedbacks are currently poorly quantified, but are essential to future climate predictions based on global circulation modeling. Constraining the magnitude and timing of past Arctic climate changes allows us to test climate feedback parameterizations at different times with different boundary conditions. Because Holocene Arctic summer temperature changes have been largest in the North Atlantic (Kaufman et al., 2004) we focus on constraining the paleoclimate of Iceland. Glaciers are highly sensitive to changes in temperature and precipitation amount. This sensitivity allows for the estimation of paleoclimate using glacier models, modern glacier mass balance data, and past glacier extents. We apply our model to the Drangajökull ice cap (~150 sq. km) in NW Iceland. Our numerical model is resolved in two-dimensions, conserves mass, and applies the shallow-ice-approximation. The bed DEM used in the model runs was constructed from radio echo data surveyed in spring 2014. We constrain the modern surface mass balance of Drangajökull using: 1) ablation and accumulation stakes; 2) ice surface digital elevation models (DEMs) from satellite, airborne LiDAR, and aerial photographs; and 3) full-stokes model-derived vertical ice velocities. The modeled vertical ice velocities and ice surface DEMs are combined to estimate past surface mass balance. We constrain Holocene glacier geometries using moraines and trimlines (e.g., Brynjolfsson, etal, 2014), proglacial-lake cores, and radiocarbon-dated dead vegetation emerging from under the modern glacier. We present a sensitivity analysis of the model to changes in parameters and show the effect of step changes of temperature and precipitation on glacier extent. Our results are placed in context with local lacustrine and marine climate proxies as well as with glacier extent and volume changes across the North Atlantic.

Analytically based forward and inverse models of fluvial landscape evolution during temporally continuous climatic and tectonic variations

NASA Astrophysics Data System (ADS)

Goren, Liran; Petit, Carole

2017-04-01

Fluvial channels respond to changing tectonic and climatic conditions by adjusting their patterns of erosion and relief. It is therefore expected that by examining these patterns, we can infer the tectonic and climatic conditions that shaped the channels. However, the potential interference between climatic and tectonic signals complicates this inference. Within the framework of the stream power model that describes incision rate of mountainous bedrock rivers, climate variability has two effects: it influences the erosive power of the river, causing local slope change, and it changes the fluvial response time that controls the rate at which tectonically and climatically induced slope breaks are communicated upstream. Because of this dual role, the fluvial response time during continuous climate change has so far been elusive, which hinders our understanding of environmental signal propagation and preservation in the fluvial topography. An analytic solution of the stream power model during general tectonic and climatic histories gives rise to a new definition of the fluvial response time. The analytic solution offers accurate predictions for landscape evolution that are hard to achieve with classical numerical schemes and thus can be used to validate and evaluate the accuracy of numerical landscape evolution models. The analytic solution together with the new definition of the fluvial response time allow inferring either the tectonic history or the climatic history from river long profiles by using simple linear inversion schemes. Analytic study of landscape evolution during periodic climate change reveals that high frequency (10-100 kyr) climatic oscillations with respect to the response time, such as Milankovitch cycles, are not expected to leave significant fingerprints in the upstream reaches of fluvial channels. Linear inversion schemes are applied to the Tinee river tributaries in the southern French Alps, where tributary long profiles are used to recover the incision rate history of the Tinee main trunk. Inversion results show periodic, high incision rate pulses, which are correlated with interglacial episodes. Similar incision rate histories are recovered for the past 100 kyr when assuming constant climatic conditions or periodic climatic oscillations, in agreement with theoretical predictions.

Coupling records of fluvial activity from the last interglacial-glacial cycle with climate forcing using both geochronology and numerical modelling

NASA Astrophysics Data System (ADS)

Briant, Rebecca; Mottram, Gareth; Wainwright, John

2010-05-01

River systems are a critical component of the landscape. An understanding of their response to variations in the Earth's climate is vital in light of the expected changes in global climate (e.g. 1.8 to 4.8°C temperature rise) that are forecast to occur over the next c. 100 years. Over the longer term, it becomes increasingly likely that the changes we will see may even be of a magnitude for which the most appropriate analogue we have is the glacial-interglacial scale (c. 10°C temperature change) and other climate changes typical of the Quaternary period (last 2 million years). Therefore it is crucial to apply our understanding of climate-driven changes during the Quaternary to future projections of both climate and landscape change, especially since landscape instability is a key characteristic of the Quaternary. Linking river activity to climate requires both the recognition of potentially climate-driven changes within the fluvial sedimentary record and the linkage of these to external climate records using various geochronological techniques. To this end, this paper firstly presents results from the Welland catchment, Fenland Basin where climatically-driven phases of river activity have been identified using detailed sedimentological analysis and palaeontological environmental reconstruction. Dating of these using radiocarbon and optically-stimulated luminescence dating has shown broad correspondence to external climate fluctuations at a marine isotope substage scale over the last interglacial-glacial cycle (MIS 5d onwards). The precision and accuracy of the two different age techniques varies in different parts of this time period and this will be discussed. Limitations in the precision of these geochronological techniques have prompted the use of a further, complementary to improve understanding of these sequences, i.e. ensemble numerical modeling. The rationale behind this approach is that river response to climate can be traced within the model and validated against the known geological record. If the known geological record can be replicated, then the detailed linkages between climate and river activity shown in the model can be used understand to the relationships between climate change and river activity more clearly. This paper will present the results of three-dimensional cellular automata modeling of the Welland catchment, compare them to the geological record, and draw out what this means for our understanding of earth surface processes.

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

NASA Technical Reports Server (NTRS)

Xue, Yongkang; Liou, Kuo-Nan; Kasahara, Akira

1990-01-01

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

Tempest: Tools for Addressing the Needs of Next-Generation Climate Models

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.; Pinheiro, M. C.; Fong, J.

2015-12-01

Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for identifying weather extremes in large climate datasets. In this presentation, the latest advances with the implementation of this framework will be discussed, and a number of projects now utilizing these tools will be featured.

The impacts of climate changes in the renewable energy resources in the Caribbean region

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

Erickson III, David J

2010-02-01

Assessment of renewable energy resources such as surface solar radiation and wind current has great relevance in the development of local and regional energy policies. This paper examines the variability and availability of these resources as a function of possible climate changes for the Caribbean region. Global climate changes have been reported in the last decades, causing changes in the atmospheric dynamics, which affects the net solar radiation balance at the surface and the wind strength and direction. For this investigation, the future climate changes for the Caribbean are predicted using the parallel climate model (PCM) and it is coupledmore » with the numerical model regional atmospheric modeling system (RAMS) to simulate the solar and wind energy spatial patterns changes for the specific case of the island of Puerto Rico. Numerical results from PCM indicate that the Caribbean basin from 2041 to 2055 will experience a slight decrease in the net surface solar radiation (with respect to the years 1996-2010), which is more pronounced in the western Caribbean sea. Results also indicate that the easterly winds have a tendency to increase in its magnitude, especially from the years 2070 to 2098. The regional model showed that important areas to collect solar energy are located in the eastern side of Puerto Rico, while the more intense wind speed is placed around the coast. A future climate change is expected in the Caribbean that will result in higher energy demands, but both renewable energy sources will have enough intensity to be used in the future as alternative energy resources to mitigate future climate changes.« less

Topographic Evolution and Climate Aridification during Continental Collision: Insights from Computer Simulations

PubMed Central

2015-01-01

How do the feedbacks between tectonics, sediment transport and climate work to shape the topographic evolution of the Earth? This question has been widely addressed via numerical models constrained with thermochronological and geomorphological data at scales ranging from local to orogenic. Here we present a novel numerical model that aims at reproducing the interaction between these processes at the continental scale. For this purpose, we combine in a single computer program: 1) a thin-sheet viscous model of continental deformation; 2) a stream-power surface-transport approach; 3) flexural isostasy allowing for the formation of large sedimentary foreland basins; and 4) an orographic precipitation model that reproduces basic climatic effects such as continentality and rain shadow. We quantify the feedbacks between these processes in a synthetic scenario inspired by the India-Asia collision and the growth of the Tibetan Plateau. We identify a feedback between erosion and crustal thickening leading locally to a <50% increase in deformation rates in places where orographic precipitation is concentrated. This climatically-enhanced deformation takes place preferentially at the upwind flank of the growing plateau, specially at the corners of the indenter (syntaxes). We hypothesize that this may provide clues for better understanding the mechanisms underlying the intriguing tectonic aneurisms documented in the Himalayas. At the continental scale, however, the overall distribution of topographic basins and ranges seems insensitive to climatic factors, despite these do have important, sometimes counterintuitive effects on the amount of sediments trapped within the continent. The dry climatic conditions that naturally develop in the interior of the continent, for example, trigger large intra-continental sediment trapping at basins similar to the Tarim Basin because they determine its endorheic/exorheic drainage. These complex climatic-drainage-tectonic interactions make the development of steady-state topography at the continental scale unlikely. PMID:26244662

Topographic Evolution and Climate Aridification during Continental Collision: Insights from Computer Simulations.

PubMed

Garcia-Castellanos, Daniel; Jiménez-Munt, Ivone

2015-01-01

How do the feedbacks between tectonics, sediment transport and climate work to shape the topographic evolution of the Earth? This question has been widely addressed via numerical models constrained with thermochronological and geomorphological data at scales ranging from local to orogenic. Here we present a novel numerical model that aims at reproducing the interaction between these processes at the continental scale. For this purpose, we combine in a single computer program: 1) a thin-sheet viscous model of continental deformation; 2) a stream-power surface-transport approach; 3) flexural isostasy allowing for the formation of large sedimentary foreland basins; and 4) an orographic precipitation model that reproduces basic climatic effects such as continentality and rain shadow. We quantify the feedbacks between these processes in a synthetic scenario inspired by the India-Asia collision and the growth of the Tibetan Plateau. We identify a feedback between erosion and crustal thickening leading locally to a <50% increase in deformation rates in places where orographic precipitation is concentrated. This climatically-enhanced deformation takes place preferentially at the upwind flank of the growing plateau, specially at the corners of the indenter (syntaxes). We hypothesize that this may provide clues for better understanding the mechanisms underlying the intriguing tectonic aneurisms documented in the Himalayas. At the continental scale, however, the overall distribution of topographic basins and ranges seems insensitive to climatic factors, despite these do have important, sometimes counterintuitive effects on the amount of sediments trapped within the continent. The dry climatic conditions that naturally develop in the interior of the continent, for example, trigger large intra-continental sediment trapping at basins similar to the Tarim Basin because they determine its endorheic/exorheic drainage. These complex climatic-drainage-tectonic interactions make the development of steady-state topography at the continental scale unlikely.

A New Attempt of 2-D Numerical Ice Flow Model to Reconstruct Paleoclimate from Mountain Glaciers

NASA Astrophysics Data System (ADS)

Candaş, Adem; Akif Sarıkaya, Mehmet

2017-04-01

A new two dimensional (2D) numerical ice flow model is generated to simulate the steady-state glacier extent for a wide range of climate conditions. The simulation includes the flow of ice enforced by the annual mass balance gradient of a valley glacier. The annual mass balance is calculated by the difference of the net accumulation and ablation of snow and (or) ice. The generated model lets users to compare the simulated and field observed ice extent of paleoglaciers. As a result, model results provide the conditions about the past climates since simulated ice extent is a function of predefined climatic conditions. To predict the glacier shape and distribution in two dimension, time dependent partial differential equation (PDE) is solved. Thus, a 2D glacier flow model code is constructed in MATLAB and a finite difference method is used to solve this equation. On the other hand, Parallel Ice Sheet Model (PISM) is used to regenerate paleoglaciers in the same area where the MATLAB code is applied. We chose the Mount Dedegöl, an extensively glaciated mountain in SW Turkey, to apply both models. Model results will be presented and discussed in this presentation. This study was supported by TÜBİTAK 114Y548 project.

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.

Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

USGS Publications Warehouse

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

2013-01-01

High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

Progress in Earth System Modeling since the ENIAC Calculation

NASA Astrophysics Data System (ADS)

Fung, I.

2009-05-01

The success of the first numerical weather prediction experiment on the ENIAC computer in 1950 was hinged on the expansion of the meteorological observing network, which led to theoretical advances in atmospheric dynamics and subsequently the implementation of the simplified equations on the computer. This paper briefly reviews the progress in Earth System Modeling and climate observations, and suggests a strategy to sustain and expand the observations needed to advance climate science and prediction.

Multi-Decadal Oscillations of the Ocean Active Upper-Layer Heat Content

NASA Astrophysics Data System (ADS)

Byshev, Vladimir I.; Neiman, Victor G.; Anisimov, Mikhail V.; Gusev, Anatoly V.; Serykh, Ilya V.; Sidorova, Alexandra N.; Figurkin, Alexander L.; Anisimov, Ivan M.

2017-07-01

Spatial patterns in multi-decadal variability in upper ocean heat content for the last 60 years are examined using a numerical model developed at the Institute of Numerical Mathematics of Russia (INM Model) and sea water temperature-salinity data from the World Ocean Database (in: Levitus, NOAA Atlas NESDIS 66, U.S. Wash.: Gov. Printing Office, 2009). Both the model and the observational data show that the heat content of the Active Upper Layer (AUL) in particular regions of the Atlantic, Pacific and Southern oceans have experienced prominent simultaneous variations on multi-decadal (25-35 years) time scales. These variations are compared earlier revealed climatic alternations in the Northern Atlantic region during the last century (Byshev et al. in Doklady Earth Sci 438(2):887-892, 2011). We found that from the middle of 1970s to the end of 1990s the AUL heat content decreased in several oceanic regions, while the mean surface temperature increased on Northern Hemisphere continents according to IPCC (in: Stocker et al. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, 2013). This means that the climate-forcing effect of the ocean-atmosphere interaction in certain energy-active areas determines not only local climatic processes, but also have an influence on global-scale climate phenomena. Here we show that specific regional features of the AUL thermal structure are in a good agreement with climatic conditions on the adjacent continents. Further, the ocean AUL in the five distinctive regions identified in our study have resumed warming in the first decade of this century. By analogy inference from previous climate scenarios, this may signal the onset of more continental climate over mainlands.

Simulating infectious disease risk based on climatic drivers: from numerical weather prediction to long term climate change scenario

NASA Astrophysics Data System (ADS)

Caminade, C.; Ndione, J. A.; Diallo, M.; MacLeod, D.; Faye, O.; Ba, Y.; Dia, I.; Medlock, J. M.; Leach, S.; McIntyre, K. M.; Baylis, M.; Morse, A. P.

2012-04-01

Climate variability is an important component in determining the incidence of a number of diseases with significant health and socioeconomic impacts. In particular, vector born diseases are the most likely to be affected by climate; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the surrounding environmental conditions. Disease risk models of various complexities using different streams of climate forecasts as inputs have been developed within the QWeCI EU and ENHanCE ERA-NET project frameworks. This work will present two application examples, one for Africa and one for Europe. First, we focus on Rift Valley fever over sub-Saharan Africa, a zoonosis that affects domestic animals and humans by causing an acute fever. We show that the Rift Valley fever outbreak that occurred in late 2010 in the northern Sahelian region of Mauritania might have been anticipated ten days in advance using the GFS numerical weather prediction system. Then, an ensemble of regional climate projections is employed to model the climatic suitability of the Asian tiger mosquito for the future over Europe. The Asian tiger mosquito is an invasive species originally from Asia which is able to transmit West Nile and Chikungunya Fever among others. This species has spread worldwide during the last decades, mainly through the shipments of goods from Asia. Different disease models are employed and inter-compared to achieve such a task. Results show that the climatic conditions over southern England, central Western Europe and the Balkans might become more suitable for the mosquito (including the proviso that the mosquito has already been introduced) to establish itself in the future.

Sensitivity of Regional Climate to Deforestation in the Amazon Basin

NASA Technical Reports Server (NTRS)

Eltahir, Elfatih A. B.; Bras, Rafael L.

1994-01-01

The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.

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

PubMed Central

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

2014-01-01

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

New Observationally-Based Metrics for the Analysis of Coupled Climate Model and Earth System Model Simulations of the Southern Ocean

NASA Astrophysics Data System (ADS)

Russell, J. L.

2014-12-01

The exchange of heat and carbon dioxide between the atmosphere and ocean are major controls on Earth's climate under conditions of anthropogenic forcing. The Southern Ocean south of 30°S, occupying just over ¼ of the surface ocean area, accounts for a disproportionate share of the vertical exchange of properties between the deep and surface waters of the ocean and between the surface ocean and the atmosphere; thus this region can be disproportionately influential on the climate system. Despite the crucial role of the Southern Ocean in the climate system, understanding of the particular mechanisms involved remains inadequate, and the model studies underlying many of these results are highly controversial. As part of the overall goal of working toward reducing uncertainties in climate projections, we present an analysis using new data/model metrics based on a unified framework of theory, quantitative datasets, and numerical modeling. These new metrics quantify the mechanisms, processes, and tendencies relevant to the role of the Southern Ocean in climate.

UTCI-Fiala multi-node model of human heat transfer and temperature regulation

NASA Astrophysics Data System (ADS)

Fiala, Dusan; Havenith, George; Bröde, Peter; Kampmann, Bernhard; Jendritzky, Gerd

2012-05-01

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

Secular trends and climate drift in coupled ocean-atmosphere general circulation models

NASA Astrophysics Data System (ADS)

Covey, Curt; Gleckler, Peter J.; Phillips, Thomas J.; Bader, David C.

2006-02-01

Coupled ocean-atmosphere general circulation models (coupled GCMs) with interactive sea ice are the primary tool for investigating possible future global warming and numerous other issues in climate science. A long-standing problem with such models is that when different components of the physical climate system are linked together, the simulated climate can drift away from observation unless constrained by ad hoc adjustments to interface fluxes. However, 11 modern coupled GCMs, including three that do not employ flux adjustments, behave much better in this respect than the older generation of models. Surface temperature trends in control run simulations (with external climate forcing such as solar brightness and atmospheric carbon dioxide held constant) are small compared with observed trends, which include 20th century climate change due to both anthropogenic and natural factors. Sea ice changes in the models are dominated by interannual variations. Deep ocean temperature and salinity trends are small enough for model control runs to extend over 1000 simulated years or more, but trends in some regions, most notably the Arctic, differ substantially among the models and may be problematic. Methods used to initialize coupled GCMs can mitigate climate drift but cannot eliminate it. Lengthy "spin-ups" of models, made possible by increasing computer power, are one reason for the improvements this paper documents.

Introduction. Progress in Earth science and climate studies.

PubMed

Thompson, J Michael T

2008-12-28

In this introductory paper, I review the 'visions of the future' articles prepared by top young scientists for the second of the two Christmas 2008 Triennial Issues of Phil. Trans. R. Soc.A, devoted respectively to astronomy and Earth science. Topics covered in the Earth science issue include: trace gases in the atmosphere; dynamics of the Antarctic circumpolar current; a study of the boundary between the Earth's rocky mantle and its iron core; and two studies of volcanoes and their plumes. A final section devoted to ecology and climate covers: the mathematical modelling of plant-soil interactions; the effects of the boreal forests on the Earth's climate; the role of the past palaeoclimate in testing and calibrating today's numerical climate models; and the evaluation of these models including the quantification of their uncertainties.

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

NASA Astrophysics Data System (ADS)

Chen, B.; Posselt, D. J.; Nguyen, H.; Wu, L.; Su, H.; Braverman, A. J.

2017-12-01

Earth's weather and climate are sensitive to a variety of control factors (e.g., initial state, forcing functions, etc). Characterizing the response of the atmosphere to a change in initial conditions or model forcing is critical for weather forecasting (ensemble prediction) and climate change assessment. Input - response relationships can be quantified by generating an ensemble of multiple (100s to 1000s) realistic realizations of weather and climate states. Atmospheric numerical models generate simulated data through discretized numerical approximation of the partial differential equations (PDEs) governing the underlying physics. However, the computational expense of running high resolution atmospheric state models makes generation of more than a few simulations infeasible. Here, we discuss an experiment wherein we approximate the numerical PDE solver within the Weather Research and Forecasting (WRF) Model using neural networks trained on a subset of model run outputs. Once trained, these neural nets can produce large number of realization of weather states from a small number of deterministic simulations with speeds that are orders of magnitude faster than the underlying PDE solver. Our neural network architecture is inspired by the governing partial differential equations. These equations are location-invariant, and consist of first and second derivations. As such, we use a 3x3 lon-lat grid of atmospheric profiles as the predictor in the neural net to provide the network the information necessary to compute the first and second moments. Results indicate that the neural network algorithm can approximate the PDE outputs with high degree of accuracy (less than 1% error), and that this error increases as a function of the prediction time lag.

Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

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

B. Faybishenko

At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing themmore » with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.« less

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

USGS Publications Warehouse

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

2003-01-01

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

Dynamics of climate-based malaria transmission model with age-structured human population

NASA Astrophysics Data System (ADS)

Addawe, Joel; Pajimola, Aprimelle Kris

2016-10-01

In this paper, we proposed to study the dynamics of malaria transmission with periodic birth rate of the vector and an age-structure for the human population. The human population is divided into two compartments: pre-school (0-5 years) and the rest of the human population. We showed the existence of a disease-free equilibrium point. Using published epidemiological parameters, we use numerical simulations to show potential effect of climate change in the dynamics of age-structured malaria transmission. Numerical simulations suggest that there exists an asymptotically attractive solution that is positive and periodic.

Ensemble Models

EPA Science Inventory

Ensemble forecasting has been used for operational numerical weather prediction in the United States and Europe since the early 1990s. An ensemble of weather or climate forecasts is used to characterize the two main sources of uncertainty in computer models of physical systems: ...

Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Foley, Kevin M.; Stoll, Danielle K.

2010-01-01

Numerical models of the global climate system are the primary tools used to understand and project climate disruptions in the form of future global warming. The Pliocene has been identified as the closest, albeit imperfect, analog to climate conditions expected for the end of this century, making an independent data set of Pliocene conditions necessary for ground truthing model results. Because most climate model output is produced in the form ofmean annual conditions, we present a derivative of the USGS PRISM3 Global Climate Reconstruction which integrates multiple proxies of sea surface temperature (SST) into single surface temperature anomalies. We analyze temperature estimates from faunal and floral assemblage data,Mg/Ca values and alkenone unsaturation indices to arrive at a single mean annual SST anomaly (Pliocene minus modern) best describing each PRISM site, understanding that multiple proxies should not necessarily show concordance. The power of themultiple proxy approach lies within its diversity, as no two proxies measure the same environmental variable. This data set can be used to verify climate model output, to serve as a starting point for model inter-comparisons, and for quantifying uncertainty in Pliocene model prediction in perturbed physics ensembles.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: An Earth Modeling System Software Framework Strawman Design that Integrates Cactus and UCLA/UCB Distributed Data Broker

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task. both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation, while maintaining high performance across numerous supercomputer and workstation architectures. This document proposes a strawman framework design for the climate community based on the integration of Cactus, from the relativistic physics community, and UCLA/UCB Distributed Data Broker (DDB) from the climate community. This design is the result of an extensive survey of climate models and frameworks in the climate community as well as frameworks from many other scientific communities. The design addresses fundamental development and runtime needs using Cactus, a framework with interfaces for FORTRAN and C-based languages, and high-performance model communication needs using DDB. This document also specifically explores object-oriented design issues in the context of climate modeling as well as climate modeling issues in terms of object-oriented design.

Ocean Hydrodynamics Numerical Model in Curvilinear Coordinates for Simulating Circulation of the Global Ocean and its Separate Basins.

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Diansky, Nikolay; Zalesny, Vladimir

2010-05-01

The original program complex is proposed for the ocean circulation sigma-model, developed in the Institute of Numerical Mathematics (INM), Russian Academy of Sciences (RAS). The complex can be used in various curvilinear orthogonal coordinate systems. In addition to ocean circulation model, the complex contains a sea ice dynamics and thermodynamics model, as well as the original system of the atmospheric forcing implementation on the basis of both prescribed meteodata and atmospheric model results. This complex can be used as the oceanic block of Earth climate model as well as for solving the scientific and practical problems concerning the World ocean and its separate oceans and seas. The developed program complex can be effectively used on parallel shared memory computational systems and on contemporary personal computers. On the base of the complex proposed the ocean general circulation model (OGCM) was developed. The model is realized in the curvilinear orthogonal coordinate system obtained by the conformal transformation of the standard geographical grid that allowed us to locate the system singularities outside the integration domain. The horizontal resolution of the OGCM is 1 degree on longitude, 0.5 degree on latitude, and it has 40 non-uniform sigma-levels in depth. The model was integrated for 100 years starting from the Levitus January climatology using the realistic atmospheric annual cycle calculated on the base of CORE datasets. The experimental results showed us that the model adequately reproduces the basic characteristics of large-scale World Ocean dynamics, that is in good agreement with both observational data and results of the best climatic OGCMs. This OGCM is used as the oceanic component of the new version of climatic system model (CSM) developed in INM RAS. The latter is now ready for carrying out the new numerical experiments on climate and its change modelling according to IPCC (Intergovernmental Panel on Climate Change) scenarios in the scope of the CMIP-5 (Coupled Model Intercomparison Project). On the base of the complex proposed the Pacific Ocean circulation eddy-resolving model was realized. The integration domain covers the Pacific from Equator to Bering Strait. The model horizontal resolution is 0.125 degree and it has 20 non-uniform sigma-levels in depth. The model adequately reproduces circulation large-scale structure and its variability: Kuroshio meandering, ocean synoptic eddies, frontal zones, etc. Kuroshio high variability is shown. The distribution of contaminant was simulated that is admittedly wasted near Petropavlovsk-Kamchatsky. The results demonstrate contaminant distribution structure and provide us understanding of hydrological fields formation processes in the North-West Pacific.

CRN Dating and Numerical Glacier Modeling to Investigate Climate During the Last Glacial Maximum, and the Subsequent Deglaciation, Sawatch Range, Colorado

NASA Astrophysics Data System (ADS)

Russell, C.; Leonard, E. M.

2016-12-01

The current study employs a combination of cosmogenic radionuclide (CRN) surface-exposure dating and numerical glacier modeling to investigate the climate during and following the last glacial maximum (LGM) in the Sawatch Range of Colorado. A coupled 2-D energy/mass balance and flow model is used to asses the combinations of temperature and precipitation change that could have sustained glaciers in the range at their LGM extents in five valleys along the eastern flank of the range, by matching modeled ice extent to the well-preserved LGM moraines in each valley. In addition, the study couples modeling with CRN geochronology of post-LGM ice recession to try to understand the dynamics of deglaciation and the magnitudes and rates of the climate changes that drove it. Results to date include an equilibrium glacier model that fits LGM moraines in all five valleys with a 5.4°C temperature depression and no change from modern precipitation amounts or seasonality. Modeling of deglaciation indicates, however, that the response of individual glacier systems is strongly influenced by valley hypsometry as was suggested by previous workers. Low-gradient glacier systems in the range, including the Lake Creek and Clear Creek glaciers, respond dramatically to even small temperature increases, while much steeper systems, such as the Pine Creek glacier, experience much more limited retreat in response to the same climate forcing A CRN-based deglaciation chronology is available for the Lake Creek glacier, the largest of five paleoglaciers studied. The ages show that portions of the valley floor were ice-covered for several hundred years longer than the cirques above. The numerical model is currently being used to investigate two possible explanations for this. One possibility is that climate ameliorated and deglaciation proceeded so fast that thin ice in the cirques melted out before much thicker stagnant ice melted in the valley. A second possibility is that cross-divide flow from the wetter west side of the range maintained small east-side valley glaciers even as the east-side cirques deglaciated. Ongoing work will model a larger area of range to gain a better understanding of range-wide patterns of ice flow that could have affected deglaciation of the Lake Creek valley.

Modeling of the Global Water Cycle - Analytical Models

Treesearch

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

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

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.

Numerical modeling of the agricultural-hydrologic system in Punjab, India

NASA Astrophysics Data System (ADS)

Nyblade, M.; Russo, T. A.; Zikatanov, L.; Zipp, K.

2017-12-01

The goal of food security for India's growing population is threatened by the decline in freshwater resources due to unsustainable water use for irrigation. The issue is acute in parts of Punjab, India, where small landholders produce a major quantity of India's food with declining groundwater resources. To further complicate this problem, other regions of the state are experiencing groundwater logging and salinization, and are reliant on canal systems for fresh water delivery. Due to the lack of water use records, groundwater consumption for this study is estimated with available data on crop yields, climate, and total canal water delivery. The hydrologic and agricultural systems are modeled using appropriate numerical methods and software. This is a state-wide hydrologic numerical model of Punjab that accounts for multiple aquifer layers, agricultural water demands, and interactions between the surface canal system and groundwater. To more accurately represent the drivers of agricultural production and therefore water use, we couple an economic crop optimization model with the hydrologic model. These tools will be used to assess and optimize crop choice scenarios based on farmer income, food production, and hydrologic system constraints. The results of these combined models can be used to further understand the hydrologic system response to government crop procurement policies and climate change, and to assess the effectiveness of possible water conservation solutions.

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Ice group works on sea ice analysis from satellite, sea ice modeling, and ice-atmosphere-ocean / VISION | About EMC Analysis Drift Model KISS Model Numerical Forecast Systems The Polar and Great Lakes

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

An Improved Radiative Transfer Model for Climate Calculations

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Effect of climate change on morphology around a port

NASA Astrophysics Data System (ADS)

Bharathan Radhamma, R.; Deo, M. C.

2017-12-01

It is well known that with the construction of a port and harbour structure the natural shoreline gets interrupted and this disturbs the surrounding coastal morphology. Added to this concern is another one of recent origin, namely, the likely impact of climate change induced by global warming. The present work addresses this issue by describing a case study at New Mangalore Port situated along the west coast of India. The harbour was formed by constructing two breakwaters along either side of the port since the year 1975. We have first determined the rate of change of the shoreline surrounding the port using historic satellite imageries over a period of 36 years. Thereafter a numerical shoreline change model: LITPACK was used to do the same and it was forced by waves simulated over a period of past 36 years varying from 1979 to 2016 and future 36 years ranging from 2016 to 2052. The wave simulation was done with the help of numerical wave model: Mike21-SW which was driven by the wind from a regional climate model called CORDEX. This climate model was earlier run for a moderate global warming pathway called: RCP-4.5. The analysis of satellite imageries indicated that in the past the shoreline change varied from -1.69 m/year to 2.56 m/year with an uncertainty of ± 0.35 m/year and approximately half of the coastal stretch faced extensive erosion. It was found that the wind and waves at this region would intensify in future and also raise the probability of occurrence of high waves. As per the numerical shoreline modelling this would give rise to a much enhanced rate of erosion, namely -2.87 m/year to -3.62 m/year. This would call for a modified shoreline management strategy around the port area. The study highlights the importance of considering potential changes in wind and wave forcing because of the climate change in evaluating future rates of shoreline changes around a port and harbour structure.

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

Background Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. Methods This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Results Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. Conclusion A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts. PMID:15350206

The influences of land use and land cover on climate; an analysis of the Washington-Baltimore area that couples remote sensing with numerical simulation

USGS Publications Warehouse

Pease, R.W.; Jenner, C.B.; Lewis, J.E.

1980-01-01

The Sun drives the atmospheric heat engine by warming the terrestrial surface which in turn warms the atmosphere above. Climate, therefore, is significantly controlled by complex interaction of energy flows near and at the terrestrial surface. When man alters this delicate energy balance by his use of the land, he may alter his climatic environment as well. Land use climatology has emerged as a discipline in which these energy interactions are studied; first, by viewing the spatial distributions of their surface manifestations, and second, by analyzing the energy exchange processes involved. Two new tools for accomplishing this study are presented: one that can interpret surface energy exchange processes from space, and another that can simulate the complex of energy transfers by a numerical simulation model. Use of a satellite-borne multispectral scanner as an imaging radiometer was made feasible by devising a gray-window model that corrects measurements made in space for the effects of the atmosphere in the optical path. The simulation model is a combination of mathematical models of energy transfer processes at or near the surface. Integration of these two analytical approaches was applied to the Washington-Baltimore area to coincide with the August 5, 1973, Skylab 3 overpass which provided data for constructing maps of the energy characteristics of the Earth's surface. The use of the two techniques provides insights into the relationship of climate to land use and land cover and in predicting alterations of climate that may result from alterations of the land surface.

Numerical Modeling of Climatic Change from the Terminus Record of Lewis Glacier, Mount Kenya.

NASA Astrophysics Data System (ADS)

Kruss, Phillip Donald

Over the last 100 years, the glaciers and lakes of East Africa have undergone dramatic change in response to climatic forcing. However, the available conventional meterological series have not proven sufficient to explain these environmental events. The secular climatic change at Lewis Glacier, Mount Kenya (0(DEGREES)9'S, 37(DEGREES)19'E), is reconstructed from its terminus record documented since 1893. The short-time-step numerical model developed for this study consists of climate and ice dynamics segments. The climate segment directly computes the effect on the net balance of change in the four forcings: precipitation, albedo, cloudiness, and temperature. The flow segment calculates the dynamic glacier response to net balance variation. Climatic change occurs over a wide range of time scales. Each glacier responds in a unique fashion to this spectrum of climatic forcings. The response of the Lewis terminus extent to repeated sinusoidal fluctuation in the net balance is calculated. The net balance versus elevation profile is separately translated along the orthogonal balance and elevation axes. Net balance amplitudes of 0.1 to 0.5 m a('-1) of ice and 10 to 50 m elevation, respectively, and periods ranging from 20 to 1000 years are covered. Consideration of the Lewis response is perspective with similar results for Hintereisferner, Storglaciaren, and Berendon and South Cascade Glaciers identifies general characteristics of the time lag and amplitude of the terminus response. The magnitude and timing of the change in only one of the climatic forcings precipitation, albedo, cloudiness, or temperature necessary to produce the retreat of the Lewis terminus from its late 19th century maximum are computed. Equivalent changes for two scenarios of simultaneous variation, namely precipitation/albedo/cloudiness and temperature/albedo, are also estimated. These numerical results are interpreted in the light of long-term lake level, river flow, and instrumental information. A decrease in the annual precipitation of about 160 (+OR-) 70 mm between the early 1880's and the very beginning of the 20th century followed by a secular air temperature rise of 0.35 (+OR-) 0.2(DEGREES)C during the first half of the 1900's, with most warming occurring after about 1920--these climatic changes together with associated albedo and cloudiness variation constitute the most likely cause of the Lewis Glacier wastage during the last 100 years. The modeling and interpretation techniques developed offer the potential for deriving climatic information from the long terminus records and dated geological evidence of past ice extents available for other glaciers. Given the difficulty of documenting climatic change by conventional techniques, the possible role for glaciers and other climate -sensitive environmental components in the monitoring of recent climatic change should be explored.

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

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

Hydrological changes in the tropics: an Holocene perspective

NASA Astrophysics Data System (ADS)

Braconnot, Pascale

2015-04-01

Past climates offer a large set of natural experiences that can be used to better understand the relative role of different climate feedbacks arising from changes in the Earth's global energetics, Earth's hydrological cycle or from the coupling between climate and biogeochemical cycles. In addition, the numerous climate reconstructions from different and independent ice, marine and terrestrial climate archives allow to test how climate models reproduce past changes and to assess their credibility when used for future climate projections. The presentation will review some of the mechanisms affecting the long term trend in the location of the intertropical convergence zone and the Afro-Asian monsoon. Using simulations of the PMIP project, as well as sensitivity experiments with the IPSL model, I'll discuss the role of monsoon changes in the global Earth's energetics and the different feedbacks from ocean and land-surface. The presentation will contrast the conditions in the Early, the mid and late Holocene and show how robust features of monsoon changes can be used to better assess future changes in regions where model results are uncertain, such as West Africa.

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

WRF Test on IBM BG/L:Toward High Performance Application to Regional Climate Research

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

Chin, H S

The effects of climate change will mostly be felt on local to regional scales (Solomon et al., 2007). To develop better forecast skill in regional climate change, an integrated multi-scale modeling capability (i.e., a pair of global and regional climate models) becomes crucially important in understanding and preparing for the impacts of climate change on the temporal and spatial scales that are critical to California's and nation's future environmental quality and economical prosperity. Accurate knowledge of detailed local impact on the water management system from climate change requires a resolution of 1km or so. To this end, a high performancemore » computing platform at the petascale appears to be an essential tool in providing such local scale information to formulate high quality adaptation strategies for local and regional climate change. As a key component of this modeling system at LLNL, the Weather Research and Forecast (WRF) model is implemented and tested on the IBM BG/L machine. The objective of this study is to examine the scaling feature of WRF on BG/L for the optimal performance, and to assess the numerical accuracy of WRF solution on BG/L.« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

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

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Uncertainty quantification of US Southwest climate from IPCC projections.

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

Boslough, Mark Bruce Elrick

2011-01-01

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

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

PubMed

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

2016-01-01

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

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

Changes in Concurrent Precipitation and Temperature Extremes

DOE PAGES

Hao, Zengchao; AghaKouchak, Amir; Phillips, Thomas J.

2013-08-01

While numerous studies have addressed changes in climate extremes, analyses of concurrence of climate extremes are scarce, and climate change effects on joint extremes are rarely considered. This study assesses the occurrence of joint (concurrent) monthly continental precipitation and temperature extremes in Climate Research Unit (CRU) and University of Delaware (UD) observations, and in 13 Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate simulations. Moreover, the joint occurrences of precipitation and temperature extremes simulated by CMIP5 climate models are compared with those derived from the CRU and UD observations for warm/wet, warm/dry, cold/wet, and cold/dry combinations of joint extremes.more » The number of occurrences of these four combinations during the second half of the 20th century (1951–2004) is assessed on a common global grid. CRU and UD observations show substantial increases in the occurrence of joint warm/dry and warm/wet combinations for the period 1978–2004 relative to 1951–1977. The results show that with respect to the sign of change in the concurrent extremes, the CMIP5 climate model simulations are in reasonable overall agreement with observations. The results reveal notable discrepancies between regional patterns and the magnitude of change in individual climate model simulations relative to the observations of precipitation and temperature.« less

Comparing Mid-Century Climate Change Projections at Convective Resolving Scales (2-km) for Life Zones Within Puerto Rico

NASA Astrophysics Data System (ADS)

Bowden, J.; Wootten, A.; Terando, A. J.; Boyles, R.; Misra, V.; Bhardwaj, A.

2016-12-01

Puerto Rico is home to over 3.5 million people and numerous endemic plant and animal species that may be at risk as a result of anthropogenic climate change. This study downscales three CMIP5 Global Circulation Models (GCMs) to a 2-km horizontal resolution using different regional climate models (RCMs) to resolve the island's climate. Here we compare projected climate change from a single GCM, CCSM4, from two RCMs centered on the mid-century, 2041-2060, for a high greenhouse gas emission scenario, RCP8.5. We will discuss similarities and differences in ecologically relevant climate variables, which were selected based on dialogue with experts who have knowledge about potential biological impacts of climate change for current life zones within Puerto Rico. Notable differences appear between the RCMs and include regions with critical ecosystems, such as the El Yunque National Forest in northeast Puerto Rico. This study helps to highlight RCMs structural uncertainty at convective resolving scales.

Hygrothermal Simulation of Wood Exposed To the Effect of External Climate

NASA Astrophysics Data System (ADS)

Dohnal, Jakub; Hradil, Petr; Pencik, Jan

2017-10-01

The article is focused on simulation of moisture transfer in wood of norway spruce (Picea abies L.). Experimental specimen was exposed to the northern climatic conditions in Lund University, Sweden. The moisture content of wood was measured 10 mm from the surface for nearly three years. The ABAQUS program was used for numerical modelling of moisture transfer simulation in 3D. The surface sorption of wood was simulated using user defined subroutine DFLUX developed by VTT Research Centre of Finland Ltd. for the needs of European Project Durable Timber Bridges. Climate data for the analysis was used from insitu measurement nearby realized by weather station. The temperature, relative humidity of the air and precipitation data was record each hour. Numerical analysis took into account influence of rain effect on different parts of specimen surface.

A parallel direct numerical simulation of dust particles in a turbulent flow

NASA Astrophysics Data System (ADS)

Nguyen, H. V.; Yokota, R.; Stenchikov, G.; Kocurek, G.

2012-04-01

Due to their effects on radiation transport, aerosols play an important role in the global climate. Mineral dust aerosol is a predominant natural aerosol in the desert and semi-desert regions of the Middle East and North Africa (MENA). The Arabian Peninsula is one of the three predominant source regions on the planet "exporting" dust to almost the entire world. Mineral dust aerosols make up about 50% of the tropospheric aerosol mass and therefore produces a significant impact on the Earth's climate and the atmospheric environment, especially in the MENA region that is characterized by frequent dust storms and large aerosol generation. Understanding the mechanisms of dust emission, transport and deposition is therefore essential for correctly representing dust in numerical climate prediction. In this study we present results of numerical simulations of dust particles in a turbulent flow to study the interaction between dust and the atmosphere. Homogenous and passive dust particles in the boundary layers are entrained and advected under the influence of a turbulent flow. Currently no interactions between particles are included. Turbulence is resolved through direct numerical simulation using a parallel incompressible Navier-Stokes flow solver. Model output provides information on particle trajectories, turbulent transport of dust and effects of gravity on dust motion, which will be used to compare with the wind tunnel experiments at University of Texas at Austin. Results of testing of parallel efficiency and scalability is provided. Future versions of the model will include air-particle momentum exchanges, varying particle sizes and saltation effect. The results will be used for interpreting wind tunnel and field experiments and for improvement of dust generation parameterizations in meteorological models.

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

NASA Technical Reports Server (NTRS)

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

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.

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2011-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested.

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2012-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from largescale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol--cloud-precipitation interactions are suggested.

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post do data transfer from Gaea to Vapor; DTN (Nwave) has set up for all users but wants one user to test numerous cpu intensive scripts? Click here to view more information Open Effects of the problem: NCEP pre

Pliocene climate

USGS Publications Warehouse

Dowsett, Harry J.; Caballero-Gill, R. P.

2010-01-01

The Pliocene Epoch, 5.3 Ma to 1.8 Ma, was a time when paleoclimate conditions ranged from very warm, equable climates (on a global scale), rhythmically varying every 40,000 years, to high-amplitude glacial-interglacial cycles that led to the “Ice Ages” of the Pleistocene. Evidence for paleoclimate conditions comes from fossils, geochemical data, and the integration of these data with sophisticated numerical models. The Pliocene exhibited a range in atmospheric CO2 concentrations with highs estimated to be at most ~425 ppm in the early Pliocene followed by overall decrease toward preindustrial levels by the close of the Pliocene Epoch (Pagani et al. 2010). Sea levels were estimated to be 25m higher than present day and the size and position of ice sheets in Greenland and Antarctica were decidedly different from today. On the other hand, by the mid-Pliocene, the majority of fauna and flora as well as continental configurations were basically the same as today. Man’s ability to adapt to or mitigate the effects of future climate require a deep understanding of the rates and magnitude of future climate change on an ever finer scale. Since conditions projected for the end of this century are not in the human experience, we depend upon a combination of numerical climate models and comparison to analogous conditions in the geologic past. The Pliocene contains what might be the closest analog to climate conditions expected in the near future, and therefore understanding the Pliocene is not only of academic interest but essential for human adaptation.

Cryosphere-hydrosphere interactions: numerical modeling using the Regional Ocean Modeling System (ROMS) at different scales

NASA Astrophysics Data System (ADS)

Bergamasco, A.; Budgell, W. P.; Carniel, S.; Sclavo, M.

2005-03-01

Conveyor belt circulation controls global climate through heat and water fluxes with atmosphere and from tropical to polar regions and vice versa. This circulation, commonly referred to as thermohaline circulation (THC), seems to have millennium time scale and nowadays--a non-glacial period--appears to be as rather stable. However, concern is raised by the buildup of CO2 and other greenhouse gases in the atmosphere (IPCC, Third assessment report: Climate Change 2001. A contribution of working group I, II and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, UK) 2001, http://www.ipcc.ch) as these may affect the THC conveyor paths. Since it is widely recognized that dense-water formation sites act as primary sources in strengthening quasi-stable THC paths (Stommel H., Tellus131961224), in order to simulate properly the consequences of such scenarios a better understanding of these oceanic processes is needed. To successfully model these processes, air-sea-ice-integrated modelling approaches are often required. Here we focus on two polar regions using the Regional Ocean Modeling System (ROMS). In the first region investigated, the North Atlantic-Arctic, where open-ocean deep convection and open-sea ice formation and dispersion under the intense air-sea interactions are the major engines, we use a new version of the coupled hydrodynamic-ice ROMS model. The second area belongs to the Antarctica region inside the Southern Ocean, where brine rejections during ice formation inside shelf seas origin dense water that, flowing along the continental slope, overflow becoming eventually abyssal waters. Results show how nowadays integrated-modelling tasks have become more and more feasible and effective; numerical simulations dealing with large computational domains or challenging different climate scenarios can be run on multi-processors platforms and on systems like LINUX clusters, made of the same hardware as PCs, and codes have been accordingly modified.This relevant numerical help coming from the computer science can now allow scientists to devote larger attention in the efforts of understanding the deep mechanisms of such complex processes.

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

An overview of mineral dust modeling over East Asia

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

Chen, Siyu; Huang, Jianping; Qian, Yun

Dust aerosol, one of the most abundant aerosol species in the atmosphere, has significant impacts on the energy balance and climatic feedback of the Earth system through its influence on solar and terrestrial radiation as well as clouds. East Asia is the one of prominent regions of dust generation. The East Asia dust life cycle and associated radiative and climatic effects are the outstanding science issues in understanding climate change at regional and even global scale. In the past decades, numerous dust models have been developed and applied to comprehend a series of dust-related processes studies, including emission, transport, andmore » deposition, and to understand the effects of dust aerosol on the radiation and climate over East Asian. In this paper, we review the recent achievements and progresses in East Asian dust modeling research and discuss the potential challenges in future studies.« less

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Atlas : A library for numerical weather prediction and climate modelling

NASA Astrophysics Data System (ADS)

Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

2017-11-01

The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

Numerical modelling of climate change impacts on freshwater lenses on the North Sea Island of Borkum

NASA Astrophysics Data System (ADS)

Sulzbacher, H.; Wiederhold, H.; Siemon, B.; Grinat, M.; Igel, J.; Burschil, T.; Günther, T.; Hinsby, K.

2012-03-01

A numerical variable-density groundwater model is set up for the North Sea Island of Borkum to estimate climate change impacts on coastal aquifers and especially the situation of barrier islands in the Wadden Sea. The database includes information from boreholes, a seismic survey, a helicopter-borne electromagnetic survey (HEM), monitoring of the freshwater-saltwater boundary by vertical electrode chains in two boreholes, measurements of groundwater table, pumping and slug tests, as well as water samples. Based on a statistical analysis of borehole columns, seismic sections and HEM, a hydrogeological model is set up. The groundwater model is developed using the finite-element programme FEFLOW. The variable-density groundwater model is calibrated on the basis of hydraulic, hydrological and geophysical data, in particular spatial HEM and local monitoring data. Verification runs with the calibrated model show good agreement between measured and computed hydraulic heads. A good agreement is also obtained between measured and computed density or total dissolved solids data for both the entire freshwater lens on a large scale and in the area of the well fields on a small scale. For simulating future changes in this coastal groundwater system until the end of the current century we use the climate scenario A2, specified by the Intergovernmental Panel on Climate Change and in particular the data for the German North Sea coast. Simulation runs show proceeding salinization with time beneath the well fields of the two waterworks Waterdelle and Ostland. The modelling study shows that spreading of well fields is an appropriate protection measure against excessive salinization of the water supply until the end of the current century.

Numerical modelling of climate change impacts on freshwater lenses on the North Sea Island of Borkum using hydrological and geophysical methods

NASA Astrophysics Data System (ADS)

Sulzbacher, H.; Wiederhold, H.; Siemon, B.; Grinat, M.; Igel, J.; Burschil, T.; Günther, T.; Hinsby, K.

2012-10-01

A numerical, density dependent groundwater model is set up for the North Sea Island of Borkum to estimate climate change impacts on coastal aquifers and especially the situation of barrier islands in the Wadden Sea. The database includes information from boreholes, a seismic survey, a helicopter-borne electromagnetic (HEM) survey, monitoring of the freshwater-saltwater boundary by vertical electrode chains in two boreholes, measurements of groundwater table, pumping and slug tests, as well as water samples. Based on a statistical analysis of borehole columns, seismic sections and HEM, a hydrogeological model is set up. The groundwater model is developed using the finite-element programme FEFLOW. The density dependent groundwater model is calibrated on the basis of hydraulic, hydrological and geophysical data, in particular spatial HEM and local monitoring data. Verification runs with the calibrated model show good agreement between measured and computed hydraulic heads. A good agreement is also obtained between measured and computed density or total dissolved solids data for both the entire freshwater lens on a large scale and in the area of the well fields on a small scale. For simulating future changes in this coastal groundwater system until the end of the current century, we use the climate scenario A2, specified by the Intergovernmental Panel on Climate Change and, in particular, the data for the German North Sea coast. Simulation runs show proceeding salinisation with time beneath the well fields of the two waterworks Waterdelle and Ostland. The modelling study shows that the spreading of well fields is an appropriate protection measure against excessive salinisation of the water supply until the end of the current century.

GPU-accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model (version 2.52)

NASA Astrophysics Data System (ADS)

Alvanos, Michail; Christoudias, Theodoros

2017-10-01

This paper presents an application of GPU accelerators in Earth system modeling. We focus on atmospheric chemical kinetics, one of the most computationally intensive tasks in climate-chemistry model simulations. We developed a software package that automatically generates CUDA kernels to numerically integrate atmospheric chemical kinetics in the global climate model ECHAM/MESSy Atmospheric Chemistry (EMAC), used to study climate change and air quality scenarios. A source-to-source compiler outputs a CUDA-compatible kernel by parsing the FORTRAN code generated by the Kinetic PreProcessor (KPP) general analysis tool. All Rosenbrock methods that are available in the KPP numerical library are supported.Performance evaluation, using Fermi and Pascal CUDA-enabled GPU accelerators, shows achieved speed-ups of 4. 5 × and 20. 4 × , respectively, of the kernel execution time. A node-to-node real-world production performance comparison shows a 1. 75 × speed-up over the non-accelerated application using the KPP three-stage Rosenbrock solver. We provide a detailed description of the code optimizations used to improve the performance including memory optimizations, control code simplification, and reduction of idle time. The accuracy and correctness of the accelerated implementation are evaluated by comparing to the CPU-only code of the application. The median relative difference is found to be less than 0.000000001 % when comparing the output of the accelerated kernel the CPU-only code.The approach followed, including the computational workload division, and the developed GPU solver code can potentially be used as the basis for hardware acceleration of numerous geoscientific models that rely on KPP for atmospheric chemical kinetics applications.

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

On the Reconstruction of Palaeo-Ice Sheets: Recent Advances and Future Challenges

NASA Technical Reports Server (NTRS)

Stokes, Chris R.; Tarasov, Lev; Blomdin, Robin; Cronin, Thomas M.; Fisher, Timothy G.; Gyllencreutz, Richard; Hattestrand, Clas; Heyman, Jacob; Hindmarsh, Richard C. A.; Hughes, Anna L. C.;

On the reconstruction of palaeo-ice sheets: Recent advances and future challenges

USGS Publications Warehouse

Stokes, Chris R.; Tarasov, Lev; Blomdin, Robin; Cronin, Thomas M.; Fisher, Timothy G.; Gyllencreutz, Richard; Hattestrand, Clas; Heyman, Jakob; Hindmarsh, Richard C. A.; Hughes, Anna L. C.; Jakobsson, Martin; Kirchner, Nina; Livingstone, Stephen J.; Margold, Martin; Murton, Julian B.; Noormets, Riko; Peltier, W. Richard; Peteet, Dorothy M.; Piper, David J. W.; Preusser, Frank; Renssen, Hans; Roberts, David H.; Roche, Didier M.; Saint-Ange, Francky; Stroeven, Arjen P.; Teller, James T.

2015-01-01

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress.

Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

NASA Astrophysics Data System (ADS)

Thomas, C.; Lark, R. M.

2013-12-01

Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second (spherical) model, it cuts off at a temporal range. Having fitted the model, multiple realisations were generated; the random effects were simulated by specifying a covariance matrix for the simulated values, with the estimated parameters. The Cholesky factorisation of the covariance matrix was computed and realizations of the random component of the model generated by pre-multiplying a vector of iid standard Gaussian variables by the lower triangular factor. The resulting random variate was added to the mean value computed from the fixed effects, and the result back-transformed to the original scale of the measurement. Realistic simulations result from approach described above. Background exploratory data analysis was undertaken on 20-day sets of 30-minute buoy data, selected from days 5-24 of months January, April, July, October, 2011, to elucidate daily to weekly variations, and to keep numerical analysis tractable computationally. Work remains to be undertaken to develop suitable models for synthetic directional data. We suggest that the general principles of the method will have applications in other geomorphological modelling endeavours requiring time series of stochastically variable environmental parameters.

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

NASA Astrophysics Data System (ADS)

Beach, Robert H.; Cai, Yongxia; Thomson, Allison; Zhang, Xuesong; Jones, Russell; McCarl, Bruce A.; Crimmins, Allison; Martinich, Jeremy; Cole, Jefferson; Ohrel, Sara; DeAngelo, Benjamin; McFarland, James; Strzepek, Kenneth; Boehlert, Brent

2015-09-01

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from 32.7 billion to 54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.

A virtual climate library of surface temperature over North America for 1979-2015

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-10-01

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context—for example, to document trends in extreme events in response to climate change—is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979-2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life.

A virtual climate library of surface temperature over North America for 1979–2015

PubMed Central

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-01-01

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context—for example, to document trends in extreme events in response to climate change—is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979–2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life. PMID:29039842

A virtual climate library of surface temperature over North America for 1979-2015.

PubMed

Kravtsov, Sergey; Roebber, Paul; Brazauskas, Vytaras

2017-10-17

The most comprehensive continuous-coverage modern climatic data sets, known as reanalyses, come from combining state-of-the-art numerical weather prediction (NWP) models with diverse available observations. These reanalysis products estimate the path of climate evolution that actually happened, and their use in a probabilistic context-for example, to document trends in extreme events in response to climate change-is, therefore, limited. Free runs of NWP models without data assimilation can in principle be used for the latter purpose, but such simulations are computationally expensive and are prone to systematic biases. Here we produce a high-resolution, 100-member ensemble simulation of surface atmospheric temperature over North America for the 1979-2015 period using a comprehensive spatially extended non-stationary statistical model derived from the data based on the North American Regional Reanalysis. The surrogate climate realizations generated by this model are independent from, yet nearly statistically congruent with reality. This data set provides unique opportunities for the analysis of weather-related risk, with applications in agriculture, energy development, and protection of human life.

Building Models in the Classroom: Taking Advantage of Sophisticated Geomorphic Numerical Tools Using a Simple Graphical User Interface

NASA Astrophysics Data System (ADS)

Roy, S. G.; Koons, P. O.; Gerbi, C. C.; Capps, D. K.; Tucker, G. E.; Rogers, Z. A.

2014-12-01

Sophisticated numerical tools exist for modeling geomorphic processes and linking them to tectonic and climatic systems, but they are often seen as inaccessible for users with an exploratory level of interest. We have improved the accessibility of landscape evolution models by producing a simple graphics user interface (GUI) that takes advantage of the Channel-Hillslope Integrated Landscape Development (CHILD) model. Model access is flexible: the user can edit values for basic geomorphic, tectonic, and climate parameters, or obtain greater control by defining the spatiotemporal distributions of those parameters. Users can make educated predictions by choosing their own parametric values for the governing equations and interpreting the results immediately through model graphics. This method of modeling allows users to iteratively build their understanding through experimentation. Use of this GUI is intended for inquiry and discovery-based learning activities. We discuss a number of examples of how the GUI can be used at the upper high school, introductory university, and advanced university level. Effective teaching modules initially focus on an inquiry-based example guided by the instructor. As students become familiar with the GUI and the CHILD model, the class can shift to more student-centered exploration and experimentation. To make model interpretations more robust, digital elevation models can be imported and direct comparisons can be made between CHILD model results and natural topography. The GUI is available online through the University of Maine's Earth and Climate Sciences website, through the Community Surface Dynamics Modeling System (CSDMS) model repository, or by contacting the corresponding author.

Changes in the shoreline at Paradip Port, India in response to climate change

NASA Astrophysics Data System (ADS)

Gopikrishna, B.; Deo, M. C.

2018-02-01

One of the popular methods to predict shoreline shifts into the future involves use of a shoreline evolution model driven by the historical wave climate. It is however understood by now that historical wave conditions might substantially change in future in response to climate change induced by the global warming. The future shoreline changes as well as sediment transport therefore need to be determined with the help of future projections of wave climate. In this work this is done at the port of Paradip situated along the east coast of India. The high resolution wind resulting from a climate modelling experiment called: CORDEX, South Asia, was used to simulate waves over two time-slices of 25 years each in past and future. The wave simulations were carried out with the help of a numerical wave model. Thereafter, rates of longshore sediment transport as well as shoreline shifts were determined over past and future using a numerical shoreline model. It was found that at Paradip Port the net littoral drift per metre width of cross-shore might go up by 37% and so also the net accumulated drift over the entire cross-shore width by 71%. This could be caused by an increase in the mean significant wave height of around 32% and also by changes in the frequency and direction of waves. The intensification of waves in turn might result from an increase in the mean wind speed of around 19%. Similarly, the horizontal extent of the beach accretion and erosion at the port's southern breakwater might go up by 4 m and 8 m, respectively, from the current level in another 25 years. This study should be useful in framing future port management strategies.

Sediment transport drives tidewater glacier periodicity.

PubMed

Brinkerhoff, Douglas; Truffer, Martin; Aschwanden, Andy

2017-07-21

Most of Earth's glaciers are retreating, but some tidewater glaciers are advancing despite increasing temperatures and contrary to their neighbors. This can be explained by the coupling of ice and sediment dynamics: a shoal forms at the glacier terminus, reducing ice discharge and causing advance towards an unstable configuration followed by abrupt retreat, in a process known as the tidewater glacier cycle. Here we use a numerical model calibrated with observations to show that interactions between ice flow, glacial erosion, and sediment transport drive these cycles, which occur independent of climate variations. Water availability controls cycle period and amplitude, and enhanced melt from future warming could trigger advance even in glaciers that are steady or retreating, complicating interpretations of glacier response to climate change. The resulting shifts in sediment and meltwater delivery from changes in glacier configuration may impact interpretations of marine sediments, fjord geochemistry, and marine ecosystems.The reason some of the Earth's tidewater glaciers are advancing despite increasing temperatures is not entirely clear. Here, using a numerical model that simulates both ice and sediment dynamics, the authors show that internal dynamics drive glacier variability independent of climate.

Large-Scale and Global Hydrology. Chapter 92

NASA Technical Reports Server (NTRS)

Rodell, Matthew; Beaudoing, Hiroko Kato; Koster, Randal; Peters-Lidard, Christa D.; Famiglietti, James S.; Lakshmi, Venkat

2016-01-01

Powered by the sun, water moves continuously between and through Earths oceanic, atmospheric, and terrestrial reservoirs. It enables life, shapes Earths surface, and responds to and influences climate change. Scientists measure various features of the water cycle using a combination of ground, airborne, and space-based observations, and seek to characterize it at multiple scales with the aid of numerical models. Over time our understanding of the water cycle and ability to quantify it have improved, owing to advances in observational capabilities, the extension of the data record, and increases in computing power and storage. Here we present some of the most recent estimates of global and continental ocean basin scale water cycle stocks and fluxes and provide examples of modern numerical modeling systems and reanalyses.Further, we discuss prospects for predicting water cycle variability at seasonal and longer scales, which is complicated by a changing climate and direct human impacts related to water management and agriculture. Changes to the water cycle will be among the most obvious and important facets of climate change, thus it is crucial that we continue to invest in our ability to monitor it.

Wave climate and trends along the eastern Chukchi Arctic Alaska coast

USGS Publications Warehouse

Erikson, L.H.; Storlazzi, C.D.; Jensen, R.E.

2011-01-01

Due in large part to the difficulty of obtaining measurements in the Arctic, little is known about the wave climate along the coast of Arctic Alaska. In this study, numerical model simulations encompassing 40 years of wave hind-casts were used to assess mean and extreme wave conditions. Results indicate that the wave climate was strongly modulated by large-scale atmospheric circulation patterns and that mean and extreme wave heights and periods exhibited increasing trends in both the sea and swell frequency bands over the time-period studied (1954-2004). Model simulations also indicate that the upward trend was not due to a decrease in the minimum icepack extent. ?? 2011 ASCE.

On the stability of the Atlantic meridional overturning circulation.

PubMed

Hofmann, Matthias; Rahmstorf, Stefan

2009-12-08

One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC.

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

REGRESSION MODELS THAT RELATE STREAMS TO WATERSHEDS: COPING WITH NUMEROUS, COLLINEAR PEDICTORS

EPA Science Inventory

GIS efforts can produce a very large number of watershed variables (climate, land use/land cover and topography, all defined for multiple areas of influence) that could serve as candidate predictors in a regression model of reach-scale stream features. Invariably, many of these ...

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

PubMed

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

2013-10-28

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

High mean water vapour pressure promotes the transmission of bacillary dysentery.

PubMed

Li, Guo-Zheng; Shao, Feng-Feng; Zhang, Hao; Zou, Chun-Pu; Li, Hui-Hui; Jin, Jue

2015-01-01

Bacillary dysentery is an infectious disease caused by Shigella dysenteriae, which has a seasonal distribution. External environmental factors, including climate, play a significant role in its transmission. This paper identifies climate-related risk factors and their role in bacillary dysentery transmission. Harbin, in northeast China, with a temperate climate, and Quzhou, in southern China, with a subtropical climate, are chosen as the study locations. The least absolute shrinkage and selectionator operator is applied to select relevant climate factors involved in the transmission of bacillary dysentery. Based on the selected relevant climate factors and incidence rates, an AutoRegressive Integrated Moving Average (ARIMA) model is established successfully as a time series prediction model. The numerical results demonstrate that the mean water vapour pressure over the previous month results in a high relative risk for bacillary dysentery transmission in both cities, and the ARIMA model can successfully perform such a prediction. These results provide better explanations for the relationship between climate factors and bacillary dysentery transmission than those put forth in other studies that use only correlation coefficients or fitting models. The findings in this paper demonstrate that the mean water vapour pressure over the previous month is an important predictor for the transmission of bacillary dysentery.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Major challenges for correlational ecological niche model projections to future climate conditions.

PubMed

Peterson, A Townsend; Cobos, Marlon E; Jiménez-García, Daniel

2018-06-20

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions. © 2018 New York Academy of Sciences.

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

The UK Earth System Model project

NASA Astrophysics Data System (ADS)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

Unmanned Aerial Systems as Part of a Multi-Component Assessment Strategy to Address Climate Change and Atmospheric Processes

NASA Astrophysics Data System (ADS)

Lange, Manfred; Vrekoussis, Mihalis; Sciare, Jean; Argyrides, Marios; Ioannou, Stelios; Keleshis, Christos

2015-04-01

Unmanned Aerial Systems (UAS) have been established as versatile tools for different applications, providing data and observations for atmospheric and Earth-Systems research. They offer an urgently needed link between in-situ ground based measurements and satellite remote sensing observations and are distinguished by significant versatility, flexibility and moderate operational costs. UAS have the proven potential to contribute to a multi-component assessment strategy that combines remote-sensing, numerical modelling and surface measurements in order to elucidate important atmospheric processes. This includes physical and chemical transformations related to ongoing climate change as well as issues linked to aerosol-cloud interactions and air quality. The distinct advantages offered by UAS comprise, to name but a few: (i) their ability to operate from altitudes of a few meters to up to a few kilometers; (ii) their capability to perform autonomously controlled missions, which provides for repeat-measurements to be carried out at precisely defined locations; (iii) their relative ease of operation, which enables flexible employment at short-term notice and (iv) the employment of more than one platform in stacked formation, which allows for unique, quasi-3D-observations of atmospheric properties and processes. These advantages are brought to bear in combining in-situ ground based observations and numerical modeling with UAS-based remote sensing in elucidating specific research questions that require both horizontally and vertically resolved measurements at high spatial and temporal resolutions. Employing numerical atmospheric modelling, UAS can provide survey information over spatially and temporally localized, focused areas of evolving atmospheric phenomena, as they become identified by the numerical models. Conversely, UAS observations offer urgently needed data for model verification and provide boundary conditions for numerical models. In this presentation, we will briefly describe the current elements of our observational capabilities that enable the aforementioned multi-component assessment strategy by the Unmanned Systems Research Laboratory of the Cyprus Institute. This strategy is applied and utilized in the context of the EU-funded BACCHUS project, aside from other tasks. The ongoing and planned observations are particularly relevant as they are carried out in the Eastern Mediterranean and the Middle East, a region characterized by increasing anthropogenic pressures and ongoing and anticipated severe climatic changes and their impacts.

Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

ERIC Educational Resources Information Center

Carey, Cayelan C.; Gougis, Rebekka Darner

2017-01-01

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing)…

The Mars Climate Database (MCD version 5.2)

NASA Astrophysics Data System (ADS)

Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team

2015-10-01

The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2

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.

Seafloor weathering buffering climate: numerical experiments

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Archer, D. E.; Abbot, D. S.

2013-12-01

Continental silicate weathering is widely held to consume atmospheric CO2 at a rate controlled in part by temperature, resulting in a climate-weathering feedback [Walker et al., 1981]. It has been suggested that weathering of oceanic crust of warm mid-ocean ridge flanks also has a CO2 uptake rate that is controlled by climate [Sleep and Zahnle, 2001; Brady and Gislason, 1997]. Although this effect might not be significant on present-day Earth [Caldeira, 1995], seafloor weathering may be more pronounced during snowball states [Le Hir et al., 2008], during the Archean when seafloor spreading rates were faster [Sleep and Zahnle, 2001], and on waterworld planets [Abbot et al., 2012]. Previous studies of seafloor weathering have made significant contributions using qualitative, generally one-box, models, and the logical next step is to extend this work using a spatially resolved model. For example, experiments demonstrate that seafloor weathering reactions are temperature dependent, but it is not clear whether the deep ocean temperature affects the temperature at which the reactions occur, or if instead this temperature is set only by geothermal processes. Our goal is to develop a 2-D numerical model that can simulate hydrothermal circulation and resulting alteration of oceanic basalts, and can therefore address such questions. A model of diffusive and convective heat transfer in fluid-saturated porous media simulates hydrothermal circulation through porous oceanic basalt. Unsteady natural convection is solved for using a Darcy model of porous media flow that has been extensively benchmarked. Background hydrothermal circulation is coupled to mineral reaction kinetics of basaltic alteration and hydrothermal mineral precipitation. In order to quantify seafloor weathering as a climate-weathering feedback process, this model focuses on hydrothermal reactions that influence carbon uptake as well as ocean alkalinity: silicate rock dissolution, calcium and magnesium leaching reactions, carbonate precipitation, and clay formation.

A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies

NASA Astrophysics Data System (ADS)

Bonetti, F.; McInnes, C. R.

2016-12-01

Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.

Quantifying climatic variability in monsoonal northern China over the last 2200 years and its role in driving Chinese dynastic changes

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Zhang, David D.; Zhang, Xiaojian; Xu, Qinghai; Lee, Harry F.; Pei, Qing; Cheng, Bo; Li, Chunhai; Ni, Jian; Sun, Aizhi; Lu, Fengyan; Zong, Yongqiang

2017-03-01

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal- to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial- to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ∼100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4%) may have been more important than temperature (32.5%) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

NASA Astrophysics Data System (ADS)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Abrupt climate change and extinction events

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.

1988-01-01

There is a growing body of theoretical and empirical support for the concept of instabilities in the climate system, and indications that abrupt climate change may in some cases contribute to abrupt extinctions. Theoretical indications of instabilities can be found in a broad spectrum of climate models (energy balance models, a thermohaline model of deep-water circulation, atmospheric general circulation models, and coupled ocean-atmosphere models). Abrupt transitions can be of several types and affect the environment in different ways. There is increasing evidence for abrupt climate change in the geologic record and involves both interglacial-glacial scale transitions and the longer-term evolution of climate over the last 100 million years. Records from the Cenozoic clearly show that the long-term trend is characterized by numerous abrupt steps where the system appears to be rapidly moving to a new equilibrium state. The long-term trend probably is due to changes associated with plate tectonic processes, but the abrupt steps most likely reflect instabilities in the climate system as the slowly changing boundary conditions caused the climate to reach some threshold critical point. A more detailed analysis of abrupt steps comes from high-resolution studies of glacial-interglacial fluctuations in the Pleistocene. Comparison of climate transitions with the extinction record indicates that many climate and biotic transitions coincide. The Cretaceous-Tertiary extinction is not a candidate for an extinction event due to instabilities in the climate system. It is quite possible that more detailed comparisons and analysis will indicate some flaws in the climate instability-extinction hypothesis, but at present it appears to be a viable candidate as an alternate mechanism for causing abrupt environmental changes and extinctions.

CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE PAGES

Stouffer, R. J.; Eyring, V.; Meehl, G. A.; ...

2017-01-23

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

CMIP5 Scientific Gaps and Recommendations for CMIP6

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

Stouffer, R. J.; Eyring, V.; Meehl, G. A.

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

Numerical Modeling of Geomorphic Change on Sandy Coasts as a Function of Changing Wave Climate

NASA Astrophysics Data System (ADS)

Adams, P. N.; McNamara, D.; Murray, A. B.; Lovering, J.

2009-12-01

Climate change is expected to affect sandy coast geomorphology through two principal mechanisms: (1) sea level rise, which affects cross-shore sediment transport tending to drive shoreline retreat, and (2) alteration of statistical distributions in ocean storm wave climate (deep water wave height, period, and direction), which affects longshore sediment transport gradients that result in shoreline erosion and accretion. To address potential climate change-driven effects on longshore sediment transport gradients, we are developing techniques to link various numerical models of wave transformation with several different longshore sediment transport formulae in accordance with the Community Surface Dynamics Modeling System (CSDMS) project. Results of the various wave transformation models are compared to field observations of cross-shelf wave transformation along the North Florida Atlantic coast for purposes of model verification and calibration. Initial comparisons between wave-transformation methods (assumption of shore-parallel contours, simple wave ray tracing, and the SWAN spectral wave model) on artificially constructed continental shelves reveal an increasing discrepancy of results for increasing complexity of shelf bathymetry. When the more advanced SWAN spectral wave model is coupled with a simple CERC-type formulation of longshore sediment transport and applied to a real coast with complex offshore shoals (Cape Canaveral region of the North Florida Atlantic Coast), the patterns of erosion and accretion agree with results of the simplest wave-propagation models for some wave conditions, but disagree in others. Model simulations in which wave height and period are held constant show that locations of divergence and convergence of sediment flux shift with deep water wave-approach angle in ways that would not always be predicted using less sophisticated wave propagation models. Thus, predicting long-term local shoreline change on actual coastlines featuring complex bathymetry requires the extra computational effort to run the more advanced model over a wide range of wave conditions.

Sensitivity of leaf size and shape to climate: Global patterns and paleoclimatic applications

USGS Publications Warehouse

Peppe, D.J.; Royer, D.L.; Cariglino, B.; Oliver, S.Y.; Newman, S.; Leight, E.; Enikolopov, G.; Fernandez-Burgos, M.; Herrera, F.; Adams, J.M.; Correa, E.; Currano, E.D.; Erickson, J.M.; Hinojosa, L.F.; Hoganson, J.W.; Iglesias, A.; Jaramillo, C.A.; Johnson, K.R.; Jordan, G.J.; Kraft, N.J.B.; Lovelock, E.C.; Lusk, C.H.; Niinemets, U.; Penuelas, J.; Rapson, G.; Wing, S.L.; Wright, I.J.

2011-01-01

Paleobotanists have long used models based on leaf size and shape to reconstruct paleoclimate. However, most models incorporate a single variable or use traits that are not physiologically or functionally linked to climate, limiting their predictive power. Further, they often underestimate paleotemperature relative to other proxies. Here we quantify leaf-climate correlations from 92 globally distributed, climatically diverse sites, and explore potential confounding factors. Multiple linear regression models for mean annual temperature (MAT) and mean annual precipitation (MAP) are developed and applied to nine well-studied fossil floras. We find that leaves in cold climates typically have larger, more numerous teeth, and are more highly dissected. Leaf habit (deciduous vs evergreen), local water availability, and phylogenetic history all affect these relationships. Leaves in wet climates are larger and have fewer, smaller teeth. Our multivariate MAT and MAP models offer moderate improvements in precision over univariate approaches (??4.0 vs 4.8??C for MAT) and strong improvements in accuracy. For example, our provisional MAT estimates for most North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence. Our study demonstrates that the inclusion of additional leaf traits that are functionally linked to climate improves paleoclimate reconstructions. This work also illustrates the need for better understanding of the impact of phylogeny and leaf habit on leaf-climate relationships. ?? 2011 The Authors. New Phytologist ?? 2011 New Phytologist Trust.

Geomorphology and landscape organization of a northern peatland complex

NASA Astrophysics Data System (ADS)

Richardson, M. C.

2012-12-01

The geomorphic evolution of northern peatlands is governed by complex ecohydrological feedback mechanisms and associated hydro-climatic drivers. For example, prevailing models of bog development (i.e. Ingram's groundwater mounding hypothesis and variants) attempt to explicitly link bog dome characteristics to the regional climate based on analytical and numerical models of lateral groundwater flow and the first-order control of water table position on rates of peat accumulation. In this talk I will present new results from quantitative geomorphic analyses of a northern peatland complex at the De Beers Victor diamond mine site in the Hudson Bay Lowlands of northern Ontario. This work capitalizes on spatially-extensive, high-resolution topographic (LiDAR) data to rigorously test analytical and numerical models of bog dome development in this landscape. The analysis and discussion are then expanded beyond individual bog formations to more broadly consider ecohydrological drivers of landscape organization, with implications for understanding and modeling catchment-scale runoff response. Results show that in this landscape, drainage patterns exhibit relatively well-organized characteristics consistent with observed runoff responses in six gauged research catchments. Interpreted together, the results of these geomorphic and hydrologic analyses help refine our understanding of water balance partitioning among different landcover types within northern peatland complexes. These findings can be used to help guide the development of appropriate numerical model structures for hydrologic prediction in ungauged peatland basins of northern Canada.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

PubMed

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-02-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling

PubMed Central

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-01-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631

Monitoring the performance of the next Climate Forecast System version 3, throughout its development stage at EMC/NCEP

NASA Astrophysics Data System (ADS)

Peña, M.; Saha, S.; Wu, X.; Wang, J.; Tripp, P.; Moorthi, S.; Bhattacharjee, P.

2016-12-01

The next version of the operational Climate Forecast System (version 3, CFSv3) will be a fully coupled six-components system with diverse applications to earth system modeling, including weather and climate predictions. This system will couple the earth's atmosphere, land, ocean, sea-ice, waves and aerosols for both data assimilation and modeling. It will also use the NOAA Environmental Modeling System (NEMS) software super structure to couple these components. The CFSv3 is part of the next Unified Global Coupled System (UGCS), which will unify the global prediction systems that are now operational at NCEP. The UGCS is being developed through the efforts of dedicated research and engineering teams and through coordination across many CPO/MAPP and NGGPS groups. During this development phase, the UGCS is being tested for seasonal purposes and undergoes frequent revisions. Each new revision is evaluated to quickly discover, isolate and solve problems that negatively impact its performance. In the UGCS-seasonal model, components (e.g., ocean, sea-ice, atmosphere, etc.) are coupled through a NEMS-based "mediator". In this numerical infrastructure, model diagnostics and forecast validation are carried out, both component by component, and as a whole. The next stage, model optimization, will require enhanced performance diagnostics tools to help prioritize areas of numerical improvements. After the technical development of the UGCS-seasonal is completed, it will become the first realization of the CFSv3. All future development of this system will be carried out by the climate team at NCEP, in scientific collaboration with the groups that developed the individual components, as well as the climate community. A unique challenge to evaluate this unified weather-climate system is the large number of variables, which evolve over a wide range of temporal and spatial scales. A small set of performance measures and scorecard displays are been created, and collaboration and software contributions from research and operational centers are being incorporated. A status of the CFSv3/UGCS-seasonal development and examples of its performance and measuring tools will be presented.

Assessing groundwater availability in a folded carbonate aquifer through the development of a numerical model

NASA Astrophysics Data System (ADS)

Di Salvo, Cristina; Romano, Emanuele; Guyennon, Nicolas; Bruna Petrangeli, Anna; Preziosi, Elisabetta

2015-04-01

The study of aquifer systems from a quantitative point of view is fundamental for adopting water management plans aiming at preserving water resources and reducing environmental risks related to groundwater level and discharge changes. This is also what the European Union Water Framework Directive (WFD, 2000/60/EC) states, holding the development of numerical models as a key aspect for groundwater management. The objective of this research is to i) define a methodology for modeling a complex hydrogeological structure in a structurally folded carbonate area and ii) estimate the concurrent effects of exploitation and climate changes on groundwater availability through the implementation of a 3D groundwater flow model. This study concerns the Monte Coscerno karst aquifer located in the Apennine chain in Central Italy in the Nera River Valley.This aquifer, is planned to be exploited in the near future for water supply. Negative trends of precipitation in Central Italy have been reported in relation to global climate changes, which are expected to affect the availability of recharge to carbonate aquifers throughout the region . A great concern is the combined impact of climate change and groundwater exploitation, hence scenarios are needed taking into account the effect of possible temperature and precipitation trends on recharge rates. Following a previous experience with model conceptualization and long-term simulation of groundwater flow, an integrated three-dimensional groundwater model has been developed for the Monte Coscerno aquifer. In a previous paper (Preziosi et al 2014) the spatial distribution of recharge to this aquifer was estimated through the Thornthwaite Mather model at a daily time step using as inputs past precipitation and temperature values (1951-2013) as well as soil and landscape properties. In this paper the numerical model development is described. On the basis of well logs from private consulting companies and literature cross sections the multilayer aquifer was conceptualized as five folded hydrostratigraphic units: three main carbonate aquifers are separated by two aquitards, which can be locally discontinuous, leading to a complicated flow pattern. In general the vertical leakance is upward from the basal aquifer to the unconfined uppermost aquifer. As shown by the increasing discharge from north to south, the Nera river acts as the main sink of the study area, gaining groundwater as it cuts through the folded terrain. The numerical model was implemented using the MODFLOW-2000 code and extends over an area of 235 km2 with a grid spacing of 100 meters in each of the 5 layers. Model calibration was achieved by comparing the model results with observed streamflow of the Nera river (8-10 measures per year during 1991-1993 and 1996-2012) which on the basis of the river hydrograph at gaging locations is considered to be derived entirely from groundwater. The effects of climate variation on groundwater discharge to the river in the past 60 years are analyzed. Key issues related to the elaboration of a numerical model of a folded structure are also described.

DRIAS project : A component of French Climate Services

NASA Astrophysics Data System (ADS)

Lémond, J.; Dandin, P.; Moisselin, J. M.; Franchistéguy, L.; Kerdoncuff, M.; Pagé, C.; Vautard, R.; Déqué, M.; Planton, S.

2010-09-01

DRIAS (Providing access to French Regionalized climate scenarios for the Impact and the Adaptation of our Societies and environment) is a 2 years project, funded by the GICC (Management and Impacts of Climate Change) programme of the French Ministery of Ecology and Sustainable Development. Its aim is to provide regionalized climate simulations, data and products performed by French climate modeling, as well as to support users of these informations. In addition to numerical data, the project aims to make available probabilistic products, allowing the user to apprehend and take into account in studies the uncertainty inherent in modeling. From a technical perspective, the challenge will be to provide standardized informations between different producers. The combined accompaniment should be under different forms (metadata, hotline, training, forum), which will allow optimal use of products supplied. DRIAS gathers different partners and expertises. Its composed by representatives of French laboratories in which regionalized numerical simulations are produced : IPSL, CERFACS, and CNRM. The project is coordonned by the Climatology Departement of Météo-France which will provide expertise in the production and tools of availability of climatological data, acquired through the development of an existing data service access called Climathèque (http://climatheque.meteo.fr). In addition, a multidisciplinary committee of users representing different sectors concerned by climate change and different kind of structures (public, parapublic, private, association) accompanies the project. Its role is to express needs, validate the choices made, do tests... and thus facilitate communication between producers and users. Thus, the DRIAS project participates in the development effort of French Climate Services. The aim of this work is to present and introduce these key aspects.

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

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

Reconstruction of the Eemian climate using a fully coupled Earth system model

NASA Astrophysics Data System (ADS)

Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Huybrechts, Philippe

2017-04-01

Climate of the Last Interglacial (LIG) between ca. 130 and 115 kyr BP is thought to be a good analogue for future climate warming. Though the driving mechanisms of the past and current climate evolution differ, analysis of the LIG climate may provide important insights for projections of future environmental changes. We do not know properly what was spatial distribution and magnitude of surface air temperature and precipitation anomalies with respect to present. Sparse proxy data are attributed mostly to the continental margins, internal areas of ice sheets and particular regions of the World Ocean. Combining mathematical modeling and indirect evidence can help to identify driving mechanisms and feed-backs which formed climatic conditions of the LIG. In order to reproduce the LIG climate, we carried out transient numerical experiments using a fully coupled Earth System Model (ESM) consisting of an AO GCM, which includes decription of the biosphere, atmospheric and oceanic chemistry ets. (INMCM), developed in the Institute of Numerical Mathematics (Moscow, Russia) and the models of Greenland and Antarctic ice sheets (GrISM and AISM, Vrije Uninersiteit Brussel, Belgium). Though the newest version of the INMCM has rather high spatial resolution, it canot be used in long transient numerical experimemts because of high computational demand. Coupling of the GrISM and AISM to the low resolution version of the INMCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmosphere and the ocean components of the ESM (spatial resolution 5˚×4˚, 21 vertical layers in the atmospheric block, 2.5°×2°, 6 min. temporal resolution; 33 vertical layers in the oceanic block; 20×20 km, 51 vertical layers and 1 yr temporal resolution in the GrISM and AISM). We apply two different coupling strategies. AISM is incorporated into the ESM via using procedures of resampling and interpolation of the input fields of annually averaged air surface temperatures and precipitation fields generated by the INMCM. To provide interactive coupling of the INMCM and the GrISM, we employ a special energy- and water balance model (EWBM-G), which serves as a buffer providing effective data exchange between sub-models. EWBM-G operates in a rectangle domain including Greenland and calculates annual surface mass balance (further transferred as an external forcing to the GrISM) and fresh water flux (transferred to the oceanic block of the INMCM). Orbital parameters of the LIG were set with 1 kyr step with further interpolation to 100 years. Assuming concentrations of greenhouse gases during the LIG were not very much different from the preindustrial values, this potential forcing was neglected. Climatic block of the ESM was called every 100 model years to follow changes in orbital forcing. AISM and GrISM were asynchronously coupled to sub-models of the atmosphere and the ocean with the ratio of model years as 100 to 1. Obtained fields of deviations of air surface temperature from preindustrial values correspond in general to the estimates made in earlier studies. Evaluated contribution of the Greenland ice sheet to the global sea level rise (approximately 2 m) supports the newest estimates based on model results and proxy data analysis.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

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

Beach, Robert H.; Cai, Yongxia; Thomson, Allison

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices.more » The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from $32.7 billion to $54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.« less

An empirical perspective for understanding climate change impacts in Switzerland

USGS Publications Warehouse

Henne, Paul; Bigalke, Moritz; Büntgen, Ulf; Colombaroli, Daniele; Conedera, Marco; Feller, Urs; Frank, David; Fuhrer, Jürg; Grosjean, Martin; Heiri, Oliver; Luterbacher, Jürg; Mestrot, Adrien; Rigling, Andreas; Rössler, Ole; Rohr, Christian; Rutishauser, This; Schwikowski, Margit; Stampfli, Andreas; Szidat, Sönke; Theurillat, Jean-Paul; Weingartner, Rolf; Wilcke, Wolfgan; Tinner, Willy

2018-01-01

Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.

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

PubMed Central

Olson, Deanna H.; Blaustein, Andrew R.

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. PMID:27513565

The U.S. Geological Survey Climate Geo Data Portal: an integrated broker for climate and geospatial data

USGS Publications Warehouse

Blodgett, David L.

2013-01-01

The increasing availability of downscaled climate projections and other data products that summarize or predict climate conditions, is making climate data use more common in research and management. Scientists and decisionmakers often need to construct ensembles and compare climate hindcasts and future projections for particular spatial areas. These tasks generally require an investigator to procure all datasets of interest en masse, integrate the various data formats and representations into commonly accessible and comparable formats, and then extract the subsets of the datasets that are actually of interest. This process can be challenging and time intensive due to data-transfer, -storage, and(or) -processing limits, or unfamiliarity with methods of accessing climate data. Data management for modeling and assessing the impacts of future climate conditions is also becoming increasingly expensive due to the size of the datasets. The Climate Geo Data Portal (http://cida.usgs.gov/climate/gdp/) addresses these limitations, making access to numerous climate datasets for particular areas of interest a simple and efficient task.

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A Biome map for Modelling Global Mid-Pliocene Climate Change

NASA Astrophysics Data System (ADS)

Salzmann, U.; Haywood, A. M.

2006-12-01

The importance of vegetation-climate feedbacks was highlighted by several paleo-climate modelling exercises but their role as a boundary condition in Tertiary modelling has not been fully recognised or explored. Several paleo-vegetation datasets and maps have been produced for specific time slabs or regions for the Tertiary, but the vegetation classifications that have been used differ, thus making meaningful comparisons difficult. In order to facilitate further investigations into Tertiary climate and environmental change we are presently implementing the comprehensive GIS database TEVIS (Tertiary Environment and Vegetation Information System). TEVIS integrates marine and terrestrial vegetation data, taken from fossil pollen, leaf or wood, into an internally consistent classification scheme to produce for different time slabs global Tertiary Biome and Mega- Biome maps (Harrison & Prentice, 2003). In the frame of our ongoing 5-year programme we present a first global vegetation map for the mid-Pliocene time slab, a period of sustained global warmth. Data were synthesised from the PRISM data set (Thompson and Fleming 1996) after translating them to the Biome classification scheme and from new literature. The outcomes of the Biome map are compared with modelling results using an advanced numerical general circulation model (HadAM3) and the BIOME 4 vegetation model. Our combined proxy data and modelling approach will provide new palaeoclimate datasets to test models that are used to predict future climate change, and provide a more rigorous picture of climate and environmental changes during the Neogene.

Linking Physical Climate Research and Economic Assessments of Mitigation Policies

NASA Astrophysics Data System (ADS)

Stainforth, David; Calel, Raphael

2017-04-01

Evaluating climate change policies requires economic assessments which balance the costs and benefits of climate action. A certain class of Integrated Assessment Models (IAMS) are widely used for this type of analysis; DICE, PAGE and FUND are three of the most influential. In the economics community there has been much discussion and debate about the economic assumptions implemented within these models. Two aspects in particular have gained much attention: i) the costs of damages resulting from climate change - the so-called damage function, and ii) the choice of discount rate applied to future costs and benefits. There has, however, been rather little attention given to the consequences of the choices made in the physical climate models within these IAMS. Here we discuss the practical aspects of the implementation of the physical models in these IAMS, as well as the implications of choices made in these physical science components for economic assessments[1]. We present a simple breakdown of how these IAMS differently represent the climate system as a consequence of differing underlying physical models, different parametric assumptions (for parameters representing, for instance, feedbacks and ocean heat uptake) and different numerical approaches to solving the models. We present the physical and economic consequences of these differences and reflect on how we might better incorporate the latest physical science understanding in economic models of this type. [1] Calel, R. and Stainforth D.A., "On the Physics of Three Integrated Assessment Models", Bulletin of the American Meteorological Society, in press.

Implications of between-isolate variation for climate change impact modelling of Haemonchus contortus populations.

PubMed

Rose Vineer, H; Steiner, J; Knapp-Lawitzke, F; Bull, K; von Son-de Fernex, E; Bosco, A; Hertzberg, H; Demeler, J; Rinaldi, L; Morrison, A A; Skuce, P; Bartley, D J; Morgan, E R

2016-10-15

The impact of climate change on parasites and parasitic diseases is a growing concern and numerous empirical and mechanistic models have been developed to predict climate-driven spatial and temporal changes in the distribution of parasites and disease risk. Variation in parasite phenotype and life-history traits between isolates could undermine the application of such models at broad spatial scales. Seasonal variation in the transmission of the haematophagous gastrointestinal nematode Haemonchus contortus, one of the most pathogenic helminth species infecting sheep and goats worldwide, is primarily determined by the impact of environmental conditions on the free-living stages. To evaluate variability in the development success and mortality of the free-living stages of H. contortus and the impact of this variability on future climate impact modelling, three isolates of diverse origin were cultured at a range of temperatures between 15°C and 37°C to determine their development success compared with simulations using the GLOWORM-FL H. contortus model. No significant difference was observed in the developmental success of the three isolates of H. contortus tested, nor between isolates and model simulations. However, development success of all isolates at 37°C was lower than predicted by the model, suggesting the potential for overestimation of transmission risk at higher temperatures, such as those predicted under some scenarios of climate change. Recommendations are made for future climate impact modelling of gastrointestinal nematodes. Copyright © 2016 Elsevier B.V. All rights reserved.

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Estimating the numerical diapycnal mixing in the GO5.0 ocean model

NASA Astrophysics Data System (ADS)

Megann, Alex; Nurser, George

2014-05-01

Constant-depth (or "z-coordinate") ocean models such as MOM and NEMO have become the de facto workhorse in climate applications, and have attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes (e.g. Hofmann and Maqueda, 2006), and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimations have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is the latest ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre (Megann et al, 2013). It uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. Two approaches to quantifying the numerical diapycnal mixing in this model are described: the first is based on the isopycnal watermass analysis of Lee et al (2002), while the second uses a passive tracer to diagnose mixing across density surfaces. Results from these two methods will be compared and contrasted. Hofmann, M. and Maqueda, M. A. M., 2006. Performance of a second-order moments advection scheme in an ocean general circulation model. JGR-Oceans, 111(C5). Lee, M.-M., Coward, A.C., Nurser, A.G., 2002. Spurious diapycnal mixing of deep waters in an eddy-permitting global ocean model. JPO 32, 1522-1535 Megann, A., Storkey, D., Aksenov, Y., Alderson, S., Calvert, D., Graham, T., Hyder, P., Siddorn, J., and Sinha, B., 2013: GO5.0: The joint NERC-Met Office NEMO global ocean model for use in coupled and forced applications, Geosci. Model Dev. Discuss., 6, 5747-5799,.

Splitting turbulence algorithm for mixing parameterization embedded in the ocean climate model. Examples of data assimilation and Prandtl number variations.

NASA Astrophysics Data System (ADS)

Moshonkin, Sergey; Gusev, Anatoly; Zalesny, Vladimir; Diansky, Nikolay

2017-04-01

Series of experiments were performed with a three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM) using vertical grid refinement in the zone of fully developed turbulence (40 sigma-levels). The model variables are horizontal velocity components, potential temperature, and salinity as well as free surface height. For parameterization of viscosity and diffusivity, the original splitting turbulence algorithm (STA) is used when total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF) split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage the analytical solution was obtained for TKE and TDF as functions of the buoyancy and velocity shift frequencies (BF and VSF). The proposed model with STA is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. For mixing simulation in the zone of turbulence decay, the two kind numerical experiments were carried out, as with assimilation of annual mean climatic buoyancy frequency, as with variation of Prandtl number function dependence upon the BF, VSF, TKE and TDF. The CORE-II data for 1948-2009 were used for experiments. Quality of temperature T and salinity S structure simulation is estimated by the comparison of model monthly profiles T and S averaged for 1980-2009, with T and S monthly data from the World Ocean Atlas 2013. Form of coefficients in equations for TKE and TDF on the generation-dissipation stage makes it possible to assimilate annual mean climatic buoyancy frequency in a varying degree that cardinally improves adequacy of model results to climatic data in all analyzed model domain. The numerical experiments with modified Prandtl number presents possibility for essential improvement of the TKE attenuation with depth and more realistic water entrainment from pycnocline into the mixed layer. The high sensitivity is revealed of the eddy-permitting circulation stable model solution to the change of the used above mixing parameterizations. This sensitivity is connected with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, assimilation of annual mean climatic buoyancy frequency in equations for TKE and TDF leads to more realistic circulation in the North Atlantic. Variations of Prandtl number made it possible to simulate intense circulation in Beaufort Gyre owing to steric effect during the whole period under consideration. The research was supported by the Russian Foundation for Basic Research (grants №16-05-00534 and 15-05-00557).

Diffusion impact on atmospheric moisture transport

NASA Astrophysics Data System (ADS)

Moseley, C.; Haerter, J.; Göttel, H.; Hagemann, S.; Jacob, D.

2009-04-01

To ensure numerical stability, many global and regional climate models employ numerical diffusion to dampen short wavelength modes. Terrain following sigma diffusion is known to cause unphysical effects near the surface in orographically structured regions. They can be reduced by applying z-diffusion on geopotential height levels. We investigate the effect of the diffusion scheme on atmospheric moisture transport and precipitation formation at different resolutions in the European region. With respect to a better understanding of diffusion in current and future grid-space global models, current day regional models may serve as the appropriate tool for studies of the impact of diffusion schemes: Results can easily be constrained to a small test region and checked against reliable observations, which often are unavailable on a global scale. Special attention is drawn to the Alps - a region of strong topographic gradients and good observational coverage. Our study is further motivated by the appearance of the "summer drying problem" in South Eastern Europe. This too warm and too dry simulation of climate is common to many regional climate models and also to some global climate models, and remains a permanent unsolved problem in the community. We perform a systematic comparison of the two diffusion-schemes with respect to the hydrological cycle. In particular, we investigate how local meteorological quantities - such as the atmospheric moisture in the region east of the Alps - depend on the spatial model resolution. Higher model resolution would lead to a more accurate representation of the topography and entail larger gradients in the Alps. This could lead to consecutively stronger transport of moisture along the slopes in the case of sigma-diffusion with subsequent orographic precipitation, whereas the effect could be qualitatively different in the case of z-diffusion. For our study, we analyse a sequence of simulations of the regional climate model REMO employing the different diffusion methods over Europe. For these simulations, REMO was forced at the lateral boundaries with ERA40 reanalysis data for a five year period. For our higher resolution simulations we employ the double nesting technique.

Theoretical Assessment of the Impact of Climatic Factors in a Vibrio Cholerae Model.

PubMed

Kolaye, G; Damakoa, I; Bowong, S; Houe, R; Békollè, D

2018-05-04

A mathematical model for Vibrio Cholerae (V. Cholerae) in a closed environment is considered, with the aim of investigating the impact of climatic factors which exerts a direct influence on the bacterial metabolism and on the bacterial reservoir capacity. We first propose a V. Cholerae mathematical model in a closed environment. A sensitivity analysis using the eFast method was performed to show the most important parameters of the model. After, we extend this V. cholerae model by taking account climatic factors that influence the bacterial reservoir capacity. We present the theoretical analysis of the model. More precisely, we compute equilibria and study their stabilities. The stability of equilibria was investigated using the theory of periodic cooperative systems with a concave nonlinearity. Theoretical results are supported by numerical simulations which further suggest the necessity to implement sanitation campaigns of aquatic environments by using suitable products against the bacteria during the periods of growth of aquatic reservoirs.

Introduction. Pliocene climate, processes and problems

USGS Publications Warehouse

Haywood, A.M.; Dowsett, H.J.; Valdes, P.J.; Lunt, D.J.; Francis, J.E.; Sellwood, B.W.

2009-01-01

Climate predictions produced by numerical climate models, often referred to as general circulation models (GCMs), suggest that by the end of the twenty-first century global mean annual surface air temperatures will increase by 1.1-6.4??C. Trace gas records from ice cores indicate that atmospheric concentrations of CO2 are already higher than at any time during the last 650000 years. In the next 50 years, atmospheric CO2 concentrations are expected to reach a level not encountered since an epoch of time known as the Pliocene. Uniformitarianism is a key principle of geological science, but can the past also be a guide to the future? To what extent does an examination of the Pliocene geological record enable us to successfully understand and interpret this guide? How reliable are the 'retrodictions' of Pliocene climates produced by GCMs and what does this tell us about the accuracy of model predictions for the future? These questions provide the scientific rationale for this Theme Issue. ?? 2008 The Royal Society.

Comparative study on change in groundwaters of rural and urban areas in Korea: effects of climate change

NASA Astrophysics Data System (ADS)

Yun, Sang Woong; Seul Kim, Ye; Kim, Dong Hyun; Kim, Ho Chul; Shin, Min Cheol; Park, Jae Yong; Kim, Heejung; Lee, Jin-Yong

2013-04-01

Groundwater occupies a considerable proportion of the world's water resources and is affected by climate change. It is important to understand how water budget responds to future precipitation variability for sustainable management of groundwater resources. In order to evaluate the effects of climate change on groundwater resources in the future, it is necessary to not only collect field data but also predict groundwater change using some groundwater numerical modelling. In this study, a relevant climate change scenario (RCP 4.5) was adopted and Visual MODFLOW was used as a main tool for predicting water budget. The predicted precipitation and air temperature data were obtained from Climate Change Information Center (CCIC) of Korea. By using the data on the scenario from 2011 to 2100, the future water budget was calculated using groundwater numerical modelling for both Wonju (WJ: urban area) and Yanggu (YG: rural area) of Gangwon Province in Korea. The model calibration was done by the groundwater level measured at 10 monitoring wells. For the numerical prediction, the groundwater recharge (WJ: 10.1%, YG: 13.3%) was estimated using watertable fluctuation (WTF) method and a concept of threshold precipitation (WJ: 240.5 mm, YG: 363.8 mm) was applied. Consequently, the water levels in both Wonju and Yanggu showed gradually increasing trends and ranged from 3.0 to 10.8 m, from 0.5 to 1.8 m in 2100, respectively. Under annual precipitation fluctuation on the scenario (2011-2100), water budget IN-OUT value (-0.87~1.07 m3/day) in Wonju city gradually increases while that (-0.73~0.46 m3/day) of Yanggu county does not. However, its annual difference is enlarged with year for both areas. The results indicate that securing groundwater resource and its management will be difficult because of frequent annual change of the groundwater storage. This work was supported by Science High School R&E program (No. C1008804-01-01) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2012-0002628).

Numerical studies on groundwater-grassland relations in an inland arid region in China

NASA Astrophysics Data System (ADS)

Wang, J. R.; Hu, L. T.; Sun, K. N.; Liu, X. M.

2017-08-01

In this study, a 2-D numerical model was developed to assess the impacts of groundwater on grassland ecology in the Hulun Lake Basin. An extreme dry climate scenario and water resource management scenario and their interactions in the Hulun Lake Basin were designed, and their influence on groundwater was evaluated. The results show that the grassland ecology is heavily dependent on groundwater, and a distribution of groundwater with a depth of 8 m correlates well with the distribution of grassland. Under the water resource management scenario, the groundwater level will increase to a maximum value of 2.5 m after 15 years around Hulun Lake. The groundwater level will decrease dramatically under the extreme dry climate scenario, thus affecting the environment.

The new version of the Institute of Numerical Mathematics Sigma Ocean Model (INMSOM) for simulation of Global Ocean circulation and its variability

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Fomin, Vladimir; Diansky, Nikolay; Korshenko, Evgeniya

2017-04-01

In this paper, we present the improved version of the ocean general circulation sigma-model developed in the Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS). The previous version referred to as INMOM (Institute of Numerical Mathematics Ocean Model) is used as the oceanic component of the IPCC climate system model INMCM (Institute of Numerical Mathematics Climate Model (Volodin et al 2010,2013). Besides, INMOM as the only sigma-model was used for simulations according to CORE-II scenario (Danabasoglu et al. 2014,2016; Downes et al. 2015; Farneti et al. 2015). In general, INMOM results are comparable to ones of other OGCMs and were used for investigation of climatic variations in the North Atlantic (Gusev and Diansky 2014). However, detailed analysis of some CORE-II INMOM results revealed some disadvantages of the INMOM leading to considerable errors in reproducing some ocean characteristics. So, the mass transport in the Antarctic Circumpolar Current (ACC) was overestimated. As well, there were noticeable errors in reproducing thermohaline structure of the ocean. After analysing the previous results, the new version of the OGCM was developed. It was decided to entitle is INMSOM (Institute of Numerical Mathematics Sigma Ocean Model). The new title allows one to distingwish the new model, first, from its older version, and second, from another z-model developed in the INM RAS and referred to as INMIO (Institute of Numerical Mathematics and Institute of Oceanology ocean model) (Ushakov et al. 2016). There were numerous modifications in the model, some of them are as follows. 1) Formulation of the ocean circulation problem in terms of full free surface with taking into account water amount variation. 2) Using tensor form of lateral viscosity operator invariant to rotation. 3) Using isopycnal diffusion including Gent-McWilliams mixing. 4) Using atmospheric forcing computation according to NCAR methodology (Large and Yeager 2009). 5) Improvement river runoff algorithm accounting the total amount of discharged water. 6) Using explicit leapfrog time scheme for all lateral operators and implicit Euler scheme for vertical diffusion and viscosity. The INMSOM is tested by reproducing World Ocean circulation and thermohaline characteristics using the well-proved CORE dataset. The presentation is devoted to the analysis of new INMSOM simulation results, estimation of their quality and comparison to the ones previously obtained with the INMOM. The main aim of the INMSOM development is using it as the oceanic component of the next version of INMCM. The work was supported by the Russian Foundation for Basic Research (grants № 16-05-00534 and № 15-05-07539) References 1. Danabasoglu, G., Yeager S.G., Bailey D., et al., 2014: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states. Ocean Modelling, 73, 76-107. 2. Danabasoglu, G., Yeager S.G., Kim W.M. et al., 2016: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability. Ocean Modelling, 97, 65-90. 3. Downes S.M., Farneti R., Uotila P. et al. An assessment of Southern Ocean water masses and sea ice during 1988-2007 in a suite of interannual CORE-II simulations. Ocean Modelling (2015), 94, 67-94. 4. Farneti R., Downes S.M., Griffies S.M. et al. An assessment of Antarctic Circumpolar Current and Southern Ocean Meridional Overturning Circulation during 1958-2007 in a suite of interannual CORE-II simulations, Ocean Modelling (2015), 93, 84-120. 5. Gusev A.V. and Diansky N.A. Numerical simulation of the World ocean circulation and its climatic variability for 1948-2007 using the INMOM. Izvestiya, Atmospheric and Oceanic Physics, 2014, V. 50, N. 1, P. 1-12 6. Large, W., Yeager, S., 2009. The global climatology of an interannually varying air-sea flux data set. Clim Dyn, V. 33, P. 341-364. 7. Ushakov K.V., Grankina T.B., Ibraev R.A. Modeling the water circulation in the North Atlantic in the scope of the CORE-II experiment. Izvestiya, Atmospheric and Oceanic Physics. 2016. V. 52, № 4, P. 365-375

Remedying excessive numerical diapycnal mixing in a global 0.25° NEMO configuration

NASA Astrophysics Data System (ADS)

Megann, Alex; Nurser, George; Storkey, Dave

2016-04-01

If numerical ocean models are to simulate faithfully the upwelling branches of the global overturning circulation, they need to have a good representation of the diapycnal mixing processes which contribute to conversion of the bottom and deep waters produced in high latitudes into less dense watermasses. It is known that the default class of depth-coordinate ocean models such as NEMO and MOM5, as used in many state-of-the art coupled climate models and Earth System Models, have excessive numerical diapycnal mixing, resulting from irreversible advection across coordinate surfaces. The GO5.0 configuration of the NEMO ocean model, on an "eddy-permitting" 0.25° global grid, is used in the current UK GC1 and GC2 coupled models. Megann and Nurser (2016) have shown, using the isopycnal watermass analysis of Lee et al (2002), that spurious numerical mixing is substantially larger than the explicit mixing prescribed by the mixing scheme used by the model. It will be shown that increasing the biharmonic viscosity by a factor of three tends to suppress small-scale noise in the vertical velocity in the model. This significantly reduces the numerical mixing in GO5.0, and we shall show that it also leads to large-scale improvements in model biases.

What can a numerical landscape evolution model tell us about the evolution of a real landscape? Two examples of modeling a real landscape without recreating it

NASA Astrophysics Data System (ADS)

Gasparini, N. M.; Whipple, K. X.; Willenbring, J.; Crosby, B. T.; Brocard, G. Y.

2013-12-01

Numerical landscape evolution models (LEMs) offer us the unique opportunity to watch a landscape evolve under any set of environmental forcings that we can quantify. The possibilities for using LEMs are infinite, but complications arise when trying to model a real landscape. Specifically, numerical models cannot recreate every aspect of a real landscape because exact initial conditions are unknown, there will always be gaps in the known tectonic and climatic history, and the geomorphic transport laws that govern redistribution of mass due to surface processes will always be a simplified representation of the actual process. Yet, even with these constraints, numerical models remain the only tool that offers us the potential to explore a limitless range of evolutionary scenarios, allowing us to, at the very least, identify possible drivers responsible for the morphology of the current landscape, and just as importantly, rule out others. Here we highlight two examples in which we use a numerical model to explore the signature of different forcings on landscape morphology and erosion patterns. In the first landscape, the Northern Bolivian Andes, the relative imprint of rock uplift and precipitation patterns on landscape morphology is widely contested. We use the CHILD LEM to systematically vary climate and tectonics and quantify their fingerprints on channel profiles across a steep mountain front. We find that rock uplift and precipitation patterns in this landscape and others can be teased out by examining channel profiles of variably sized catchments that drain different parts of the topography. In the second landscape, the South Fork Eel River (SFER), northern California, USA, the tectonic history is relatively well known; a wave of rock uplift swept through the watershed from headwaters to outlet, perturbing the landscape and sending a wave of bedrock incision upstream. Nine millennial-scale erosion rates from along the mainstem of the river illustrate a pattern of downstream increasing erosion rate. Similarly, the proportion of the landscape that has adjusted to the tectonic perturbation increases from upstream to downstream. We use the CHILD LEM to explore whether the relationship between erosion rates and proportion of adjusted landscape is unique to the tectonic history of the SFER and if this relationship can be used as a fingerprint to identify the nature of tectonic perturbations in other locations. In both study sites, we do not try to recreate the exact morphology of the real landscape. Rather, we identify patterns in erosion rates and the morphology of the numerical landscape that can be used to interpret the tectonic history, climatic history, or both in these and other real landscapes.

Rapid Late Holocene glacier fluctuations reconstructed from South Georgia lake sediments using novel analytical and numerical techniques

NASA Astrophysics Data System (ADS)

van der Bilt, Willem; Bakke, Jostein; Werner, Johannes; Paasche, Øyvind; Rosqvist, Gunhild

2016-04-01

The collapse of ice shelves, rapidly retreating glaciers and a dramatic recent temperature increase show that Southern Ocean climate is rapidly shifting. Also, instrumental and modelling data demonstrate transient interactions between oceanic and atmospheric forcings as well as climatic teleconnections with lower-latitude regions. Yet beyond the instrumental period, a lack of proxy climate timeseries impedes our understanding of Southern Ocean climate. Also, available records often lack the resolution and chronological control required to resolve rapid climate shifts like those observed at present. Alpine glaciers are found on most Southern Ocean islands and quickly respond to shifts in climate through changes in mass balance. Attendant changes in glacier size drive variations in the production of rock flour, the suspended product of glacial erosion. This climate response may be captured by downstream distal glacier-fed lakes, continuously recording glacier history. Sediment records from such lakes are considered prime sources for paleoclimate reconstructions. Here, we present the first reconstruction of Late Holocene glacier variability from the island of South Georgia. Using a toolbox of advanced physical, geochemical (XRF) and magnetic proxies, in combination with state-of-the-art numerical techniques, we fingerprinted a glacier signal from glacier-fed lake sediments. This lacustrine sediment signal was subsequently calibrated against mapped glacier extent with the help of geomorphological moraine evidence and remote sensing techniques. The outlined approach enabled us to robustly resolve variations of a complex glacier at sub-centennial timescales, while constraining the sedimentological imprint of other geomorphic catchment processes. From a paleoclimate perspective, our reconstruction reveals a dynamic Late Holocene climate, modulated by long-term shifts in regional circulation patterns. We also find evidence for rapid medieval glacier retreat as well as a synchronous bi-polar Little Ice Age (LIA). In conclusion, our work shows the potential of novel analytical and numerical tools to improve the robustness and resolution of lake sediment-based paleoclimate reconstructions beyond the current state-of-the-art.

Advance strategy for climate change adaptation and mitigation in cities

NASA Astrophysics Data System (ADS)

Varquez, A. C. G.; Kanda, M.; Darmanto, N. S.; Sueishi, T.; Kawano, N.

2017-12-01

An on-going 5-yr project financially supported by the Ministry of Environment, Japan, has been carried out to specifically address the issue of prescribing appropriate adaptation and mitigation measures to climate change in cities. Entitled "Case Study on Mitigation and Local Adaptation to Climate Change in an Asian Megacity, Jakarta", the project's relevant objectives is to develop a research framework that can consider both urbanization and climate change with the main advantage of being readily implementable for all cities around the world. The test location is the benchmark city, Jakarta, Indonesia, with the end focus of evaluating the benefits of various mitigation and adaptation strategies in Jakarta and other megacities. The framework was designed to improve representation of urban areas when conducting climate change investigations in cities; and to be able to quantify separately the impacts of urbanization and climate change to all cities globally. It is comprised of a sophisticated, top-down, multi-downscaling approach utilizing a regional model (numerical weather model) and a microscale model (energy balance model and CFD model), with global circulation models (GCM) as input. The models, except the GCM, were configured to reasonably consider land cover, urban morphology, and anthropogenic heating (AH). Equally as important, methodologies that can collect and estimate global distribution of urban parametric and AH datasets are continually being developed. Urban growth models, climate scenario matrices that match representative concentration pathways with shared socio-economic pathways, present distribution of socio-demographic indicators such as population and GDP, existing GIS datasets of urban parameters, are utilized. From these tools, future urbanization (urban morphological parameters and AH) can be introduced into the models. Sensitivity using various combinations of GCM and urbanization can be conducted. Furthermore, since the models utilize parameters that can be readily modified to suit certain countermeasures, adaptation and mitigation strategies can be evaluated using thermal comfort and other social indicators. With the approaches introduced through this project, a deeper understanding of urban-climate interactions in the changing global climate can be achieved.

High regional climate sensitivity over continental China constrained by glacial-recent changes in temperature and the hydrological cycle.

PubMed

Eagle, Robert A; Risi, Camille; Mitchell, Jonathan L; Eiler, John M; Seibt, Ulrike; Neelin, J David; Li, Gaojun; Tripati, Aradhna K

2013-05-28

The East Asian monsoon is one of Earth's most significant climatic phenomena, and numerous paleoclimate archives have revealed that it exhibits variations on orbital and suborbital time scales. Quantitative constraints on the climate changes associated with these past variations are limited, yet are needed to constrain sensitivity of the region to changes in greenhouse gas levels. Here, we show central China is a region that experienced a much larger temperature change since the Last Glacial Maximum than typically simulated by climate models. We applied clumped isotope thermometry to carbonates from the central Chinese Loess Plateau to reconstruct temperature and water isotope shifts from the Last Glacial Maximum to present. We find a summertime temperature change of 6-7 °C that is reproduced by climate model simulations presented here. Proxy data reveal evidence for a shift to lighter isotopic composition of meteoric waters in glacial times, which is also captured by our model. Analysis of model outputs suggests that glacial cooling over continental China is significantly amplified by the influence of stationary waves, which, in turn, are enhanced by continental ice sheets. These results not only support high regional climate sensitivity in Central China but highlight the fundamental role of planetary-scale atmospheric dynamics in the sensitivity of regional climates to continental glaciation, changing greenhouse gas levels, and insolation.

Increasing risk of great floods in a changing climate

USGS Publications Warehouse

Milly, P.C.D.; Wetherald, R.T.; Dunne, K.A.; Delworth, T.L.

2002-01-01

Radiative effects of anthropogenic changes in atmospheric composition are expected to cause climate changes, in particular an intensification of the global water cycle with a consequent increase in flood risk. But the detection of anthropogenically forced changes in flooding is difficult because of the substantial natural variability; the dependence of streamflow trends on flow regime further complicates the issue. Here we investigate the changes in risk of great floods - that is, floods with discharges exceeding 100-year levels from basins larger than 200,000 km2 - using both streamflow measurements and numerical simulations of the anthropogenic climate change associated with greenhouse gases and direct radiative effects of sulphate aerosols. We find that the frequency of great floods increased substantially during the twentieth century. The recent emergence of a statistically significant positive trend in risk of great floods is consistent with results from the climate model, and the model suggests that the trend will continue.

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

NASA Astrophysics Data System (ADS)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Surface Mass Balance of the Greenland Ice Sheet Derived from Paleoclimate Reanalysis

NASA Astrophysics Data System (ADS)

Badgeley, J.; Steig, E. J.; Hakim, G. J.; Anderson, J.; Tardif, R.

2017-12-01

Modeling past ice-sheet behavior requires independent knowledge of past surface mass balance. Though models provide useful insight into ice-sheet response to climate forcing, if past climate is unknown, then ascertaining the rate and extent of past ice-sheet change is limited to geological and geophysical constraints. We use a novel data-assimilation framework developed under the Last Millennium Reanalysis Project (Hakim et al., 2016) to reconstruct past climate over ice sheets with the intent of creating an independent surface mass balance record for paleo ice-sheet modeling. Paleoclimate data assimilation combines the physics of climate models and the time series evidence of proxy records in an offline, ensemble-based approach. This framework allows for the assimilation of numerous proxy records and archive types while maintaining spatial consistency with known climate dynamics and physics captured by the models. In our reconstruction, we use the Community Climate System Model version 4, CMIP5 last millennium simulation (Taylor et al., 2012; Landrum et al., 2013) and a nearly complete database of ice core oxygen isotope records to reconstruct Holocene surface temperature and precipitation over the Greenland Ice Sheet on a decadal timescale. By applying a seasonality to this reconstruction (from the TraCE-21ka simulation; Liu et al., 2009), our reanalysis can be used in seasonally-based surface mass balance models. Here we discuss the methods behind our reanalysis and the performance of our reconstruction through prediction of unassimilated proxy records and comparison to paleoclimate reconstructions and reanalysis products.

Increasing horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea?

PubMed

Wedi, Nils P

2014-06-28

The steady path of doubling the global horizontal resolution approximately every 8 years in numerical weather prediction (NWP) at the European Centre for Medium Range Weather Forecasts may be substantially altered with emerging novel computing architectures. It coincides with the need to appropriately address and determine forecast uncertainty with increasing resolution, in particular, when convective-scale motions start to be resolved. Blunt increases in the model resolution will quickly become unaffordable and may not lead to improved NWP forecasts. Consequently, there is a need to accordingly adjust proven numerical techniques. An informed decision on the modelling strategy for harnessing exascale, massively parallel computing power thus also requires a deeper understanding of the sensitivity to uncertainty--for each part of the model--and ultimately a deeper understanding of multi-scale interactions in the atmosphere and their numerical realization in ultra-high-resolution NWP and climate simulations. This paper explores opportunities for substantial increases in the forecast efficiency by judicious adjustment of the formal accuracy or relative resolution in the spectral and physical space. One path is to reduce the formal accuracy by which the spectral transforms are computed. The other pathway explores the importance of the ratio used for the horizontal resolution in gridpoint space versus wavenumbers in spectral space. This is relevant for both high-resolution simulations as well as ensemble-based uncertainty estimation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Integrated numerical modeling of a landslide early warning system in a context of adaptation to future climatic pressures

NASA Astrophysics Data System (ADS)

Khabarov, Nikolay; Huggel, Christian; Obersteiner, Michael; Ramírez, Juan Manuel

2010-05-01

Mountain regions are typically characterized by rugged terrain which is susceptible to different types of landslides during high-intensity precipitation. Landslides account for billions of dollars of damage and many casualties, and are expected to increase in frequency in the future due to a projected increase of precipitation intensity. Early warning systems (EWS) are thought to be a primary tool for related disaster risk reduction and climate change adaptation to extreme climatic events and hydro-meteorological hazards, including landslides. An EWS for hazards such as landslides consist of different components, including environmental monitoring instruments (e.g. rainfall or flow sensors), physical or empirical process models to support decision-making (warnings, evacuation), data and voice communication, organization and logistics-related procedures, and population response. Considering this broad range, EWS are highly complex systems, and it is therefore difficult to understand the effect of the different components and changing conditions on the overall performance, ultimately being expressed as human lives saved or structural damage reduced. In this contribution we present a further development of our approach to assess a landslide EWS in an integral way, both at the system and component level. We utilize a numerical model using 6 hour rainfall data as basic input. A threshold function based on a rainfall-intensity/duration relation was applied as a decision criterion for evacuation. Damage to infrastructure and human lives was defined as a linear function of landslide magnitude, with the magnitude modelled using a power function of landslide frequency. Correct evacuation was assessed with a ‘true' reference rainfall dataset versus a dataset of artificially reduced quality imitating the observation system component. Performance of the EWS using these rainfall datasets was expressed in monetary terms (i.e. damage related to false and correct evacuation). We applied this model to a landslide EWS in Colombia that is currently being implemented within a disaster prevention project. We evaluated the EWS against rainfall data with artificially introduced error and computed with multiple model runs the probabilistic damage functions depending on rainfall error. Then we modified the original precipitation pattern to reflect possible climatic changes e.g. change in annual precipitation as well as change in precipitation intensity with annual values remaining constant. We let the EWS model adapt for changed conditions to function optimally. Our results show that for the same errors in rainfall measurements the system's performance degrades with expected changing climatic conditions. The obtained results suggest that EWS cannot internally adapt to climate change and require exogenous adaptive measures to avoid increase in overall damage. The model represents a first attempt to integrally simulate and evaluate EWS under future possible climatic pressures. Future work will concentrate on refining model components and spatially explicit climate scenarios.

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.

Tracing Multi-Scale Climate Change at Low Latitude from Glacier Shrinkage

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Kaser, G.

2009-12-01

Significant shrinkage of glaciers on top of Africa's highest mountain (Kilimanjaro, 5895 m a.s.l.) has been observed between the late 19th century and the present. Multi-year data from our automatic weather station on the largest remaining slope glacier at 5873 m allow us to force and verify a process-based distributed glacier mass balance model. This generates insights into energy and mass fluxes at the glacier-atmosphere interface, their feedbacks, and how they are linked to atmospheric conditions. By means of numerical atmospheric modeling and global climate model simulations, we explore the linkages of the local climate in Kilimanjaro's summit zone to larger-scale climate dynamics - which suggests a causal connection between Indian Ocean dynamics, mesoscale mountain circulation, and glacier mass balance. Based on this knowledge, the verified mass balance model is used for backward modeling of the steady-state glacier extent observed in the 19th century, which yields the characteristics of local climate change between that time and the present (30-45% less precipitation, 0.1-0.3 hPa less water vapor pressure, 2-4 percentage units less cloud cover at present). Our multi-scale approach provides an important contribution, from a cryospheric viewpoint, to the understanding of how large-scale climate change propagates to the tropical free troposphere. Ongoing work in this context targets the millennium-scale relation between large-scale climate and glacier behavior (by downscaling precipitation), and the possible effects of regional anthropogenic activities (land use change) on glacier mass balance.

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Volcanic effects on climate

NASA Technical Reports Server (NTRS)

Robock, Alan

1991-01-01

Volcanic eruptions which inject large amounts of sulfur-rich gas into the stratosphere produce dust veils which last years and cool the earth's surface. At the same time, these dust veils absorb enough solar radiation to warm the stratosphere. Since these temperature changes at the earth's surface and in the stratosphere are both in the opposite direction of hypothesized effects from greenhouse gases, they act to delay and mask the detection of greenhouse effects on the climate system. Tantalizing recent research results have suggested regional effects of volcanic eruptions, including effects on El Nino/Southern Oscillation (ENSO). In addition, a large portion of the global climate change of the past 100 years may be due to the effects of volcanoes, but a definite answer is not yet clear. While effects of several years were demonstrated with both data studies and numerical models, long-term effects, while found in climate model calculations, await confirmation with more realistic models. Extremely large explosive prehistoric eruptions may have produced severe weather and climate effects, sometimes called a 'volcanic winter'. Complete understanding of the above effects of volcanoes is hampered by inadequacies of data sets on volcanic dust veils and on climate change. Space observations can play an increasingly important role in an observing program in the future. The effects of volcanoes are not adequately separated from ENSO events, and climate modeling of the effects of volcanoes is in its infancy. Specific suggestions are made for future work to improve the knowledge of this important component of the climate system.

Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA

USGS Publications Warehouse

Jenni, K.; Graves, D.; Hardiman, Jill M.; Hatten, James R.; Mastin, Mark C.; Mesa, Matthew G.; Montag, J.; Nieman, Timothy; Voss, Frank D.; Maule, Alec G.

2014-01-01

Designing climate-related research so that study results will be useful to natural resource managers is a unique challenge. While decision makers increasingly recognize the need to consider climate change in their resource management plans, and climate scientists recognize the importance of providing locally-relevant climate data and projections, there often remains a gap between management needs and the information that is available or is being collected. We used decision analysis concepts to bring decision-maker and stakeholder perspectives into the applied research planning process. In 2009 we initiated a series of studies on the impacts of climate change in the Yakima River Basin (YRB) with a four-day stakeholder workshop, bringing together managers, stakeholders, and scientists to develop an integrated conceptual model of climate change and climate change impacts in the YRB. The conceptual model development highlighted areas of uncertainty that limit the understanding of the potential impacts of climate change and decision alternatives by those who will be most directly affected by those changes, and pointed to areas where additional study and engagement of stakeholders would be beneficial. The workshop and resulting conceptual model highlighted the importance of numerous different outcomes to stakeholders in the basin, including social and economic outcomes that go beyond the physical and biological outcomes typically reported in climate impacts studies. Subsequent studies addressed several of those areas of uncertainty, including changes in water temperatures, habitat quality, and bioenergetics of salmonid populations.

Climate projections of spatial variations in coastal storm surges along the Gulf of Mexico and U.S. east coast

NASA Astrophysics Data System (ADS)

Yao, Zhigang; Xue, Zuo; He, Ruoying; Bao, Xianwen; Xie, Jun; Ge, Qian

2017-02-01

Using statistically downscaled atmospheric forcing, we performed a numerical investigation to evaluate future climate's impact on storm surges along the Gulf of Mexico and U.S. east coast. The focus is on the impact of climatic changes in wind pattern and surface pressure while neglecting sea level rise and other factors. We adapted the regional ocean model system (ROMS) to the study region with a mesh grid size of 7-10 km in horizontal and 18 vertical layers. The model was validated by a hindcast of the coastal sea levels in the winter of 2008. Model's robustness was confirmed by the good agreement between model-simulated and observed sea levels at 37 tidal gages. Two 10-year forecasts, one for the IPCC Pre-Industry (PI) and the other for the A1FI scenario, were conducted. The differences in model-simulated surge heights under the two climate scenarios were analyzed. We identified three types of responses in extreme surge heights to future climate: a clear decrease in Middle Atlantic Bight, an increase in the western Gulf of Mexico, and non-significant response for the remaining area. Such spatial pattern is also consistent with previous projections of sea surface winds and ocean wave heights.

Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS

NASA Technical Reports Server (NTRS)

Pawson, Steven; Kodera, Kunihiko

2003-01-01

The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.

Reliable low precision simulations in land surface models

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

2017-12-01

Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

Controls on the Archean climate system investigated with a global climate model.

PubMed

Wolf, E T; Toon, O B

2014-03-01

The most obvious means of resolving the faint young Sun paradox is to invoke large quantities of greenhouse gases, namely, CO2 and CH4. However, numerous changes to the Archean climate system have been suggested that may have yielded additional warming, thus easing the required greenhouse gas burden. Here, we use a three-dimensional climate model to examine some of the factors that controlled Archean climate. We examine changes to Earth's rotation rate, surface albedo, cloud properties, and total atmospheric pressure following proposals from the recent literature. While the effects of increased planetary rotation rate on surface temperature are insignificant, plausible changes to the surface albedo, cloud droplet number concentrations, and atmospheric nitrogen inventory may each impart global mean warming of 3-7 K. While none of these changes present a singular solution to the faint young Sun paradox, a combination can have a large impact on climate. Global mean surface temperatures at or above 288 K could easily have been maintained throughout the entirety of the Archean if plausible changes to clouds, surface albedo, and nitrogen content occurred.

Quantifying Climate Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions

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

Schlosser, Courtney Adam; Walter-Anthony, Katey; Zhuang, Qianlai

2013-04-26

Our overall goal was to quantify the potential for threshold changes in natural emission rates of trace gases, particularly methane and carbon dioxide, from pan-arctic terrestrial systems under the spectrum of anthropogenically forced climate warming, and the extent to which these emissions provide a strong feedback mechanism to global climate warming. This goal is motivated under the premise that polar amplification of global climate warming will induce widespread thaw and degradation of the permafrost, and would thus cause substantial changes in the extent of wetlands and lakes, especially thermokarst (thaw) lakes, over the Arctic. Through a coordinated effort of fieldmore » measurements, model development, and numerical experimentation with an integrated assessment model framework, we have investigated the following hypothesis: There exists a climate-warming threshold beyond which permafrost degradation becomes widespread and thus instigates strong and/or sharp increases in methane emissions (via thermokarst lakes and wetland expansion). These would outweigh any increased uptake of carbon (e.g. from peatlands) and would result in a strong, positive feedback to global climate warming.« less

On the stability of the Atlantic meridional overturning circulation

PubMed Central

Hofmann, Matthias; Rahmstorf, Stefan

2009-01-01

One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. PMID:19897722

Simulated forecast error and climate drift resulting from the omission of the upper stratosphere in numerical models

NASA Technical Reports Server (NTRS)

Boville, Byron A.; Baumhefner, David P.

1990-01-01

Using an NCAR community climate model, Version I, the forecast error growth and the climate drift resulting from the omission of the upper stratosphere are investigated. In the experiment, the control simulation is a seasonal integration of a medium horizontal general circulation model with 30 levels extending from the surface to the upper mesosphere, while the main experiment uses an identical model, except that only the bottom 15 levels (below 10 mb) are retained. It is shown that both random and systematic errors develop rapidly in the lower stratosphere with some local propagation into the troposphere in the 10-30-day time range. The random growth rate in the troposphere in the case of the altered upper boundary was found to be slightly faster than that for the initial-condition uncertainty alone. However, this is not likely to make a significant impact in operational forecast models, because the initial-condition uncertainty is very large.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

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

2013-08-01

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

Comparison of Stream Temperature Modeling Approaches: The Case of a High Alpine Watershed in the Context of Climate Change

NASA Astrophysics Data System (ADS)

Gallice, A.

2015-12-01

Stream temperature controls important aspects of the riverine habitat, such as the rate of spawning or death of many fish species, or the concentration of numerous dissolved substances. In the current context of accelerating climate change, the future evolution of stream temperature is regarded as uncertain, particularly in the Alps. This uncertainty fostered the development of many prediction models, which are usually classified in two categories: mechanistic models and statistical models. Based on the numerical resolution of physical conservation laws, mechanistic models are generally considered to provide more reliable long-term estimates than regression models. However, despite their physical basis, these models are observed to differ quite significantly in some aspects of their implementation, notably (1) the routing of water in the river channel and (2) the estimation of the temperature of groundwater discharging into the stream. For each one of these two aspects, we considered several of the standard modeling approaches reported in the literature and implemented them in a new modular framework. The latter is based on the spatially-distributed snow model Alpine3D, which is essentially used in the framework to compute the amount of water infiltrating in the upper soil layer. Starting from there, different methods can be selected for the computation of the water and energy fluxes in the hillslopes and in the river network. We relied on this framework to compare the various methodologies for river channel routing and groundwater temperature modeling. We notably assessed the impact of each these approaches on the long-term stream temperature predictions of the model under a typical climate change scenario. The case study was conducted over a high Alpine catchment in Switzerland, whose hydrological and thermal regimes are expected to be markedly affected by climate change. The results show that the various modeling approaches lead to significant differences in the model predictions, and that these differences may be larger than the uncertainties in future air temperature. It is also shown that the temperature of groundwater discharging into the stream has a marked impact on the modeled stream temperature at the catchment outlet.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Recent Naval Postgraduate School Publications.

DTIC Science & Technology

1980-04-01

Numerical models of ocean circulation and Climate interaction Revs, of Geophis,.and Space Phys., vol. 17, no. 7, p. 1494-1507, (1 979) Haney, R 1...POSTGRADUATE SCHOOL Monterey, California DEPARTMENT OF COMPUTER SCIENCE C06FEBENCE PRESENTATIONS Bradley, G H Enerqy modelling with network optimization...Systems Analysis, Sept., 97 Bradley, G H; Brown, G G Network optimization and defense modeling Center for Nay. Analyses, Arlington, Va., Aug., 1976

Two decades of numerical modelling to understand long term fluvial archives: Advances and future perspectives

NASA Astrophysics Data System (ADS)

Veldkamp, A.; Baartman, J. E. M.; Coulthard, T. J.; Maddy, D.; Schoorl, J. M.; Storms, J. E. A.; Temme, A. J. A. M.; van Balen, R.; van De Wiel, M. J.; van Gorp, W.; Viveen, W.; Westaway, R.; Whittaker, A. C.

2017-06-01

The development and application of numerical models to investigate fluvial sedimentary archives has increased during the last decades resulting in a sustained growth in the number of scientific publications with keywords, 'fluvial models', 'fluvial process models' and 'fluvial numerical models'. In this context we compile and review the current contributions of numerical modelling to the understanding of fluvial archives. In particular, recent advances, current limitations, previous unexpected results and future perspectives are all discussed. Numerical modelling efforts have demonstrated that fluvial systems can display non-linear behaviour with often unexpected dynamics causing significant delay, amplification, attenuation or blurring of externally controlled signals in their simulated record. Numerical simulations have also demonstrated that fluvial records can be generated by intrinsic dynamics without any change in external controls. Many other model applications demonstrate that fluvial archives, specifically of large fluvial systems, can be convincingly simulated as a function of the interplay of (palaeo) landscape properties and extrinsic climate, base level and crustal controls. All discussed models can, after some calibration, produce believable matches with real world systems suggesting that equifinality - where a given end state can be reached through many different pathways starting from different initial conditions and physical assumptions - plays an important role in fluvial records and their modelling. The overall future challenge lies in the development of new methodologies for a more independent validation of system dynamics and research strategies that allow the separation of intrinsic and extrinsic record signals using combined fieldwork and modelling.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Climate Change: The Physical Basis and Latest Results

ScienceCinema

Stocker, Thomas

2018-05-18

The 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) concludes: "Warming in the climate system is unequivocal." Without the contribution of Physics to climate science over many decades, such a statement would not have been possible. Experimental physics enables us to read climate archives such as polar ice cores and so provides the context for the current changes. For example, today the concentration of CO2 in the atmosphere, the second most important greenhouse gas, is 28% higher than any time during the last 800,000 years. Classical fluid mechanics and numerical mathematics are the basis of climate models from which estimates of future climate change are obtained. But major instabilities and surprises in the Earth System are still unknown. These are also to be considered when the climatic consequences of proposals for geo-engineering are estimated. Only Physics will permit us to further improve our understanding in order to provide the foundation for policy decisions facing the global climate change challenge.

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

NASA Astrophysics Data System (ADS)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes =

NASA Astrophysics Data System (ADS)

Carvalho, David Joao da Silva

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

A new paradigm for predicting zonal-mean climate and climate change

NASA Astrophysics Data System (ADS)

Armour, K.; Roe, G.; Donohoe, A.; Siler, N.; Markle, B. R.; Liu, X.; Feldl, N.; Battisti, D. S.; Frierson, D. M.

2016-12-01

How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories. Here we present evidence that zonal-mean climate, and its changes, can be understood in terms of a moist energy balance model that represents atmospheric heat transport as a simple diffusion of latent and sensible heat (as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude). We show that the theoretical underpinnings of this model derive from the principle of maximum entropy production; that its predictions are empirically supported by atmospheric reanalyses; and that it successfully predicts the behavior of a hierarchy of climate models - from a gray radiation aquaplanet moist GCM, to comprehensive GCMs participating in CMIP5. As an example of the power of this paradigm, we show that, given only patterns of local radiative feedbacks and climate forcing, the moist energy balance model accurately predicts the evolution of zonal-mean temperature and atmospheric heat transport as simulated by the CMIP5 ensemble. These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient; this principle appears to explain zonal-mean climate and its changes under global warming.

CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind

NASA Astrophysics Data System (ADS)

Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.

2010-12-01

We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.

Impact of climate change and seasonal trends on the fate of Arctic oil spills.

PubMed

Nordam, Tor; Dunnebier, Dorien A E; Beegle-Krause, C J; Reed, Mark; Slagstad, Dag

2017-12-01

We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009-2012 and 2050-2053 (representing a warmer future) as inputs to the model. Future atmospheric forcing was based on the IPCC's A1B scenario, with the ocean data generated by the hydrodynamic model SINMOD. We found differences in "typical" outcome of a spill in a warmer future compared to the present, mainly due to a longer season of open water. We have demonstrated that ice cover is extremely important for predicting the fate of an Arctic oil spill, and find that oil spills in a warming climate will in some cases result in greater areal coverage and shoreline exposure.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

2016-08-01

The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

Development of a stream-aquifer numerical flow model to assess river water management under water scarcity in a Mediterranean basin.

PubMed

Mas-Pla, Josep; Font, Eva; Astui, Oihane; Menció, Anna; Rodríguez-Florit, Agustí; Folch, Albert; Brusi, David; Pérez-Paricio, Alfredo

2012-12-01

Stream flow, as a part of a basin hydrological cycle, will be sensible to water scarcity as a result of climate change. Stream vulnerability should then be evaluated as a key component of the basin water budget. Numerical flow modeling has been applied to an alluvial formation in a small mountain basin to evaluate the stream-aquifer relationship under these future scenarios. The Arbúcies River basin (116 km(2)) is located in the Catalan Inner Basins (NE Spain) and its lower reach, which is related to an alluvial aquifer, usually becomes dry during the summer period. This study seeks to determine the origin of such discharge losses whether from natural stream leakage and/or induced capture due to groundwater withdrawal. Our goal is also investigating how discharge variations from the basin headwaters, representing potential effects of climate change, may affect stream flow, aquifer recharge, and finally environmental preservation and human supply. A numerical flow model of the alluvial aquifer, based on MODFLOW and especially in the STREAM routine, reproduced the flow system after the usual calibration. Results indicate that, in the average, stream flow provides more than 50% of the water inputs to the alluvial aquifer, being responsible for the amount of stored water resources and for satisfying groundwater exploitation for human needs. Detailed simulations using daily time-steps permit setting threshold values for the stream flow entering at the beginning of the studied area so surface discharge is maintained along the whole watercourse and ecological flow requirements are satisfied as well. The effects of predicted rainfall and temperature variations on the Arbúcies River alluvial aquifer water balance are also discussed from the outcomes of the simulations. Finally, model results indicate the relevance of headwater discharge management under future climate scenarios to preserve downstream hydrological processes. They also point out that small mountain basins could be self-sufficient units so long as the response of the main hydrological components to external forces that produce water scarcity, as climate change or human pressures, is appropriately considered in water resource planning. Copyright © 2012 Elsevier B.V. All rights reserved.

Climate change risks and conservation implications for a threatened small-range mammal species.

PubMed

Morueta-Holme, Naia; Fløjgaard, Camilla; Svenning, Jens-Christian

2010-04-29

Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species. We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070-2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming. Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change.

Climate Change Risks and Conservation Implications for a Threatened Small-Range Mammal Species

PubMed Central

Morueta-Holme, Naia; Fløjgaard, Camilla; Svenning, Jens-Christian

2010-01-01

Background Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species. Methodology/Principal Findings We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070–2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming. Conclusions/Significance Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change. PMID:20454451

Role of Internal Variability in Surface Temperature and Precipitation Change Uncertainties over India.

NASA Astrophysics Data System (ADS)

Achutarao, K. M.; Singh, R.

2017-12-01

There are various sources of uncertainty in model projections of future climate change. These include differences in the formulation of climate models, internal variability, and differences in scenarios. Internal variability in a climate system represents the unforced change due to the chaotic nature of the climate system and is considered irreducible (Deser et al., 2012). Internal variability becomes important at regional scales where it can dominate forced changes. Therefore it needs to be carefully assessed in future projections. In this study we segregate the role of internal variability in the future temperature and precipitation projections over the Indian region. We make use of the Coupled Model Inter-comparison Project - phase 5 (CMIP5; Taylor et al., 2012) database containing climate model simulations carried out by various modeling centers around the world. While the CMIP5 experimental protocol recommended producing numerous ensemble members, only a handful of the modeling groups provided multiple realizations. Having a small number of realizations is a limitation in producing a quantification of internal variability. We therefore exploit the Community Earth System Model Large Ensemble (CESM-LE; Kay et al., 2014) dataset which contains a 40 member ensemble of a single model- CESM1 (CAM5) to explore the role of internal variability in Future Projections. Surface air temperature and precipitation change projections over regional and sub-regional scale are analyzed under the IPCC emission scenario (RCP8.5) for different seasons and homogeneous climatic zones over India. We analyze the spread in projections due to internal variability in the CESM-LE and CMIP5 datasets over these regions.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Software Testing and Verification in Climate Model Development

NASA Technical Reports Server (NTRS)

Clune, Thomas L.; Rood, RIchard B.

2011-01-01

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Numerical investigation on super-cooled large droplet icing of fan rotor blade in jet engine

NASA Astrophysics Data System (ADS)

Isobe, Keisuke; Suzuki, Masaya; Yamamoto, Makoto

2014-10-01

Icing (or ice accretion) is a phenomenon in which super-cooled water droplets impinge and accrete on a body. It is well known that ice accretion on blades and vanes leads to performance degradation and has caused severe accidents. Although various anti-icing and deicing systems have been developed, such accidents still occur. Therefore, it is important to clarify the phenomenon of ice accretion on an aircraft and in a jet engine. However, flight tests for ice accretion are very expensive, and in the wind tunnel it is difficult to reproduce all climate conditions where ice accretion can occur. Therefore, it is expected that computational fluid dynamics (CFD), which can estimate ice accretion in various climate conditions, will be a useful way to predict and understand the ice accretion phenomenon. On the other hand, although the icing caused by super-cooled large droplets (SLD) is very dangerous, the numerical method has not been established yet. This is why SLD icing is characterized by splash and bounce phenomena of droplets and they are very complex in nature. In the present study, we develop an ice accretion code considering the splash and bounce phenomena to predict SLD icing, and the code is applied to a fan rotor blade. The numerical results with and without the SLD icing model are compared. Through this study, the influence of the SLD icing model is numerically clarified.

An overview of mineral dust modeling over East Asia

NASA Astrophysics Data System (ADS)

Chen, Siyu; Huang, Jianping; Qian, Yun; Zhao, Chun; Kang, Litai; Yang, Ben; Wang, Yong; Liu, Yuzhi; Yuan, Tiangang; Wang, Tianhe; Ma, Xiaojun; Zhang, Guolong

2017-08-01

East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.

A GEOCLIM Simulation Of Climatic And Biogeochemical Consequences Of Pangea Break Up

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; Godderis, Y.; Pierrehumbert, R.; Dromart, G.; Jacob, R.

2006-12-01

Large fluctuations in continental configuration occur all along the Mesozoic times. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulation have been done given the lack of a spatially resolved climate- carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea break up. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long 4.5°lat. Seven time slices have been simulated. We show that the break up of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic, down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Ma during the Middle-Late Triassic. In the super continent case, given the relative aridity that cannot be climatically overwhelmed, the model generates high CO2 values to produce very warm continental temperatures compensating for the lack of continental humidity. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence, producing a CO2 drawdown and a fall in continental temperatures. Finally, an other unexpected outcome is the pronounced fluctuations in carbonate accumulation simulated by the model in response to the Pangea break up. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

Age, origin and evolution of Antarctic debris-covered glaciers: Implications for landscape evolution and long-term climate change

NASA Astrophysics Data System (ADS)

Mackay, Sean Leland

Antarctic debris-covered glaciers are potential archives of long-term climate change. However, the geomorphic response of these systems to climate forcing is not well understood. To address this concern, I conducted a series of field-based and numerical modeling studies in the McMurdo Dry Valleys of Antarctica (MDV), with a focus on Mullins and Friedman glaciers. I used data and results from geophysical surveys, ice-core collection and analysis, geomorphic mapping, micro-meteorological stations, and numerical-process models to (1) determine the precise origin and distribution of englacial and supraglacial debris within these buried-ice systems, (2) quantify the fundamental processes and feedbacks that govern interactions among englacial and supraglacial debris, (3) establish a process-based model to quantify the inventory of cosmogenic nuclides within englacial and supraglacial debris, and (4) isolate the governing relationships between the evolution of englacial /supraglacial debris and regional climate forcing. Results from 93 field excavations, 21 ice cores, and 24 km of ground-penetrating radar data show that Mullins and Friedman glaciers contain vast areas of clean glacier ice interspersed with inclined layers of concentrated debris. The similarity in the pattern of englacial debris bands across both glaciers, along with model results that call for negligible basal entrainment, is best explained by episodic environmental change at valley headwalls. To constrain better the timing of debris-band formation, I developed a modeling framework that tracks the accumulation of cosmogenic 3He in englacial and supraglacial debris. Results imply that ice within Mullins Glacier increases in age non-linearly from 12 ka to ˜220 ka in areas of active flow (up to >> 1.6 Ma in areas of slow-moving-to-stagnant ice) and that englacial debris bands originate with a periodicity of ˜41 ka. Modeling studies suggest that debris bands originate in synchronicity with changes in obliquity-paced, total integrated summer insolation. The implication is that the englacial structure and surface morphology of some cold-based, debris-covered glaciers can preserve high-resolution climate archives that exceed the typical resolution of Antarctic terrestrial deposits and moraine records.

Development of a 3D Soil-Plant-Atmosphere Continuum (SPAC) coupled to a Land Surface Model

NASA Astrophysics Data System (ADS)

Bisht, G.; Riley, W. J.; Lorenzetti, D.; Tang, J.

2015-12-01

Exchange of water between the atmosphere and biosphere via evapotranspiration (ET) influences global hydrological, energy, and biogeochemical cycles. Isotopic analysis has shown that evapotranspiration over the continents is largely dominated by transpiration. Water is taken up from soil by plant roots, transported through the plant's vascular system, and evaporated from the leaves. Yet current Land Surface Models (LSMs) integrated into Earth System Models (ESMs) treat plant roots as passive components. These models distribute the ET sink vertically over the soil column, neglect the vertical pressure distribution along the plant vascular system, and assume that leaves can directly access water from any soil layer within the root zone. Numerous studies have suggested that increased warming due to climate change will lead drought and heat-induced tree mortality. A more mechanistic treatment of water dynamics in the soil-plant-atmosphere continuum (SPAC) is essential for investigating the fate of ecosystems under a warmer climate. In this work, we describe a 3D SPAC model that can be coupled to a LSM. The SPAC model uses the variably saturated Richards equations to simulate water transport. The model uses individual governing equations and constitutive relationships for the various SPAC components (i.e., soil, root, and xylem). Finite volume spatial discretization and backward Euler temporal discretization is used to solve the SPAC model. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is used to numerically integrate the discretized system of equations. Furthermore, PETSc's multi-physics coupling capability (DMComposite) is used to solve the tightly coupled system of equations of the SPAC model. Numerical results are presented for multiple test problems.

Retrieval of effective cloud field parameters from radiometric data

NASA Astrophysics Data System (ADS)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

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.

Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications

USGS Publications Warehouse

Wootten, Adrienne; Smith, Kara; Boyles, Ryan; Terando, Adam; Stefanova, Lydia; Misra, Vasru; Smith, Tom; Blodgett, David L.; Semazzi, Fredrick

2014-01-01

Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several downscaled climate projections (or downscaled datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these downscaled datasets, known as downscaling, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for downscaling and the number of downscaled datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available downscaled datasets, how do these model outputs compare to each other? Which variables are available, and are certain downscaled datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these downscaled datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.

Numerical Uncertainties in the Simulation of Reversible Isentropic Processes and Entropy Conservation.

NASA Astrophysics Data System (ADS)

Johnson, Donald R.; Lenzen, Allen J.; Zapotocny, Tom H.; Schaack, Todd K.

2000-11-01

A challenge common to weather, climate, and seasonal numerical prediction is the need to simulate accurately reversible isentropic processes in combination with appropriate determination of sources/sinks of energy and entropy. Ultimately, this task includes the distribution and transport of internal, gravitational, and kinetic energies, the energies of water substances in all forms, and the related thermodynamic processes of phase changes involved with clouds, including condensation, evaporation, and precipitation processes.All of the processes noted above involve the entropies of matter, radiation, and chemical substances, conservation during transport, and/or changes in entropies by physical processes internal to the atmosphere. With respect to the entropy of matter, a means to study a model's accuracy in simulating internal hydrologic processes is to determine its capability to simulate the appropriate conservation of potential and equivalent potential temperature as surrogates of dry and moist entropy under reversible adiabatic processes in which clouds form, evaporate, and precipitate. In this study, a statistical strategy utilizing the concept of `pure error' is set forth to assess the numerical accuracies of models to simulate reversible processes during 10-day integrations of the global circulation corresponding to the global residence time of water vapor. During the integrations, the sums of squared differences between equivalent potential temperature e numerically simulated by the governing equations of mass, energy, water vapor, and cloud water and a proxy equivalent potential temperature te numerically simulated as a conservative property are monitored. Inspection of the differences of e and te in time and space and the relative frequency distribution of the differences details bias and random errors that develop from nonlinear numerical inaccuracies in the advection and transport of potential temperature and water substances within the global atmosphere.A series of nine global simulations employing various versions of Community Climate Models CCM2 and CCM3-all Eulerian spectral numerics, all semi-Lagrangian numerics, mixed Eulerian spectral, and semi-Lagrangian numerics-and the University of Wisconsin-Madison (UW) isentropic-sigma gridpoint model provides an interesting comparison of numerical accuracies in the simulation of reversibility. By day 10, large bias and random differences were identified in the simulation of reversible processes in all of the models except for the UW isentropic-sigma model. The CCM2 and CCM3 simulations yielded systematic differences that varied zonally, vertically, and temporally. Within the comparison, the UW isentropic-sigma model was superior in transporting water vapor and cloud water/ice and in simulating reversibility involving the conservation of dry and moist entropy. The only relative frequency distribution of differences that appeared optimal, in that the distribution remained unbiased and equilibrated with minimal variance as it remained statistically stationary, was the distribution from the UW isentropic-sigma model. All other distributions revealed nonstationary characteristics with spreading and/or shifting of the maxima as the biases and variances of the numerical differences of e and te amplified.

Simulated Changes in Northwest U.S. Climate in Response to Amazon Deforestation

EPA Science Inventory

Numerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of defo...

Technical Report Series on Global Modeling and Data Assimilation, Volume 43. MERRA-2; Initial Evaluation of the Climate

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Bosilovich, Michael G.; Akella, Santha; Lawrence, Coy; Cullather, Richard; Draper, Clara; Gelaro, Ronald; Kovach, Robin; Liu, Qing; Molod, Andrea;

Can we trust climate models to realistically represent severe European windstorms?

NASA Astrophysics Data System (ADS)

Trzeciak, Tomasz M.; Knippertz, Peter; Owen, Jennifer S. R.

2014-05-01

Despite the enormous advances made in climate change research, robust projections of the position and the strength of the North Atlantic stormtrack are not yet possible. In particular with respect to damaging windstorms, this incertitude bears enormous risks to European societies and the (re)insurance industry. Previous studies have addressed the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data and found that there is large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such statistical evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms. Compensating effects between the two might conceal errors and suggest higher reliability than there really is. A possible way to separate influences of fast and slow processes in climate projections is through a "seamless" approach of hindcasting historical, severe storms with climate models started from predefined initial conditions and run in a numerical weather prediction mode on the time scale of several days. Such a cost-effective case-study approach, which draws from and expands on the concepts from the Transpose-AMIP initiative, has recently been undertaken in the SEAMSEW project at the University of Leeds funded by the AXA Research Fund. Key results from this work focusing on 20 historical storms and using different lead times and horizontal and vertical resolutions include: (a) Tracks are represented reasonably well by most hindcasts. (b) Sensitivity to vertical resolution is low. (c) There is a systematic underprediction of cyclone depth for a coarse resolution of T63, but surprisingly no systematic bias is found for higher-resolution runs using T127, showing that climate models are in fact able to represent the storm dynamics well, if given the correct initial conditions. Combined with a too low number of deep cyclones in many climate models, this points too an insufficient number of storm-prone initial conditions in free-running climate runs. This question will be addressed in future work.

Mixing parametrizations for ocean climate modelling

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir

2016-04-01

The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model. The high sensitivity of the eddy-permitting circulation model to the definition of mixing is revealed, which is associated with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, usage of the turbulence parameterization instead of PP algorithm leads to increasing circulation velocity in the Gulf Stream and North Atlantic Current, as well as the subpolar cyclonic gyre in the North Atlantic and Beaufort Gyre in the Arctic basin are reproduced more realistically. Consideration of the Prandtl number as a function of the Richardson number significantly increases the modelling quality. The research was supported by the Russian Foundation for Basic Research (grant № 16-05-00534) and the Council on the Russian Federation President Grants (grant № MK-3241.2015.5)

A GEOCLIM simulation of climatic and biogeochemical consequences of Pangea breakup

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; GoddéRis, Y.; Pierrehumbert, R.; Dromart, G.; Fluteau, F.; Jacob, R.

2006-11-01

Large fluctuations in continental configuration occur throughout the Mesozoic. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulations have been done, because of the lack of a spatially resolved climate-carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea breakup. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long × 4.5°lat. Seven time slices have been simulated. We show that the breakup of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in global mean annual continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Myr during the Middle-Late Triassic. In the super continent case, given the persistent aridity, the model generates high CO2 values to produce very warm continental temperatures. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence producing a CO2 drawdown and a fall in continental temperatures. Finally, another unexpected outcome is the pronounced fluctuation in carbonate accumulation simulated by the model in response to the Pangea breakup. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

Assessing the Global Climate Response to Freshwater Forcing from the Antarctic Ice Sheet Under Future Climate Scenarios

NASA Astrophysics Data System (ADS)

Rogstad, S.; Condron, A.; DeConto, R.; Pollard, D.

2017-12-01

Observational evidence indicates that the West Antarctic Ice Sheet (WAIS) is losing mass at an accelerating rate. Impacts to global climate resulting from changing ocean circulation patterns due to increased freshwater runoff from Antarctica in the future could have significant implications for global heat transport, but to-date this topic has not been investigated using complex numerical models with realistic freshwater forcing. Here, we present results from a high resolution fully coupled ocean-atmosphere model (CESM 1.2) forced with runoff from Antarctica prescribed from a high resolution regional ice sheet-ice shelf model. Results from the regional simulations indicate a potential freshwater contribution from Antarctica of up to 1 m equivalent sea level rise by the end of the century under RCP 8.5 indicating that a substantial input of freshwater into the Southern Ocean is possible. Our high resolution global simulations were performed under IPCC future climate scenarios RCP 4.5 and 8.5. We will present results showing the impact of WAIS collapse on global ocean circulation, sea ice, air temperature, and salinity in order to assess the potential for abrupt climate change triggered by WAIS collapse.

Indicators of Arctic Sea Ice Bistability in Climate Model Simulations and Observations

DTIC Science & Technology

2014-09-30

ultimately developed a novel mathematical method to solve the system of equations involving the addition of a numerical “ ghost ” layer, as described in the...balance models ( EBMs ) and (ii) seasonally-varying single-column models (SCMs). As described in Approach item #1, we developed an idealized model that...includes both latitudinal and seasonal variations (Fig. 1). The model reduces to a standard EBM or SCM as limiting cases in the parameter space, thus

Using Virtualization to Integrate Weather, Climate, and Coastal Science Education

NASA Astrophysics Data System (ADS)

Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a single ready-to-use package. Thus, the previous ornery task of setting up and compiling these tools becomes obsolete and the research, educator or student can focus on using the tools to study the interactions between weather, climate and the coastal environment. The incorporation of WRF into the CSEVA has been designed to be synergistic with the extensive online tutorials and biannual tutorials hosted by NCAR. Included are working examples of the idealized test simulations provided with WRF (2D sea breeze and squalls, a large eddy simulation, a Held and Suarez simulation, etc.) To demonstrate the integration of weather, coastal and coastal science education, example applications are being developed to demonstrate how the system can be used to couple a coastal and estuarine circulation, transport and storm surge model with downscale reanalysis weather and future climate predictions. Documentation, tutorials and the enhanced CSEVA itself will be found on the web at: http://cseva.coastal.ufl.edu.

Influence of land-surface evapotranspiration on the earth's climate

NASA Technical Reports Server (NTRS)

Shukla, J.; Mintz, Y.

1982-01-01

Land-surface evapotranspiration is shown to strongly influence global fields of rainfall, temperature and motion by calculations using a numerical model of the atmosphere, confirming the general belief in the importance of evapotranspiration-producing surface vegetation for the earth's climate. The current version of the Goddard Laboratory atmospheric general circulation model is used in the present experiment, in which conservation equations for mass, momentum, moisture and energy are expressed in finite-difference form for a spherical grid to calculate (1) surface pressure field evolution, and (2) the wind, temperature, and water vapor fields at nine levels between the surface and a 20 km height.

The Martian climate: Energy balance models with CO2/H2O atmospheres

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1985-01-01

Coupled equations are developed for mass and heat transport in a seasonal Mars model with condensation and sublimation of CO2 at the polar caps. Topics covered include physical considerations of planetary as mass and energy balance; effects of phase changes at the surface on mass and heat flux; atmospheric transport and governing equations; and numerical analysis.

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

2007-01-01

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

PubMed

Edlund, Stefan; Davis, Matthew; Douglas, Judith V; Kershenbaum, Arik; Waraporn, Narongrit; Lessler, Justin; Kaufman, James H

2012-09-18

The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence) built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data). The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation's Spatiotemporal Epidemiological Modeller (STEM). Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS) error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166-2 national subdivisions and with monthly time sampling. The high spatial resolution possible with state-of-the-art numerical models can identify regions most likely to require intervention due to climate changes. Higher-resolution surveillance data can provide a better understanding of how climate fluctuations affect malaria incidence and improve predictions. An open-source modelling framework, such as STEM, can be a valuable tool for the scientific community and provide a collaborative platform for developing such models.

Can we trust climate models to realistically represent severe European windstorms?

NASA Astrophysics Data System (ADS)

Trzeciak, Tomasz M.; Knippertz, Peter; Pirret, Jennifer S. R.; Williams, Keith D.

2016-06-01

Cyclonic windstorms are one of the most important natural hazards for Europe, but robust climate projections of the position and the strength of the North Atlantic storm track are not yet possible, bearing significant risks to European societies and the (re)insurance industry. Previous studies addressing the problem of climate model uncertainty through statistical comparisons of simulations of the current climate with (re-)analysis data show large disagreement between different climate models, different ensemble members of the same model and observed climatologies of intense cyclones. One weakness of such evaluations lies in the difficulty to separate influences of the climate model's basic state from the influence of fast processes on the development of the most intense storms, which could create compensating effects and therefore suggest higher reliability than there really is. This work aims to shed new light into this problem through a cost-effective "seamless" approach of hindcasting 20 historical severe storms with the two global climate models, ECHAM6 and GA4 configuration of the Met Office Unified Model, run in a numerical weather prediction mode using different lead times, and horizontal and vertical resolutions. These runs are then compared to re-analysis data. The main conclusions from this work are: (a) objectively identified cyclone tracks are represented satisfactorily by most hindcasts; (b) sensitivity to vertical resolution is low; (c) cyclone depth is systematically under-predicted for a coarse resolution of T63 by both climate models; (d) no systematic bias is found for the higher resolution of T127 out to about three days, demonstrating that climate models are in fact able to represent the complex dynamics of explosively deepening cyclones well, if given the correct initial conditions; (e) an analysis using a recently developed diagnostic tool based on the surface pressure tendency equation points to too weak diabatic processes, mainly latent heating, as the main source for the under-prediction in the coarse-resolution runs. Finally, an interesting implication of these results is that the too low number of deep cyclones in many free-running climate simulations may therefore be related to an insufficient number of storm-prone initial conditions. This question will be addressed in future work.

The InterFrost benchmark of Thermo-Hydraulic codes for cold regions hydrology - first inter-comparison results

NASA Astrophysics Data System (ADS)

Grenier, Christophe; Roux, Nicolas; Anbergen, Hauke; Collier, Nathaniel; Costard, Francois; Ferrry, Michel; Frampton, Andrew; Frederick, Jennifer; Holmen, Johan; Jost, Anne; Kokh, Samuel; Kurylyk, Barret; McKenzie, Jeffrey; Molson, John; Orgogozo, Laurent; Rivière, Agnès; Rühaak, Wolfram; Selroos, Jan-Olof; Therrien, René; Vidstrand, Patrik

2015-04-01

The impacts of climate change in boreal regions has received considerable attention recently due to the warming trends that have been experienced in recent decades and are expected to intensify in the future. Large portions of these regions, corresponding to permafrost areas, are covered by water bodies (lakes, rivers) that interact with the surrounding permafrost. For example, the thermal state of the surrounding soil influences the energy and water budget of the surface water bodies. Also, these water bodies generate taliks (unfrozen zones below) that disturb the thermal regimes of permafrost and may play a key role in the context of climate change. Recent field studies and modeling exercises indicate that a fully coupled 2D or 3D Thermo-Hydraulic (TH) approach is required to understand and model the past and future evolution of landscapes, rivers, lakes and associated groundwater systems in a changing climate. However, there is presently a paucity of 3D numerical studies of permafrost thaw and associated hydrological changes, and the lack of study can be partly attributed to the difficulty in verifying multi-dimensional results produced by numerical models. Numerical approaches can only be validated against analytical solutions for a purely thermic 1D equation with phase change (e.g. Neumann, Lunardini). When it comes to the coupled TH system (coupling two highly non-linear equations), the only possible approach is to compare the results from different codes to provided test cases and/or to have controlled experiments for validation. Such inter-code comparisons can propel discussions to try to improve code performances. A benchmark exercise was initialized in 2014 with a kick-off meeting in Paris in November. Participants from USA, Canada, Germany, Sweden and France convened, representing altogether 13 simulation codes. The benchmark exercises consist of several test cases inspired by existing literature (e.g. McKenzie et al., 2007) as well as new ones. They range from simpler, purely thermal cases (benchmark T1) to more complex, coupled 2D TH cases (benchmarks TH1, TH2, and TH3). Some experimental cases conducted in cold room complement the validation approach. A web site hosted by LSCE (Laboratoire des Sciences du Climat et de l'Environnement) is an interaction platform for the participants and hosts the test cases database at the following address: https://wiki.lsce.ipsl.fr/interfrost. The results of the first stage of the benchmark exercise will be presented. We will mainly focus on the inter-comparison of participant results for the coupled cases (TH1, TH2 & TH3). Further perspectives of the exercise will also be presented. Extensions to more complex physical conditions (e.g. unsaturated conditions and geometrical deformations) are contemplated. In addition, 1D vertical cases of interest to the Climate Modeling community will be proposed. Keywords: Permafrost; Numerical modeling; River-soil interaction; Arctic systems; soil freeze-thaw

Biological production models as elements of coupled, atmosphere-ocean models for climate research

NASA Technical Reports Server (NTRS)

Platt, Trevor; Sathyendranath, Shubha

1991-01-01

Process models of phytoplankton production are discussed with respect to their suitability for incorporation into global-scale numerical ocean circulation models. Exact solutions are given for integrals over the mixed layer and the day of analytic, wavelength-independent models of primary production. Within this class of model, the bias incurred by using a triangular approximation (rather than a sinusoidal one) to the variation of surface irradiance through the day is computed. Efficient computation algorithms are given for the nonspectral models. More exact calculations require a spectrally sensitive treatment. Such models exist but must be integrated numerically over depth and time. For these integrations, resolution in wavelength, depth, and time are considered and recommendations made for efficient computation. The extrapolation of the one-(spatial)-dimension treatment to large horizontal scale is discussed.

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

NASA Astrophysics Data System (ADS)

De La Chevrotière, Michèle; Khouider, Boualem

2017-02-01

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

Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)

NASA Astrophysics Data System (ADS)

Dethloff, Klaus; Rex, Markus; Shupe, Matthew

2016-04-01

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) is an international initiative under the International Arctic Science Committee (IASC) umbrella that aims to improve numerical model representations of sea ice, weather, and climate processes through coupled system observations and modeling activities that link the central Arctic atmosphere, sea ice, ocean, and the ecosystem. Observations of many critical parameters such as cloud properties, surface energy fluxes, atmospheric aerosols, small-scale sea-ice and oceanic processes, biological feedbacks with the sea-ice ice and ocean, and others have never been made in the central Arctic in all seasons, and certainly not in a coupled system fashion. The primary objective of MOSAiC is to develop a better understanding of these important coupled-system processes so they can be more accurately represented in regional- and global-scale weather- and climate models. Such enhancements will contribute to improved modeling of global climate and weather, and Arctic sea-ice predictive capabilities. The MOSAiC observations are an important opportunity to gather the high quality and comprehensive observations needed to improve numerical modeling of critical, scale-dependent processes impacting Arctic predictability given diminished sea ice coverage and increased model complexity. Model improvements are needed to understand the effects of a changing Arctic on mid-latitude weather and climate. MOSAiC is specifically designed to provide the multi-parameter, coordinated observations needed to improve sub-grid scale model parameterizations especially with respect to thinner ice conditions. To facilitate, evaluate, and develop the needed model improvements, MOSAiC will employ a hierarchy of modeling approaches ranging from process model studies, to regional climate model intercomparisons, to operational forecasts and assimilation of real-time observations. Model evaluations prior to the field program will be used to identify specific gaps and parameterization needs. Preliminary modeling and operational forecasting will also be necessary to directly guide field planning and optimal implementation of field resources, and to support the safety of the project. The MOSAiC Observatory will be deployed in, and drift with, the Arctic sea-ice pack for at least a full annual cycle, starting in fall 2019 and ending in autumn 2020. Initial plans are for the drift to start in the newly forming autumn sea-ice in, or near, the East Siberian Sea. The specific location will be selected to allow for the observatory to follow the Transpolar Drift towards the North Pole and on to the Fram Strait. IASC has adopted MOSAiC as a key international activity, the German Alfred Wegener Institute has made the huge contribution of the icebreaker Polarstern to serve as the central drifting observatory for this year long endeavor, and the US Department of Energy has committed a comprehensive atmospheric measurement suite. Many other nations and agencies have expressed interest in participation and in gaining access to this unprecedented observational dataset. International coordination is needed to support this groundbreaking endeavor.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

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.

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

NASA Technical Reports Server (NTRS)

Seaman, Nelson L.; Stauffer, David R.; Munoz, Ricardo C.

2001-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

Fluctuations of a Greenlandic tidewater glacier driven by changes in atmospheric forcing: observations and modelling of Kangiata Nunaata Sermia, 1859-present

NASA Astrophysics Data System (ADS)

Lea, J. M.; Mair, D. W. F.; Nick, F. M.; Rea, B. R.; van As, D.; Morlighem, M.; Nienow, P. W.; Weidick, A.

2014-11-01

Many tidewater glaciers in Greenland are known to have undergone significant retreat during the last century following their Little Ice Age maxima. Where it is possible to reconstruct glacier change over this period, they provide excellent records for comparison to climate records, as well as calibration/validation for numerical models. These glacier change records therefore allow for tests of numerical models that seek to simulate tidewater glacier behaviour over multi-decadal to centennial timescales. Here we present a detailed record of behaviour from Kangiata Nunaata Sermia (KNS), SW Greenland, between 1859 and 2012, and compare it against available oceanographic and atmospheric temperature data between 1871 and 2012. We also use these records to evaluate the ability of a well-established one-dimensional flow-band model to replicate behaviour for the observation period. The record of terminus change demonstrates that KNS has advanced/retreated in phase with atmosphere and ocean climate anomalies averaged over multi-annual to decadal timescales. Results from an ensemble of model runs demonstrate that observed dynamics can be replicated. Model runs that provide a reasonable match to observations always require a significant atmospheric forcing component, but do not necessarily require an oceanic forcing component. Although the importance of oceanic forcing cannot be discounted, these results demonstrate that changes in atmospheric forcing are likely to be a primary driver of the terminus fluctuations of KNS from 1859 to 2012. We propose that the detail and length of the record presented makes KNS an ideal site for model validation exercises investigating links between climate, calving rates, and tidewater glacier dynamics.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

Binational climate change vulnerability assessment of migratory birds in the Great Lakes Basins: Tools and impediments.

PubMed

Rempel, Robert S; Hornseth, Megan L

2017-01-01

Climate change is a global concern, requiring international strategies to reduce emissions, however, climate change vulnerability assessments are often local in scope with assessment areas restricted to jurisdictional boundaries. In our study we explored tools and impediments to understanding and responding to the effects of climate change on vulnerability of migratory birds from a binational perspective. We apply and assess the utility of a Climate Change Vulnerability Index on 3 focal species using distribution or niche modeling frameworks. We use the distributional forecasts to explore possible changes to jurisdictional conservation responsibilities resulting from shifting distributions for: eastern meadowlark (Sturnella magna), wood thrush (Hylocichla mustelina), and hooded warbler (Setophaga citrina). We found the Climate Change Vulnerability Index to be a well-organized approach to integrating numerous lines of evidence concerning effects of climate change, and provided transparency to the final assessment of vulnerability. Under this framework, we identified that eastern meadowlark and wood thrush are highly vulnerable to climate change, but hooded warbler is less vulnerable. Our study revealed impediments to assessing and modeling vulnerability to climate change from a binational perspective, including gaps in data or modeling for climate exposure parameters. We recommend increased cross-border collaboration to enhance the availability and resources needed to improve vulnerability assessments and development of conservation strategies. We did not find evidence to suggest major shifts in jurisdictional responsibility for the 3 focal species, but results do indicate increasing responsibility for these birds in the Canadian Provinces. These Provinces should consider conservation planning to help ensure a future supply of necessary habitat for these species.

Binational climate change vulnerability assessment of migratory birds in the Great Lakes Basins: Tools and impediments

PubMed Central

2017-01-01

Climate change is a global concern, requiring international strategies to reduce emissions, however, climate change vulnerability assessments are often local in scope with assessment areas restricted to jurisdictional boundaries. In our study we explored tools and impediments to understanding and responding to the effects of climate change on vulnerability of migratory birds from a binational perspective. We apply and assess the utility of a Climate Change Vulnerability Index on 3 focal species using distribution or niche modeling frameworks. We use the distributional forecasts to explore possible changes to jurisdictional conservation responsibilities resulting from shifting distributions for: eastern meadowlark (Sturnella magna), wood thrush (Hylocichla mustelina), and hooded warbler (Setophaga citrina). We found the Climate Change Vulnerability Index to be a well-organized approach to integrating numerous lines of evidence concerning effects of climate change, and provided transparency to the final assessment of vulnerability. Under this framework, we identified that eastern meadowlark and wood thrush are highly vulnerable to climate change, but hooded warbler is less vulnerable. Our study revealed impediments to assessing and modeling vulnerability to climate change from a binational perspective, including gaps in data or modeling for climate exposure parameters. We recommend increased cross-border collaboration to enhance the availability and resources needed to improve vulnerability assessments and development of conservation strategies. We did not find evidence to suggest major shifts in jurisdictional responsibility for the 3 focal species, but results do indicate increasing responsibility for these birds in the Canadian Provinces. These Provinces should consider conservation planning to help ensure a future supply of necessary habitat for these species. PMID:28225817

A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

NASA Astrophysics Data System (ADS)

Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

2013-04-01

Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at 110 coastal locations along the French coast. The model, based on the BAJ parameterization of the source terms (Bidlot et al, 2007) was calibrated against ten years of GlobWave altimeter observations (2000-2009) and validated through deep and shallow water buoy observations. The dynamical downscaling method has been performed with the same numerical wave model TOMAWAC used for building ANEMOC-2. Forecast simulations are forced by the 10m wind fields of ARPEGE-CLIMAT (A1B, A2, B1) from 2010 to 2100. The model covers the Atlantic Ocean and uses a spatial resolution along the French and European coast of 10 and 20 km respectively. The results of the model are stored with a time resolution of one hour. References: Benoit M., Marcos F., and F. Becq, (1996). Development of a third generation shallow-water wave model with unstructured spatial meshing. Proc. 25th Int. Conf. on Coastal Eng., (ICCE'1996), Orlando (Florida, USA), pp 465-478. Bidlot J-R, Janssen P. and Adballa S., (2007). A revised formulation of ocean wave dissipation and its model impact, technical memorandum ECMWF n°509. Menendez, M., Mendez, F.J., Izaguirre,C., Camus, P., Espejo, A., Canovas, V., Minguez, R., Losada, I.J., Medina, R. (2011). Statistical Downscaling of Multivariate Wave Climate Using a Weather Type Approach, 12th International Workshop on Wave Hindcasting and Forecasting and 3rd Coastal Hazard Symposium, Kona (Hawaii).

Assessing climate-sensitive ecosystems in the southeastern United States

USGS Publications Warehouse

Costanza, Jennifer; Beck, Scott; Pyne, Milo; Terando, Adam; Rubino, Matthew J.; White, Rickie; Collazo, Jaime

2016-08-11

Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects.Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.

Numerical Weather Prediction Models on Linux Boxes as tools in meteorological education in Hungary

NASA Astrophysics Data System (ADS)

Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.

2012-04-01

Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree (BSc, MSc and PhD). The three year long base BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. BasicsFundamentals in Mathematics (Calculus), Physics (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at our the Eötvös Loránd uUniversity in the our country. Our aim is to give a basic education in all fields of Meteorology. Main topics are: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, modeling Modeling of surfaceSurface-atmosphere Iinteractions and Cclimate change. Education is performed in two branches: Climate Researcher and Forecaster. Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree. The three year long BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. Fundamentals in Mathematics (Calculus), (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at the Eötvös Loránd University in our country. Our aim is to give a basic education in all fields of Meteorology: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, Modeling of Surface-atmosphere Interactions and Climate change. Education is performed in two branches: Climate Researcher and Forecaster. Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the computer resources needed for the integration of both WRF and ALADIN/CHAPEAU models will be briefly described. The software developments performed for the evaluation and comparison of the different modeling systems will be demonstrated. The main objectives of the education program on the practical numerical weather modeling will be introduced, as well as its detailed thematics and the structure of the labs.

Hygrothermal behavior for a clay brick wall

NASA Astrophysics Data System (ADS)

Allam, R.; Issaadi, N.; Belarbi, R.; El-Meligy, M.; Altahrany, A.

2018-06-01

In Egypt, the clay brick is the common building materials which are used. By studying clay brick walls behavior for the heat and moisture transfer, the efficient use of the clay brick can be reached. So, this research studies the hygrothermal transfer in this material by measuring the hygrothermal properties and performing experimental tests for a constructed clay brick wall. We present the model for the hygrothermal transfer in the clay brick which takes the temperature and the vapor pressure as driving potentials. In addition, this research compares the presented model with previous models. By constructing the clay brick wall between two climates chambers with different boundary conditions, we can validate the numerical model and analyze the hygrothermal transfer in the wall. The temperature and relative humidity profiles within the material are measured experimentally and determined numerically. The numerical and experimental results have a good convergence with 3.5% difference. The surface boundary conditions, the ground effect, the infiltration from the closed chambers and the material heterogeneity affects the results. Thermal transfer of the clay brick walls reaches the steady state very rapidly than the moisture transfer. That means the effect of using only the external brick wall in the building in hot climate without increase the thermal resistance for the wall, will add more energy losses in the clay brick walls buildings. Also, the behavior of the wall at the heat and mass transfer calls the three-dimensional analysis for the whole building to reach the real behavior.

Hygrothermal behavior for a clay brick wall

NASA Astrophysics Data System (ADS)

Allam, R.; Issaadi, N.; Belarbi, R.; El-Meligy, M.; Altahrany, A.

2018-01-01

In Egypt, the clay brick is the common building materials which are used. By studying clay brick walls behavior for the heat and moisture transfer, the efficient use of the clay brick can be reached. So, this research studies the hygrothermal transfer in this material by measuring the hygrothermal properties and performing experimental tests for a constructed clay brick wall. We present the model for the hygrothermal transfer in the clay brick which takes the temperature and the vapor pressure as driving potentials. In addition, this research compares the presented model with previous models. By constructing the clay brick wall between two climates chambers with different boundary conditions, we can validate the numerical model and analyze the hygrothermal transfer in the wall. The temperature and relative humidity profiles within the material are measured experimentally and determined numerically. The numerical and experimental results have a good convergence with 3.5% difference. The surface boundary conditions, the ground effect, the infiltration from the closed chambers and the material heterogeneity affects the results. Thermal transfer of the clay brick walls reaches the steady state very rapidly than the moisture transfer. That means the effect of using only the external brick wall in the building in hot climate without increase the thermal resistance for the wall, will add more energy losses in the clay brick walls buildings. Also, the behavior of the wall at the heat and mass transfer calls the three-dimensional analysis for the whole building to reach the real behavior.

Projected 21st century coastal flooding in the Southern California Bight. Part 1: Development of the third generation CoSMoS model

USGS Publications Warehouse

O'Neill, Andrea; Erikson, Li; Barnard, Patrick; Limber, Patrick; Vitousek, Sean; Warrick, Jonathan; Foxgrover, Amy C.; Lovering, Jessica

2018-01-01

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the sustainability of coastal communities, development, and ecosystems as we know them today. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies due to projected increased levels of coastal flooding and erosion, coastal managers need local-scale hazards projections using the best available climate and coastal science. In collaboration with leading scientists world-wide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea-level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections in a thorough and comprehensive numerical modeling framework. In Part 1 of a two-part submission on CoSMoS, methods and the latest improvements are discussed, and an example of hazard projections is presented.

Predicted effects of climate change on northern Gulf of Mexico hypoxia

EPA Science Inventory

U.S. state and federal partners are working cooperatively to develop nutrient management strategies to reduce hypoxia (O2 < 63 mmol m-3) in the northern Gulf of Mexico. Numerical models that represent eutrophication and hypoxia development processes have been an important too...

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.

On procedures for model selection in providing climate scenario data for impact studies - A challenge to both communities

NASA Astrophysics Data System (ADS)

Fox Maule, Cathrine; Sloth Madsen, Marianne; May, Wilhelm; Hesselbjerg Christensen, Jens; Yang, Shuting; Christensen, Ole B.

2015-04-01

Climate impact studies are based on climate simulations originating from regional or global climate models, provided either through the climate modeling centers directly or through climate data portals. In order to give the most beneficial results, the climate model data need to fulfill various requirements related to the respective impact models. These requirements, however, are often not well defined and subjected to individual impact models, and hence, can lead to discrepancies between the climate data provided by the climate modeling community and the data required by the impact models. As the climate model data are the first step in a process chain, limitations and problems with these data will affect the studies based on the results by the impact models and, hence, might confine the value of a project working with these results. DMI has over the past years provided climate scenario data for impact studies in several international and national research projects, including ENSEMBLES, WATCH, CRES and HYACINTS as well as the still ongoing projects IMPRESSIONS, IMPACT2C and MODEXTREME, dealing with numerous different impact sectors. Thus DMI has gained experience with a wide range of projects from very different disciplines including agriculture, hydrology, socio-economics, air-pollution and sea-level rise. The lessons learned from all these projects is that there is no standard procedure that can be implemented, but rather that individual solutions have to be constructed on a case-by-case basis for each project. This is due to the fact that the requirements for different impact models differ. For example, some impact models may need monthly input data, while others need daily data. Some need very high horizontal resolution while others may make do with relatively coarse resolution; some operate on global scale while others focus on regional or local scale. Some models need only a few variables as e.g. precipitation and temperature, while others also require e.g. radiation and evaporation. All of these requirements - and many more - shape the outcome of each individual project. Here, we highlight some of the procedures developed in some of the projects we have been involved in, and reason why the given steps were taken in those projects; focus is on MODEXTREME and IMPRESSIONS. We also point out some of the limiting factors that arise in concrete cases, often due to lack of useful observations or simulations. To conclude, we suggest a flow chart for decision as guidance to ease the procedure of providing suitable climate model output data for impact studies in future projects.

Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events

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

Chang, Ping

Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less

Modeling of Long-Term Evolution of Hydrophysical Fields of the Black Sea

NASA Astrophysics Data System (ADS)

Dorofeyev, V. L.; Sukhikh, L. I.

2017-11-01

The long-term evolution of the Black Sea dynamics (1980-2020) is reconstructed by numerical simulation. The model of the Black Sea circulation has 4.8 km horizontal spatial resolution and 40 levels in z-coordinates. The mixing processes in the upper layer are parameterized by Mellor-Yamada turbulent model. For the sea surface boundary conditions, atmospheric forcing functions were used, provided for the Black Sea region by the Euro mediterranean Center on Climate Change (CMCC) from the COSMO-CLM regional climate model. These data have a spatial resolution of 14 km and a daily temporal resolution. To evaluate the quality of the hydrodynamic fields derived from the simulation, they were compared with in-situ hydrological measurements and similar results from physical reanalysis of the Black Sea.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Investigating the Geomorphic Behavior of the Cape Canaveral Coast Through High-Resolution Beach Monitoring, Sediment Analysis, Oceanographic Observations, and Numerical Modeling

NASA Astrophysics Data System (ADS)

Adams, P. N.; Jaeger, J. M.; MacKenzie, R. A.; Kline, S. W.; Maibauer, B. J.; Plant, N. G.; Gravens, M. B.; Pierro, T. P.; Shaffer, J.

2011-12-01

The salient of Cape Canaveral interrupts a relatively straight, sandy, passive margin coastline that extends nearly 400 km from the St. Johns River mouth to the St. Lucie Inlet along the Florida Atlantic coast. OSL dating indicates that the modern cape has been prograding rapidly since the LGM and subtle topographic features, inland from the modern cape, suggest that this salient has persisted over several sea level cycles since the early Pleistocene. Dynamic shoreline change over the past decade at the Kennedy Space Center (KSC) is threatening critical NASA infrastructure and has prompted officials to develop a mitigation strategy through a partnership among researchers from the U.S. Geological Survey, the U.S. Army Corps of Engineers, private coastal engineering firms, and the University of Florida. Since May 2009, the research team has assembled data on decadal to event-scale shoreline change (dGPS), beach and nearshore morphodynamics (dGPS and Argus), beach sedimentary character (grain size analysis), wave climate and transformation (ADCP), and inner shelf bathymetry (Echo Sounding) in an effort to assess dune vulnerability and flooding risk. In addition, SWAN numerical modeling simulations offer insight into the influence of irregular bathymetry (cape-associated shoals) on the alteration of spatial patterns of wave energy flux during a decadal shift in deep-water wave climate. Beach-fx, modeling of cross-shore profile evolution is being applied to evaluate the performance of alternative protective measures, estimate project costs, and examine ecological influences of the proposed alternative protective measures. By combining contemporaneous data of coastal geomorphic and sedimentary response to wave forcing with numerical model results that explore a range of climate scenarios, we aim to develop a useful understanding of the coastal geomorphic behavior at KSC that can be used to make a mitigation recommendation.

Climate projection of synoptic patterns forming extremely high wind speed over the Barents Sea

NASA Astrophysics Data System (ADS)

Surkova, Galina; Krylov, Aleksey

2017-04-01

Frequency of extreme weather events is not very high, but their consequences for the human well-being may be hazardous. These seldom events are not always well simulated by climate models directly. Sometimes it is more effective to analyze numerical projection of large-scale synoptic event generating extreme weather. For example, in mid-latitude surface wind speed depends mainly on the sea level pressure (SLP) field - its configuration and horizontal pressure gradient. This idea was implemented for analysis of extreme wind speed events over the Barents Sea. The calendar of high surface wind speed V (10 m above the surface) was prepared for events with V exceeding 99th percentile value in the central part of the Barents Sea. Analysis of probability distribution function of V was carried out on the base of ERA-Interim reanalysis data (6-hours, 0.75x0.75 degrees of latitude and longitude) for the period 1981-2010. Storm wind events number was found to be 240 days. Sea level pressure field over the sea and surrounding area was selected for each storm wind event. For the climate of the future (scenario RCP8.5), projections of SLP from CMIP5 numerical experiments were used. More than 20 climate models results of projected SLP (2006-2100) over the Barents Sea were correlated with modern storm wind SLP fields. Our calculations showed the positive tendency of annual frequency of storm SLP patterns over the Barents Sea by the end of 21st century.

Numerical Modeling of River Fluxes Under Changing Environmental Conditions (Invited)

NASA Astrophysics Data System (ADS)

Simpson, G.

2013-12-01

High frequency climate cycles have a major impact on landscapes, but it remains uncertain if alluvial rivers can transfer the resulting sediment pulses downstream to sedimentary basins. Stratigraphic records located near the mouth of rivers exhibit cyclicity consistent with orbital forcing. However, in some cases, the sediment supply from rivers appears to have remained remarkably constant despite changes in climate, which has been interpreted to indicate that rivers dampen rapid variability. Here, we employ a physically-based numerical model to resolve this outstanding problem. Our simulations show that rivers forced with water flux cycles exhibit highly pulsed sediment outflux records, even when the period of forcing is several orders of magnitude shorter than river response times. This non-linear amplified system response characterised by positive feedback is related to the strong negative correlation between water flux and the equilibrium slope of a river. We also show that the apparent stability of sediment fluxes based on time-averaged data is an artifact of integrating highly episodic records over multiple cycles rather than a signature of diffusive floodplain processes. We conclude that marine sedimentary basins may record sediment-flux cycles resulting from discharge (and ultimately climate) variability, whereas they may be relatively insensitive to pure sediment-flux perturbations (such as for example those induced by tectonics).

Numerical simulation of the effects of urban land-use changes on the local climate of multiple desert cities

NASA Astrophysics Data System (ADS)

Kamal, S. M.; Huang, H. P.; Myint, S. W.

2016-12-01

This study quantifies the effect of urbanization on local climate by numerical simulations for multiple desert cities with a wide range of urban size, baseline climatology, and composition of land cover. The numerical experiments use the Weather Research and Forecasting (WRF) model with multiple layers of nesting centered at a desert city. To extract the influence of land-use changes, twin runs are performed with each pair driven by the same time-varying lateral boundary conditions from reanalysis but different land surface conditions from Landsat observations for 1985 and 2010. The differences in the meteorological fields between the two runs are interpreted as the effects of land-use changes due to urbanization from 1985-2010. Using this strategy, simulations are carried out for five desert cities: (1) Las Vegas, United States, (2) Hotan, China, (3) Kharga, Egypt, (4) Beer Sheva, Israel, and (5) Jodhpur, India. The results of the simulations reveal a common pattern of the climatic effect of desert urbanization with nighttime warming but daytime cooling over areas where urbanization occurred. This effect is mainly confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding non-urban areas. The pattern is similar in winter and summer. Exceptions to this pattern are found in a few cases in which the noisiness of local circulation, specifically monsoon and land-sea breeze, overwhelms the climatic signal induced by land-use changes. Although the local climatic responses to urbanization are qualitatively similar for the five desert cities, quantitative differences exist in the magnitudes of nighttime warming and daytime cooling. The possible reasons for those secondary differences are discussed.

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

NASA Technical Reports Server (NTRS)

Hou, Arthur; Zhang, Sara; daSilva, Arlindo; Li, Frank; Atlas, Robert (Technical Monitor)

2002-01-01

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Assessing the Problem Formulation in an Integrated Assessment Model: Implications for Climate Policy Decision-Support

NASA Astrophysics Data System (ADS)

Garner, G. G.; Reed, P. M.; Keller, K.

2014-12-01

Integrated assessment models (IAMs) are often used with the intent to aid in climate change decisionmaking. Numerous studies have analyzed the effects of parametric and/or structural uncertainties in IAMs, but uncertainties regarding the problem formulation are often overlooked. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the problem formulation. The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decisionmakers, however, may be concerned with a broader range of values and preferences that are not captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing both (ii) the costs of abatement and (iii) the damages due to climate change. We derive a set of Pareto-optimal solutions over which decisionmakers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Drought variability in six catchments in the UK

NASA Astrophysics Data System (ADS)

Kwok-Pan, Chun; Onof, Christian; Wheater, Howard

2010-05-01

Drought is fundamentally related to consistent low precipitation levels. Changes in global and regional drought patterns are suggested by numerous recent climate change studies. However, most of the climate change adaptation measures are at a catchment scale, and the development of a framework for studying persistence in precipitation is still at an early stage. Two stochastic approaches for modelling drought severity index (DSI) are proposed to investigate possible changes in droughts in six catchments in the UK. They are the autoregressive integrated moving average (ARIMA) and the generalised linear model (GLM) approach. Results of ARIMA modelling show that mean sea level pressure and possibly the North Atlantic Oscillation (NAO) index are important climate variables for short term drought forecasts, whereas relative humidity is not a significant climate variable despite its high correlation with the DSI series. By simulating rainfall series, the generalised linear model (GLM) approach can provide the probability density function of the DSI. GLM simulations indicate that the changes in the 10th and 50th quantiles of drought events are more noticeable than in the 90th extreme droughts. The possibility of extending the GLM approach to support risk-based water management is also discussed.

Determining the Current and Future Health of Low-Latitude Andean Glaciers Using an Equilibrium Line Altitude Model and Hypsometric Data from the Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.; MacAyeal, D. R.

2015-12-01

Mountain glaciers have been described as the water towers of world, and for many populations in the low-latitude South American Andes, glacial runoff is vital for agricultural, industrial, and basic water needs. Previous studies of low-latitude Andean glaciers suggest a precarious future due to contemporary warming. These studies have looked at trends in freezing level heights or observations of contemporary retreat. However, regional-scale understanding of low-latitude glacial responses to present and future climate change is limited, in part due to incomplete information about the extent and elevation distribution of low-latitude glaciers. The recently published Randolph Glacier Inventory (RGI) (5.0) provides the necessary information about the size and elevation distribution of low-latitude glaciers to begin such studies. We determine the contemporary equilibrium line altitudes (ELAs) for low-latitude Andean glaciers in the RGI, using a numerical energy balance ablation model driven with reanalysis and gridded data products. Contemporary ELAs tend to fall around the peak of the elevation histogram, with an exception being the southern-most outer tropical glaciers whose modeled ELAs tend to be higher than the elevation histogram for that region (see below figure). Also, we use the linear tends in temperature and precipitation from the contemporary climatology to extrapolate 21stcentury climate forcings. Modeled ELAs by the middle on the century are universally predicted to rise, with outer tropical ELAs rising more than the inner tropical glaciers. These trends continue through the end of the century. Finally, we explore how climate variables and parameters in our numerical model may vary for different warming scenarios from United Nation's IPCC AR5 report. We quantify the impacts of these changes on ELAs for various climate change trajectories. These results support previous work on the precarious future of low latitude Andean glaciers, while providing a richer understanding of the glacial impacts of contemporary and future warming. Also, this work provides analysis of processes and feedbacks between different climate variables important to glacier mass balances in a warming world, improving predictions for the fate of low-latitude Andean glaciers.

Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

2010-12-01

NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center/ Earth System Research Laboratory (ESRL) Twentieth Century Reanalysis Project data set (20CR, G. Compo, et al.), a historical reanalysis that will provide climate information dating back to 1850 to the present; and 3) the CPC’s Upper Air Reanlaysis. NCMP will advance the highly successful NOAA National Operational Model Archive and Distribution System (NOMADS, Rutledge, BAMS 2006), and standards already in use including Unidata’s THREDDS (TDS), PMEL’s Live Access Server (LAS) and the GrADS Data Server (GDS) from COLA; the Department of Energy (DOE) Earth System Grid (ESG) and the associated IPCC Climate model archive located at the Program for Climate Model Diagnostics and Inter-comparison (PCMDI) through the ESG; and NOAA’s Unified Access Framework (UAF) effort; and core standards developed by Open Geospatial Consortium (OGC). The format neutral OPeNDAP protocol as used in the NOMADS system will also be a key aspect of the design of NCMP.

Modernizing Earth and Space Science Modeling Workflows in the Big Data Era

NASA Astrophysics Data System (ADS)

Kinter, J. L.; Feigelson, E.; Walker, R. J.; Tino, C.

2017-12-01

Modeling is a major aspect of the Earth and space science research. The development of numerical models of the Earth system, planetary systems or astrophysical systems is essential to linking theory with observations. Optimal use of observations that are quite expensive to obtain and maintain typically requires data assimilation that involves numerical models. In the Earth sciences, models of the physical climate system are typically used for data assimilation, climate projection, and inter-disciplinary research, spanning applications from analysis of multi-sensor data sets to decision-making in climate-sensitive sectors with applications to ecosystems, hazards, and various biogeochemical processes. In space physics, most models are from first principles, require considerable expertise to run and are frequently modified significantly for each case study. The volume and variety of model output data from modeling Earth and space systems are rapidly increasing and have reached a scale where human interaction with data is prohibitively inefficient. A major barrier to progress is that modeling workflows isn't deemed by practitioners to be a design problem. Existing workflows have been created by a slow accretion of software, typically based on undocumented, inflexible scripts haphazardly modified by a succession of scientists and students not trained in modern software engineering methods. As a result, existing modeling workflows suffer from an inability to onboard new datasets into models; an inability to keep pace with accelerating data production rates; and irreproducibility, among other problems. These factors are creating an untenable situation for those conducting and supporting Earth system and space science. Improving modeling workflows requires investments in hardware, software and human resources. This paper describes the critical path issues that must be targeted to accelerate modeling workflows, including script modularization, parallelization, and automation in the near term, and longer term investments in virtualized environments for improved scalability, tolerance for lossy data compression, novel data-centric memory and storage technologies, and tools for peer reviewing, preserving and sharing workflows, as well as fundamental statistical and machine learning algorithms.

Comparison of different synthetic 5-min rainfall time series on the results of rainfall runoff simulations in urban drainage modelling

NASA Astrophysics Data System (ADS)

Krämer, Stefan; Rohde, Sophia; Schröder, Kai; Belli, Aslan; Maßmann, Stefanie; Schönfeld, Martin; Henkel, Erik; Fuchs, Lothar

2015-04-01

The design of urban drainage systems with numerical simulation models requires long, continuous rainfall time series with high temporal resolution. However, suitable observed time series are rare. As a result, usual design concepts often use uncertain or unsuitable rainfall data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic rainfall data as input for urban drainage modelling are advanced, tested, and compared. Synthetic rainfall time series of three different precipitation model approaches, - one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model-, are provided for three catchments with different sewer system characteristics in different climate regions in Germany: - Hamburg (northern Germany): maritime climate, mean annual rainfall: 770 mm; combined sewer system length: 1.729 km (City center of Hamburg), storm water sewer system length (Hamburg Harburg): 168 km - Brunswick (Lower Saxony, northern Germany): transitional climate from maritime to continental, mean annual rainfall: 618 mm; sewer system length: 278 km, connected impervious area: 379 ha, height difference: 27 m - Friburg in Brisgau (southern Germany): Central European transitional climate, mean annual rainfall: 908 mm; sewer system length: 794 km, connected impervious area: 1 546 ha, height difference 284 m Hydrodynamic models are set up for each catchment to simulate rainfall runoff processes in the sewer systems. Long term event time series are extracted from the - three different synthetic rainfall time series (comprising up to 600 years continuous rainfall) provided for each catchment and - observed gauge rainfall (reference rainfall) according national hydraulic design standards. The synthetic and reference long term event time series are used as rainfall input for the hydrodynamic sewer models. For comparison of the synthetic rainfall time series against the reference rainfall and against each other the number of - surcharged manholes, - surcharges per manhole, - and the average surcharge volume per manhole are applied as hydraulic performance criteria. The results are discussed and assessed to answer the following questions: - Are the synthetic rainfall approaches suitable to generate high resolution rainfall series and do they produce, - in combination with numerical rainfall runoff models - valid results for design of urban drainage systems? - What are the bounds of uncertainty in the runoff results depending on the synthetic rainfall model and on the climate region? The work is carried out within the SYNOPSE project, funded by the German Federal Ministry of Education and Research (BMBF).

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.

Evidence for 20th century climate warming and wetland drying in the North American Prairie Pothole Region

USGS Publications Warehouse

Werner, B.A.; Johnson, W. Carter; Guntenspergen, Glenn R.

2013-01-01

The Prairie Pothole Region (PPR) of North America is a globally important resource that provides abundant and valuable ecosystem goods and services in the form of biodiversity, groundwater recharge, water purification, flood attenuation, and water and forage for agriculture. Numerous studies have found these wetlands, which number in the millions, to be highly sensitive to climate variability. Here, we compare wetland conditions between two 30-year periods (1946–1975; 1976–2005) using a hindcast simulation approach to determine if recent climate warming in the region has already resulted in changes in wetland condition. Simulations using the WETLANDSCAPE model show that 20th century climate change may have been sufficient to have a significant impact on wetland cover cycling. Modeled wetlands in the PPR's western Canadian prairies show the most dramatic effects: a recent trend toward shorter hydroperiods and less dynamic vegetation cycles, which already may have reduced the productivity of hundreds of wetland-dependent species.

Evidence for 20th century climate warming and wetland drying in the North American Prairie Pothole Region.

PubMed

Werner, Brett A; Johnson, W Carter; Guntenspergen, Glenn R

2013-09-01

The Prairie Pothole Region (PPR) of North America is a globally important resource that provides abundant and valuable ecosystem goods and services in the form of biodiversity, groundwater recharge, water purification, flood attenuation, and water and forage for agriculture. Numerous studies have found these wetlands, which number in the millions, to be highly sensitive to climate variability. Here, we compare wetland conditions between two 30-year periods (1946-1975; 1976-2005) using a hindcast simulation approach to determine if recent climate warming in the region has already resulted in changes in wetland condition. Simulations using the WETLANDSCAPE model show that 20th century climate change may have been sufficient to have a significant impact on wetland cover cycling. Modeled wetlands in the PPR's western Canadian prairies show the most dramatic effects: a recent trend toward shorter hydroperiods and less dynamic vegetation cycles, which already may have reduced the productivity of hundreds of wetland-dependent species.

Stress and deformation characteristics of sea ice in a high resolution numerical sea ice model.

NASA Astrophysics Data System (ADS)

Heorton, Harry; Feltham, Daniel; Tsamados, Michel

2017-04-01

The drift and deformation of sea ice floating on the polar oceans is due to the applied wind and ocean currents. The deformations of sea ice over ocean basin length scales have observable patterns; cracks and leads in satellite images and within the velocity fields generated from floe tracking. In a climate sea ice model the deformation of sea ice over ocean basin length scales is modelled using a rheology that represents the relationship between stresses and deformation within the sea ice cover. Here we investigate the link between observable deformation characteristics and the underlying internal sea ice stresses and force balance using the Los Alamos numerical sea ice climate model. In order to mimic laboratory experiments on the deformation of small cubes of sea ice we have developed an idealised square domain that tests the model response at spatial resolutions of up to 500m. We use the Elastic Anisotropic Plastic and Elastic Viscous Plastic rheologies, comparing their stability over varying resolutions and time scales. Sea ice within the domain is forced by idealised winds in order to compare the confinement of wind stresses and internal sea ice stresses. We document the characteristic deformation patterns of convergent, divergent and rotating stress states.

Response of ice cover on shallow Arctic lakes to contemporary climate conditions: Numerical modeling and remote sensing data analysis

NASA Astrophysics Data System (ADS)

Duguay, C.; Surdu, C.; Brown, L.; Samuelsson, P.

2012-04-01

Lake ice cover has been shown to be a robust indicator of climate variability and change. Recent studies have demonstrated that break-up dates, in particular, have been occurring earlier in many parts of the Northern Hemisphere over the last 50 years in response to warmer climatic conditions in the winter and spring seasons. The impacts of trends in air temperature and winter precipitation over the last five decades and those projected by global climate models will affect the timing and duration of ice cover (and ice thickness) on Arctic lakes. This will likely, in turn, have an important feedback effect on energy, water, and biogeochemical cycling in various regions of the Arctic. In the case of shallow tundra lakes, many of which are less than 3-m deep, warmer climate conditions could result in a smaller fraction of lakes that freeze to their bed in winter since thinner ice covers are expected to develop. Shallow lakes of the coastal plain of northern Alaska, and other similar regions of the Arctic, have likely been experiencing changes in seasonal ice thickness (and phenology) over the last few decades but these have not yet been documented. This paper presents results from a numerical lake ice modeling experiment and the analysis of ERS-1/2 synthetic aperture radar (SAR) data to elucidate the response of ice cover (thickness, freezing to bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA)to climate conditions over the last three decades. New downscaled data specific for the Arctic domain (at a resolution of 0.44 degrees using ERA Interim Reanalysis as boundary condition) produced by the Rossby Centre regional atmospheric model (RCA4) was used to force the Canadian Lake Ice Model (CLIMo) for the period 1979-2010. Output from CLIMo included freeze-up and break-up dates as well as ice thickness on a daily basis. ERS-1/2 data was used to map areas of shallow lakes that freeze to bed and when this happens (timing) in winter for the period 1991-2010. Preliminary results from a sub-region of the NSA show that the interannual variability in ice thickness simulated with CLIMo match well that of the fraction of lakes that freeze to their bed in winter as determined from the analysis of SAR data.

A mathematical model for the Andean Tiwanaku civilization collapse: climate variations.

PubMed

Flores, J C; Bologna, Mauro; Urzagasti, Deterlino

2011-12-21

We propose a mathematical nonlinear model for the Tiwanaku civilization collapse based on the assumption, supported by archeological data, that a drought caused a lack of the main resource, water. We evaluate the parameter of our model using archaeological data. According to our numerical simulation the population core should have decreased from 45,000 to 2000 inhabitants due to lake surface contraction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Improving city forests through assessment, modelling and monitoring

Treesearch

D.J. Nowak

2018-01-01

Urban and peri-urban forests produce numerous benefits for society. These include moderating the climate; reducing energy use in buildings; sequestering atmospheric carbon dioxide; improving air and water quality; mitigating rainfall run-off and flooding; providing an aesthetic environment and recreational opportunities; enhancing human health and social well-being;...

Climate projections of the ALARO-0 model on the EURO-CORDEX domain

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Berckmans, Julie; Caluwaerts, Steven; De Troch, Rozemien; De Cruz, Lesley; Duchêne, François; Giot, Olivier; Hamdi, Rafiq; Termonia, Piet

2016-04-01

Results of the future scenario runs are presented within the EURO-CORDEX framework using the regional climate model ALARO-0. This model has been primarily developed for operational numerical weather predictions and is therefore not tuned specifically for climate purposes. It features a new microphysics scheme called 3MT, which allows for a more sophisticated representation of convective precipitation. In Giot et al. (2015) validation results were presented for the 12.5-km and 50-km resolution runs forced by ERA-Interim reanalysis. It was shown that ALARO-0 is well capable of representing the European climate. More specifically, most of the ALARO-0 scores were within the existing EURO-CORDEX ensemble. For precipitation, due to the 3MT scheme, the ALARO-0 model produces some of the best scores within the ensemble. The comparison of the historical run with the climate scenarios runs (RCP8.5, RCP4.5) allows the determination of the ALARO-0 climate changes. These runs are all coupled to the GCM of Météo-France, namely CNRM-CM5. The climate-change signals are investigated with a focus on heavy precipitation and heat wave changes and the signals are put against the ones of the other EURO-CORDEX models (Jacob et al., 2013). Giot, O., Termonia, P., Degrauwe, D., De Troch, R., Caluwaerts, S., Smet, G., Berckmans, J., Deckmyn, A., De Cruz, L., De Meutter, P., Duerinckx, A., Gerard, L., Hamdi, R., Van den Bergh, J., Van Ginderachter, M., and Van Schaeybroeck, B.: Validation of the ALARO-0 model within the EURO-CORDEX framework, Geosci. Model Dev. Discuss., 8, 8387-8409, 2015. Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., et al., 2014. EURO-CORDEX: new high-resolution climate change projections for european impact research. Regional Environmental Change 14 (2), 563-578.

The Finer Details: Climate Modeling

NASA Technical Reports Server (NTRS)

2000-01-01

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

Bayesian Processor of Output for Probabilistic Quantitative Precipitation Forecasting

NASA Astrophysics Data System (ADS)

Krzysztofowicz, R.; Maranzano, C. J.

2006-05-01

The Bayesian Processor of Output (BPO) is a new, theoretically-based technique for probabilistic forecasting of weather variates. It processes output from a numerical weather prediction (NWP) model and optimally fuses it with climatic data in order to quantify uncertainty about a predictand. The BPO is being tested by producing Probabilistic Quantitative Precipitation Forecasts (PQPFs) for a set of climatically diverse stations in the contiguous U.S. For each station, the PQPFs are produced for the same 6-h, 12-h, and 24-h periods up to 84- h ahead for which operational forecasts are produced by the AVN-MOS (Model Output Statistics technique applied to output fields from the Global Spectral Model run under the code name AVN). The inputs into the BPO are estimated as follows. The prior distribution is estimated from a (relatively long) climatic sample of the predictand; this sample is retrieved from the archives of the National Climatic Data Center. The family of the likelihood functions is estimated from a (relatively short) joint sample of the predictor vector and the predictand; this sample is retrieved from the same archive that the Meteorological Development Laboratory of the National Weather Service utilized to develop the AVN-MOS system. This talk gives a tutorial introduction to the principles and procedures behind the BPO, and highlights some results from the testing: a numerical example of the estimation of the BPO, and a comparative verification of the BPO forecasts and the MOS forecasts. It concludes with a list of demonstrated attributes of the BPO (vis- à-vis the MOS): more parsimonious definitions of predictors, more efficient extraction of predictive information, better representation of the distribution function of predictand, and equal or better performance (in terms of calibration and informativeness).

Shallow bedrock limits groundwater seepage-based headwater climate refugia

USGS Publications Warehouse

Briggs, Martin A.; Lane, John W.; Snyder, Craig D.; White, Eric A.; Johnson, Zachary; Nelms, David L.; Hitt, Nathaniel P.

2018-01-01

Groundwater/surface-water exchanges in streams are inexorably linked to adjacent aquifer dynamics. As surface-water temperatures continue to increase with climate warming, refugia created by groundwater connectivity is expected to enable cold water fish species to survive. The shallow alluvial aquifers that source groundwater seepage to headwater streams, however, may also be sensitive to seasonal and long-term air temperature dynamics. Depth to bedrock can directly influence shallow aquifer flow and thermal sensitivity, but is typically ill-defined along the stream corridor in steep mountain catchments. We employ rapid, cost-effective passive seismic measurements to evaluate the variable thickness of the shallow colluvial and alluvial aquifer sediments along a headwater stream supporting cold water-dependent brook trout (Salvelinus fontinalis) in Shenandoah National Park, VA, USA. Using a mean depth to bedrock of 2.6 m, numerical models predicted strong sensitivity of shallow aquifer temperature to the downward propagation of surface heat. The annual temperature dynamics (annual signal amplitude attenuation and phase shift) of potential seepage sourced from the shallow modeled aquifer were compared to several years of paired observed stream and air temperature records. Annual stream water temperature patterns were found to lag local air temperature by ∼8–19 d along the stream corridor, indicating that thermal exchange between the stream and shallow groundwater is spatially variable. Locations with greater annual signal phase lag were also associated with locally increased amplitude attenuation, further suggestion of year-round buffering of channel water temperature by groundwater seepage. Numerical models of shallow groundwater temperature that incorporate regional expected climate warming trends indicate that the summer cooling capacity of this groundwater seepage will be reduced over time, and lower-elevation stream sections may no longer serve as larger-scale climate refugia for cold water fish species, even with strong groundwater discharge.

A comparison of river discharge calculated by using a regional climate model output with different reanalysis datasets in 1980s and 1990s

NASA Astrophysics Data System (ADS)

Ma, X.; Yoshikane, T.; Hara, M.; Adachi, S. A.; Wakazuki, Y.; Kawase, H.; Kimura, F.

2014-12-01

To check the influence of boundary input data on a modeling result, we had a numerical investigation of river discharge by using runoff data derived by a regional climate model with a 4.5-km resolution as input data to a hydrological model. A hindcast experiment, which to reproduce the current climate was carried out for the two decades, 1980s and 1990s. We used the Advanced Research WRF (ARW) (ver. 3.2.1) with a two-way nesting technique and the WRF single-moment 6-class microphysics scheme. Noah-LSM is adopted to simulate the land surface process. The NCEP/NCAR and ERA-Interim 6-hourly reanalysis datasets were used as the lateral boundary condition for the runs, respectively. The output variables used for river discharge simulation from the WRF model were underground runoff and surface runoff. Four rivers (Mogami, Agano, Jinzu and Tone) were selected in this study. The results showed that the characteristic of river discharge in seasonal variation could be represented and there were overestimated compared with measured one.

A numerical study of the effect of urbanization on the climate of Las Vegas metropolitan area

NASA Astrophysics Data System (ADS)

Kamal, S. M.; Huang, H. P.; Myint, S. W.

2014-12-01

Las Vegas is one of the fastest growing desert cities. Its developed area has doubled in the last 30 years. An accurate prediction of the effect of urbanization on the climate of the city is crucial for resource management and planning. In this study, we use the Weather Research and Forecasting (WRF) model coupled with a land surface and urban canopy model to investigate the effects of urbanization on the regional climate pattern around Las Vegas. High resolution numerical simulations are performed with a 3 km resolution over the metropolitan area. With identical lateral boundary conditions, three land-use land-cover maps, representing 2006, 1992 and hypothetical 1900, are used in multiple simulations. The differences in the simulated climate among those cases are used to quantify the urban effect. The simulated surface air temperature is validated against observational data from the weather station at the McCarran airport. It is found that urbanization affects substantial warming during the night but a minor cooling during the day. Detailed diagnostics of the surface energy budget are performed to help interpret this result. In addition, the emerging urban structures are found to have a mechanical effect of slowing down the climatological wind field over the urban area. The change in wind, in turn, leads to a secondary modification of the temperature structure within the air shed of the city. This finding suggests the need to combine the mechanical and thermodynamic effects to construct a complete picture of the influence of land cover on urban climate. In all cases of the simulations, it is also demonstrated that urbanization influences surface air temperature mainly within the metropolitan area.

Numerical simulation of geomorphic, climatic and anthropogenic drivers of soil distribution on semi-arid hillslopes

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Cohen, S.; Svoray, T.; Sela, S.; Hancock, G. R.

2010-12-01

Numerical models are an important tool for studying landscape processes as they allow us to isolate specific processes and drivers and test various physics and spatio-temporal scenarios. Here we use a distributed physically-based soil evolution model (mARM4D) to describe the drivers and processes controlling soil-landscape evolution on a field-site at the fringe between the Mediterranean and desert regions of Israel. This study is an initial effort in a larger project aimed at improving our understanding of the mechanisms and drivers that led to the extensive removal of soils from the loess covered hillslopes of this region. This specific region is interesting as it is located between the Mediterranean climate region in which widespread erosion from hillslopes was attributed to human activity during the Holocene and the arid region in which extensive removal of loess from hillslopes was shown to have been driven by climatic changes during the late-Pleistocene. First we study the sediment transport mechanism of the soil-landscape evolution processes in our study-site. We simulate soil-landscape evolution with only one sediment transport process (fluvial or diffusive) at a time. We find that diffusive sediment transport is likely the dominant process in this site as it resulted in soil distributions that better corresponds to current observations. We then simulate several realistic climatic/anthropogenic scenarios (based on the literature) in order to quantify the sensitivity of the soil-landscape evolution process to temporal fluctuations. We find that this site is relatively insensitive to short term (several thousands of years) sharp, changes. This suggests that climate, rather then human activity, was the main driver for the extensive removal of loess from the hillslopes.

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Reconstruction of the Greenland ice sheet dynamics in a fully coupled Earth System Model

NASA Astrophysics Data System (ADS)

Rybak, Oleg; Volodin, Evgeny; Huybrechts, Philippe

2016-04-01

Earth system models (ESMs) are undoubtedly effective tools for studying climate dynamics. Incorporation of evolving ice sheets to ESMs is a challenging task because response times of the climate system and of ice sheets differ by several orders of magnitude. Besides, AO GCMs operate on spatial and temporal resolutions substantially differing from those of ice sheet models (ICMs). Therefore elaboration of an effective coupling methodology of an AO GCM and an ICM is the key problem of an ESM construction and utilization. Several downscaling strategies of varying complexity exist now of data exchange between modeled climate system and ice sheets. Application of a particular strategy depends on the research objectives. In our view, the optimum approach for model studying of significant environmental changes (e.g. glacial/interglacial transitions) when ice sheets undergo substantial evolution of geometry and volume would be an asynchronous coupling. The latter allows simulation in the interactive way of growth and decay of ice sheets in the changing climatic conditions. In the focus of the presentation, is the overview of coupling aspects of an AO GCM INMCM32 elaborated in the Institute of Numerical Mathematics (Moscow, Russia) to the Greenland ice sheet model (GrISM, Vrije Uninersiteit Brussel, Belgium). To provide interactive coupling of INMCM32 (spatial resolution 5°×4°, 21 vertical layers and temporal resolution 6 min. in the atmospheric block) and GrISM (spatial resolution 20×20 km, 51 vertical layers and 1 yr temporal resolution), we employ a special energy- and water balance model (EWBM-G), which serves as a buffer providing effective data exchange between INMCM32 and GrISM. EWBM-G operates in a rectangle domain including Greenland. Transfer of daily meanings of simulated climatic variables (air surface temperature and specific humidity) is provided on the lateral boundarias of the domain and inside the domain (sea level air pressure, wind speed and total cloudiness) after applying spline interpolation. EWBM-G calculates annual surface mass balance, SMB, (further transferred as an external forcing to the GrISM) and fresh water flux (transferred to the oceanic block of the INMCM32). After receiving SMB, GrIS is integrated and returns update surface topography back to the INMCM32. The aim of the current research is to establish equilibration time of climate and GrIS in the transient coupled run and to elaborate optimum methodology for performing numerical experiments simulating glacial/interglacial transitions.

Development of virtual research environment for regional climatic and ecological studies and continuous education support

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Bogomolov, Vasily; Gordova, Yulia; Martynova, Yulia; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2014-05-01

Volumes of environmental data archives are growing immensely due to recent models, high performance computers and sensors development. It makes impossible their comprehensive analysis in conventional manner on workplace using in house computing facilities, data storage and processing software at hands. One of possible answers to this challenge is creation of virtual research environment (VRE), which should provide a researcher with an integrated access to huge data resources, tools and services across disciplines and user communities and enable researchers to process structured and qualitative data in virtual workspaces. VRE should integrate data, network and computing resources providing interdisciplinary climatic research community with opportunity to get profound understanding of ongoing and possible future climatic changes and their consequences. Presented are first steps and plans for development of VRE prototype element aimed at regional climatic and ecological monitoring and modeling as well as at continuous education and training support. Recently developed experimental software and hardware platform aimed at integrated analysis of heterogeneous georeferenced data "Climate" (http://climate.scert.ru/, Gordov et al., 2013; Shulgina et al., 2013; Okladnikov et al., 2013) is used as a VRE element prototype and approach test bench. VRE under development will integrate on the base of geoportal distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. VRE specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenaria. Currently the VRE element is accessible via developed geoportal at the same link (http://climate.scert.ru/) and integrates the WRF and «Planet Simulator» models, basic reanalysis and instrumental measurements data and support profound statistical analysis of storaged and modeled on demand data. In particular, one can run the integrated models, preprocess modeling results data, using dedicated modules for numerical processing perform analysys and visualize obtained results. New functionality recently has been added to the statistical analysis tools set aimed at detailed studies of climatic extremes occurring in Northern Asia. The VRE element is also supporting thematic educational courses for students and post-graduate students of the Tomsk State University. In particular, it allow students to perform on-line thematic laboratory work cycles on the basics of analysis of current and potential future regional climate change using Siberia territory as an example (Gordova et al, 2013). We plan to expand the integrated models set and add comprehensive surface and Arctic Ocean description. Developed VRE element "Climate" provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even a user without programming skills can process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, grant 14-05-00502, and integrated project SB RAS 131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computationaland information technologies for monitoring and modeling of climate changes and their consequences. Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya,A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131. (in Russian) 3. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko,A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data //Numerical methods and programming, 2013. Vol. 14. P. 123-131.(in Russian) 4. Yu.E. Gordova, E.Yu. Genina, V.P. Gorbatenko, E.P. Gordov, I.V. Kuzhevskaya, Yu.V. Martynova , I.G. Okladnikov, A.G. Titov, T.M. Shulgina, N.K. Barashkova Support of the educational process in modern climatology within the web-gis platform «Climate». Open and Distant Education. 2013, No 1(49)., P. 14-19.(in Russian)

Glacial meltwater cooling of the Gulf of Mexico - GCM implications for Holocene and present-day climates

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Maasch, Kirk A.; Saltzman, Barry

1989-01-01

The NCAR Community Climate Model GCM is presently used to investigate the possible effects on regional and hemispheric climates of reduced SSTs in the Gulf of Mexico, in view of delta-O-18 records and terrestrial evidence for at least two major glacial meltwater discharges after the last glacial maximum. Three numerical experiments have been conducted with imposed gulfwide SST coolings of 3, 6, and 12 C; in all cases, significant reductions arise in the North Atlantic storm-track intensity, together with a strong decrease in transient eddy water vapor transport out of the Gulf of Mexico. Other statistically significant changes occur across the Northern Hemisphere.

Development of a numerical model to simulate groundwater flow in the shallow aquifer system of Assateague Island, Maryland and Virginia

USGS Publications Warehouse

Masterson, John P.; Fienen, Michael N.; Gesch, Dean B.; Carlson, Carl S.

2013-01-01

A three-dimensional groundwater-flow model was developed for Assateague Island in eastern Maryland and Virginia to simulate both groundwater flow and solute (salt) transport to evaluate the groundwater system response to sea-level rise. The model was constructed using geologic and spatial information to represent the island geometry, boundaries, and physical properties and was calibrated using an inverse modeling parameter-estimation technique. An initial transient solute-transport simulation was used to establish the freshwater-saltwater boundary for a final calibrated steady-state model of groundwater flow. This model was developed as part of an ongoing investigation by the U.S. Geological Survey Climate and Land Use Change Research and Development Program to improve capabilities for predicting potential climate-change effects and provide the necessary tools for adaptation and mitigation of potentially adverse impacts.

Mediterranean summer climate and the monsoon regimes

NASA Astrophysics Data System (ADS)

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

2003-04-01

The Authors examine the general features of climate of the Mediterranean Region, i.e. its variability and trends in the last 40 years, and the teleconnections between Mediterranean climate and the global climate, using zonal and global indices. In particular they focus the attention on the analysis of the summer Mediterranean climate, and its variability and connection with the summer monsoon regimes. Several subregions can be distinguished in the Mediterranean for each season, and the occurrence of Mediterranean Oscillation is evident between West and East sub-basins. Precipitation and SLP fields in the Eastern basin are shown to be correlated with Mediterranean Oscillation. A total decrease of precipitation has been detected in last few years, although there are some very intense. During winter a fundamental role is played by NAO index, which, influencing the storm tracks coming from the Atlantic and passing over the Mediterranean and North Europe, it has a major role in the precipitation patterns over the Region. Moreover, temperature analysis over the last 40 years in the Mediterranean shows a distinct warming, in agreement with the pattern over North Emisphere and NAO index fluctuations. During summer the Hadley cell extend further northwards, influencing the Mediterranean climate, and there is evidence of a possible teleconnection with the Asian Monsoon, and the Sahel precipitation (and related Hadley cell): the SLP field in the Eastern Mediterranean is inversely correlated with those two precipitation indices, while it is positively correlated with the pressure in the Western Mediterranean. Leading mechanisms of interaction between Mediterranean summer rainfall and SLP patterns and precipitation indices associated with monsoon regimes are stressed out and investigated, as well as the influence of the position and strength of the Hadley cell, by means of both statistical and dynamical analytical arguments. A modeling study has been carried out in order to study the variations and the anomalies in the recent Mediterranean summer precipitation patterns, consisting of two main phases. In the first phase, a numerical regional atmospheric model has been used to downscale the NCEP/NCAR reanalyses, showing a good agreement between model simulations and observations, proving the capability of the modeling tool. During the second phase, following and extending recent experiences the numerical model has been used to identify the features and extent of the impacts of the location and strength of the West Africa summer monsoon - therefore the regional Hadley cell - to the Mediterranean climate, by selectively modifying the main forcing of that tropical circulation, i.e. the Gulf of Guinea sea surface temperatures.

A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

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

Ringler, Todd; Ju, Lili; Gunzburger, Max

2008-11-14

During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoimore » tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multiresolution method and the challenges ahead.« less

Assessing, understanding, and conveying the state of the Arctic sea ice cover

NASA Astrophysics Data System (ADS)

Perovich, D. K.; Richter-Menge, J. A.; Rigor, I.; Parkinson, C. L.; Weatherly, J. W.; Nghiem, S. V.; Proshutinsky, A.; Overland, J. E.

2003-12-01

Recent studies indicate that the Arctic sea ice cover is undergoing significant climate-induced changes, affecting both its extent and thickness. Satellite-derived estimates of Arctic sea ice extent suggest a reduction of about 3% per decade since 1978. Ice thickness data from submarines suggest a net thinning of the sea ice cover since 1958. Changes (including oscillatory changes) in atmospheric circulation and the thermohaline properties of the upper ocean have also been observed. These changes impact not only the Arctic, but the global climate system and are likely accelerated by such processes as the ice-albedo feedback. It is important to continue and expand long-term observations of these changes to (a) improve the fundamental understanding of the role of the sea ice cover in the global climate system and (b) use the changes in the sea ice cover as an early indicator of climate change. This is a formidable task that spans a range of temporal and spatial scales. Fortunately, there are numerous tools that can be brought to bear on this task, including satellite remote sensing, autonomous buoys, ocean moorings, field campaigns and numerical models. We suggest the integrated and coordinated use of these tools during the International Polar Year to monitor the state of the Arctic sea ice cover and investigate its governing processes. For example, satellite remote sensing provides the large-scale snapshots of such basic parameters as ice distribution, melt zone, and cloud fraction at intervals of half a day to a week. Buoys and moorings can contribute high temporal resolution and can measure parameters currently unavailable from space including ice thickness, internal ice temperature, and ocean temperature and salinity. Field campaigns can be used to explore, in detail, the processes that govern the ice cover. Numerical models can be used to assess the character of the changes in the ice cover and predict their impacts on the rest of the climate system. This work affords extraordinary opportunities for outreach activities, because of the public interest in both the Arctic and climate change. Data can be streamed to public web sites in near real time, as can photographs and commentaries from field camps. The breadth of activities affords considerable opportunities to engage the next generation of researchers in such diverse fields as computer science, engineering, and geophysics.

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

NASA Astrophysics Data System (ADS)

Almeida, Susana; Holcombe, Elizabeth Ann; Pianosi, Francesca; Wagener, Thorsten

2017-02-01

Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure. Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterizing the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g. rainfall). Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socio-economic changes, such as increased urbanization and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and Classification And Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of topsoil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89 % of the expected behaviour of the studied slope can be characterized based on only two variables - the ratio of topsoil thickness to cohesion and the ratio of rainfall intensity to duration.

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

NASA Technical Reports Server (NTRS)

Putnam, Williama

2011-01-01

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

On the differences between Last Glacial Maximum and Mid-Holocene climates in southern South America simulated by PMIP3 models

NASA Astrophysics Data System (ADS)

Berman, Ana Laura; Silvestri, Gabriel E.; Tonello, Marcela S.

2018-04-01

Differences between climate conditions during the Last Glacial Maximum (LGM) and the Mid-Holocene (MH) in southern South America inferred from the state-of-the-art PMIP3 paleoclimatic simulations are described for the first time in this paper. The aim is to expose characteristics of past climate changes occurred without human influence. In this context, numerical simulations are an indispensable tool for inferring changes in near-surface air temperature and precipitation in regions where proxy information is scarce or absent. The analyzed PMIP3 models describe MH temperatures significantly warmer than those of LGM with magnitudes of change depending on the season and the specific geographic region. In addition, models indicate that seasonal mean precipitation during MH increased with respect to LGM values in wide southern continental areas to the east of the Andes Cordillera whereas seasonal precipitation developed in areas to the west of Patagonian Andes reduced from LGM to MH.

Experimental and numerical study of a 10MW TLP wind turbine in waves and wind

NASA Astrophysics Data System (ADS)

Pegalajar-Jurado, Antonio; Hansen, Anders M.; Laugesen, Robert; Mikkelsen, Robert F.; Borg, Michael; Kim, Taeseong; Heilskov, Nicolai F.; Bredmose, Henrik

2016-09-01

This paper presents tests on a 1:60 version of the DTU 10MW wind turbine mounted on a tension leg platform and their numerical reproduction. Both the experimental setup and the numerical model are Froude-scaled, and the dynamic response of the floating wind turbine to wind and waves is compared in terms of motion in the six degrees of freedom, nacelle acceleration and mooring line tension. The numerical model is implemented in the aero-elastic code Flex5, featuring the unsteady BEM method and the Morison equation for the modelling of aerodynamics and hydrodynamics, respectively. It was calibrated with the tests by matching key system features, namely the steady thrust curve and the decay tests in water. The calibrated model is used to reproduce the wind-wave climates in the laboratory, including regular and irregular waves, with and without wind. The model predictions are compared to the measured data, and a good agreement is found for surge and heave, while some discrepancies are observed for pitch, nacelle acceleration and line tension. The addition of wind generally improves the agreement with test results. The aerodynamic damping is identified in both tests and simulations. Finally, the sources of the discrepancies are discussed and some improvements in the numerical model are suggested in order to obtain a better agreement with the experiments.

Glacier calving, dynamics, and sea-level rise. Final report

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

Meier, M.F.; Pfeffer, W.T.; Amadei, B.

1998-08-01

The present-day calving flux from Greenland and Antarctica is poorly known, and this accounts for a significant portion of the uncertainty in the current mass balance of these ice sheets. Similarly, the lack of knowledge about the role of calving in glacier dynamics constitutes a major uncertainty in predicting the response of glaciers and ice sheets to changes in climate and thus sea level. Another fundamental problem has to do with incomplete knowledge of glacier areas and volumes, needed for analyses of sea-level change due to changing climate. The authors proposed to develop an improved ability to predict the futuremore » contributions of glaciers to sea level by combining work from four research areas: remote sensing observations of calving activity and iceberg flux, numerical modeling of glacier dynamics, theoretical analysis of the calving process, and numerical techniques for modeling flow with large deformations and fracture. These four areas have never been combined into a single research effort on this subject; in particular, calving dynamics have never before been included explicitly in a model of glacier dynamics. A crucial issue that they proposed to address was the general question of how calving dynamics and glacier flow dynamics interact.« less

Potential effects of climate change on the distribution of waterbirds in the Prairie Pothole Region, U.S.A.

USGS Publications Warehouse

Steen, Valerie; Powell, Abby N.

2012-01-01

Wetland-dependent birds are considered to be at particularly high risk for negative climate change effects. Current and future distributions of American Bittern (Botaurus lentiginosus), American Coot (Fulica americana), Black Tern (Chlidonias niger), Pied-billed Grebe (Podilymbus podiceps) and Sora (Porzana carolina), five waterbird species common in the Prairie Pothole Region (PPR), were predicted using species distribution models (SDMs) in combination with climate data that projected a drier future for the PPR. Regional-scale SDMs were created for the U.S. PPR using breeding bird survey occurrence records for 1971-2000 and wetland and climate parameters. For each waterbird species, current distribution and four potential future distributions were predicted: all combinations of two Global Circulation Models and two emissions scenarios. Averaged for all five species, the ensemble range reduction was 64%. However, projected range losses for individual species varied widely with Sora and Black Tern projected to lose close to 100% and American Bittern 29% of their current range. Future distributions were also projected to a hypothetical landscape where wetlands were numerous and constant to highlight areas suitable as conservation reserves under a drier future climate. The ensemble model indicated that northeastern North Dakota and northern Minnesota would be the best areas for conservation reserves within the U.S. PPR under the modeled conditions.

How much does climate change threaten European forest tree species distributions?

PubMed

Dyderski, Marcin K; Paź, Sonia; Frelich, Lee E; Jagodziński, Andrzej M

2018-03-01

Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN, and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios-optimistic (RCP2.6), moderate (RCP4.5), and pessimistic (RPC8.5)-using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: "winners"-mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur, and Quercus petraea; "losers"-mostly pioneer species: Betula pendula, Larix decidua, Picea abies, and Pinus sylvestris; and alien species-Pseudotsuga menziesii, Quercus rubra, and Robinia pseudoacacia, which may be also considered as "winners." Assuming limited migration, most of the species studied would face a significant decrease in suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. © 2017 John Wiley & Sons Ltd.

Impacts of sea level rise and climate change on coastal plant species in the central California coast

PubMed Central

Chang, Michelle Y.; Fulda, Matthew T.; Berlin, Jonathan A.; Freed, Rachel E.; Soo-Hoo, Melissa M.; Revell, Dave L.; Ikegami, Makihiko; Flint, Lorraine E.; Flint, Alan L.; Kendall, Bruce E.

2015-01-01

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA (an area of 23,948 km2). Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species’ area, elevation, and distance from the coast, and that 10 species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km2 loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1,439 km2 for one species to a gain of 9,795 km2 for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both. PMID:26020011

Impacts of sea level rise and climate change on coastal plant species in the central California coast.

PubMed

Garner, Kendra L; Chang, Michelle Y; Fulda, Matthew T; Berlin, Jonathan A; Freed, Rachel E; Soo-Hoo, Melissa M; Revell, Dave L; Ikegami, Makihiko; Flint, Lorraine E; Flint, Alan L; Kendall, Bruce E

2015-01-01

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA (an area of 23,948 km(2)). Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species' area, elevation, and distance from the coast, and that 10 species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km(2) loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1,439 km(2) for one species to a gain of 9,795 km(2) for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both.

SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Decharme, Bertrand; Pianezze, Joris; Lebeaupin Brossier, Cindy; Sevault, Florence; Seyfried, Léo; Garnier, Valérie; Bielli, Soline; Valcke, Sophie; Alias, Antoinette; Accensi, Mickael; Ardhuin, Fabrice; Bouin, Marie-Noëlle; Ducrocq, Véronique; Faroux, Stéphanie; Giordani, Hervé; Léger, Fabien; Marsaleix, Patrick; Rainaud, Romain; Redelsperger, Jean-Luc; Richard, Evelyne; Riette, Sébastien

2017-11-01

This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications, from global and regional coupled climate systems to high-resolution numerical weather prediction systems or very fine-scale models dedicated to process studies. The objective of this development is to build and share a common structure for the atmosphere-surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models. The numerical and physical principles of SURFEX interface between the different component models are described, and the different coupled systems in which the SURFEX OASIS3-MCT-based coupling interface is already implemented are presented.

Climatic implications of the simultaneous presence of CO2 and H2O in the Martian regolith

NASA Technical Reports Server (NTRS)

Zent, A. P.

1992-01-01

The current paradigm for quasi-periodic climate change on Mars holds that perhaps a few hundred millibars of CO2 are available for exchange between the atmosphere and regolith, and that a vast majority of that CO2 is presently absorbed into the regolith. The CO2 is partitioned between the regolith and atmosphere according to an equilibrium adsorptive relationship. If the atmospheric pressure exceeds the frost point at or near the poles, then quasi-permanent polar caps form and buffer the atmospheric pressure. This model was developed based upon laboratory studies of CO2 adsorption where no other adsorbates are present. We will conduct laboratory measurements of the simultaneous adsorption of H2O and CO2 under Mars-like conditions, and develop numerical expressions for use in climate modeling based upon our results.

Incorporating changes in albedo in estimating the climate mitigation benefits of land use change projects

NASA Astrophysics Data System (ADS)

Bird, D. N.; Kunda, M.; Mayer, A.; Schlamadinger, B.; Canella, L.; Johnston, M.

2008-04-01

Some climate scientists are questioning whether the practice of converting of non-forest lands to forest land (afforestation or reforestation) is an effective climate change mitigation option. The discussion focuses particularly on areas where the new forest is primarily coniferous and there is significant amount of snow since the increased climate forcing due to the change in albedo may counteract the decreased climate forcing due to carbon dioxide removal. In this paper, we develop a stand-based model that combines changes in surface albedo, solar radiation, latitude, cloud cover and carbon sequestration. As well, we develop a procedure to convert carbon stock changes to equivalent climatic forcing or climatic forcing to equivalent carbon stock changes. Using the model, we investigate the sensitivity of combined affects of changes in surface albedo and carbon stock changes to model parameters. The model is sensitive to amount of cloud, atmospheric absorption, timing of canopy closure, carbon sequestration rate among other factors. The sensitivity of the model is investigated at one Canadian site, and then the model is tested at numerous sites across Canada. In general, we find that the change in albedo reduces the carbon sequestration benefits by approximately 30% over 100 years, but this is not drastic enough to suggest that one should not use afforestation or reforestation as a climate change mitigation option. This occurs because the forests grow in places where there is significant amount of cloud in winter. As well, variations in sequestration rate seem to be counterbalanced by the amount and timing of canopy closure. We close by speculating that the effects of albedo may also be significant in locations at lower latitudes, where there are less clouds, and where there are extended dry seasons. These conditions make grasses light coloured and when irrigated crops, dark forests or other vegetation such as biofuels replace the grasses, the change in carbon stocks may not compensate for the darkening of the surface.

On Diffusive Climatological Models.

NASA Astrophysics Data System (ADS)

Griffel, D. H.; Drazin, P. G.

1981-11-01

A simple, zonally and annually averaged, energy-balance climatological model with diffusive heat transport and nonlinear albedo feedback is solved numerically. Some parameters of the model are varied, one by one, to find the resultant effects on the steady solution representing the climate. In particular, the outward radiation flux, the insulation distribution and the albedo parameterization are varied. We have found an accurate yet simple analytic expression for the mean annual insolation as a function of latitude and the obliquity of the Earth's rotation axis; this has enabled us to consider the effects of the oscillation of the obliquity. We have used a continuous albedo function which fits the observed values; it considerably reduces the sensitivity of the model. Climatic cycles, calculated by solving the time-dependent equation when parameters change slowly and periodically, are compared qualitatively with paleoclimatic records.

The Quaternary fossil-pollen record and global change

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

Grimm, E.C.

Fossil pollen provide one of the most valuable records of vegetation and climate change during the recent geological past. Advantages of the fossil-pollen record are that deposits containing fossil pollen are widespread, especially in areas having natural lakes, that fossil pollen occurs in continuous stratigraphic sequences spanning millennia, and that fossil pollen occurs in quantitative assemblages permitting a multivariate approach for reconstructing past vegetation and climates. Because of stratigraphic continuity, fossil pollen records climate cycles on a wide range of scales, from annual to the 100 ka Milankovitch cycles. Receiving particular emphasis recently are decadal to century scale changes, possiblemore » from the sediments of varved lakes, and late Pleistocene events on a 5--10 ka scale possibly correlating with the Heinrich events in the North Atlantic marine record or the Dansgaard-Oeschger events in the Greenland ice-core record. Researchers have long reconstructed vegetation and climate by qualitative interpretation of the fossil-pollen record. Recently quantitative interpretation has developed with the aid of large fossil-pollen databases and sophisticated numerical models. In addition, fossil pollen are important climate proxy data for validating General Circulation Models, which are used for predicting the possible magnitude future climate change. Fossil-pollen data also contribute to an understanding of ecological issues associated with global climate change, including questions of how and how rapidly ecosystems might respond to abrupt climate change.« less

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

The I.A.G. / A.I.G. SEDIBUD Book Project: Source-to-Sink Fluxes in Undisturbed Cold Environments

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Dixon, John C.; Zwolinski, Zbigniew

2015-04-01

The currently prepared SEDIBUD Book on "Source-to-Sink Fluxes in Undisturbed Cold Environments" (edited by Achim A. Beylich, John C. Dixon and Zbigniew Zwolinski and published by Cambridge University Press) is summarizing and synthesizing the achievements of the International Association of Geomorphologists` (I.A.G./A.I.G.) Working Group SEDIBUD (Sediment Budgets in Cold Environments), which has been active since 2005 (http://www.geomorph.org/wg/wgsb.html). Amplified climate change and ecological sensitivity of largely undisturbed polar and high-altitude cold climate environments have been highlighted as key global environmental issues. The effects of projected climate change will change surface environments in cold regions and will alter the fluxes of sediments, nutrients and solutes, but the absence of quantitative data and coordinated geomorphic process monitoring and analysis to understand the sensitivity of the Earth surface environment in these largely undisturbed environments is acute. Our book addresses this existing key knowledge gap. The applied approach of integrating comparable and longer-term field datasets on contemporary solute and sedimentary fluxes from a number of different defined cold climate catchment geosystems for better understanding (i) the environmental drivers and rates of contemporary denudational surface processes and (ii) possible effects of projected climate change in cold regions is unique in the field of geomorphology. Largely undisturbed cold climate environments can provide baseline data for modeling the effects of environmental change. The book synthesizes work carried out by numerous SEDIBUD Members over the last decade in numerous cold climate catchment geosystems worldwide. For reaching a global cover of different cold climate environments the book is - after providing an introduction part and a basic part on climate change in cold environments and general implications for solute and sedimentary fluxes - dealing in different defined parts with Sub-Arctic and Arctic Environments, Sub-Antarctic and Antarctic Environments, and Alpine / Mountain Environments. The book includes a synthesis key chapter where comparable datasets on contemporary solute and sedimentary fluxes generated during the conducted coordinated research efforts in different cold climate catchment geosystems are integrated with the key goals to (i) identify the main environmental drivers and rates of contemporary solute and sedimentary fluxes, and (ii) model possible effects of projected climate change on solute and sedimentary fluxes in cold climate environments. The SEDIBUD Book provides new key findings on environmental drivers and rates of contemporary solute and sedimentary fluxes, and on spatial variability within global cold climate environments. The book will go in production in July 2015.

Land Conversion in Amazonia and Northern South America; Influences on Regional Hydrology and Ecosystem Response

NASA Astrophysics Data System (ADS)

Knox, Ryan Gary

A numerical model of the terrestrial biosphere (Ecosystem Demography Model) is compbined with an atmospheric model (Brazilian Regional Atmospheric Modeling System) to investigate how land conversion in the Amazon and Northern South America have changed the hydrology of the region, and to see if those changes are significant enough to produce an ecological response. Two numerical realizations of the structure and composition of terrestrial vegetation are used as boundary conditions in a simulation of the regional land surface and atmosphere. One realization seeks to capture the present day vegetation condition that includes human deforestation and land-conversion, the other is an estimate of the potential structure and composition of the region without human influence. Model output is assessed for consistent and significant differences in hydrometeorology. Locations that show compelling differences are taken as case studies. The seasonal biases in precipitation at these locations are then used to create perturbations to long-term climate datasets. These perturbations then drive long-term simulations of dynamic vegetation to see if the climate consistent with a potential regional vegetation could elicit a change in the vegetation equilibrium at the site. Results show that South American land conversion has had consistent impacts on the regional patterning of precipitation. At some locations, changes in precipitation are persistent and constitute a significant fraction of total precipitation. Land-conversion has decreased mean continental evaporation and increased mean moisture convergence. Case study simulations of long term vegetation dynamic indicate that a hydrologic climate consistent with regional potential vegetation can indeed have significant influence on ecosystem structure and composition, particularly in water limited growth conditions. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Strain-specific functional and numerical responses are required to evaluate impacts on predator-prey dynamics.

PubMed

Yang, Zhou; Lowe, Chris D; Crowther, Will; Fenton, Andy; Watts, Phillip C; Montagnes, David J S

2013-02-01

We use strains recently collected from the field to establish cultures; then, through laboratory studies we investigate how among strain variation in protozoan ingestion and growth rates influences population dynamics and intraspecific competition. We focused on the impact of changing temperature because of its well-established effects on protozoan rates and its ecological relevance, from daily fluctuations to climate change. We show, first, that there is considerable inter-strain variability in thermal sensitivity of maximum growth rate, revealing distinct differences among multiple strains of our model species Oxyrrhis marina. We then intensively examined two representative strains that exhibit distinctly different thermal responses and parameterised the influence of temperature on their functional and numerical responses. Finally, we assessed how these responses alter predator-prey population dynamics. We do this first considering a standard approach, which assumes that functional and numerical responses are directly coupled, and then compare these results with a novel framework that incorporates both functional and numerical responses in a fully parameterised model. We conclude that: (i) including functional diversity of protozoa at the sub-species level will alter model predictions and (ii) including directly measured, independent functional and numerical responses in a model can provide a more realistic account of predator-prey dynamics.

Predictive Modeling of Risk Associated with Temperature Extremes over Continental US

NASA Astrophysics Data System (ADS)

Kravtsov, S.; Roebber, P.; Brazauskas, V.

2016-12-01

We build an extremely statistically accurate, essentially bias-free empirical emulator of atmospheric surface temperature and apply it for meteorological risk assessment over the domain of continental US. The resulting prediction scheme achieves an order-of-magnitude or larger gain of numerical efficiency compared with the schemes based on high-resolution dynamical atmospheric models, leading to unprecedented accuracy of the estimated risk distributions. The empirical model construction methodology is based on our earlier work, but is further modified to account for the influence of large-scale, global climate change on regional US weather and climate. The resulting estimates of the time-dependent, spatially extended probability of temperature extremes over the simulation period can be used as a risk management tool by insurance companies and regulatory governmental agencies.

Climate Analytics as a Service

NASA Technical Reports Server (NTRS)

Schnase, John L.; Duffy, Daniel Q.; McInerney, Mark A.; Webster, W. Phillip; Lee, Tsengdar J.

2014-01-01

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

Hydrologic climate change impacts in the Columbia River Basin and their sensitivity to methodological choices

NASA Astrophysics Data System (ADS)

Chegwidden, O.; Nijssen, B.; Mao, Y.; Rupp, D. E.

2016-12-01

The Columbia River Basin (CRB) in the United States' Pacific Northwest (PNW) is highly regulated for hydropower generation, flood control, fish survival, irrigation and navigation. Historically it has had a hydrologic regime characterized by winter precipitation in the form of snow, followed by a spring peak in streamflow from snowmelt. Anthropogenic climate change is expected to significantly alter this regime, causing changes to streamflow timing and volume. While numerous hydrologic studies have been conducted across the CRB, the impact of methodological choices in hydrologic modeling has not been as heavily investigated. To better understand their impact on the spread in modeled projections of hydrological change, we ran simulations involving permutations of a variety of methodological choices. We used outputs from ten global climate models (GCMs) and two representative concentration pathways from the Intergovernmental Panel on Climate Change's Fifth Assessment Report. After downscaling the GCM output using three different techniques we forced the Variable Infiltration Capacity (VIC) model and the Precipitation Runoff Modeling System (PRMS), both implemented at 1/16th degree ( 5 km) for the period 1950-2099. For the VIC model, we used three independently-derived parameter sets. We will show results from the range of simulations, both in the form of basin-wide spatial analyses of hydrologic variables and through analyses of changes in streamflow at selected sites throughout the CRB. We will then discuss the differences in sensitivities to climate change seen among the projections, paying particular attention to differences in projections from the hydrologic models and different parameter sets.

Global change and terrestrial hydrology - A review

NASA Technical Reports Server (NTRS)

Dickinson, Robert E.

1991-01-01

This paper reviews the role of terrestrial hydrology in determining the coupling between the surface and atmosphere. Present experience with interactive numerical simulation is discussed and approaches to the inclusion of land hydrology in global climate models ae considered. At present, a wide range of answers as to expected changes in surface hydrology is given by nominally similar models. Studies of the effects of tropical deforestation and global warming illustrate this point.

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

Investigation of air pollution and regional climate change due to anthropogenic aerosols

NASA Astrophysics Data System (ADS)

Nakata, Makiko; Sano, Itaru; Mukai, Sonoyo

2016-10-01

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. In particular, large cities in East Asia have experienced numerous heavy haze episodes. Atmospheric aerosol distributions in East Asia are complex, being influenced by both natural phenomena and human activity, with urban areas in particular being dominated by fine anthropogenic aerosols released from diesel-powered vehicles and industrial activity. In Japan, air pollution levels have been reduced; nevertheless, in recent years, there is increasing concern regarding air pollution caused by fine particulate matter. The origins of air pollution were examined, focusing on the comparison between aerosol properties observed from satellites and that on the ground. Because of their short life spans, concentrations of anthropogenic aerosols are highest over the source regions, and as a result, the climatic impacts of anthropogenic aerosols are also found to be most pronounced in these regions. In this study, aerosol impacts on climate are assessed by numerical model simulations. The direct effects of aerosols include reduced solar radiation, and hence a decrease in surface temperatures. In addition to these changes in the radiation budget, aerosols have a significant potential to change cloud and precipitation fields. These climatic responses to aerosols can manifest far from their source regions with high industrial activities.

Numerical simulation of the world ocean circulation

NASA Technical Reports Server (NTRS)

Takano, K.; Mintz, Y.; Han, Y. J.

1973-01-01

A multi-level model, based on the primitive equations, is developed for simulating the temperature and velocity fields produced in the world ocean by differential heating and surface wind stress. The model ocean has constant depth, free slip at the lower boundary, and neglects momentum advection; so that there is no energy exchange between the barotropic and baroclinic components of the motion, although the former influences the latter through temperature advection. The ocean model was designed to be coupled to the UCLA atmospheric general circulation model, for the study of the dynamics of climate and climate changes. But here, the model is tested by prescribing the observed seasonally varying surface wind stress and the incident solar radiation, the surface air temperature and humidity, cloudiness and the surface wind speed, which, together with the predicted ocean surface temperature, determine the surface flux of radiant energy, sensible heat and latent heat.

A Model for Developing and Assessing Youth-Based Environmental Engagement Programmes

ERIC Educational Resources Information Center

Riemer, Manuel; Lynes, Jennifer; Hickman, Gina

2014-01-01

In this paper, we argue that a fundamental cultural shift is needed to effectively address anthropogenic causes of climate change. Evidence suggests that youth are well positioned to create such transformation. While various studies have contributed empirical evidence to numerous youth-based non-formal environmental engagement programmes, what is…

Elucidating the role of vegetation in the initiation of rainfall-induced shallow landslides: Insights from an extreme rainfall event in the Colorado Front Range

USGS Publications Warehouse

McGuire, Luke; Rengers, Francis K.; Kean, Jason W.; Coe, Jeffrey A.; Mirus, Benjamin B.; Baum, Rex L.; Godt, Jonathan W.

2016-01-01

More than 1100 debris flows were mobilized from shallow landslides during a rainstorm from 9 to 13 September 2013 in the Colorado Front Range, with the vast majority initiating on sparsely vegetated, south facing terrain. To investigate the physical processes responsible for the observed aspect control, we made measurements of soil properties on a densely forested north facing hillslope and a grassland-dominated south facing hillslope in the Colorado Front Range and performed numerical modeling of transient changes in soil pore water pressure throughout the rainstorm. Using the numerical model, we quantitatively assessed interactions among vegetation, rainfall interception, subsurface hydrology, and slope stability. Results suggest that apparent cohesion supplied by roots was responsible for the observed connection between debris flow initiation and slope aspect. Results suggest that future climate-driven modifications to forest structure could substantially influence landslide hazards throughout the Front Range and similar water-limited environments where vegetation communities may be more susceptible to small variations in climate.

numerical broadband modelling of ocean waves, from 1 to 300 s: implications for seismic wave sources and wave climate studies

NASA Astrophysics Data System (ADS)

Ardhuin, F.; Stutzmann, E.; Gualtieri, L.

2014-12-01

Ocean waves provide most of the energy that feeds the continuous vertical oscillations of the solid Earth. Three period bands are usually identified. The hum contains periods longer than 30 s, and the primary and secondary peaks are usually centered around 15 and 5 s, respectively. Motions in all three bands are recorded everywhere on our planet and can provide information on both the solid Earth structure and the ocean wave climate over the past century. Here we describe recent efforts to extend the range of validity of ocean wave models to cover periods from 1 to 300 s (Ardhuin et al., Ocean Modelling 2014), and the resulting public database of ocean wave spectra (http://tinyurl.com/iowagaftp/HINDCAST/ ). We particularly discuss the sources of uncertainty for building a numerical model of acoustic and seismic noise on this knowledge of ocean wave spectra. For acoustic periods shorter than 3 seconds, the main uncertainties are the directional distributions of wave energy (Ardhuin et al., J. Acoust. Soc. Amer. 2013). For intermediate periods (3 to 25 s), the propagation properties of seismic waves are probably the main source of error when producing synthetic spectra of Rayleigh waves (Ardhuin et al. JGR 2011, Stutzmann et al. GJI 2012). For the longer periods (25 to 300 s), the poor knowledge of the bottom topography details may be the limiting factor for estimating hum spectra or inverting hum measurements in properties of the infragravity wave field. All in all, the space and time variability of recorded seismic and acoustic spectra is generally well reproduced in the band 3 to 300 s, and work on shorter periods is under way. This direct model can be used to search for missing noise sources, such as wave scattering in the marginal ice zone, find events relevant for solid earth studies (e.g. Obrebski et al. JGR 2013) or invert wave climate properties from microseismic records. The figure shows measured spectra of the vertical ground acceleration, and modeled result for the primary and secondary mechanisms using our numerical wave model. (a) Median ground acceleration power spectra (LHZ channel) at the SSB seismic station (Geoscope Network), for the month of January 2008. (b) Spectrogram of modeled ground displacement and (c) measured spectrogram.

Characterization of the impact of land degradation in the Sahel on the West African monsoon using an ensemble of climate models from the WAMME project

NASA Astrophysics Data System (ADS)

Boone, A. A.; Xue, Y.; Ruth, C.; De Sales, F.; Hagos, S.; Mahanama, S. P. P.; Schiro, K.; Song, G.; Wang, G.; Koster, R. D.; Mechoso, C. R.

2014-12-01

There is increasing evidence from numerical studies that anthropogenic land-use and land-cover changes (LULCC) can potentially induce significant variations on the regional scale climate. However, the magnitude of these variations likely depends on the local strength of the coupling between the surface and the atmosphere, the magnitude of the surface biophysical changes and how the key processes linking the surface with the atmosphere are parameterized within a particular model framework. One key hot-spot which has received considerable attention is the Sahelian region of West Africa, for which numerous studies have reported a significant increase in anthropogenic pressure on the already limited natural resources in this region, notably in terms of land use conversion and degradation. Thus, there is a pressing need to better understand the impacts of potential land degradation on the West African Monsoon (WAM) system. One of the main goals of the West African Monsoon Modeling andEvaluation project phase 2 (WAMMEII) is to provide basic understandingof LULCC on the regional climate over West Africa, and to evaluate thesensitivity of the seasonal variability of the WAM to LULCC. Theprescribed LULCC is based on recent 50 year period which represents amaximum feasible degradation scenario. In the current study, the LULCCis applied to five state of the art global climate models over afive-year period. The imposed LULCC results in a model-average 5-7%increase in surface albedo: the corresponding lower surface netradiation mainly results in a significant reduction in surfaceevaporation (upwards of 1 mm per day over a large part of the Sahel)which leads to less convective heating of the atmosphere, lowermoisture convergence, increased subsidence and reduced cloud coverover the LULCC zone. The overall impact can be characterized as asubstantial drought effect resulting in a reduction in annual rainfallof 20-40% in the Sahel and a southward shift of the monsoon. In broadagreement with previous studies, the impact of degradation on theregional climate is found to be variable among the different coupledmodels, however, the signal is stronger and a more consistent betweenthe models here which is likely related to our emphasis onprioritizing a consistent impact on the biophysical properties of thesurface.

Seasonal modulation of the Asian summer monsoon between the Medieval Warm Period and Little Ice Age: a multi model study

NASA Astrophysics Data System (ADS)

Kamae, Youichi; Kawana, Toshi; Oshiro, Megumi; Ueda, Hiroaki

2017-12-01

Instrumental and proxy records indicate remarkable global climate variability over the last millennium, influenced by solar irradiance, Earth's orbital parameters, volcanic eruptions and human activities. Numerical model simulations and proxy data suggest an enhanced Asian summer monsoon during the Medieval Warm Period (MWP) compared to the Little Ice Age (LIA). Using multiple climate model simulations, we show that anomalous seasonal insolation over the Northern Hemisphere due to a long cycle of orbital parameters results in a modulation of the Asian summer monsoon transition between the MWP and LIA. Ten climate model simulations prescribing historical radiative forcing that includes orbital parameters consistently reproduce an enhanced MWP Asian monsoon in late summer and a weakened monsoon in early summer. Weakened, then enhanced Northern Hemisphere insolation before and after June leads to a seasonally asymmetric temperature response over the Eurasian continent, resulting in a seasonal reversal of the signs of MWP-LIA anomalies in land-sea thermal contrast, atmospheric circulation, and rainfall from early to late summer. This seasonal asymmetry in monsoon response is consistently found among the different climate models and is reproduced by an idealized model simulation forced solely by orbital parameters. The results of this study indicate that slow variation in the Earth's orbital parameters contributes to centennial variability in the Asian monsoon transition.[Figure not available: see fulltext.

A hybrid formalism of aerosol gas phase interaction for 3-D global models

NASA Astrophysics Data System (ADS)

Benduhn, F.

2009-04-01

Aerosol chemical composition is a relevant factor to the global climate system with respect to both atmospheric chemistry and the aerosol direct and indirect effects. Aerosol chemical composition determines the capacity of aerosol particles to act as cloud condensation nuclei both explicitly via particle size and implicitly via the aerosol hygroscopic property. Due to the primary role of clouds in the climate system and the sensitivity of cloud formation and radiative properties to the cloud droplet number it is necessary to determine with accuracy the chemical composition of the aerosol. Dissolution, although a formally fairly well known process, may be subject to numerically prohibitive properties that result from the chemical interaction of the species engaged. So-far approaches to model the dissolution of inorganics into the aerosol liquid phase in the framework of a 3-D global model were based on an equilibrium, transient or hybrid equilibrium-transient approach. All of these methods present the disadvantage of a priori assumptions with respect to the mechanism and/or are numerically not manageable in the context of a global climate system model. In this paper a new hybrid formalism to aerosol gas phase interaction is presented within the framework of the H2SO4/HNO3/HCl/NH3 system and a modal approach of aerosol size discretisation. The formalism is distinct from prior hybrid approaches in as much as no a priori assumption on the nature of the regime a particular aerosol mode is in is made. Whether a particular mode is set to be in the equilibrium or the transitory regime is continuously determined during each time increment against relevant criteria considering the estimated equilibration time interval and the interdependence of the aerosol modes relative to the partitioning of the dissolving species. Doing this the aerosol composition range of numerical stiffness due to species interaction during transient dissolution is effectively eluded, and the numerical expense of dissolution in the transient regime is reduced through the minimisation of the number of modes in this regime and a larger time step. Containment of the numerical expense of the modes in the equilibrium regime is ensured through the usage of either an analytical equilibrium solver that requires iteration among the equilibrium modes, or a simple numerical solver based on a differential approach that requires iteration among the chemical species. Both equilibrium solvers require iteration over the water content and the activity coefficients. Decision for using either one or the other solver is made upon the consideration of the actual equilibrating mechanism, either chemical interaction or gas phase partial pressure variation, respectively. The formalism should thus ally appropriate process simplification resulting in reasonable computation time to a high degree of real process conformity as it is ensured by a transitory representation of dissolution. The resulting effectiveness and limits of the formalism are illustrated with numerical examples.

A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains

USGS Publications Warehouse

Tadesse, Tsegaye; Brown, Jesslyn F.; Hayes, M.J.

2005-01-01

Droughts are normal climate episodes, yet they are among the most expensive natural disasters in the world. Knowledge about the timing, severity, and pattern of droughts on the landscape can be incorporated into effective planning and decision-making. In this study, we present a data mining approach to modeling vegetation stress due to drought and mapping its spatial extent during the growing season. Rule-based regression tree models were generated that identify relationships between satellite-derived vegetation conditions, climatic drought indices, and biophysical data, including land-cover type, available soil water capacity, percent of irrigated farm land, and ecological type. The data mining method builds numerical rule-based models that find relationships among the input variables. Because the models can be applied iteratively with input data from previous time periods, the method enables to provide predictions of vegetation conditions farther into the growing season based on earlier conditions. Visualizing the model outputs as mapped information (called VegPredict) provides a means to evaluate the model. We present prototype maps for the 2002 drought year for Nebraska and South Dakota and discuss potential uses for these maps.

Impacts of Rising Air Temperatures and Emissions Mitigation on Electricity Demand and Supply in the United States. A Multi-Model Comparison

DOE PAGES

McFarland, James; Zhou, Yuyu; Clarke, Leon; ...

2015-06-10

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less

Technical report series on global modeling and data assimilation. Volume 3: An efficient thermal infrared radiation parameterization for use in general circulation models

NASA Technical Reports Server (NTRS)

Suarex, Max J. (Editor); Chou, Ming-Dah

1994-01-01

A detailed description of a parameterization for thermal infrared radiative transfer designed specifically for use in global climate models is presented. The parameterization includes the effects of the main absorbers of terrestrial radiation: water vapor, carbon dioxide, and ozone. While being computationally efficient, the schemes compute very accurately the clear-sky fluxes and cooling rates from the Earth's surface to 0.01 mb. This combination of accuracy and speed makes the parameterization suitable for both tropospheric and middle atmospheric modeling applications. Since no transmittances are precomputed the atmospheric layers and the vertical distribution of the absorbers may be freely specified. The scheme can also account for any vertical distribution of fractional cloudiness with arbitrary optical thickness. These features make the parameterization very flexible and extremely well suited for use in climate modeling studies. In addition, the numerics and the FORTRAN implementation have been carefully designed to conserve both memory and computer time. This code should be particularly attractive to those contemplating long-term climate simulations, wishing to model the middle atmosphere, or planning to use a large number of levels in the vertical.

Mass and tracer transport within oceanic Lagrangian coherent vortices as diagnosed in a global mesoscale eddying climate model

NASA Astrophysics Data System (ADS)

Tarshish, Nathaniel; Abernathey, Ryan; Dufour, Carolina; Frenger, Ivy; Griffies, Stephen

2017-04-01

Transient ocean mesoscale fluctuations play a central role in the global climate system, transporting climate relevant tracers such as heat and carbon. In satellite observations and numerical simulations, mesoscale vortices feature prominently as collectively rotating regions that remain visibly coherent. Prior studies on transport from ocean vortices typically rely on Eulerian identification methods, in which vortices are identified by selecting closed contours of Eulerian fields (e.g. sea surface height, or the Okubo-Weiss parameter) that satisfy geometric criteria and anomaly thresholds. In contrast, recent studies employ Lagrangian analysis of virtual particle trajectories initialized within the selected Eulerian contours, revealing significant discrepancies between the advection of the contour's material interior and the evolution of the Eulerian field contour. This work investigates the global mass and tracer transport associated with materially coherent surface ocean vortices. Further, it addresses differences between Eulerian and Lagrangian analyses for the detection of vortices. To do so, we use GFDL's CM2.6 coupled climate model with 5-10km horizontal grid spacing. We identify coherent vortices in CM2.6 by implementing the Rotationally Coherent Lagrangian Vortex (RCLV) framework, which recently emerged from dynamical systems theory. This approach involves the numerical advection of millions of Lagrangian particles and guarantees material coherence by construction. We compute the statistics, spatial distribution, and lifetimes of coherent vortices in addition to calculating the associated mass and tracer transports. We offer compelling evidence that Eulerian vortex methods are poorly suited to answer questions of mass and tracer transport.

The interaction of climate change and methane hydrates

USGS Publications Warehouse

Ruppel, Carolyn D.; Kessler, John D.

2017-01-01

Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perception that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.

The interaction of climate change and methane hydrates

NASA Astrophysics Data System (ADS)

Ruppel, Carolyn D.; Kessler, John D.

2017-03-01

Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perception that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.

Forecasting the evolution in the mixing regime of a deep subalpine lake under climate change scenarios through numerical modelling (Lake Maggiore, Northern Italy/Southern Switzerland)

NASA Astrophysics Data System (ADS)

Fenocchi, Andrea; Rogora, Michela; Sibilla, Stefano; Ciampittiello, Marzia; Dresti, Claudia

2018-01-01

The impact of air temperature rise is eminent for the large deep lakes in the Italian subalpine district, climate change being caused there by both natural phenomena and anthropogenic greenhouse-gases (GHG) emissions. These oligomictic lakes are experiencing a decrease in the frequency of winter full turnover and an intensification of stability. As a result, hypolimnetic oxygen concentrations are decreasing and nutrients are accumulating in bottom water, with effects on the whole ecosystem functioning. Forecasting the future evolution of the mixing pattern is relevant to assess if a reduction in GHG releases would be able to revert such processes. The study focuses on Lake Maggiore, for which the thermal structure evolution under climate change in the 2016-2085 period was assessed through numerical simulations, performed with the General Lake Model (GLM). Different prospects of regional air temperature rise were considered, given by the Swiss Climate Change Scenarios CH2011. Multiple realisations were performed for each scenario to obtain robust statistical predictions, adopting random series of meteorological data produced with the Vector-Autoregressive Weather Generator (VG). Results show that a reversion in the increasing thermal stability would be possible only if global GHG emissions started to be reduced by 2020, allowing an equilibrium mixing regime to be restored by the end of the twenty-first century. Otherwise, persistent lack of complete-mixing, severe water warming and extensive effects on water quality are to be expected for the centuries to come. These projections can be extended to the other lakes in the subalpine district.

The interaction of climate change and methane hydrates

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

Ruppel, Carolyn D.; Kessler, John D.

Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perceptionmore » that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.« less

The interaction of climate change and methane hydrates

DOE PAGES

Ruppel, Carolyn D.; Kessler, John D.

2016-12-14

Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perceptionmore » that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.« less

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

The meaning and measurement of implementation climate

PubMed Central

2011-01-01

Background Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study. Discussion Implementation climate differs from constructs such as organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual-level theories of behavior change could be more useful in explaining implementation effectiveness. Summary This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use. PMID:21781328

Precipitation Estimates for Hydroelectricity

NASA Technical Reports Server (NTRS)

Tapiador, Francisco J.; Hou, Arthur Y.; de Castro, Manuel; Checa, Ramiro; Cuartero, Fernando; Barros, Ana P.

2011-01-01

Hydroelectric plants require precise and timely estimates of rain, snow and other hydrometeors for operations. However, it is far from being a trivial task to measure and predict precipitation. This paper presents the linkages between precipitation science and hydroelectricity, and in doing so it provides insight into current research directions that are relevant for this renewable energy. Methods described include radars, disdrometers, satellites and numerical models. Two recent advances that have the potential of being highly beneficial for hydropower operations are featured: the Global Precipitation Measuring (GPM) mission, which represents an important leap forward in precipitation observations from space, and high performance computing (HPC) and grid technology, that allows building ensembles of numerical weather and climate models.

Development of a Cloud Resolving Model for Heterogeneous Supercomputers

NASA Astrophysics Data System (ADS)

Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C.

2017-12-01

A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction.

Impact of climate variations on Managed Aquifer Recharge infiltration basins.

NASA Astrophysics Data System (ADS)

Barquero, Felix; Stefan, Catalin

2017-04-01

KEYWORDS: Managed Aquifer Recharge, field scale infiltration unit, climatic conditions, numerical model Managed Aquifer Recharge (MAR) is a technique that is gaining more attention as a sustainable alternative for areas where water scarcity is increasing. Main concept relies on facilitating the vertical infiltration of a source of fresh water (river water, rainwater, reclaimed water, etc). The groundwater acts as storage of water for further use in the future, for example in times of water scarcity. In some MAR types the soil itself can be used even as a filter for the removal of specific organic and inorganic compounds. In order to promote the benefits of MAR in different zones of the globe with variable climate conditions, including the effects of climate change, a numerical model (HYDRUS 2D/3D) is being set up. Coupled with the model a field-scale rapid infiltration unit (4m x 5m x 1.5m) was constructed with the capacity to log different MAR key parameters in the soil (tension, water content, temperature and electrical conductivity) in space and time. These data will feed the model for its calibration using specific hydrogeological characteristics of the packing material and hydraulic characteristics of the infiltrated fluid. The unit is located in the city of Pirna (German), 200 m north from the Elbe River where the groundwater level varies seasonally between 6 and 9 m below the ground surface. Together with the field scale rapid infiltration unit, a set of multi-parametric sensors (measuring in time: water stage, electrical conductivity, dissolved oxygen and temperature) in six monitoring wells, located on the basin surroundings, were installed. The purpose of these sensors is to estimate, via tracer experiments, the time that the infiltrated water needed to reach the groundwater and the flow speed in which it travelled once it reached the saturated zone. Once calibrated, the model will be able to estimate the flow behaviour under variable climate conditions (temperature, precipitation and evaporation), representative for different climatic zones in the globe. The simulation results of the different climate models reported by the IPCC will also be considered for critical zones where fresh water availability will decrease considerably. In the field, the first results confirmed the arrival, after 14 days of travel time, of the infiltrated river water front to the monitoring wells located next to the infiltration unit. Further tracer experiments have to be performed in order to catch a stronger breakthrough curve in more than one observation point. Interesting open questions arise from the data stored in the trench sensors. How the change of the travel velocity depends on different external parameters like time of operation, cyclic wetting and drying regime and temperature, will be analysed together with the results of the ongoing experiments.

ELICITED EXPERT PERCEPTIONS FOR CLIMATE CHANGE RISKS AND ADAPTATION IN AGRICULTURE AND FOOD PRODUCTION THROUGH MENTAL MODELS APPROACH

NASA Astrophysics Data System (ADS)

Suda, Eiko; Kubota, Hiromi; Baba, Kenshi; Hijioka, Yasuaki; Takahashi, Kiyoshi; Hanasaki, Naota

Impacts of climate change have become obvious in agriculture and food production in Japan these days, and researches to adapt to their risks have been conducted as a key effort to cope with the climate change. Numerous scientific findings on climate change impacts have been presented so far; however, prospective risks to be adapted to and their management in the context of individual on-site situations have not been investigated in detail. The structure of climate change risks and their management vary depending on geographical and social features in the regions where the adaptation options should be applied; therefore, a practical adaptation strategy should consider actual on-site situations. This study intended to clarify climate change risks to be adapted to in the Japanese agricultural sector, and factors to be considered in adaptation options, for encouragement of decision-making on adaptation implementation in the field. Semi-structured individual interviews have been conducted with 9 multidisciplinary experts engaging in climate change impacts research in agricultural production, economics, engineering, policy, and so on. Based on the results of the interviews, and the latest literatures available for risk assessment and adaptation, an expert mental model including their perceptions which cover the process from climate change impacts assessment to adaptation has been developed. The prospective risks, adaptation options, and issues to be examined to progress the development of practical and effective adaptation options and to support individual or social decision-making, have been shown on the developed expert mental model. It is the basic information for developing social communication and stakeholders cooperations in climate change adaptation strategies in agriculture and food production in Japan.

Numerical Hindcast Experiments for Study Tropical Convections and MJO Events during Year of Tropical Convection

NASA Astrophysics Data System (ADS)

Chern, J.; Tao, W.; Shen, B.

2011-12-01

The Madden-Julian oscillation (MJO) is the dominant component of intraseasonal variability in the tropic. It interacts and influences a wide range of weather and climate phenomena across different temporal and spatial scales. Despite the important role the MJO plays in the weather and climate system, past multi-model MJO intercomparison studies have shown that current global general circulation models (GCMs) still have considerable shortcomings in representing and forecasting this phenomenon. To improve representation of MJO and tropical convective cloud systems in global model, an Multiscale Modeling Framework (MMF) in which a cloud-resolving model takes the place of the sing-column cumulus parameterization used in convectional GCMs has been successfully developed at NAAS Goddard (Tao et al. 2009). To evaluate and improve the ability of this modeling system in representation and prediction of the MJO, several numerical hindcast experiments of a few selected MJO events during YOTC have been carried out. The ability of the model to simulate the MJO events is examined using diagnostic and skill metrics developed by the CLIVAR MJO Working Group Project as well as comparisons with a high-resolution global mesoscale model simulations, satellite observations, and analysis dataset. Several key variables associated with the MJO are investigated, including precipitation, outgoing longwave radiation, large-scale circulation, surface latent heat flux, low-level moisture convergence, vertical structure of moisture and hydrometers, and vertical diabatic heating profiles to gain insight of cloud processes associated with the MJO events.

Modeling groundwater quality in an arid agricultural environment in the face of an uncertain climate: the case of Mewat District, India

NASA Astrophysics Data System (ADS)

Weber, M. C.; Ward, A. S.; Muste, M.

2014-12-01

The salinization of groundwater resources is a widespread problem in arid agricultural environments. In Mewat District (Haryana, India), groundwater salinity has rendered much of the accessible supply unfit for human consumption or agriculture. Historically, this closed basin retained fresh pockets of water at the foothills of the Aravalli Hills, where monsoonal precipitation runoff from the mountains was recharged through infiltration or facilitated by man-made structures. To date, an increasing number of pumps supply the region with fresh water for consumption and agriculture leading to shrinking the freshwater zone at an accelerated pace. The potential for increased human consumption corroborated with the effects of climate change bring uncertainty about the future of water security for the Mewat communities, most of them critically bound to the existence of local water. This study addresses the sustainability of the freshwater supply under a range of land interventions and climate scenarios, using a 2-D groundwater flow and transport model. Our results quantify potential futures for this arid, groundwater-dependent location, using numerical groundwater modeling to quantify interactions between human water use, infrastructure, and climate. Outcomes of this modeling study will inform an NGO active in the area on sustainable management of groundwater resources.

Effect of climate change on shoreline shifts at a straight and continuous coast

NASA Astrophysics Data System (ADS)

Rajasree, B. R.; Deo, M. C.; Sheela Nair, L.

2016-12-01

The prediction of the rate of shoreline shifts as well as that of erosion and accretion over future at a given location is traditionally done on the basis of analysis of past wave data. However under the changing climate affected by global warming it is better done considering the projected wave conditions over the future. The same is demonstrated in this work with respect to a stretch of coastline at 'Udupi' along the west coast of India. The shoreline changes in the past are first determined with the help of historic satellite images. A numerical shoreline model is later run on the basis of wave simulations of past 35 years as well as future 35 years. The latter wave conditions are obtained from wind projections corresponding to a high resolution regional climate model run for a moderate pathway of global warming. Alternatively prediction of the changes over future 35 years is also made by using the soft computing tool of artificial neural network (ANN) trained with the help of past satellite images. The results indicate that the area under consideration presently undergoes considerable erosion and this process will accelerate in future. The volume of annual sediment transport will also substantially increase over the future. The alternative computations made with the help of an ANN confirmed the future rising trend of erosion, albeit at smaller rate than the numerically predicted one.

An analytically based numerical method for computing view factors in real urban environments

NASA Astrophysics Data System (ADS)

Lee, Doo-Il; Woo, Ju-Wan; Lee, Sang-Hyun

2018-01-01

A view factor is an important morphological parameter used in parameterizing in-canyon radiative energy exchange process as well as in characterizing local climate over urban environments. For realistic representation of the in-canyon radiative processes, a complete set of view factors at the horizontal and vertical surfaces of urban facets is required. Various analytical and numerical methods have been suggested to determine the view factors for urban environments, but most of the methods provide only sky-view factor at the ground level of a specific location or assume simplified morphology of complex urban environments. In this study, a numerical method that can determine the sky-view factors ( ψ ga and ψ wa ) and wall-view factors ( ψ gw and ψ ww ) at the horizontal and vertical surfaces is presented for application to real urban morphology, which are derived from an analytical formulation of the view factor between two blackbody surfaces of arbitrary geometry. The established numerical method is validated against the analytical sky-view factor estimation for ideal street canyon geometries, showing a consolidate confidence in accuracy with errors of less than 0.2 %. Using a three-dimensional building database, the numerical method is also demonstrated to be applicable in determining the sky-view factors at the horizontal (roofs and roads) and vertical (walls) surfaces in real urban environments. The results suggest that the analytically based numerical method can be used for the radiative process parameterization of urban numerical models as well as for the characterization of local urban climate.

Pollen-Based Inverse Modelling versus Data Assimilation, two Different Ways to Consider Priors in Paleoclimate Reconstruction: Application to the Mediterranean Holocene

NASA Astrophysics Data System (ADS)

Guiot, J.

2017-12-01

In the last decades, climate reconstruction has much evolved. A important step has been passed with inverse modelling approach proposed by Guiot et al (2000). It is based on appropriate algorithms in the frame of the Bayesian statistical theory to estimate the inputs of a vegetation model when the outputs are known. The inputs are the climate variables that we want to reconstruct and the outputs are vegetation characteristics, which can be compared to pollen data. The Bayesian framework consists in defining prior distribution of the wanted climate variables and in using data and a model to estimate posterior probability distribution. The main interest of the method is the possibility to set different values of exogenous variables as the atmospheric CO2 concentration. The fact that the CO2 concentration has an influence on the photosynthesis and that its level is different between the calibration period (the 20th century) and the past, there is an important risk of biases on the reconstructions. After that initial paper, numerous papers have been published showing the interested of the method. In that approach, the prior distribution is fixed by educated guess of by using complementary information on the expected climate (other proxies or other records). In the data assimilation approach, the prior distribution is provided by a climate model. The use of a vegetation model together with proxy data, enable to calculate posterior distributions. Data assimilation consists in constraining climate model to reproduce estimates relatively close to the data, taking into account the respective errors of the data and of the climate model (Dubinkina et al, 2011). We compare both approaches using pollen data for the Holocene from the Mediterranean. Pollen data have been extracted from the European Pollen Database. The earth system model, LOVECLIM, is run to simulate Holocene climate with appropriate boundary conditions and realistic forcing. Simulated climate variables (temperature, precipitation and sunshine) are used as the forcing parameters to a vegetation model, BIOME4, that calculates the equilibrium distribution of vegetation types and associated phenological, hydrological and biogeochemical properties. BIOME4 output, constrained with the pollen observations, are off-line coupled using a particle filter technique.

Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models

PubMed Central

Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya

2016-01-01

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182

Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

NASA Astrophysics Data System (ADS)

Ocko, Ilissa B.; Ginoux, Paul A.

2017-04-01

Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud-Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

Canary in the coal mine: Historical oxygen decline in the Gulf of St. Lawrence due to large scale climate changes

NASA Astrophysics Data System (ADS)

Claret, M.; Galbraith, E. D.; Palter, J. B.; Gilbert, D.; Bianchi, D.; Dunne, J. P.

2016-02-01

The regional signature of anthropogenic climate change on the atmosphere and upper ocean is often difficult to discern from observational timeseries, dominated as they are by decadal climate variability. Here we argue that a long-term decline of dissolved oxygen concentrations observed in the Gulf of S. Lawrence (GoSL) is consistent with anthropogenic climate change. Oxygen concentrations in the GoSL have declined markedly since 1930 due primarily to an increase of oxygen-poor North Atlantic Central Waters relative to Labrador Current Waters (Gilbert et al. 2005). We compare these observations to a climate warming simulation using a very high-resolution global coupled ocean-atmospheric climate model. The numerical model (CM2.6), developed by the Geophysical Fluid Dynamics Laboratory, is strongly eddying and includes a biogeochemical module with dissolved oxygen. The warming scenario shows that oxygen in the GoSL decreases and it is associated to changes in western boundary currents and wind patterns in the North Atlantic. We speculate that the large-scale changes behind the simulated decrease in GoSL oxygen have also been at play in the real world over the past century, although they are difficult to resolve in noisy atmospheric data.

Late Pleistocene climate drivers of early human migration.

PubMed

Timmermann, Axel; Friedrich, Tobias

2016-10-06

On the basis of fossil and archaeological data it has been hypothesized that the exodus of Homo sapiens out of Africa and into Eurasia between ~50-120 thousand years ago occurred in several orbitally paced migration episodes. Crossing vegetated pluvial corridors from northeastern Africa into the Arabian Peninsula and the Levant and expanding further into Eurasia, Australia and the Americas, early H. sapiens experienced massive time-varying climate and sea level conditions on a variety of timescales. Hitherto it has remained difficult to quantify the effect of glacial- and millennial-scale climate variability on early human dispersal and evolution. Here we present results from a numerical human dispersal model, which is forced by spatiotemporal estimates of climate and sea level changes over the past 125 thousand years. The model simulates the overall dispersal of H. sapiens in close agreement with archaeological and fossil data and features prominent glacial migration waves across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. The findings document that orbital-scale global climate swings played a key role in shaping Late Pleistocene global population distributions, whereas millennial-scale abrupt climate changes, associated with Dansgaard-Oeschger events, had a more limited regional effect.

Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

Late Pleistocene climate drivers of early human migration

NASA Astrophysics Data System (ADS)

Timmermann, Axel; Friedrich, Tobias

2016-10-01

On the basis of fossil and archaeological data it has been hypothesized that the exodus of Homo sapiens out of Africa and into Eurasia between ~50-120 thousand years ago occurred in several orbitally paced migration episodes. Crossing vegetated pluvial corridors from northeastern Africa into the Arabian Peninsula and the Levant and expanding further into Eurasia, Australia and the Americas, early H. sapiens experienced massive time-varying climate and sea level conditions on a variety of timescales. Hitherto it has remained difficult to quantify the effect of glacial- and millennial-scale climate variability on early human dispersal and evolution. Here we present results from a numerical human dispersal model, which is forced by spatiotemporal estimates of climate and sea level changes over the past 125 thousand years. The model simulates the overall dispersal of H. sapiens in close agreement with archaeological and fossil data and features prominent glacial migration waves across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. The findings document that orbital-scale global climate swings played a key role in shaping Late Pleistocene global population distributions, whereas millennial-scale abrupt climate changes, associated with Dansgaard-Oeschger events, had a more limited regional effect.

Global lake evaporation accelerated by changes in surface energy allocation in a warmer climate

NASA Astrophysics Data System (ADS)

Wang, Wei; Lee, Xuhui; Xiao, Wei; Liu, Shoudong; Schultz, Natalie; Wang, Yongwei; Zhang, Mi; Zhao, Lei

2018-06-01

Lake evaporation is a sensitive indicator of the hydrological response to climate change. Variability in annual lake evaporation has been assumed to be controlled primarily by the incoming surface solar radiation. Here we report simulations with a numerical model of lake surface fluxes, with input data based on a high-emissions climate change scenario (Representative Concentration Pathway 8.5). In our simulations, the global annual lake evaporation increases by 16% by the end of the century, despite little change in incoming solar radiation at the surface. We attribute about half of this projected increase to two effects: periods of ice cover are shorter in a warmer climate and the ratio of sensible to latent heat flux decreases, thus channelling more energy into evaporation. At low latitudes, annual lake evaporation is further enhanced because the lake surface warms more slowly than the air, leading to more long-wave radiation energy available for evaporation. We suggest that an analogous change in the ratio of sensible to latent heat fluxes in the open ocean can help to explain some of the spread among climate models in terms of their sensitivity of precipitation to warming. We conclude that an accurate prediction of the energy balance at the Earth's surface is crucial for evaluating the hydrological response to climate change.

A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph

2016-04-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they 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. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.

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.

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

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

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiativemore » quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.« less

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.

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.

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

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

NASA Technical Reports Server (NTRS)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Plant community dynamics and restoring Louisiana's wetland ecosystems

NASA Astrophysics Data System (ADS)

Duke-Sylvester, S. M.; Visser, J.

2017-12-01

We have developed a computational model of plant community dynamics. Our model is designed to evaluate the effects of management actions on the structure and health of Louisiana's coastal wetland plant communities. A number of projects have been initiated or proposed to preserve and restore this ecosystem while still allowing the area to support Louisiana's economy. These projects involve both modification of the flow of freshwater as well as restoring natural wetlands. Evaluating the long term effects of these projects is complex and involves numerous moving pieces operating over an extensive and diverse landscape. The situation is further complicated by in sea level rise and climate change associated with global warming. The vegetation model is part of a larger set of linked models that include hydrology and soil morphology. Using hydrological conditions projected by the linked hydrology models, we are able to evaluate the effects of anthropogenic and climatic changes on Louisiana's wetland plant communities. Unique features of our model include replacing the division of wetlands into coarse groups defined by salinity conditions with species level responses to environmental conditions and extending the spatial scale of modeling to encompass the entirety of Louisiana's Gulf coast. Model results showing the potential impact of alternative management and climate change scenarios are presented.

Application of empirical and dynamical closure methods to simple climate models

NASA Astrophysics Data System (ADS)

Padilla, Lauren Elizabeth

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

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

NASA Astrophysics Data System (ADS)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

NASA Astrophysics Data System (ADS)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) scientific advances and future west pacific coordination

NASA Astrophysics Data System (ADS)

Ganachaud, A. S.; Sprintall, J.; Lin, X.; Ando, K.

2016-02-01

The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR (Climate Variability and Predictability). The key objectives are to understand the Southwest Pacific Ocean circulation and Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. It was designed to measure and monitor the ocean circulation, and to validate and improve numerical models. South Pacific oceanic waters are carried from the subtropical gyre centre in the westward flowing South Equatorial Current (SEC), towards the southwest Pacific-a major circulation pathway that redistributes water from the subtropics to the equator and Southern Ocean. Water transit through the Coral and Solomon Seas is potentially of great importance to tropical climate prediction because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate ENSO and produce basin-scale climate feedbacks. On average, the oceanic circulation is driven by the Trade Winds, and subject to substantial variability, related with the SPCZ position and intensity. The circulation is complex, with the SEC splitting into zonal jets upon encountering island archipelagos, before joining either the East Australian Current or the New Guinea Costal UnderCurrent towards the equator. SPICE included large, coordinated in situ measurement programs and high resolution numerical simulations of the area. After 8 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. We will review the recent advancements and discuss our current knowledge gaps and important emerging research directions. In particular we will discuss how SPICE, along with the Northwestern Pacific Ocean Circulation and Climate Experiment (NPOCE) and Indonesian ThroughFlow (ITF) programs could evolve toward an integrative observing system under CLIVAR coordination.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

CMIP5-based global wave climate projections including the entire Arctic Ocean

NASA Astrophysics Data System (ADS)

Casas-Prat, M.; Wang, X. L.; Swart, N.

2018-03-01

This study presents simulations of the global ocean wave climate corresponding to the surface winds and sea ice concentrations as simulated by five CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models for the historical (1979-2005) and RCP8.5 scenario future (2081-2100) periods. To tackle the numerical complexities associated with the inclusion of the North Pole, the WAVEWATCH III (WW3) wave model was used with a customized unstructured Spherical Multi-Cell grid of ∼100 km offshore and ∼50 km along coastlines. The climate model simulated wind and sea ice data, and the corresponding WW3 simulated wave data, were evaluated against reanalysis and hindcast data. The results show that all the five sets of wave simulations projected lower waves in the North Atlantic, corresponding to decreased surface wind speeds there in the warmer climate. The selected CMIP5 models also consistently projected an increase in the surface wind speed in the Southern Hemisphere (SH) mid-high latitudes, which translates in an increase in the WW3 simulated significant wave height (Hs) there. The higher waves are accompanied with increased peak wave period and increased wave age in the East Pacific and Indian Oceans, and a significant counterclockwise rotation in the mean wave direction in the Southern Oceans. The latter is caused by more intense waves from the SH traveling equatorward and developing into swells. Future wave climate in the Arctic Ocean in summer is projected to be predominantly of mixed sea states, with the climatological mean of September maximum Hs ranging mostly 3-4 m. The new waves approaching Arctic coasts will be less fetch-limited as ice retreats since a predominantly southwards mean wave direction is projected in the surrounding seas.

Climatic change impacts on water balance of the Upper Jordan River

NASA Astrophysics Data System (ADS)

Heckl, A.; Kunstmann, H.

2009-04-01

The Eastern Mediterranean and Near East (EM/NE) is an extremely water scarce environment. It is expected that problems will increase due to climate change and population growth. The impact of climate change on water availability in EM/NE and in particular the Jordan River catchment is investigated in this study. Focus is set on the Upper Jordan River catchment (UJC) as it provides 1/3rd of freshwater resources in Israel and Palestine. It is a hydro-geologically extremely complex region with karstic groundwater flow and an orography with steep gradients. The methods used are high resolution coupled regional climate - hydrology simulations. Two IPCC scenarios (A2 and B2) of the global climate model ECHAM4 have been dynamically downscaled using the non-hydrostatic meteorological model MM5 in two nesting steps with resolutions of 54x54 km2 and 18x18 km2 for the period 1961-2099, whereby the time slice 1961-1989 represents the current climate. The meteorological fields are used to drive the physically based hydrological model WaSiM applied to the UJC. The hydrological model computes in detail the surface and subsurface water flow and water balance in a horizontal resolution of 450 x 450 m2 and dynamically couples to a 2-dim numerical groundwater model. Parameters like surface runoff, groundwater recharge, soil moisture and evapotranspiration can be extracted. Results show in both scenarios increasing yearly mean temperatures up to 4-5 K until 2099 and decreasing yearly precipitation amounts up to 25% (scenario A2). The effect on the water balance of the UJC are reduced discharge and groundwater recharge, increased evaporation and reduction of snow cover in the mountains which usually serves as an important freshwater reservoir for the summer discharge.

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.

Analyzing Multidecadal Trends in Cloudiness Over the Subtropical Andes Mountains of South America Using a Regional Climate Model.

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Russell, A.; Gnanadesikan, A.

2016-12-01

Satellite-based products indicate that many parts of South America have been experiencing increases in outgoing longwave radiation (OLR) and corresponding decreases in cloudiness over the last few decades, with the strongest trends occurring in the subtropical Andes Mountains - an area that is highly vulnerable to climate change due to its reliance on glacial melt for dry-season runoff. Changes in cloudiness may be contributing to increases in atmospheric temperature, thereby raising the freezing level height (FLH) - a critical geophysical parameter. Yet these trends are only partially captured in reanalysis products, while AMIP climate models generally show no significant trend in OLR over this timeframe, making it difficult to determine the underlying drivers. Therefore, controlled numerical experiments with a regional climate model are performed in order to investigate drivers of the observed OLR and cloudiness trends. The Weather Research and Forecasting model (WRF) is used here because it offers several advantages over global models, including higher resolution - a critical asset in areas of complex topography - as well as flexible physics, parameterization, and data assimilation capabilities. It is likely that changes in the mean states and meridional gradients of SSTs in the Pacific and Atlantic oceans are driving regional trends in clouds. A series of lower boundary manipulations are performed with WRF to determine to what extent changes in SSTs influence regional OLR.

Modeling aquifer behaviour under climate change and high consumption: Case study of the Sfax region, southeast Tunisia

NASA Astrophysics Data System (ADS)

Boughariou, Emna; Allouche, Nabila; Jmal, Ikram; Mokadem, Naziha; Ayed, Bachaer; Hajji, Soumaya; Khanfir, Hafedh; Bouri, Salem

2018-05-01

The water resources are exhausted by the increasing demand related to the population growth. They are also affected by climate circumstances, especially in arid and semi-arid regions. These areas are already undergoing noticeable shortages and low annual precipitation rate. This paper presents a numerical model of the Sfax shallow aquifer system that was developed by coupling the geographical information system tool ArcGIS 9.3 and ground water modeling system GMS6.5's interface, ground water flow modeling MODFLOW 2000. Being in coastal city and having an arid climate with high consumption rates, this aquifer is undergoing a hydraulic stress situation. Therefore, the groundwater piezometric variations were calibrated for the period 2003-2013 and simulated based on two scenarios; first the constant and growing consumption and second the rainfall forecast as a result of climate change scenario released by the Tunisian Ministry of Agriculture and Water Resources and the German International Cooperation Agency "GIZ" using HadCM3 as a general circulation model. The piezometric simulations globally forecast a decrease that is about 0.5 m in 2020 and 1 m in 2050 locally the decrease is more pronounced in "Chaffar" and "Djbeniana" regions and that is more evident for the increasing consumption scenario. The two scenarios announce a quantitative degradation of the groundwater by the year 2050 with an alarming marine intrusion in "Djbeniana" region.

A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

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

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

Determination of the spatial variability of temperature and moisture near a tropical Pacific island with MTI satellite images

NASA Astrophysics Data System (ADS)

Kurzeja, Robert J.; O'Steen, Byron L.; Pendergast, Malcolm M.

2002-01-01

The Tropical Pacific Island of Nauru is a US DOE ARM observation site that monitors tropical climate and atmospheric radiation. This observation site is ideal for validating MTI images because of the extensive deployment of continuously operating instruments. MTI images are also useful in assessing the effect of the island on the ocean climate and on the ARM data. An MTI image has been used to determine the spatial distribution of water vapor and sea-surface temperature near the island. The results are compared with a three-dimensional numerical model simulation.

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.

Comparative Assessment of a New Hydrological Modelling Approach for Prediction of Runoff in Gauged and Ungauged Basins, and Climate Change Impacts Assessment: A Case Study from Benin.

NASA Astrophysics Data System (ADS)

GABA, C. O. U.; Alamou, E.; Afouda, A.; Diekkrüger, B.

2016-12-01

Assessing water resources is still an important challenge especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we investigate a new modelling approach based on the Physics Principle of Least Action which was first applied to the Bétérou catchment in Benin and gave very good results. The study presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODHYPMA was applied to sixteen (16) subcatchments in Bénin, West Africa. Its performance was compared to two well-known lumped conceptual models, the GR4J and HBV models. The model was successfully calibrated and validated and showed a good performance in most catchments. The analysis revealed that the three models have similar performance and timing errors. But in contrary to other models, MODHYMA is subject to a less loss of performance from calibration to validation. In order to evaluate the usefulness of our model for the prediction of runoff in ungauged basins, model parameters were estimated from the physical catchments characteristics. We relied on statistical methods applied on calibrated model parameters to deduce relationships between parameters and physical catchments characteristics. These relationships were further tested and validated on gauged basins that were considered ungauged. This regionalization was also performed for GR4J model.We obtained NSE values greater than 0.7 for MODHYPMA while the NSE values for GR4J were inferior to 0.5. In the presented study, the effects of climate change on water resources in the Ouémé catchment at the outlet of Savè (about 23 500 km2) are quantified. The output of a regional climate model was used as input to the hydrological models.Computed within the GLOWA-IMPETUS project, the future climate projections (describing a rainfall reduction of up to 15%) are derived from the regional climate model REMO driven by the global ECHAM model.The results reveal a significant decrease in future water resources (of -66% to -53% for MODHYPMA and of -59% to -46% for GR4J) for the IPCC climate scenarios A1B and B1.

Modelling the feedbacks between mass balance, ice flow and debris transport to predict the response to climate change of debris-covered glaciers in the Himalaya

NASA Astrophysics Data System (ADS)

Rowan, Ann V.; Egholm, David L.; Quincey, Duncan J.; Glasser, Neil F.

2015-11-01

Many Himalayan glaciers are characterised in their lower reaches by a rock debris layer. This debris insulates the glacier surface from atmospheric warming and complicates the response to climate change compared to glaciers with clean-ice surfaces. Debris-covered glaciers can persist well below the altitude that would be sustainable for clean-ice glaciers, resulting in much longer timescales of mass loss and meltwater production. The properties and evolution of supraglacial debris present a considerable challenge to understanding future glacier change. Existing approaches to predicting variations in glacier volume and meltwater production rely on numerical models that represent the processes governing glaciers with clean-ice surfaces, and yield conflicting results. We developed a numerical model that couples the flow of ice and debris and includes important feedbacks between debris accumulation and glacier mass balance. To investigate the impact of debris transport on the response of a glacier to recent and future climate change, we applied this model to a large debris-covered Himalayan glacier-Khumbu Glacier in Nepal. Our results demonstrate that supraglacial debris prolongs the response of the glacier to warming and causes lowering of the glacier surface in situ, concealing the magnitude of mass loss when compared with estimates based on glacierised area. Since the Little Ice Age, Khumbu Glacier has lost 34% of its volume while its area has reduced by only 6%. We predict a decrease in glacier volume of 8-10% by AD2100, accompanied by dynamic and physical detachment of the debris-covered tongue from the active glacier within the next 150 yr. This detachment will accelerate rates of glacier decay, and similar changes are likely for other debris-covered glaciers in the Himalaya.

Long-term evolution of a small ice cap in Greenland: a dynamic perspective from numerical flow modelling

NASA Astrophysics Data System (ADS)

Vieli, Andreas; Lane, Timothy; Adamson, Kathryn

2017-04-01

Small ice caps at the periphery of the Greenland ice sheet are often close to the limit of existence and are therefore expected to respond more sensitively to climate change than the land-margin of the neighboring ice sheet. However, their past evolution and dynamic behavior is poorly understood and their use as climate indicators therefore remains so far limited. We here aim to provide a long-term dynamic reconstruction of Lyngmarksbraeen, a small (32km2) ice cap on Disko Island in West Greenland, with a particular focus on the little ice age (LIA, since 1200AD). We use a 2-dim. time-dependent numerical flow model (SIA) and a PDD-mass balance model in combination with historical observations, geomorphological mapping and exposure dating to simulate its long-term evolution and dynamic behaviour. We specifically focus on retreat since the LIA, which is well constrained by geomorphological evidence and historical maps and length records of several small outlet glaciers and data from local and regional climate stations (Qeqertarssuaq and Ilulisat). We also explore aspects related to flow dynamics and find that the dynamic state of this ice cap is, at any time, far from being balanced and is highly sensitive to the surface elevation mass balance feedback and results in an asynchronous response of the different outlets and hysteresis-type behaviour. The modelling is able to reproduce the observed LIA-extent and the almost continuous retreat over the last hundred years well. It further indicates that the ice cap was already dynamically inert since the 1960s. Today, the ice cap has lost almost its entire accumulation area and even without any further warming in the future, the ice cap is expected to vanish within a couple of decades.

How does the photosynthetic machinery of invasive perennial pepperweed allow it to adapt and respond to changes in California’s climate?

NASA Astrophysics Data System (ADS)

Runkle, B.; Sonnentag, O.; Detto, M.; Liang, X.; Dracup, J. A.; Baldocchi, D. D.

2009-12-01

Perennial pepperweed (Lepidium latifolium) is an ecological and economic nuisance to much of the western United States, where its invasion threatens a diverse set of land areas. We characterized the leaf-level parameters governing pepperweed’s photosynthesis through field measurements and determine through modelling simulations that it is well-adapted to resource procural in present and predicted future climates. These measurements are taken under field conditions for the duration of a long growing season (a nine month period in 2008) in a peatlands pasture in California’s Sacramento-San Juaquin River Delta. Through carbon and light response curves, pepperweed is found to have a high capacity for taking up carbon dioxide in either RuBP or Rubisco-limited situations, and its physiology is well-adapted to dry, hot and saline environments. Numerical modelling of the A-Ci curves suggests that internal (or mesophyll) conductance plays a negligible role in limiting carbon uptake. Pepperweed’s stomata are found to allow more conductance than predicted by models for periods of lower vapor pressure deficit, when it may be more water-use efficient to photosynthesize. Moreover, its high leaf nitrogen content (2-6% nitrogen by dry leaf mass), particularly at the start of the growing season, suggests a plant highly capable of out-competing native and economic species in acquisitioning local resources. These parameters are used in numerical exercises to move from the leaf to the field scale, where they are supported by eddy covariance measurements. This model is then used to evaluate and predict the response of pepperweed to seasonal and climatic change. The results presented here should provide a valuable point of comparison to ecologists and land managers interested in the spread of L. latifolium.

Grand challenges in understanding the interplay of climate and land changes

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing

2017-01-01

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Cenozoic climate evolution in Asian region and its influence on isotopic composition of precipitation

NASA Astrophysics Data System (ADS)

Botsyun, Svetlana; Donnadieu, Yannick; Sepulchre, Pierre; Risi, Camille; Fluteau, Frédéric

2015-04-01

The evolution of Asian climate during the Cenozoic as well as the onset of monsoon systems in this area is highly debated. Factors that control climate include the geographical position of continents, the land-sea distribution and altitude of orogens. In tern, several climatic parameters such as air temperature, precipitation amount and isotopic fractionation through mass-dependent processes impact precipitation δ18O lapse rate. Stable oxygen paleoaltimetry is considered to be a very efficient and widely applied technique, but the link between stable oxygen composition of precipitation and climate is not well established. To quantify the influence of paleogeography changes on climate and precipitation δ18O over Asia, the atmospheric general circulation model LMDZ-iso, with embedded stable oxygen isotopes, was used. For more realistic experiments, sea surface temperatures were calculated with the fully coupled model FOAM. Various scenarios of TP growth have been applied together with Paleocene, Eocene, Oligocene and Miocene boundary conditions. The results of our numerical modelling show a significant influence of paleogeography changes on the Asian climate. The retreat of the Paratethys ocean, the changes in latitudinal position of India, and the height of the Tibetan Plateau most likely control precipitation patterns over Asia and cause spatial and temporal isotopic variations linked with the amount effect. Indian Ocean currents restructuring during the Eocene induces a substantial warming over Asian continent. The adiabatic and non-adiabatic temperature effects explain some of δ18O signal variations. We highlight the importance of these multiple factor on paleoelevations estimates derived using oxygen stable isotopes.

The Effects of Positive Behavior Interventions and Support on Changing the Behavior of Red Zone Students

ERIC Educational Resources Information Center

Robinson, Fredrick

2012-01-01

In order to improve culture, safety, and climate, numerous schools nationwide are implementing Positive Behavior Interventions and Support (PBIS). The purpose of this study was to examine the effectiveness of the Positive Behavior Interventions and Support (PBIS) model for reducing high-risk behaviors of students identified as red zone. The…

A groundwater-flow model for the Treasure Valley and surrounding area, southwestern Idaho

USGS Publications Warehouse

Bartolino, James R.; Vincent, Sean

2017-04-17

The U.S. Geological Survey (USGS), in partnership with the Idaho Department of Water Resources (IDWR) and Idaho Water Resource Board (IWRB), will construct a numerical groundwater-flow model of the Treasure Valley and surrounding area. Resource managers will use the model to simulate potential anthropogenic and climatic effects on groundwater for water-supply planning and management. As part of model construction, the hydrogeologic understanding of the aquifer system will be updated with information collected during the last two decades, as well as new data collected for the study.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Nd isotopic structure of the Pacific Ocean 70-30 Ma and numerical evidence for vigorous ocean circulation and ocean heat transport in a greenhouse world

NASA Astrophysics Data System (ADS)

Thomas, Deborah J.; Korty, Robert; Huber, Matthew; Schubert, Jessica A.; Haines, Brian

2014-05-01

The oceanic meridional overturning circulation (MOC) is a crucial component of the climate system, impacting heat and nutrient transport, and global carbon cycling. Past greenhouse climate intervals present a paradox because their weak equator-to-pole temperature gradients imply a weaker MOC, yet increased poleward oceanic heat transport appears to be required to maintain these weak gradients. To investigate the mode of MOC that operated during the early Cenozoic, we compare new Nd isotope data with Nd tracer-enabled numerical ocean circulation and coupled climate model simulations. Assimilation of new Nd isotope data from South Pacific Deep Sea Drilling Project and Ocean Drilling Program Sites 323, 463, 596, 865, and 869 with previously published data confirm the hypothesized MOC characterized by vigorous sinking in the South and North Pacific 70 to 30 Ma. Compilation of all Pacific Nd isotope data indicates vigorous, distinct, and separate overturning circulations in each basin until 40 Ma. Simulations consistently reproduce South Pacific and North Pacific deep convection over a broad range of conditions, but cases using strong deep ocean vertical mixing produced the best data-model match. Strong mixing, potentially resulting from enhanced abyssal tidal dissipation, greater interaction of wind-driven internal wave activity with submarine plateaus, or higher than modern values of the geothermal heat flux enable models to achieve enhanced MOC circulation rates with resulting Nd isotope distributions consistent with the proxy data. The consequent poleward heat transport may resolve the paradox of warmer worlds with reduced temperature gradients.

A perspective on sustained marine observations for climate modelling and prediction

PubMed Central

Dunstone, Nick J.

2014-01-01

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow-down in surface global warming. PMID:25157195

Modelling the Phanerozoic carbon cycle and climate: constraints from the 87Sr/86Sr isotopic ratio of seawater

NASA Technical Reports Server (NTRS)

Francois, L. M.; Walker, J. C.

1992-01-01

A numerical model describing the coupled evolution of the biogeochemical cycles of carbon, sulfur, calcium, magnesium, phosphorus, and strontium has been developed to describe the long-term changes of atmospheric carbon dioxide and climate during the Phanerozoic. The emphasis is on the effects of coupling the cycles of carbon and strontium. Various interpretations of the observed Phanerozoic history of the seawater 87Sr/86Sr ratio are investigated with the model. More specifically, the abilities of continental weathering, volcanism, and surface lithology in generating that signal are tested and compared. It is suggested that the observed fluctuations are mostly due to a changing weatherability over time. It is shown that such a conclusion is very important for the modelling of the carbon cycle. Indeed, it implies that the conventional belief that the evolution of atmospheric carbon dioxide and climate on a long time scale is governed by the balance between the volcanic input of CO2 and the rate of silicate weathering is not true. Rather carbon exchanges between the mantle and the exogenic system are likely to have played a key role too. Further, the increase of the global weathering rates with increasing surface temperature and/or atmospheric CO2 pressure usually postulated in long-term carbon cycle and climate modelling is also inconsistent with the new model. Other factors appear to have modulated the weatherability of the continents through time, such as mountain building and the existence of glaciers and ice sheets. Based on these observations, a history of atmospheric carbon dioxide and climate during Phanerozoic time, consistent with the strontium isotopic data, is reconstructed with the model and is shown to be compatible with paleoclimatic indicators, such as the timing of glaciation and the estimates of Cretaceous paleotemperatures.

The origin of climate changes.

PubMed

Delecluse, P

2008-08-01

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

Quantifying effects of humans and climate on groundwater resources through modeling of volcanic-rock aquifers of Hawaii

NASA Astrophysics Data System (ADS)

Rotzoll, K.; Izuka, S. K.; Nishikawa, T.; Fienen, M. N.; El-Kadi, A. I.

2015-12-01

The volcanic-rock aquifers of Kauai, Oahu, and Maui are heavily developed, leading to concerns related to the effects of groundwater withdrawals on saltwater intrusion and streamflow. A numerical modeling analysis using the most recently available data (e.g., information on recharge, withdrawals, hydrogeologic framework, and conceptual models of groundwater flow) will substantially advance current understanding of groundwater flow and provide insight into the effects of human activity and climate change on Hawaii's water resources. Three island-wide groundwater-flow models were constructed using MODFLOW 2005 coupled with the Seawater-Intrusion Package (SWI2), which simulates the transition between saltwater and freshwater in the aquifer as a sharp interface. This approach allowed relatively fast model run times without ignoring the freshwater-saltwater system at the regional scale. Model construction (FloPy3), automated-parameter estimation (PEST), and analysis of results were streamlined using Python scripts. Model simulations included pre-development (1870) and current (average of 2001-10) scenarios for each island. Additionally, scenarios for future withdrawals and climate change were simulated for Oahu. We present our streamlined approach and preliminary results showing estimated effects of human activity on the groundwater resource by quantifying decline in water levels, reduction in stream base flow, and rise of the freshwater-saltwater interface.

The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines

NASA Astrophysics Data System (ADS)

Quataert, Ellen; Storlazzi, Curt; Rooijen, Arnold; Cheriton, Olivia; Dongeren, Ap

2015-08-01

A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.

New permafrost is forming around shrinking Arctic lakes, but will it last?

USGS Publications Warehouse

Briggs, Martin A.; Walvoord, Michelle Ann; McKenzie, Jeffrey M.; Voss, Clifford I.; Day-Lewis, Frederick D.; Lane, John W.

2014-01-01

Widespread lake shrinkage in cold regions has been linked to climate warming and permafrost thaw. Permafrost aggradation, however, has been observed within the margins of recently receded lakes, in seeming contradiction of climate warming. Here permafrost aggradation dynamics are examined at Twelvemile Lake, a retreating lake in interior Alaska. Observations reveal patches of recently formed permafrost within the dried lake margin, colocated with discrete bands of willow shrub. We test ecological succession, which alters shading, infiltration, and heat transport, as the driver of aggradation using numerical simulation of variably saturated groundwater flow and heat transport with phase change (i.e., freeze-thaw). Simulations support permafrost development under current climatic conditions, but only when net effects of vegetation on soil conditions are incorporated, thus pointing to the role of ecological succession. Furthermore, model results indicate that permafrost aggradation is transitory with further climate warming, as new permafrost thaws within seven decades.

The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines

USGS Publications Warehouse

Quataert, Ellen; Storlazzi, Curt; van Rooijen, Arnold; van Dongeren, Ap; Cheriton, Olivia

2015-01-01

A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.

Adapting California’s ecosystems to a changing climate

USGS Publications Warehouse

Elizabeth Chornesky,; David Ackerly,; Paul Beier,; Frank Davis,; Flint, Lorraine E.; Lawler, Joshua J.; Moyle, Peter B.; Moritz, Max A.; Scoonover, Mary; Byrd, Kristin B.; Alvarez, Pelayo; Heller, Nicole E.; Micheli, Elisabeth; Weiss, Stuart

2017-01-01

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). They illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

On the Reprocessing and Reanalysis of Observations for Climate

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Kennedy, John; Dee, Dick; ONeill, Alan

2012-01-01

The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.

The Quantum and Fluid Mechanics of Global Warming

NASA Astrophysics Data System (ADS)

Marston, Brad

2008-03-01

Quantum physics and fluid mechanics are the foundation of any understanding of the Earth's climate. In this talk I invoke three well-known aspects of quantum mechanics to explore what will happen as the concentrations of greenhouse gases such as carbon dioxide continue to increase. Fluid dynamical models of the Earth's atmosphere, demonstrated here in live simulations, yield further insight into past, present, and future climates. Statistics of geophysical flows can, however, be ascertained directly without recourse to numerical simulation, using concepts borrowed from nonequilibrium statistical mechanicsootnotetextJ. B. Marston, E. Conover, and Tapio Schneider, ``Statistics of an Unstable Barotropic Jet from a Cumulant Expansion,'' arXiv:0705.0011, J. Atmos. Sci. (in press).. I discuss several other ways that theoretical physics may be able to contribute to a deeper understanding of climate changeootnotetextJ. Carlson, J. Harte, G. Falkovich, J. B. Marston, and R. Pierrehumbert, ``Physics of Climate Change'' 2008 Program of the Kavli Institute for Theoretical Physics..

Antarctic glaciations under Pliocene climate conditions from numerical modeling and compilation of local field-based reconstructions

NASA Astrophysics Data System (ADS)

Bernales, Jorge; Rogozhina, Irina; Greve, Ralf

2014-05-01

The mid-Pliocene (3.15 to 2.85 million years before present) is the most recent period in Earth's history when temperatures and CO2 concentrations were likely sustainedly higher than pre-industrial values. Furthermore, the positions of the continents and their sea-land distributions had already reached their present configuration, sharing some similarities with today's patterns of ocean circulation and vegetation distributions. Although significant differences exist -such as a peak sea level that could have been 22 ± 10 m higher than it is today and sea surface temperatures particularly warmer at higher latitudes, mid-Pliocene has been identified as an ideal interval for studying the climate system under conditions similar to those projected for the end of this century. Among the sources of uncertainty in the projections, the response of the Antarctic ice sheet (AIS) to warmer-than-today conditions seems to play a central role. Therefore, a better understanding of AIS's behavior during periods like the mid-Pliocene will provide valuable information that could help improve future predictions. For this purpose, we have compiled a wide range of local field-based reconstructions of the ice-sheet margin from Pliocene sediments (with the inclusions of organic matters such as, for instance, diatoms or palynoflora, or ice rafted debris), geochemical records, volcanic ashes and rocks, and geomorphology, and designed numerical experiments of the AIS dynamics during the mid-Pliocene warm period using the large-scale polythermal ice sheet-shelf model SICOPOLIS (Greve, 1997 [1]; Sato and Greve, 2012 [2]). The model is run with a horizontal resolution of 40 × 40 km by the climatology obtained from the PlioMIP Atmosphere Ocean Global Circulation Model experiments (Dolan et al., 2012 [3]). Parameters of the AIS model (e.g. ice calving, sub-ice shelf and surface ice melt, basal sliding, etc.) have initially been estimated using ice-sheet simulations driven by the present-day climate and ocean conditions and calibrated against available remote-sensed and in-situ observations. In our Pliocene experiments, we employ alternative parameterizations of sub-ice shelf and ice surface melting processes to test the likelihood of numerous controversial theories and reconstructions arguing for or against significant retreat of the East Antarctic ice sheet from the coasts (locally up to 450 km) in the mid-Pliocene. Finally, we assess the sensitivity of the modeled West Antarctic/Antarctic Peninsula ice geometry to the above parameters and emphasize a crucial role of surface mass balance model parameters in modeling the Pliocene ice sheet configuration in agreement with existing reconstructions on a regional scale. 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] Dolan, A. M., Koenig, S. J., Hill, D. J., Haywood, A. M., and DeConto, R. M. (2012). Pliocene Ice Sheet Modelling Intercomparison Project (PLISMIP)-experimental design. Geoscientific Model Development, 5(4), 963-974.

Urban pluvial flood prediction: a case study evaluating radar rainfall nowcasts and numerical weather prediction models as model inputs.

PubMed

Thorndahl, Søren; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

2016-12-01

Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events - especially in the future climate - it is valuable to be able to simulate these events numerically, both historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper, radar data observations with different spatial and temporal resolution, radar nowcasts of 0-2 h leadtime, and numerical weather models with leadtimes up to 24 h are used as inputs to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on the small town of Lystrup in Denmark, which was flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps in real-time with high resolution radar rainfall data, but rather limited forecast performance in predicting floods with leadtimes more than half an hour.

Effective Engagement of Hostile Audiences on Climate Change

NASA Astrophysics Data System (ADS)

Denning, A.

2011-12-01

In 2010 and 2011, I gave invited presentations of mainstream climate science to large conferences dismissive of climate change organized by the HEartland Institute. In this presentation I review some of the common objections raised by such audiences and outline effective strategies to rebut them in public venues or the media. Respectful engagement on a human level is much more effective than appeals from authority, scientific consensus, or numerical models. Starting from a base of agreement on basic facts helps establish a basis of trust, which is then nurtured through personal anecdotes and humor. The basic science of climate change is presented in a non-confrontational way with frequent use of examples from everyday life to explain physical principles. Although a hard core of hostile individuals may not be swayed by such an approach, my experience was that this type of engagement can be very effective with ordinary people. I strongly encourage more climate scientists to work with public audiences and the media.

Climate change impact on groundwater levels in the Guarani Aquifer outcrop zone

NASA Astrophysics Data System (ADS)

Melo, D. D.; Wendland, E.

2013-12-01

The unsustainable use of groundwater in many countries might cause water availability restrictions in the future. Such issue is likely to worsen due to predicted climate changes for the incoming decades. As numerous studies suggest, aquifers recharge rates will be affected as a result of climate change. The Guarani Aquifer System (GAS) is one of the most important transboundary aquifer in the world, providing drinkable water for millions of people in four South American countries (Brazil, Argentina, Uruguay and Paraguay). Considering the GAS relevance and how its recharge rates might be altered by climatic conditions anomalies, the objective of this work is to assess possible climate changes impacts on groundwater levels in this aquifer outcrop zone. Global Climate Models' (GCM) outputs were used as inputs in a transient flux groundwater model created using the software SPA (Simulation of Process in Aquifers), enabling groundwater table fluctuation to be evaluated under distinct climatic scenarios. Six monitoring wells, located in a representative basin (Ribeirão da Onça basin) inside a GAS outcrop zone (ROB), provided water table measurements between 2004 and 2011 to calibrate the groundwater model. Using observed climatic data, a water budget method was applied to estimate recharge in different types of land uses. Statistically downscaled future climate scenarios were used as inputs for that same recharge model, which provided data for running SPA under those scenarios. The results show that most of the GCMs used here predict temperature arises over 275,15 K and major monthly rainfall mean changes to take place in the dry season. During wet seasons, those means might experience around 50% decrease. The transient model results indicate that water table variations, derived from around 70% of the climate scenarios, would vary below those measured between 2004 and 2011. Among the thirteen GCMs considered in this work, only four of them predicted more extreme climate scenarios. In some regions of the study area and under these extreme conditions, groundwater surface would decline more than 10 m. Although more optimistic scenarios resulted in an increase of groundwater levels in more than half of ROB, these would cause up to 5 m water table decline. The results reinforce the need for a permanent hydrogeological monitoring, mainly in the GAS recharge areas, along with the development of other climate change impacts assessment works using different downscaling and recharge estimates methods.

Model developments in TERRA_URB, the upcoming standard urban parametrization of the atmospheric numerical model COSMO(-CLM)

NASA Astrophysics Data System (ADS)

Wouters, Hendrik; Blahak, Ulrich; Helmert, Jürgen; Raschendorfer, Matthias; Demuzere, Matthias; Fay, Barbara; Trusilova, Kristina; Mironov, Dmitrii; Reinert, Daniel; Lüthi, Daniel; Machulskaya, Ekaterina

2015-04-01

In order to address urban climate at the regional scales, a new efficient urban land-surface parametrization TERRA_URB has been developed and coupled to the atmospheric numerical model COSMO-CLM. Hereby, several new advancements for urban land-surface models are introduced which are crucial for capturing the urban surface-energy balance and its seasonal dependency in the mid-latitudes. This includes a new PDF-based water-storage parametrization for impervious land, the representation of radiative absorption and emission by greenhouse gases in the infra-red spectrum in the urban canopy layer, and the inclusion of heat emission from human activity. TERRA_URB has been applied in offline urban-climate studies during European observation campaigns at Basel (BUBBLE), Toulouse (CAPITOUL), and Singapore, and currently applied in online studies for urban areas in Belgium, Germany, Switzerland, Helsinki, Singapore, and Melbourne. Because of its computational efficiency, high accuracy and its to-the-point conceptual easiness, TERRA_URB has been selected to become the standard urban parametrization of the atmospheric numerical model COSMO(-CLM). This allows for better weather forecasts for temperature and precipitation in cities with COSMO, and an improved assessment of urban outdoor hazards in the context of global climate change and urban expansion with COSMO-CLM. We propose additional extensions to TERRA_URB towards a more robust representation of cities over the world including their structural design. In a first step, COSMO's standard EXTernal PARarameter (EXTPAR) tool is updated for representing the cities into the land cover over the entire globe. Hereby, global datasets in the standard EXTPAR tool are used to retrieve the 'Paved' or 'sealed' surface Fraction (PF) referring to the presence of buildings and streets. Furthermore, new global data sets are incorporated in EXTPAR for describing the Anthropogenic Heat Flux (AHF) due to human activity, and optionally the Surface Area Index (SAI) derived from the Floor Space Index (FSI). In a second step, it is focussed on the urban/rural contrast in terms of turbulent transport in the surface layer by means of model sensivity experiments: On the theoretical basis of the TKE-based surface-layer transfer scheme of COSMO, we investigate the consistency between empirical functions for thermal roughness lengths and the urban/rural canopy morphology.

Impact of wildfire-induced land cover modification on local meteorology: A sensitivity study of the 2003 wildfires in Portugal

NASA Astrophysics Data System (ADS)

Hernandez, Charles; Drobinski, Philippe; Turquety, Solène

2015-10-01

Wildfires alter land cover creating changes in dynamic, vegetative, radiative, thermal and hydrological properties of the surface. However, how so drastic changes induced by wildfires and how the age of the burnt scar affect the small and meso-scale atmospheric boundary layer dynamics are largely unknown. These questions are relevant for process analysis, meteorological and air quality forecast but also for regional climate analysis. Such questions are addressed numerically in this study on the case of the Portugal wildfires in 2003 as a testbed. In order to study the effects of burnt scars, an ensemble of numerical simulations using the Weather Research and Forecasting modeling system (WRF) have been performed with different surface properties mimicking the surface state immediately after the fire, few days after the fire and few months after the fire. In order to investigate such issue in a seamless approach, the same modelling framework has been used with various horizontal resolutions of the model grid and land use, ranging from 3.5 km, which can be considered as the typical resolution of state-of-the art regional numerical weather prediction models to 14 km which is now the typical target resolution of regional climate models. The study shows that the combination of high surface heat fluxes over the burnt area, large differential heating with respect to the preserved surroundings and lower surface roughness produces very intense frontogenesis with vertical velocity reaching few meters per second. This powerful meso-scale circulation can pump more humid air from the surroundings not impacted by the wildfire and produce more cloudiness over the burnt area. The influence of soil temperature immediately after the wildfire ceases is mainly seen at night as the boundary-layer remains unstably stratified and lasts only few days. So the intensity of the induced meso-scale circulation decreases with time, even though it remains until full recovery of the vegetation. Finally all these effects are simulated whatever the land cover and model resolution and there are thus robust processes in both regional climate simulations and process studies or short-time forecast. However, the impact of burnt scars on the precipitation signal remains very uncertain, especially because low precipitation is at stake.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China

NASA Astrophysics Data System (ADS)

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

PubMed

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Climate Simulations based on a different-grid nested and coupled model

NASA Astrophysics Data System (ADS)

Li, Dan; Ji, Jinjun; Li, Yinpeng

2002-05-01

An atmosphere-vegetation interaction model (A VIM) has been coupled with a nine-layer General Cir-culation Model (GCM) of Institute of Atmospheic Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. A VIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon-gitude 7.5° and latitude 4.5°, the vegetation is given a high resolution of 1.5° by 1.5° to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis. Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris-tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu-lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

Malaria epidemics and the influence of the tropical South Atlantic on the Indian monsoon

NASA Astrophysics Data System (ADS)

Cash, B. A.; Rodó, X.; Ballester, J.; Bouma, M. J.; Baeza, A.; Dhiman, R.; Pascual, M.

2013-05-01

The existence of predictability in the climate system beyond the relatively short timescales of synoptic weather has provided significant impetus to investigate climate variability and its consequences for society. In particular, relationships between the relatively slow changes in sea surface temperature (SST) and climate variability at widely removed points across the globe provide a basis for statistical and dynamical efforts to predict numerous phenomena, from rainfall to disease incidence, at seasonal to decadal timescales. We describe here a remote influence, identified through observational analysis and supported through numerical experiments with a coupled atmosphere-ocean model, of the tropical South Atlantic (TSA) on both monsoon rainfall and malaria epidemics in arid northwest India. Moreover, SST in the TSA is shown to provide the basis for an early warning of anomalous hydrological conditions conducive to malaria epidemics four months later, therefore at longer lead times than those afforded by rainfall. We find that the TSA is not only significant as a modulator of the relationship between the monsoon and the El Niño/Southern Oscillation, as has been suggested by previous work, but for certain regions and temporal lags is in fact a dominant driver of rainfall variability and hence malaria outbreaks.

Wintertime urban heat island modified by global climate change over Japan

NASA Astrophysics Data System (ADS)

Hara, M.

2015-12-01

Urban thermal environment change, especially, surface air temperature (SAT) rise in metropolitan areas, is one of the major recent issues in urban areas. The urban thermal environmental change affects not only human health such as heat stroke, but also increasing infectious disease due to spreading out virus vectors habitat and increase of industry and house energy consumption. The SAT rise is mostly caused by global climate change and urban heat island (hereafter UHI) by urbanization. The population in Tokyo metropolitan area is over 30 millions and the Tokyo metropolitan area is one of the biggest megacities in the world. The temperature rise due to urbanization seems comparable to the global climate change in the major megacities. It is important to project how the urbanization and the global climate change affect to the future change of urban thermal environment to plan the adaptation and mitigation policy. To predict future SAT change in urban scale, we should estimate future UHI modified by the global climate change. This study investigates change in UHI intensity (UHII) of major metropolitan areas in Japan by effects of the global climate change. We performed a series of climate simulations. Present climate simulations with and without urban process are conducted for ten seasons using a high-resolution numerical climate model, the Weather Research and Forecasting (WRF) model. Future climate projections with and without urban process are also conducted. The future projections are performed using the pseudo global warming method, assuming 2050s' initial and boundary conditions estimated by a GCM under the RCP scenario. Simulation results indicated that UHII would be enhanced more than 30% in Tokyo during the night due to the global climate change. The enhancement of urban heat island is mostly caused by change of lower atmospheric stability.

The influence of lightning activity and anthropogenic factors on large-scale characteristics of natural fires

NASA Astrophysics Data System (ADS)

Eliseev, A. V.; Mokhov, I. I.; Chernokulsky, A. V.

2017-01-01

A module for simulating of natural fires (NFs) in the climate model of the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM), is extended with respect to the influence of lightning activity and population density on the ignition frequency and fire suppression. The IAP RAS CM is used to perform numerical experiments in accordance with the conditions of the project that intercompares climate models, CMIP5 (Coupled Models Intercomparison Project, phase 5). The frequency of lightning flashes was assigned in accordance with the LIS/OTD satellite data. In the calculations performed, anthropogenic ignitions play an important role in NF occurrences, except for regions at subpolar latitudes and, to a lesser degree, tropical and subtropical regions. Taking into account the dependence of fire frequency on lightning activity and population density intensifies the influence of characteristics of natural fires on the climate changes in tropics and subtropics as compared to the version of the IAP RAS CM that does not take the influence of ignition sources on the large-scale characteristics of NFs into consideration.

Paleodistribution modeling suggests glacial refugia in Scandinavia and out-of-Tibet range expansion of the Arctic fox.

PubMed

Fuentes-Hurtado, Marcelo; Hof, Anouschka R; Jansson, Roland

2016-01-01

Quaternary glacial cycles have shaped the geographic distributions and evolution of numerous species in the Arctic. Ancient DNA suggests that the Arctic fox went extinct in Europe at the end of the Pleistocene and that Scandinavia was subsequently recolonized from Siberia, indicating inability to track its habitat through space as climate changed. Using ecological niche modeling, we found that climatically suitable conditions for Arctic fox were found in Scandinavia both during the last glacial maximum (LGM) and the mid-Holocene. Our results are supported by fossil occurrences from the last glacial. Furthermore, the model projection for the LGM, validated with fossil records, suggested an approximate distance of 2000 km between suitable Arctic conditions and the Tibetan Plateau well within the dispersal distance of the species, supporting the recently proposed hypothesis of range expansion from an origin on the Tibetan Plateau to the rest of Eurasia. The fact that the Arctic fox disappeared from Scandinavia despite suitable conditions suggests that extant populations may be more sensitive to climate change than previously thought.

Interannual Variation in Phytoplankton Concentration and Community in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Rousseaux, C. S.; Gregg, W. W.

2011-01-01

Climate events such as El Nino have been shown to have an effect on the biology of our ocean. Because of the lack of data, we still have very little knowledge about the spatial and temporal effect these climate events may have on biological marine systems. In this study, we used the NASA Ocean Biogeochemical Model (NOBM) to assess the interannual variability in phytoplankton community in the Pacific Ocean between 1998 and 2005. In the North Central and Equatorial Pacific Ocean, changes in the Multivariate El Nino Index were associated with changes in phytoplankton composition. The model identified an increase in diatoms of approx.33 % in the equatorial Pacific in 1999 during a La Nina event. This increase in diatoms coincided with a decrease of approx.11 % in cyanobacteria concentration. The inverse relationship between cyanobacteria and diatoms concentration was significant (p<0.05) throughout the period of study. The use of a numerical model allows us to assess the impact climate variability has on key phytoplankton groups known to lead to contrasting food chain at a spatial and temporal resolution unachievable when relying solely on in-situ observations.

Numerical simulation of large-scale ocean-atmosphere coupling and the ocean's role in climate

NASA Technical Reports Server (NTRS)

Gates, W. L.

1983-01-01

The problem of reducing model generated sigma coordinate data to pressure levels is considered. A mass consistent scheme for performing budget analyses is proposed, wherein variables interpolated to a given pressure level are weighted according to the mass between a nominal pressure level above and either a nominal pressure level below or the Earth's surface, whichever is closer. The method is applied to the atmospheric energy cycle as simulated by the OSU two level atmospheric general circulation model. The results are more realistic than sigma coordinate analyses with respect to eddy decomposition, and are in agreement with the sigma coordinate evaluation of the numerical energy sink. Comparison with less sophisticated budget schemes indicates superiority locally, but not globally.

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

NASA Astrophysics Data System (ADS)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

Extensions and applications of a second-order landsurface parameterization

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

An Efficient Non-iterative Bulk Parametrization of Surface Fluxes for Stable Atmospheric Conditions Over Polar Sea-Ice

NASA Astrophysics Data System (ADS)

Gryanik, Vladimir M.; Lüpkes, Christof

2018-02-01

In climate and weather prediction models the near-surface turbulent fluxes of heat and momentum and related transfer coefficients are usually parametrized on the basis of Monin-Obukhov similarity theory (MOST). To avoid iteration, required for the numerical solution of the MOST equations, many models apply parametrizations of the transfer coefficients based on an approach relating these coefficients to the bulk Richardson number Rib. However, the parametrizations that are presently used in most climate models are valid only for weaker stability and larger surface roughnesses than those documented during the Surface Heat Budget of the Arctic Ocean campaign (SHEBA). The latter delivered a well-accepted set of turbulence data in the stable surface layer over polar sea-ice. Using stability functions based on the SHEBA data, we solve the MOST equations applying a new semi-analytic approach that results in transfer coefficients as a function of Rib and roughness lengths for momentum and heat. It is shown that the new coefficients reproduce the coefficients obtained by the numerical iterative method with a good accuracy in the most relevant range of stability and roughness lengths. For small Rib, the new bulk transfer coefficients are similar to the traditional coefficients, but for large Rib they are much smaller than currently used coefficients. Finally, a possible adjustment of the latter and the implementation of the new proposed parametrizations in models are discussed.

Rapid Ice-Sheet Changes and Mechanical Coupling to Solid-Earth/Sea-Level and Space Geodetic Observation

NASA Astrophysics Data System (ADS)

Adhikari, S.; Ivins, E. R.; Larour, E. Y.

2015-12-01

Perturbations in gravitational and rotational potentials caused by climate driven mass redistribution on the earth's surface, such as ice sheet melting and terrestrial water storage, affect the spatiotemporal variability in global and regional sea level. Here we present a numerically accurate, computationally efficient, high-resolution model for sea level. Unlike contemporary models that are based on spherical-harmonic formulation, the model can operate efficiently in a flexible embedded finite-element mesh system, thus capturing the physics operating at km-scale yet capable of simulating geophysical quantities that are inherently of global scale with minimal computational cost. One obvious application is to compute evolution of sea level fingerprints and associated geodetic and astronomical observables (e.g., geoid height, gravity anomaly, solid-earth deformation, polar motion, and geocentric motion) as a companion to a numerical 3-D thermo-mechanical ice sheet simulation, thus capturing global signatures of climate driven mass redistribution. We evaluate some important time-varying signatures of GRACE inferred ice sheet mass balance and continental hydrological budget; for example, we identify dominant sources of ongoing sea-level change at the selected tide gauge stations, and explain the relative contribution of different sources to the observed polar drift. We also report our progress on ice-sheet/solid-earth/sea-level model coupling efforts toward realistic simulation of Pine Island Glacier over the past several hundred years.

Identifying bird and reptile vulnerabilities to climate change in the southwestern United States

USGS Publications Warehouse

Hatten, James R.; Giermakowski, J. Tomasz; Holmes, Jennifer A.; Nowak, Erika M.; Johnson, Matthew J.; Ironside, Kirsten E.; van Riper, Charles; Peters, Michael; Truettner, Charles; Cole, Kenneth L.

2016-07-06

Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.

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

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu; Marx, L.

2007-10-01

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

Modelling Soil Heat and Water Flow as a Coupled Process in Land Surface Models

NASA Astrophysics Data System (ADS)

García González, Raquel; Verhoef, Anne; Vidale, Pier Luigi; Braud, Isabelle

2010-05-01

To improve model estimates of soil water and heat flow by land surface models (LSMs), in particular in the first few centimetres of the near-surface soil profile, we have to consider in detail all the relevant physical processes involved (see e.g. Milly, 1982). Often, thermal and iso-thermal vapour fluxes in LSMs are neglected and the simplified Richard's equation is used as a result. Vapour transfer may affect the water fluxes and heat transfer in LSMs used for hydrometeorological and climate simulations. Processes occurring in the top 50 cm soil may be relevant for water and heat flux dynamics in the deeper layers, as well as for estimates of evapotranspiration and heterotrophic respiration, or even for climate and weather predictions. Water vapour transfer, which was not incorporated in previous versions of the MOSES/JULES model (Joint UK Land Environment Simulator; Cox et al., 1999), has now been implemented. Furthermore, we also assessed the effect of the soil vertical resolution on the simulated soil moisture and temperature profiles and the effect of the processes occurring at the upper boundary, mainly in terms of infiltration rates and evapotranspiration. SiSPAT (Simple Soil Plant Atmosphere Transfer Model; Braud et al., 1995) was initially used to quantify the changes that we expect to find when we introduce vapour transfer in JULES, involving parameters such as thermal vapour conductivity and diffusivity. Also, this approach allows us to compare JULES to a more complete and complex numerical model. Water vapour flux varied with soil texture, depth and soil moisture content, but overall our results suggested that water vapour fluxes change temperature gradients in the entire soil profile and introduce an overall surface cooling effect. Increasing the resolution smoothed and reduced temperature differences between liquid (L) and liquid/vapour (LV) simulations at all depths, and introduced a temperature increase over the entire soil profile. Thermal gradients rather than soil water potential gradients seem to cause temporal and spatial (vertical) soil temperature variability. We conclude that a multi-soil layer configuration may improve soil water dynamics, heat transfer and coupling of these processes, as well as evapotranspiration estimates and land surface-atmosphere coupling. However, a compromise should be reached between numerical and process-simulation aspects. References: Braud I., A.C. Dantas-Antonino, M. Vauclin, J.L. Thony and P. Ruelle, 1995b: A Simple Soil Plant Atmo- sphere Transfer model (SiSPAT), Development and field verification, J. Hydrol, 166: 213-250 Cox, P.M., R.A. Betts, C.B. Bunton, R.L.H. Essery, P.R. Rowntree, and J. Smith (1999), The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim. Dyn., 15, 183-203. Milly, P.C.D., 1982. Moisture and heat transport in hysteric inhomogeneous porous media: a matric head- based formulation and a numerical model, Water Resour. Res., 18:489-498

Lake Ice Cover of Shallow Lakes and Climate Interactions in Arctic Regions (1950-2011): SAR Data Analysis and Numerical Modeling

NASA Astrophysics Data System (ADS)

Surdu, C.; Duguay, C.; Brown, L.; Fernàndez-Prieto, D.; Samuelsson, P.

2012-12-01

Lake ice cover is highly correlated with climatic conditions and has, therefore, been demonstrated to be an essential indicator of climate variability and change. Recent studies have shown that the duration of the lake ice cover has decreased, mainly as a consequence of earlier thaw dates in many parts of the Northern Hemisphere over the last 50 years, mainly as a feedback to increased winter and spring air temperature. In response to projected air temperature and winter precipitation changes by climate models until the end of the 21st century, the timing, duration, and thickness of ice cover on Arctic lakes are expected to be impacted. This, in turn, will likely alter the energy, water, and bio-geochemical cycling in various regions of the Arctic. In the case of shallow tundra lakes, many of which are less than 3-m deep, warmer climate conditions could result in a smaller fraction of lakes that fully freeze to the bottom at the time of maximum winter ice thickness since thinner ice covers are predicted to develop. Shallow thermokarst lakes of the coastal plain of northern Alaska, and of other similar Arctic regions, have likely been experiencing changes in seasonal ice phenology and thickness over the last few decades but these have not yet been comprehensively documented. Analysis of a 20-year time series of ERS-1/2 synthetic aperture radar (SAR) data and numerical lake ice modeling were employed to determine the response of ice cover (thickness, freezing to bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last three decades. New downscaled data specific to the Arctic domain (at a resolution of 0.44 degrees using ERA Interim Reanalysis as boundary condition) produced by the Rossby Centre Regional Atmospheric Climate Model (RCA4) was used to drive the Canadian Lake Ice Model (CLIMo) for the period 1950-2011. In order to assess and integrate the SAR-derived observed changes into a longer historical context, and to improve the simulation outputs, CLIMo was also forced with climatic data recorded at the Barrow airport meteorological station since the middle of the 20th century. ERS-1/2 data was used to map areas of the shallow lakes that freeze to bed and the rate at which this occurs during the ice season for the period 1991-2011. The results were compared to daily ice thickness results derived from CLIMo. Analysis from a sub-region of the NSA near Barrow shows that the interannual variability in ice thickness simulated with CLIMo compares favorably with the fraction of lakes that freeze to their bed in winter, thicker ice cover corresponding to a higher ratio of lakes fully frozen to the bottom, as determined from the analysis of SAR data.

Response of salt-marsh carbon accumulation to climate change.

PubMed

Kirwan, Matthew L; Mudd, Simon M

2012-09-27

About half of annual marine carbon burial takes place in shallow water ecosystems where geomorphic and ecological stability is driven by interactions between the flow of water, vegetation growth and sediment transport. Although the sensitivity of terrestrial and deep marine carbon pools to climate change has been studied for decades, there is little understanding of how coastal carbon accumulation rates will change and potentially feed back on climate. Here we develop a numerical model of salt marsh evolution, informed by recent measurements of productivity and decomposition, and demonstrate that competition between mineral sediment deposition and organic-matter accumulation determines the net impact of climate change on carbon accumulation in intertidal wetlands. We find that the direct impact of warming on soil carbon accumulation rates is more subtle than the impact of warming-driven sea level rise, although the impact of warming increases with increasing rates of sea level rise. Our simulations suggest that the net impact of climate change will be to increase carbon burial rates in the first half of the twenty-first century, but that carbon-climate feedbacks are likely to diminish over time.

Recent Advances in our Understanding of Debris-covered Glacier Response to Climate

NASA Astrophysics Data System (ADS)

Pellicciotti, F.

2016-12-01

Debris-covered glaciers are relevant in many mountainous regions, but both modelling and observational studies are less numerous compared to those on traditional "clean" glaciers. A number of conjectures about their behaviour and response to climate have been made. First, it is assumed that in a warming climate debris cover would increase because of slope instability and increased meltout of englacial debris. Second, large-scale remote sensing studies have suggested that their thinning rates are comparable to those of debris-free glaciers, in spite of the insulating effect of a debris mantle. This apparent anomaly has been explained conceptually through high rates of energy absorption at supraglacial cliffs and ponds, but no evidence for this argument exists at the glacier scale. We validate each of these assumptions based on numerical modelling, analysis of satellite data and field observations from High Mountain Asia and the well monitored Langtang catchment in the Himalaya, in particular. First, no change in debris-covered area is apparent for regions of stable or positive mass balance such as the Karakoram, in line with the reasoning that sustained negative mass balance triggers an increase in debris. Second, results from an ensemble of DEM differences for the Langtang glaciers show that thinning rates of the debris-covered glaciers are not equivalent to those of the debris-free glaciers, contradicting results from the large-scale studies. However, thinning rates are higher than would be expected for a debris-covered surface, and can be explained through physically-based models of cliffs and lakes. These dynamic features form on low-gradient glacier sections between stagnant and dynamic zones, evolve in time and can survive or disappear depending on their characteristics. Ablation from cliffs and lakes is very high and can account between 10 to 30% of mass losses from the glaciers, despite covering a small percentage of the glacier area. Among the mechanisms controlling their persistence and relationship to climate, a key finding is that coupling of cliffs and ponds is a prerequisite for their long term survival. Our study provides a significant step towards a better understanding of the response of debris-covered glaciers to climate change, and highlights avenues of future research.

Climate Change, Extreme Weather Events, and Fungal Disease Emergence and Spread

NASA Technical Reports Server (NTRS)

Tucker, Compton J.; Yager, Karina; Anyamba, Assaf; Linthicum, Kenneth J.

2011-01-01

Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.

The UPSCALE project: a large simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, Matthew; Roberts, Malcolm; Vidale, Pier Luigi; Schiemann, Reinhard; Demory, Marie-Estelle; Strachan, Jane

2014-05-01

The development of a traceable hierarchy of HadGEM3 global climate models, based upon the Met Office Unified Model, at resolutions from 135 km to 25 km, now allows the impact of resolution on the mean state, variability and extremes of climate to be studied in a robust fashion. In 2011 we successfully obtained a single-year grant of 144 million core hours of supercomputing time from the PRACE organization to run ensembles of 27 year atmosphere-only (HadGEM3-A GA3.0) climate simulations at 25km resolution, as used in present global weather forecasting, on HERMIT at HLRS. Through 2012 the UPSCALE project (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) ran over 650 years of simulation at resolutions of 25 km (N512), 60 km (N216) and 135 km (N96) to look at the value of high resolution climate models in the study of both present climate and a potential future climate scenario based on RCP8.5. Over 400 TB of data was produced using HERMIT, with additional simulations run on HECToR (UK supercomputer) and MONSooN (Met Office NERC Supercomputing Node). The data generated was transferred to the JASMIN super-data cluster, hosted by STFC CEDA in the UK, where analysis facilities are allowing rapid scientific exploitation of the data set. Many groups across the UK and Europe are already taking advantage of these facilities and we welcome approaches from other interested scientists. This presentation will briefly cover the following points; Purpose and requirements of the UPSCALE project and facilities used. Technical implementation and hurdles (model porting and optimisation, automation, numerical failures, data transfer). Ensemble specification. Current analysis projects and access to the data set. A full description of UPSCALE and the data set generated has been submitted to Geoscientific Model development, with overview information available from http://proj.badc.rl.ac.uk/upscale .

Mosquito populations dynamics associated with climate variations.

PubMed

Wilke, André Barretto Bruno; Medeiros-Sousa, Antônio Ralph; Ceretti-Junior, Walter; Marrelli, Mauro Toledo

2017-02-01

Mosquitoes are responsible for the transmission of numerous serious pathogens. Members of the Aedes and Culex genera, which include many important vectors of mosquito-borne diseases, are highly invasive and adapted to man-made environments. They are spread around the world involuntarily by humans and are highly adapted to urbanized environments, where they are exposed to climate-related abundance drivers. We investigated Culicidae fauna in two urban parks in the city of São Paulo to analyze the correlations between climatic variables and the population dynamics of mosquitoes in these urban areas. Mosquitoes were collected monthly over one year, and sampling sufficiency was evaluated after morphological identification of the specimens. The average monthly temperature and accumulated rainfall for the collection month and previous month were used to explain climate-related abundance drivers for the six most abundant species (Aedes aegypti, Aedes albopictus, Aedes fluviatilis, Aedes scapularis, Culex nigripalpus and Culex quinquefasciatus) and then analyzed using generalized linear statistical models and the Akaike Information Criteria corrected for small samples (AICc). The strength of evidence in favor of each model was evaluated using Akaike weights, and the explanatory model power was measured by McFadden's Pseudo-R 2 . Associations between climate and mosquito abundance were found in both parks, indicating that predictive models based on climate variables can provide important information on mosquito population dynamics. We also found that this association is species-dependent. Urbanization processes increase the abundance of a few mosquito species that are well adapted to man-made environments and some of which are important vectors of pathogens. Predictive models for abundance based on climate variables may help elucidate the population dynamics of urban mosquitoes and their impact on the risk of disease transmission, allowing better predictive scenarios to be developed and supporting the implementation of vector mosquito control strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Air-sea exchange over Black Sea estimated from high resolution regional climate simulations

NASA Astrophysics Data System (ADS)

Velea, Liliana; Bojariu, Roxana; Cica, Roxana

2013-04-01

Black Sea is an important influencing factor for the climate of bordering countries, showing cyclogenetic activity (Trigo et al, 1999) and influencing Mediterranean cyclones passing over. As for other seas, standard observations of the atmosphere are limited in time and space and available observation-based estimations of air-sea exchange terms present quite large ranges of uncertainty. The reanalysis datasets (e.g. ERA produced by ECMWF) provide promising validation estimates of climatic characteristics against the ones in available climatic data (Schrum et al, 2001), while cannot reproduce some local features due to relatively coarse horizontal resolution. Detailed and realistic information on smaller-scale processes are foreseen to be provided by regional climate models, due to continuous improvements of physical parameterizations and numerical solutions and thus affording simulations at high spatial resolution. The aim of the study is to assess the potential of three regional climate models in reproducing known climatological characteristics of air-sea exchange over Black Sea, as well as to explore the added value of the model compared to the input (reanalysis) data. We employ results of long-term (1961-2000) simulations performed within ENSEMBLE project (http://ensemblesrt3.dmi.dk/) using models ETHZ-CLM, CNRM-ALADIN, METO-HadCM, for which the integration domain covers the whole area of interest. The analysis is performed for the entire basin for several variables entering the heat and water budget terms and available as direct output from the models, at seasonal and annual scale. A comparison with independent data (ERA-INTERIM) and findings from other studies (e.g. Schrum et al, 2001) is also presented. References: Schrum, C., Staneva, J., Stanev, E. and Ozsoy, E., 2001: Air-sea exchange in the Black Sea estimated from atmospheric analysis for the period 1979-1993, J. Marine Systems, 31, 3-19 Trigo, I. F., T. D. Davies, and G. R. Bigg (1999): Objective climatology of cyclones in the Mediterranean region. J. Climate, 12, 1685- 169

Scaling Forest Management Practices in Earth System Models: Case Study of Southeast and Pacific Northwest Forests

NASA Astrophysics Data System (ADS)

Pourmokhtarian, A.; Becknell, J. M.; Hall, J.; Desai, A. R.; Boring, L. R.; Duffy, P.; Staudhammer, C. L.; Starr, G.; Dietze, M.

2014-12-01

A wide array of human-induced disturbances can alter the structure and function of forests, including climate change, disturbance and management. While there have been numerous studies on climate change impacts on forests, interactions of management with changing climate and natural disturbance are poorly studied. Forecasts of the range of plausible responses of forests to climate change and management are need for informed decision making on new management approaches under changing climate, as well as adaptation strategies for coming decades. Terrestrial biosphere models (TBMs) provide an excellent opportunity to investigate and assess simultaneous responses of terrestrial ecosystems to climatic perturbations and management across multiple spatio-temporal scales, but currently do not represent a wide array of management activities known to impact carbon, water, surface energy fluxes, and biodiversity. The Ecosystem Demography model 2 (ED2) incorporates non-linear impacts of fine-scale (~10-1 km) heterogeneity in ecosystem structure both horizontally and vertically at a plant level. Therefore it is an ideal candidate to incorporate different forest management practices and test various hypotheses under changing climate and across various spatial scales. The management practices that we implemented were: clear-cut, conversion, planting, partial harvest, low intensity fire, restoration, salvage, and herbicide. The results were validated against observed data across 8 different sites in the U.S. Southeast (Duke Forest, Joseph Jones Ecological Research Center, North Carolina Loblolly Pine, and Ordway-Swisher Biological Station) and Pacific Northwest (Metolius Research Natural Area, H.J. Andrews Experimental Forest, Wind River Field Station, and Mount Rainier National Park). These sites differ in regards to climate, vegetation, soil, and historical land disturbance as well as management approaches. Results showed that different management practices could successfully and realistically be implemented in the ED2 model at a site level. Moreover, sensitivity analyses determined the most important processes at different spatial scales, and also those which could be ignored while minimizing overall error.

The Role of Forcing and Internal Dynamics in explaining the 'Medieval Climate Anomaly'

NASA Technical Reports Server (NTRS)

Goossee, Hugues; Crespin, Elisabeth; Dubinkina, Svetlana; Loutre, Marie-France; Mann, Michael E.; Renssen, Hans; Shindell, Drew

2012-01-01

Proxy reconstructions suggest that peak global temperature during the past warm interval known as the Medieval Climate Anomaly (MCA, roughly 950-1250 AD) has been exceeded only during the most recent decades. To better understand the origin of this warm period, we use model simulations constrained by data assimilation establishing the spatial pattern of temperature changes that is most consistent with forcing estimates, model physics and the empirical information contained in paleoclimate proxy records. These numerical experiments demonstrate that the reconstructed spatial temperature pattern of the MCA can be explained by a simple thermodynamical response of the climate system to relatively weak changes in radiative forcing combined with a modification of the atmospheric circulation, displaying some similarities with the positive phase of the so-called Arctic Oscillation, and with northward shifts in the position of the Gulf Stream and Kuroshio currents. The mechanisms underlying the MCA are thus quite different from anthropogenic mechanisms responsible for modern global warming.

Numerical modeling techniques for flood analysis

NASA Astrophysics Data System (ADS)

Anees, Mohd Talha; Abdullah, K.; Nawawi, M. N. M.; Ab Rahman, Nik Norulaini Nik; Piah, Abd. Rahni Mt.; Zakaria, Nor Azazi; Syakir, M. I.; Mohd. Omar, A. K.

2016-12-01

Topographic and climatic changes are the main causes of abrupt flooding in tropical areas. It is the need to find out exact causes and effects of these changes. Numerical modeling techniques plays a vital role for such studies due to their use of hydrological parameters which are strongly linked with topographic changes. In this review, some of the widely used models utilizing hydrological and river modeling parameters and their estimation in data sparse region are discussed. Shortcomings of 1D and 2D numerical models and the possible improvements over these models through 3D modeling are also discussed. It is found that the HEC-RAS and FLO 2D model are best in terms of economical and accurate flood analysis for river and floodplain modeling respectively. Limitations of FLO 2D in floodplain modeling mainly such as floodplain elevation differences and its vertical roughness in grids were found which can be improve through 3D model. Therefore, 3D model was found to be more suitable than 1D and 2D models in terms of vertical accuracy in grid cells. It was also found that 3D models for open channel flows already developed recently but not for floodplain. Hence, it was suggested that a 3D model for floodplain should be developed by considering all hydrological and high resolution topographic parameter's models, discussed in this review, to enhance the findings of causes and effects of flooding.

Do we need to account for scenarios of land use/land cover changes in regional climate modeling and impact studies?

NASA Astrophysics Data System (ADS)

Strada, Susanna; de Noblet-Ducoudré, Nathalie; Perrin, Mathieu; Stefanon, Marc

2016-04-01

By modifying the Earth's natural landscapes, humans have introduced an imbalance in the Earth System's energy, water and emission fluxes via land-use and land-cover changes (LULCCs). Through land-atmosphere interactions, LULCCs influence weather, air quality and climate at different scales, from regional/local (a few ten kilometres) (Pielke et al., 2011) to global (a few hundred kilometres) (Mahmood et al., 2014). Therefore, in the context of climate change, LULCCs will play a role locally/regionally in altering weather/atmospheric conditions. In addition to the global climate change impacts, LULCCs will possibly induce further changes in the functioning of terrestrial ecosystems and thereby affect adaptation strategies. If LULCCs influence weather/atmospheric conditions, could land use planning alter climate conditions and ease the impact of climate change by wisely shaping urban and rural landscapes? Nowadays, numerical land-atmosphere modelling allows to assess LULCC impacts at different scales (e.g., Marshall et al., 2003; de Noblet-Ducoudré et al., 2011). However, most scenarios of climate changes used to force impact models result from downscaling procedures that do not account for LULCCs (e.g., Jacob et al., 2014). Therefore, if numerical modelling may help in tackling the discussion about LULCCs, do existing LULCC scenarios encompass realistic changes in terms of land use planning? In the present study, we apply a surface model to compare projected LULCC scenarios over France and to assess their impacts on surface fluxes (i.e., water, heat and carbon dioxide fluxes) and on water and carbon storage in soils. To depict future LULCCs in France, we use RCP scenarios from the IPCC AR5 report (Moss et al., 2011). LULCCs encompassed in RCPs are discussed in terms of: (a) their impacts on water and energy balance over France, and (b) their feasibility in the framework of land use planning in France. This study is the first step to quantify the sensitivity of land-atmosphere models to LULCCs. RCP scenarios showing the largest impact on surface fluxes and carbon-water soil storage will be selected to force a coupled land-atmosphere model. Coupled land-atmosphere simulations will allow to account for atmospheric feedbacks in the assessment of the sensitivity of land-atmosphere models to LULCCs. In addition, this study aims to push further scenario development to build compelling LULCC scenarios. If the assessment of LULCC scenarios through numerical modelling may provide land planners with an established scientific basis to draw future land use policy, LULCC scenarios should depict realistic as well as extreme modifications at scales at which changes in landscapes are actually shaped. References de Noblet-Ducoudré, N., Boisier, J.-P., Pitman, A., Bonan, G. B., Brovkin, V., Cruz, F., Delire, C., Gayler, V., Van den Hurk, B. J. J. M., Lawrence, P. J., Van Der Molen, M. K., Müller, C., Reick, C. H. , Strengers, B. J., and Voldoire, A.: Determining robust impacts of land-use-induced land cover changes on surface climate over North America and Eurasia: results from the first set of LUCID experiments, J. Clim., 25, 3261‒3281, 2012. 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. and Yiou, P.: EURO-CORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, Springer Berlin Heidelberg, 2013, 1-16. Mahmood, R., Pielke, R. A., Hubbard, K. G., Niyogi, D., Dirmeyer, P. A., McAlpine, C., Carleton, A. M., Hale, R., Gameda, S., Beltrán-Przekurat, A., Baker, B., McNider, R., Legates, D. R., Shepherd, M., Du, J., Blanken, P. D., Frauenfeld, O., W., Nair, U.S., and Fall, S.: Land cover changes and their biogeophysical effects on climate, Int. J. Climatol., 34, 929-953, 2014. Marshall, C. H., Pielke, R. A., Steyaert, L. T.: Crop freezes and land-use change in Florida, Nature, vol. 426, p. 29, 2003. Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of scenarios for climate change and assessment, Nature, 463, 747-756, 2011. Pielke, R. A., Pitman, A., Niyogi, D., Mahmood, R., McAlpine, C., Hossain, F., Goldewijk, K. K., Nair, U., Betts, R., Fall, S., Reichstein, M., Kabat, P. , and de Noblet, N.: Land use/land cover changes and climate: modeling analysis and observational evidence, WIREs Clim Change, 2(6), 828-850, 2011.

Spring leaf phenology and the diurnal temperature range in a temperate maple forest.

PubMed

Hanes, Jonathan M

2014-03-01

Spring leaf phenology in temperate climates is intricately related to numerous aspects of the lower atmosphere [e.g., surface energy balance, carbon flux, humidity, the diurnal temperature range (DTR)]. To further develop and improve the accuracy of ecosystem and climate models, additional investigations of the specific nature of the relationships between spring leaf phenology and various ecosystem and climate processes are required in different environments. This study used visual observations of maple leaf phenology, below-canopy light intensities, and micrometeorological data collected during the spring seasons of 2008, 2009, and 2010 to examine the potential influence of leaf phenology on a seasonal transition in the trend of the DTR. The timing of a reversal in the DTR trend occurred near the time when the leaves were unfolding and expanding. The results suggest that the spring decline in the DTR can be attributed primarily to the effect of canopy closure on daily maximum temperature. These findings improve our understanding of the relationship between leaf phenology and the diurnal temperature range in temperate maple forests during the spring. They also demonstrate the necessity of incorporating accurate phenological data into ecosystem and climate models and warrant a careful examination of the extent to which canopy phenology is currently incorporated into existing models.

Simulations of Moscow megacity heat island with the COSMO-CLM model using two different urban canopy schemes and realistic building parameters, derived from OpenStreetMap data

NASA Astrophysics Data System (ADS)

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

2017-04-01

In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio, we used originally technology of GIS-based processing of realistic OpenStreetMap data, which includes size and shape of the most of the in the city (Samsonov et al., 2015). Our testbed allows to make more detailed comparison between the modelling approaches, and also reveals the importance of correct definition of the of turbulent mixing in the ABL in the atmospheric model, and the realistic specification of the building morphology parameters and anthropogenic heat fluxes. In addition, strong seasonal variation of the importance of different factors, responsible for UHI appearance, was shown. Moreover, the framework allows to identify and solve issues regarding the different model approaches: detailed analysis of spatial and temporal variations of modelled urban temperature anomalies and their vertical extent has shown that version of COSMO-CLM model with TERRA-URB scheme simulate UHI effect in more realistic way. Research was supported by Russian Foundation for Basic Research (RFBR) and Russian Geographic Society (RGS): RFBR projects № 16-35-00474, 15-35-21129 and 16-05-00704 A, RGS-RFBR project № 13-05-41306. References: 1. Lokoshchenko, M. A. (2014). Urban 'heat island' in Moscow. Urban Climate, 10, 550-562. 2. Samsonov, T. E., Konstantinov, P. I., & Varentsov, M. I. (2015). Object-oriented approach to urban canyon analysis and its applications in meteorological modeling. Urban Climate, 13, 122-139. 3. Trusilova K., Früh, B., Brienen, S., Walter, A., Masson, V., Pigeon, G., Becker, P. Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM// Journal of Applied Meteorology and Climatology. 2013. Vol. 52. P. 2296-2311. 4. Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

NASA Technical Reports Server (NTRS)

Krueger, Steven K.

1998-01-01

The interactions between sea ice, open ocean, atmospheric radiation, and clouds over the Arctic Ocean exert a strong influence on global climate. Uncertainties in the formulation of interactive air-sea-ice processes in global climate models (GCMs) result in large differences between the Arctic, and global, climates simulated by different models. Arctic stratus clouds are not well-simulated by GCMs, yet exert a strong influence on the surface energy budget of the Arctic. Leads (channels of open water in sea ice) have significant impacts on the large-scale budgets during the Arctic winter, when they contribute about 50 percent of the surface fluxes over the Arctic Ocean, but cover only 1 to 2 percent of its area. Convective plumes generated by wide leads may penetrate the surface inversion and produce condensate that spreads up to 250 km downwind of the lead, and may significantly affect the longwave radiative fluxes at the surface and thereby the sea ice thickness. The effects of leads and boundary layer clouds must be accurately represented in climate models to allow possible feedbacks between them and the sea ice thickness. The FIRE III Arctic boundary layer clouds field program, in conjunction with the SHEBA ice camp and the ARM North Slope of Alaska and Adjacent Arctic Ocean site, will offer an unprecedented opportunity to greatly improve our ability to parameterize the important effects of leads and boundary layer clouds in GCMs.

Assessing the performances of low impact development alternatives by long-term simulation for a semi-arid area in Tianjin, northern China.

PubMed

Huang, Jinhui Jeanne; Li, Yu; Niu, Shuai; Zhou, Shu H

2014-01-01

For areas that are urbanized rapidly, the practice of low impact development (LID) has gained an important place in stormwater management and urban planning due to its capability and beneficial effects in restoring the original hydrological cycle. The performances of LID alternatives can vary substantially due to different climate conditions. This study investigated the performances of five LID alternatives under a semi-arid climate in northern China on water balance and flood control. A numerical model, Storm Water Management Model version 5 (US Environmental Protection Agency), was employed to run 10 years' rainfall events for these objectives. Two evaluation methods were proposed in this study: the efficiency index for water balance and a performance radar chart. The investigation of the five LID alternatives revealed that these LID alternatives functioned differently in flood control and water balance, and porous pavement performed best in all indices except the lag time. The two evaluation methods, in conjunction with the long-term numerical simulation, can facilitate design and decision making by providing a clear picture of the performance and functions for these LID alternatives.

An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the U.S. northern and central Great Plains

USGS Publications Warehouse

Yang, Limin; Wylie, Bruce K.; Tieszen, Larry L.; Reed, Bradley C.

1998-01-01

Time-integrated normalized difference vegetation index (TI NDVI) derived from the multitemporal satellite imagery (1989–1993) was used as a surrogate for primary production to investigate climate impacts on grassland performance for central and northern Great Plains grasslands. Results suggest that spatial and temporal variability in growing season precipitation, potential evapotranspiration, and growing degree days are the most important controls on grassland performance and productivity. When TI NDVI and climate data of all grassland land cover classes were examined as a whole, a statistical model showed significant positive correlation between the TI NDVI and accumulated spring and summer precipitation, and a negative correlation between TI NDVI and spring potential evapotranspiration. The coefficient of determination (R2) of the general model was 0.45. When the TI NDVI-climate relationship was examined by individual land cover type, the relationship was generally better defined in terms of the variance accounted for by class-specific models . The photosynthetic pathway is an important determinant of grassland performance with northern mixed prairie (mixture of C3 and C4 grassland) TI NDVI affected by both thermal and moisture conditions during the growing season while southern plains grasslands (primarily C4grassland) were predominantly influenced by spring and summer precipitation. Grassland land cover classes associated with sandy soils also demonstrated a strong relationship between TI NDVI and growing season rainfall. Significant impact of interannual climate variability on the TI NDVI–climate relationship was also observed. The study suggests an integrated approach involving numerical models, satellite remote sensing, and field observations to monitor grassland ecosystem dynamics on a regional scale.

Storylines of combined land use and climatic drivers and their hydrological impacts in an alpine catchment (Brixental/Austria)

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Förster, Kristian; Meissl, Gertraud; Marke, Thomas; Schermer, Markus; Stotten, Rike; Formayer, Herbert; Themessl, Matthias

2017-04-01

We present a numerical modelling experiment with storylines of coupled land use and climate evolution as input in the physically-based, distributed water balance model WaSiM. The aim is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The climatic background is defined by simulations for the A1B and RCP 8.5 emission scenarios until 2050. These two climate projections were combined with three future land use developments for forest management, developed in an inter- and transdisciplinary assessment with local actors using plausible and consisent projections for forest management, policy, social cooperation, tourism and economy: (i) Ecological adaptation: The forest management consequently applies the political guidelines, and the forest cover is dominated by an ecological, place-adapted mixed cultivation with a harmonious age structure. (ii) Economical overexploitation and wildness: The increase in efficiency, cost reduction and short term results are in focus of the forest management. (iii) Withdrawal and wildness: Cultivation in general is decreasing, and the forest becomes vulnerable against natural hazards. A new module for snow-canopy interaction simulation, providing explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands, has been implemented in WaSiM. The new version of the model is used to model the coupled future climate/land use storylines for the Brixental. Results show the effects of climate change and land use on the water balance and streamflow in the catchment.

Impact of tropical cyclones on modeled extreme wind-wave climate

DOE PAGES

Timmermans, Ben; Stone, Daithi; Wehner, Michael; ...

2017-02-16

Here, the effect of forcing wind resolution on the extremes of global wind-wave climate are investigated in numerical simulations. Forcing winds from the Community Atmosphere Model at horizontal resolutions of ~1.0° and ~0.25° are used to drive Wavewatch III. Differences in extreme wave height are found to manifest most strongly in tropical cyclone (TC) regions, emphasizing the need for high-resolution forcing in those areas. Comparison with observations typically show improvement in performance with increased forcing resolution, with a strong influence in the tail of the distribution, although simulated extremes can exceed observations. A simulation for the end of the 21stmore » century under a RCP 8.5 type emission scenario suggests further increases in extreme wave height in TC regions.« less

Impact of tropical cyclones on modeled extreme wind-wave climate

NASA Astrophysics Data System (ADS)

Timmermans, Ben; Stone, Dáithí; Wehner, Michael; Krishnan, Harinarayan

2017-02-01

The effect of forcing wind resolution on the extremes of global wind-wave climate are investigated in numerical simulations. Forcing winds from the Community Atmosphere Model at horizontal resolutions of ˜1.0° and ˜0.25° are used to drive Wavewatch III. Differences in extreme wave height are found to manifest most strongly in tropical cyclone (TC) regions, emphasizing the need for high-resolution forcing in those areas. Comparison with observations typically show improvement in performance with increased forcing resolution, with a strong influence in the tail of the distribution, although simulated extremes can exceed observations. A simulation for the end of the 21st century under a RCP 8.5 type emission scenario suggests further increases in extreme wave height in TC regions.

A study of model parameters associated with the urban climate using HCMM data. [analysis of St. Louis, Missouri infrared imagery

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in the study of the intensity of the urban heat island is reported. The intensity of the heat island is commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions. The intensity is considered as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. Twelve case studies were selected and CCT's were ordered. In situ data was obtained from sixteen stations scattered about the city of St. Louis. Upper-air meteorological data were obtained and the water vapor and the temperature data were processed. Atmospheric transmissivities were computed for each of the case studies.

Assessing the Robustness of Green Infrastructure under Stochastic Design Storms and Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Chui, T. F. M.; Yang, Y.

2017-12-01

Green infrastructures (GI) have been widely used to mitigate flood risk, improve surface water quality, and to restore predevelopment hydrologic regimes. Commonly-used GI include, bioretention system, porous pavement and green roof, etc. They are normally sized to fulfil different design criteria (e.g. providing certain storage depths, limiting peak surface flow rates) that are formulated for current climate conditions. While GI commonly have long lifespan, the sensitivity of their performance to climate change is however unclear. This study first proposes a method to formulate suitable design criteria to meet different management interests (e.g. different levels of first flush reduction and peak flow reduction). Then typical designs of GI are proposed. In addition, a high resolution stochastic design storm generator using copulas and random cascade model is developed, which is calibrated using recorded rainfall time series. Then, few climate change scenarios are generated by varying the duration and depth of design storms, and changing the parameters of the calibrated storm generator. Finally, the performance of GI with typical designs under the random synthesized design storms are then assessed using numerical modeling. The robustness of the designs is obtained by the comparing their performance in the future scenarios to the current one. This study overall examines the robustness of the current GI design criteria under uncertain future climate conditions, demonstrating whether current GI design criteria should be modified to account for climate change.

Impacts of Aerosol Direct Effects on the South Asian climate: Assessment of Radiative Feedback Processes Using Model Simulations and Satellite/surface Measurements

NASA Astrophysics Data System (ADS)

Wang, S.; Gautam, R.; Lau, W. K.; Tsay, S.; Sun, W.; Kim, K.; Chern, J.; Colarco, P. R.; Hsu, N. C.; Lin, N.

2011-12-01

Current assessment of aerosol radiative effect is hindered by our incomplete knowledge of aerosol optical properties, especially absorption, and our current inability to quantify physical and microphysical processes. In this research, we investigate direct aerosol radiative effect over heavy aerosol loading areas (e.g., Indo-Gangetic Plains, South/East Asia) and its feedbacks on the South Asian climate during the pre-monsoon season (March-June) using the Purdue Regional Climate Model (PRCM) with prescribed aerosol data derived by the NASA Goddard Earth Observing System Model (GEOS-5). Our modeling domain covers South and East Asia (60-140E and 0-50N) with spatial resolutions of 45 km in horizontal and 28 layers in vertical. The model is integrated from 15 February to 30 June 2008 continuously without nudging (i.e., only forced by initial/boundary conditions). Two numerical experiments are conducted with and without the aerosol-radiation effects. Both simulations are successful in reproducing the synoptic patterns on seasonal-to-interannual time scales and capturing a pre-monsoon feature of the northward rainfall propagation over Indian region in early June which shown in Tropical Rainfall Measuring Mission (TRMM) observation. Preliminary result suggests aerosol-radiation interactions mainly alter surface-atmosphere energetics and further result in an adjustment of the vertical temperature distribution in lower atmosphere (below 700 hPa). The modifications of temperature and associated rainfall and circulation feedbacks on the regional climate will be discussed in the presentation. In addition to modeling study, we will also present the most recent results on aerosol properties, regional aerosol absorption, and radiative forcing estimation based on NASA's operational satellite and ground-based remote sensing. Observational results show spatial gradients in aerosol loading and solar absorption accounting over Indo-Gangetic Plains during the pre-monsoon season. The direct radiative forcing of aerosols at surface to be -19-23 Wm-2 (12-15 % of the surface solar insolation) over NW India is estimated using an observational approach. A comparison of aerosol radiative forcing between numerical simulation and observational estimate will be presented. Overall, this work will demonstrate the aerosol direct effects from both modeling and observation perspectives, and further to assess the physical processes underlying the aerosol radiative feedbacks and possible impacts on the large-scale South Asian monsoon system.

Uncertainties in assessing climate change impacts on the hydrology of Mediterranean basins

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2013-04-01

There is substantial evidence in historical and recent observations that the Mediterranean and neighboring regions are especially vulnerable to the impacts of climate change. Numerous climate projections, stemming from ensembles of global and regional climate models, agree on severe changes in the climate forcing which are likely to exacerbate subsequent ecological, economic and social impacts. Many of these causal connections are closely linked to the general expectation that water availability will decline in the already water-stressed basins of Africa, the Mediterranean region and the Near East, even though considerable regional variances must be expected. Consequently, climate change impacts on water resources are raising concerns regarding their possible management and security implications. Decreasing access to water resources and other related factors could be a cause or a 'multiplier' of tensions within and between countries. Whether security threats arise from climate impacts or options for cooperation evolve does not depend only on the severity of the impacts themselves, but on social, economic, and institutional vulnerabilities or resilience as well as factors that influence local, national and international relations. However, an assessment of vulnerability and risks hinges on natural, socio-economic, and political conditions and responses, all of which are uncertain. Multidisciplinary research is needed to tackle the multi-facet complexity of climate change impacts on water resources in the Mediterranean and neighboring countries. This is particularly true in a region of overall data scarcity and poor data management and exchange structures. The current potential to develop appropriate regional adaptation measures towards climate change impacts suffers heavily from large uncertainties. These spread along a long chain of components, starting from the definition of emission scenarios to global and regional climate modeling to impact models and a subsequent variety of management options and adaptation strategies. Therefore, the 4-year FP7-project CLIMB (Climate induced changes on the hydrology of Mediterranean basins, GA: 244151) includes a major focus on the assessment and quantification of uncertainties. First, CLIMB employs a rigorous climate change model analysis, auditing the Global and Regional Climate Model data available through the ENSEMBLES and PRUDENCE initiatives. The audits lead to select the best regional performers as compared to observed values during the climatic reference period (1971- 2000). Specific bias correction and downscaling procedures are applied to provide the driving inputs and meet the demands of the subsequent impact models, transferring a future climate signal (2041-2070) into hydrological quantities at the catchment or landscape scale. However, very limited quantitative knowledge is as yet available about the role of hydrological model complexity for climate change impact assessment, where predictive power becomes more and more important and raises the demand for process-based and spatially explicit model types. Thus, CLIMB uses hydrological model ensembles to analyze the performance of existing models and works to identify the appropriate level of model complexity, and thus to determine the data specifications required to provide robust results in a climate change context. The presentation focuses on the CLIMB multi-level strategy to uncertainty assessment and highlights latest findings in some of the seven CLIMB case studies. In particular, the presentation will demonstrate the current constraints of hydro-meteorological data availability and processing and searches for solutions that can eventually be provided by integrating hydro-meteorology and ICT research communities.

Short-term Time Step Convergence in a Climate Model

DOE PAGES

Wan, Hui; Rasch, Philip J.; Taylor, Mark; ...

2015-02-11

A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore » expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less

Modelled responses of the Kalahari Desert to 21st century climate and land use change.

PubMed

Mayaud, Jerome R; Bailey, Richard M; Wiggs, Giles F S

2017-06-20

Drylands are home to over 2 billion people globally, many of whom use the land for agricultural and pastoral activities. These vulnerable livelihoods could be disrupted if desert dunefields become more active in response to climate and land use change. Despite increasing knowledge about the role that wind, moisture availability and vegetation cover play in shaping dryland landscapes, relatively little is known about how drylands might respond to climatic and population pressures over the 21 st century. Here we use a newly developed numerical model, which fully couples vegetation and sediment-transport dynamics, to simulate potential landscape evolution at three locations in the Kalahari Desert, under two future emissions scenarios: stabilising (RCP 4.5) and high (RCP 8.5). Our simulations suggest that whilst our study sites will experience some climatically-induced landscape change, the impacts of climate change alone on vegetation cover and sediment mobility may be relatively small. However, human activity could strongly exacerbate certain landscape trajectories. Fire frequency has a primary impact on vegetation cover, and, together with grazing pressure, plays a significant role in modulating shrub encroachment and ensuing land degradation processes. Appropriate land management strategies must be implemented across the Kalahari Desert to avoid severe environmental and socio-economic consequences over the coming decades.

Climate Impacts of Cover Crops

NASA Astrophysics Data System (ADS)

Lombardozzi, D.; Wieder, W. R.; Bonan, G. B.; Morris, C. K.; Grandy, S.

2016-12-01

Cover crops are planted in agricultural rotation with the intention of protecting soil rather than harvest. Cover crops have numerous environmental benefits that include preventing soil erosion, increasing soil fertility, and providing weed and pest control- among others. In addition to localized environmental benefits, cover crops can have important regional or global biogeochemical impacts by increasing soil organic carbon, changing emissions of greenhouse trace gases like nitrous oxide and methane, and reducing hydrologic nitrogen losses. Cover crops may additionally affect climate by changing biogeophysical processes, like albedo and latent heat flux, though these potential changes have not yet been evaluated. Here we use the coupled Community Atmosphere Model (CAM5) - Community Land Model (CLM4.5) to test how planting cover crops in the United States may change biogeophysical fluxes and climate. We present seasonal changes in albedo, heat fluxes, evaporative partitioning, radiation, and the resulting changes in temperature. Preliminary analyses show that during seasons when cover crops are planted, latent heat flux increases and albedo decreases, changing the evaporative fraction and surface temperatures. Understanding both the biogeophysical changes caused by planting cover crops in this study and the biogeochemical changes found in other studies will give a clearer picture of the overall impacts of cover crops on climate and atmospheric chemistry, informing how this land use strategy will impact climate in the future.

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

Baptista, António M.

This work focuses on the numerical modeling of Columbia River estuarine circulation and associated modeling-supported analyses conducted as an integral part of a multi-disciplinary and multi-institutional effort led by NOAA's Northwest Fisheries Science Center. The overall effort is aimed at: (1) retrospective analyses to reconstruct historic bathymetric features and assess effects of climate and river flow on the extent and distribution of shallow water, wetland and tidal-floodplain habitats; (2) computer simulations using a 3-dimensional numerical model to evaluate the sensitivity of salmon rearing opportunities to various historical modifications affecting the estuary (including channel changes, flow regulation, and diking of tidalmore » wetlands and floodplains); (3) observational studies of present and historic food web sources supporting selected life histories of juvenile salmon as determined by stable isotope, microchemistry, and parasitology techniques; and (4) experimental studies in Grays River in collaboration with Columbia River Estuary Study Taskforce (CREST) and the Columbia Land Trust (CLT) to assess effects of multiple tidal wetland restoration projects on various life histories of juvenile salmon and to compare responses to observed habitat-use patterns in the mainstem estuary. From the above observations, experiments, and additional modeling simulations, the effort will also (5) examine effects of alternative flow-management and habitat-restoration scenarios on habitat opportunity and the estuary's productive capacity for juvenile salmon. The underlying modeling system is part of the SATURN1coastal-margin observatory [1]. SATURN relies on 3D numerical models [2, 3] to systematically simulate and understand baroclinic circulation in the Columbia River estuary-plume-shelf system [4-7] (Fig. 1). Multi-year simulation databases of circulation are produced as an integral part of SATURN, and have multiple applications in understanding estuary/plume variability, the role of the estuary and plume on salmon survival, and functional changes in the estuary-plume system in response to climate and human activities.« less

Physical modeling of the effects of climate change on freshwater lenses

NASA Astrophysics Data System (ADS)

Stoeckl, L.; Houben, G.

2012-04-01

The investigation of the fragile equilibrium between fresh and saline water on oceanic islands is of major importance for a sustainable management and protection of freshwater lenses. Overexploitation will lead to salt water intrusion (up-coning), in turn causing damages or even destruction of a lens in the long term. We have performed a series of experiments on the laboratory scale to investigate and visualize processes of freshwater lenses under different boundary conditions. In addition these scenarios were numerically simulated using the finite-element model FEFLOW. Results were also compared to analytical solutions for problems regarding e.g. mean travel times of flow paths within a freshwater lens. On the laboratory scale, a cross section of an island was simulated by setting up a sand-box model (200 cm x 50 cm x 5 cm). Lens dynamics are driven by density contrasts of saline and fresh water, recharge rate and Kf-values of the medium. We used a time-dependent, sequential application of the tracers uranine, eosine and indigotine, to represent different recharge events. With a stepwise increase of freshwater recharge, we could show that the maximum thickness of the lens increased in a non-linear behavior. Moreover we measured that the degradation of a freshwater lens after turning off the precipitation does not follow the same function as its development does. This means that a steady state freshwater lens does not degrade as fast as it develops under constant recharge. On the other side, we could show that this is not true for a partial degradation of the lens due to passing forces, like anthropogenic pumping or climate change. This is, because the recovery to equilibrium is always a quasi asymptotic process. Thus, times of re-equilibration to steady state will take longer after e.g. a drought, than the degradation during the draught itself. This behavior could also be verified applying the numerical finite-element model FEFLOW. In addition, numerical simulations will be used to close the gap between laboratory results and future field investigations. For example, impacts due to sea level rise induced by climate change can be up-scaled and compared to the results achieved from physical experiments. Analytical models (e.g. Fetter 1972, Vacher et al. 1990, Chesnaux & Allen 2007) were used as benchmarks in our investigations. Models in general are simplifications of a real situation trying to display the relevant processes. For further investigations it is planned to compare different models and generate new benchmark experiments to improve the accuracy of existing models.

High resolution regional climate simulation of the Hawaiian Islands - Validation of the historical run from 2003 to 2012

NASA Astrophysics Data System (ADS)

Xue, L.; Newman, A. J.; Ikeda, K.; Rasmussen, R.; Clark, M. P.; Monaghan, A. J.

2016-12-01

A high-resolution (a 1.5 km grid spacing domain nested within a 4.5 km grid spacing domain) 10-year regional climate simulation over the entire Hawaiian archipelago is being conducted at the National Center for Atmospheric Research (NCAR) using the Weather Research and Forecasting (WRF) model version 3.7.1. Numerical sensitivity simulations of the Hawaiian Rainband Project (HaRP, a filed experiment from July to August in 1990) showed that the simulated precipitation properties are sensitive to initial and lateral boundary conditions, sea surface temperature (SST), land surface models, vertical resolution and cloud droplet concentration. The validations of model simulated statistics of the trade wind inversion, temperature, wind field, cloud cover, and precipitation over the islands against various observations from soundings, satellites, weather stations and rain gauges during the period from 2003 to 2012 will be presented at the meeting.

Whole Atmosphere Simulation of Anthropogenic Climate Change

NASA Astrophysics Data System (ADS)

Solomon, Stanley C.; Liu, Han-Li; Marsh, Daniel R.; McInerney, Joseph M.; Qian, Liying; Vitt, Francis M.

2018-02-01

We simulated anthropogenic global change through the entire atmosphere, including the thermosphere and ionosphere, using the Whole Atmosphere Community Climate Model-eXtended. The basic result was that even as the lower atmosphere gradually warms, the upper atmosphere rapidly cools. The simulations employed constant low solar activity conditions, to remove the effects of variable solar and geomagnetic activity. Global mean annual mean temperature increased at a rate of +0.2 K/decade at the surface and +0.4 K/decade in the upper troposphere but decreased by about -1 K/decade in the stratosphere-mesosphere and -2.8 K/decade in the thermosphere. Near the mesopause, temperature decreases were small compared to the interannual variation, so trends in that region are uncertain. Results were similar to previous modeling confined to specific atmospheric levels and compared favorably with available measurements. These simulations demonstrate the ability of a single comprehensive numerical model to characterize global change throughout the atmosphere.

Wind and wave extremes over the world oceans from very large ensembles

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Aarnes, Ole Johan; Abdalla, Saleh; Bidlot, Jean-Raymond; Janssen, Peter A. E. M.

2014-07-01

Global return values of marine wind speed and significant wave height are estimated from very large aggregates of archived ensemble forecasts at +240 h lead time. Long lead time ensures that the forecasts represent independent draws from the model climate. Compared with ERA-Interim, a reanalysis, the ensemble yields higher return estimates for both wind speed and significant wave height. Confidence intervals are much tighter due to the large size of the data set. The period (9 years) is short enough to be considered stationary even with climate change. Furthermore, the ensemble is large enough for nonparametric 100 year return estimates to be made from order statistics. These direct return estimates compare well with extreme value estimates outside areas with tropical cyclones. Like any method employing modeled fields, it is sensitive to tail biases in the numerical model, but we find that the biases are moderate outside areas with tropical cyclones.

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.

Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive

DOE Data Explorer

Kumar, Jitendra; Collier, Nathan; Bisht, Gautam; Mills, Richard T.; Thornton, Peter E.; Iversen, Colleen M.; Romanovsky, Vladimir

2016-01-27

This Modeling Archive is in support of an NGEE Arctic discussion paper under review and available at http://www.the-cryosphere-discuss.net/tc-2016-29/. Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to atmosphere under warming climate. Ice--wedge polygons in the low-gradient polygonal tundra create a complex mosaic of microtopographic features. The microtopography plays a critical role in regulating the fine scale variability in thermal and hydrological regimes in the polygonal tundra landscape underlain by continuous permafrost. Modeling of thermal regimes of this sensitive ecosystem is essential for understanding the landscape behaviour under current as well as changing climate. We present here an end-to-end effort for high resolution numerical modeling of thermal hydrology at real-world field sites, utilizing the best available data to characterize and parameterize the models. We develop approaches to model the thermal hydrology of polygonal tundra and apply them at four study sites at Barrow, Alaska spanning across low to transitional to high-centered polygon and representative of broad polygonal tundra landscape. A multi--phase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using high resolution LiDAR DEM, microtopographic features of the landscape were characterized and represented in the high resolution model mesh. Best available soil data from field observations and literature was utilized to represent the complex hetogeneous subsurface in the numerical model. This data collection provides the complete set of input files, forcing data sets and computational meshes for simulations using PFLOTRAN for four sites at Barrow Environmental Observatory. It also document the complete computational workflow for this modeling study to allow verification, reproducibility and follow up studies.

A CBO Study: The Economics of Climate Change: A Primer

DTIC Science & Technology

2003-04-01

issues related to climate change , focusing primarily on its economic aspects. The study draws from numerous published sources to summarize the current...state of climate science and provide a conceptual framework for addressing climate change as an economic problem. It also examines public policy

GLACE: The Global Land-Atmosphere Coupling Experiment. Part 1; Overview

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Guo, Zhi-Chang; Dirmeyer, Paul A.; Bonan, Gordon; Chan, Edmond; Cox, Peter; Davies, Harvey; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva

2005-01-01

GLACE is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land-atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The twelve AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, enough similarity to pinpoint multi-model "hot spots" of land-atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model s coupling strength within the broad range of those documented here.