The regional aerosol-climate model REMO-HAM

Directory of Open Access Journals (Sweden)

J.-P. Pietikäinen

2012-11-01

Full Text Available REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km² and 10 × 10 km². Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

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

Science.gov (United States)

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

2013-04-01

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

Effect of model resolution on a regional climate model simulation over southeast Australia

KAUST Repository

Evans, J. P.; McCabe, Matthew

2013-01-01

Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

Effect of model resolution on a regional climate model simulation over southeast Australia

KAUST Repository

Evans, J. P.

2013-03-26

Dynamically downscaling climate projections from global climate models (GCMs) for use in impacts and adaptation research has become a common practice in recent years. In this study, the CSIRO Mk3.5 GCM is downscaled using the Weather Research and Forecasting (WRF) regional climate model (RCM) to medium (50 km) and high (10 km) resolution over southeast Australia. The influence of model resolution on the present-day (1985 to 2009) modelled regional climate and projected future (2075 to 2099) changes are examined for both mean climate and extreme precipitation characteristics. Increasing model resolution tended to improve the simulation of present day climate, with larger improvements in areas affected by mountains and coastlines. Examination of circumstances under which increasing the resolution decreased performance revealed an error in the GCM circulation, the effects of which had been masked by the coarse GCM topography. Resolution modifications to projected changes were largest in regions with strong topographic and coastline influences, and can be large enough to change the sign of the climate change projected by the GCM. Known physical mechanisms for these changes included orographic uplift and low-level blocking of air-masses caused by mountains. In terms of precipitation extremes, the GCM projects increases in extremes even when the projected change in the mean was a decrease: but this was not always true for the higher resolution models. Thus, while the higher resolution RCM climate projections often concur with the GCM projections, there are times and places where they differ significantly due to their better representation of physical processes. It should also be noted that the model resolution can modify precipitation characteristics beyond just its mean value.

A Reusable Framework for Regional Climate Model Evaluation

Science.gov (United States)

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

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and

Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

Science.gov (United States)

Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

2012-12-01

Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions

Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

Science.gov (United States)

Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

2016-01-01

Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

Hydrological Modeling in Northern Tunisia with Regional Climate Model Outputs: Performance Evaluation and Bias-Correction in Present Climate Conditions

Directory of Open Access Journals (Sweden)

Asma Foughali

2015-07-01

Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

Czech Academy of Sciences Publication Activity Database

Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan

2014-01-01

Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014

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

Science.gov (United States)

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

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

Science.gov (United States)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

Science.gov (United States)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Effective single scattering albedo estimation using regional climate model

CSIR Research Space (South Africa)

Tesfaye, M

2011-09-01

Full Text Available In this study, by modifying the optical parameterization of Regional Climate model (RegCM), the authors have computed and compared the Effective Single-Scattering Albedo (ESSA) which is a representative of VIS spectral region. The arid, semi...

Climate change scenarios of precipitation extremes in the Carpathian region based on an ENSEMBLE of regional climate models

Czech Academy of Sciences Publication Activity Database

Gaál, Ladislav; Beranová, Romana; Hlavčová, K.; Kyselý, Jan

2014-01-01

Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.946, year: 2014 http://www.hindawi.com/journals/amete/2014/943487/

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

Directory of Open Access Journals (Sweden)

Dmitry V. Sein

2014-07-01

Full Text Available The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis. Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the

Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

Science.gov (United States)

Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

2016-01-01

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against

A multi-model assessment of regional climate disparities caused by solar geoengineering

International Nuclear Information System (INIS)

Kravitz, Ben; Rasch, Philip J; Singh, Balwinder; Yoon, Jin-Ho; MacMartin, Douglas G; Robock, Alan; Ricke, Katharine L; Cole, Jason N S; Curry, Charles L; Irvine, Peter J; Ji, Duoying; Moore, John C; Keith, David W; Egill Kristjánsson, Jón; Muri, Helene; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting

2014-01-01

Global-scale solar geoengineering is the deliberate modification of the climate system to offset some amount of anthropogenic climate change by reducing the amount of incident solar radiation at the surface. These changes to the planetary energy budget result in differential regional climate effects. For the first time, we quantitatively evaluate the potential for regional disparities in a multi-model context using results from a model experiment that offsets the forcing from a quadrupling of CO 2 via reduction in solar irradiance. We evaluate temperature and precipitation changes in 22 geographic regions spanning most of Earth's continental area. Moderate amounts of solar reduction (up to 85% of the amount that returns global mean temperatures to preindustrial levels) result in regional temperature values that are closer to preindustrial levels than an un-geoengineered, high CO 2 world for all regions and all models. However, in all but one model, there is at least one region for which no amount of solar reduction can restore precipitation toward its preindustrial value. For most metrics considering simultaneous changes in both variables, temperature and precipitation values in all regions are closer to the preindustrial climate for a moderate amount of solar reduction than for no solar reduction. (letter)

A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

Science.gov (United States)

Rummukainen, M.; Räisänen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willén, U.; Hansson, U.; Jones, C.

This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results.

A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M.; Raeisaenen, J.; Bringfelt, B.; Ullerstig, A.; Omstedt, A.; Willen, U.; Hansson, U.; Jones, C. [Rossby Centre, Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)

2001-03-01

This work presents a regional climate model, the Rossby Centre regional Atmospheric model (RCA1), recently developed from the High Resolution Limited Area Model (HIRLAM). The changes in the HIRLAM parametrizations, necessary for climate-length integrations, are described. A regional Baltic Sea ocean model and a modeling system for the Nordic inland lake systems have been coupled with RCA1. The coupled system has been used to downscale 10-year time slices from two different general circulation model (GCM) simulations to provide high-resolution regional interpretation of large-scale modeling. A selection of the results from the control runs, i.e. the present-day climate simulations, are presented: large-scale free atmospheric fields, the surface temperature and precipitation results and results for the on-line simulated regional ocean and lake surface climates. The regional model modifies the surface climate description compared to the GCM simulations, but it is also substantially affected by the biases in the GCM simulations. The regional model also improves the representation of the regional ocean and the inland lakes, compared to the GCM results. (orig.)

Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

Science.gov (United States)

Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

2018-06-01

The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

Towards a regional climate model coupled to a comprehensive hydrological model

Science.gov (United States)

Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

2010-12-01

When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

Regional Scale/Regional Climate Model Development and Its Applications at Goddard

Science.gov (United States)

Tao, W.-K.; Lau, W.; Qian, J.; Jia, Y.; Wetzel, P.; Chou, M.-D.; Wang, Y.; Lynn, B.

2000-01-01

A Regional Land-Atmosphere Climate Simulation System (RELACS) is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model (Penn State/NCAR MM5) with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the Indo-China/South China Sea (SCS)/China, N. America and S. America region.

Intercomparison of four regional climate models for the German State of Saxonia

Science.gov (United States)

Kreienkamp, F.; Spekat, A.; Enke, W.

2009-09-01

Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.

Ensemble of regional climate model projections for Ireland

Science.gov (United States)

Nolan, Paul; McGrath, Ray

2016-04-01

The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season

Implications of regional improvement in global climate models for agricultural impact research

International Nuclear Information System (INIS)

Ramirez-Villegas, Julian; Thornton, Philip K; Jarvis, Andy; Challinor, Andrew J

2013-01-01

Global climate models (GCMs) have become increasingly important for climate change science and provide the basis for most impact studies. Since impact models are highly sensitive to input climate data, GCM skill is crucial for getting better short-, medium- and long-term outlooks for agricultural production and food security. The Coupled Model Intercomparison Project (CMIP) phase 5 ensemble is likely to underpin the majority of climate impact assessments over the next few years. We assess 24 CMIP3 and 26 CMIP5 simulations of present climate against climate observations for five tropical regions, as well as regional improvements in model skill and, through literature review, the sensitivities of impact estimates to model error. Climatological means of seasonal mean temperatures depict mean errors between 1 and 18 ° C (2–130% with respect to mean), whereas seasonal precipitation and wet-day frequency depict larger errors, often offsetting observed means and variability beyond 100%. Simulated interannual climate variability in GCMs warrants particular attention, given that no single GCM matches observations in more than 30% of the areas for monthly precipitation and wet-day frequency, 50% for diurnal range and 70% for mean temperatures. We report improvements in mean climate skill of 5–15% for climatological mean temperatures, 3–5% for diurnal range and 1–2% in precipitation. At these improvement rates, we estimate that at least 5–30 years of CMIP work is required to improve regional temperature simulations and at least 30–50 years for precipitation simulations, for these to be directly input into impact models. We conclude with some recommendations for the use of CMIP5 in agricultural impact studies. (letter)

Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas

Directory of Open Access Journals (Sweden)

R. Deidda

2013-12-01

Full Text Available This paper discusses the relative performance of several climate models in providing reliable forcing for hydrological modeling in six representative catchments in the Mediterranean region. We consider 14 Regional Climate Models (RCMs, from the EU-FP6 ENSEMBLES project, run for the A1B emission scenario on a common 0.22° (about 24 km rotated grid over Europe and the Mediterranean region. In the validation period (1951 to 2010 we consider daily precipitation and surface temperatures from the observed data fields (E-OBS data set, available from the ENSEMBLES project and the data providers in the ECA&D project. Our primary objective is to rank the 14 RCMs for each catchment and select the four best-performing ones to use as common forcing for hydrological models in the six Mediterranean basins considered in the EU-FP7 CLIMB project. Using a common suite of four RCMs for all studied catchments reduces the (epistemic uncertainty when evaluating trends and climate change impacts in the 21st century. We present and discuss the validation setting, as well as the obtained results and, in some detail, the difficulties we experienced when processing the data. In doing so we also provide useful information and advice for researchers not directly involved in climate modeling, but interested in the use of climate model outputs for hydrological modeling and, more generally, climate change impact studies in the Mediterranean region.

Climatic features of the Red Sea from a regional assimilative model

KAUST Repository

Viswanadhapalli, Yesubabu

2016-08-16

The Advanced Research version of Weather Research and Forecasting (WRF-ARW) model was used to generate a downscaled, 10-km resolution regional climate dataset over the Red Sea and adjacent region. The model simulations are performed based on two, two-way nested domains of 30- and 10-km resolutions assimilating all conventional observations using a cyclic three-dimensional variational approach over an initial 12-h period. The improved initial conditions are then used to generate regional climate products for the following 24 h. We combined the resulting daily 24-h datasets to construct a 15-year Red Sea atmospheric downscaled product from 2000 to 2014. This 15-year downscaled dataset is evaluated via comparisons with various in situ and gridded datasets. Our analysis indicates that the assimilated model successfully reproduced the spatial and temporal variability of temperature, wind, rainfall, relative humidity and sea level pressure over the Red Sea region. The model also efficiently simulated the seasonal and monthly variability of wind patterns, the Red Sea Convergence Zone and associated rainfall. Our results suggest that dynamical downscaling and assimilation of available observations improve the representation of regional atmospheric features over the Red Sea compared to global analysis data from the National Centers for Environmental Prediction. We use the dataset to describe the atmospheric climatic conditions over the Red Sea region. © 2016 Royal Meteorological Society.

Regional climate model sensitivity to domain size

Energy Technology Data Exchange (ETDEWEB)

Leduc, Martin [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada); UQAM/Ouranos, Montreal, QC (Canada); Laprise, Rene [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network, ESCER Centre, Montreal (Canada)

2009-05-15

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the ''perfect model'' approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 x 100 grid points). The permanent ''spatial spin-up'' corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere. (orig.)

Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

NARCIS (Netherlands)

Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

2016-01-01

Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

A review on regional convection permitting climate modeling

Science.gov (United States)

van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

2016-04-01

are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361

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

Science.gov (United States)

Horton, Radley M.

Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even

Integration of climatic indices in an objective probabilistic model for establishing and mapping viticultural climatic zones in a region

Science.gov (United States)

Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; Honorio, Fulgencio

2016-05-01

Different climatic indices have been proposed to determine the wine suitability in a region. Some of them are related to the air temperature, but the hydric component of climate should also be considered which, in turn, is influenced by the precipitation during the different stages of the grapevine growing and ripening periods. In this study, we propose using the information obtained from ten climatic indices [heliothermal index (HI), cool night index (CI), dryness index (DI), growing season temperature (GST), the Winkler index (WI), September mean thermal amplitude (MTA), annual precipitation (AP), precipitation during flowering (PDF), precipitation before flowering (PBF), and summer precipitation (SP)] as inputs in an objective and probabilistic model, the Rasch model, with the aim of integrating the individual effects of them, obtaining the climate data that summarize all main climatic indices, which could influence on wine suitability from a climate viewpoint, and utilizing the Rasch measures to generate homogeneous climatic zones. The use of the Rasch model to estimate viticultural climatic suitability constitutes a new application of great practical importance, enabling to rationally determine locations in a region where high viticultural potential exists and establishing a ranking of the climatic indices which exerts an important influence on wine suitability in a region. Furthermore, from the measures of viticultural climatic suitability at some locations, estimates can be computed using a geostatistical algorithm, and these estimates can be utilized to map viticultural climatic zones in a region. To illustrate the process, an application to Extremadura, southwestern Spain, is shown.

An intercomparison of regional climate model data for hydrological impact studies in Denmark

DEFF Research Database (Denmark)

Van Roosmalen, Lieke Petronella G; Christensen, Jens Hesselbjerg; Butts, Michael

2010-01-01

The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject to consider......The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject...... to considerable systematic errors. In this study, projected climate change data from the RCM HIRHAM4 are used to generate climate scenario time series of precipitation, temperature, and reference evapotranspiration for the period 2071-2100 for hydrological impact assessments in Denmark. RCM output for the present......-day period (1961-1990) are compared to an observational data set, with precipitation corrected for undercatch and wetting losses, to quantify systematic model errors. A delta change method is applied to cope with these biases. A question arises as to how variable the climate change signals are...

Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

DEFF Research Database (Denmark)

Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

Regional climate change scenarios

International Nuclear Information System (INIS)

Somot, S.

2005-01-01

Because studies of the regional impact of climate change need higher spatial resolution than that obtained in standard global climate change scenarios, developing regional scenarios from models is a crucial goal for the climate modelling community. The zoom capacity of ARPEGE-Climat, the Meteo-France climate model, allows use of scenarios with a horizontal resolution of about 50 km over France and the Mediterranean basin. An IPCC-A2 scenario for the end of the 21. century in France shows higher temperatures in each season and more winter and less summer precipitation than now. Tuning the modelled statistical distributions to observed temperature and precipitation allows us to study changes in the frequency of extreme events between today's climate and that at the end of century. The frequency of very hot days in summer will increase. In particular, the frequency of days with a maximum temperature above 35 deg C will be multiplied by a factor of 10, on average. In our scenario, the Toulouse area and Provence might see one quarter of their summer days with a maximum temperature above 35 deg C. (author)

Use of regional climate model simulations as an input for hydrological models for the Hindukush-Karakorum-Himalaya region

NARCIS (Netherlands)

Akhtar, M.; Ahmad, N.; Booij, Martijn J.

2009-01-01

The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and

Regional climate model sensitivity to domain size

Science.gov (United States)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Science.gov (United States)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Regional climate models downscaling in the Alpine area with multimodel superensemble

Directory of Open Access Journals (Sweden)

D. Cane

2013-05-01

Full Text Available The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs, are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project, which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to

Regional climate models downscaling in the Alpine area with multimodel superensemble

Science.gov (United States)

Cane, D.; Barbarino, S.; Renier, L. A.; Ronchi, C.

2013-05-01

The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the

Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

Science.gov (United States)

Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

2015-12-01

In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

Regional greenhouse climate effects

International Nuclear Information System (INIS)

Hansen, J.; Rind, D.; Delgenio, A.; Lacis, A.; Lebedeff, S.; Prather, M.; Ruedy, R.; Karl, T.

1990-01-01

The authors discuss the impact of an increasing greenhouse effect on three aspects of regional climate: droughts, storms and temperature. A continuous of current growth rates of greenhouse gases causes an increase in the frequency and severity of droughts in their climate model simulations, with the greatest impacts in broad regions of the subtropics and middle latitudes. But the greenhouse effect enhances both ends of the hydrologic cycle in the model, that is, there is an increased frequency of extreme wet situations, as well as increased drought. Model results are shown to imply that increased greenhouse warming will lead to more intense thunderstorms, that is, deeper thunderstorms with greater rainfall. Emanual has shown that the model results also imply that the greenhouse warming leads to more destructive tropical cyclones. The authors present updated records of observed temperatures and show that the observations and model results, averaged over the globe and over the US, are generally consistent. The impacts of simulated climate changes on droughts, storms and temperature provide no evidence that there will be regional winners if greenhouse gases continue to increase rapidly

Internal variability in a regional climate model over West Africa

Energy Technology Data Exchange (ETDEWEB)

Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)

2008-02-15

Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)

Multisite bias correction of precipitation data from regional climate models

Czech Academy of Sciences Publication Activity Database

Hnilica, Jan; Hanel, M.; Puš, V.

2017-01-01

Roč. 37, č. 6 (2017), s. 2934-2946 ISSN 0899-8418 R&D Projects: GA ČR GA16-05665S Grant - others:Grantová agentura ČR - GA ČR(CZ) 16-16549S Institutional support: RVO:67985874 Keywords : bias correction * regional climate model * correlation * covariance * multivariate data * multisite correction * principal components * precipitation Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Climatic research Impact factor: 3.760, year: 2016

Evaluating the impacts of climate change on diurnal wind power cycles using multiple regional climate models

KAUST Repository

Goddard, Scott D.

2015-05-01

Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind-generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high-resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi-parametric mixed model is fit using cubic B-splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production.

Mixed precipitation occurrences over southern Québec, Canada, under warmer climate conditions using a regional climate model

Science.gov (United States)

Matte, Dominic; Thériault, Julie M.; Laprise, René

2018-05-01

Winter weather events with temperatures near 0°C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11° grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980-2009) are found to be comparable to observations. The projections for the future scenario (2070-2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

Impact of surface waves in a Regional Climate Model

DEFF Research Database (Denmark)

Rutgersson, Anna; Sætra, Oyvind; Semedo, Alvaro

2010-01-01

A coupled regional atmosphere-wave model system is developed with the purpose of investigating the impact of climate changes on the wave field, as well as feed-back effects of the wave field on the atmospheric parameters. This study focuses on the effects of introducing a two-way atmosphere...

FY08 LDRD Final Report Regional Climate

Energy Technology Data Exchange (ETDEWEB)

Bader, D C; Chin, H; Caldwell, P M

2009-05-19

An integrated, multi-model capability for regional climate change simulation is needed to perform original analyses to understand and prepare for the impacts of climate change on the time and space scales that are critical to California's future environmental quality and economic prosperity. Our intent was to develop a very high resolution regional simulation capability to address consequences of climate change in California to complement the global modeling capability that is supported by DOE at LLNL and other institutions to inform national and international energy policies. The California state government, through the California Energy Commission (CEC), institutionalized the State's climate change assessment process through its biennial climate change reports. The bases for these reports, however, are global climate change simulations for future scenarios designed to inform international policy negotiations, and are primarily focused on the global to continental scale impacts of increasing emissions of greenhouse gases. These simulations do not meet the needs of California public and private officials who will make major decisions in the next decade that require an understanding of climate change in California for the next thirty to fifty years and its effects on energy use, water utilization, air quality, agriculture and natural ecosystems. With the additional development of regional dynamical climate modeling capability, LLNL will be able to design and execute global simulations specifically for scenarios important to the state, then use those results to drive regional simulations of the impacts of the simulated climate change for regions as small as individual cities or watersheds. Through this project, we systematically studied the strengths and weaknesses of downscaling global model results with a regional mesoscale model to guide others, particularly university researchers, who are using the technique based on models with less complete

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

Science.gov (United States)

Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing 10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Regional Spectral Model simulations of the summertime regional climate over Taiwan and adjacent areas

Science.gov (United States)

Ching-Teng Lee; Ming-Chin Wu; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) version 97 was used to investigate the regional summertime climate over Taiwan and adjacent areas for June-July-August of 1990 through 2000. The simulated sea-level-pressure and wind fields of RSM1 with 50-km grid space are similar to the reanalysis, but the strength of the...

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

Science.gov (United States)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land

Application of remote sensing for analyzing climatic variation in the boreal and subarctic regions of Canada and for validating the Canadian Regional Climate Model; Application de la teledetection a l'analyse de la variabilite climatique des regions boreales et subarctiques du Canada et a la validation du modele regional canadien du climat

Energy Technology Data Exchange (ETDEWEB)

Fillol, E.J.

2003-07-01

This study examined climate variations over the past few decades as well as the tools used to model future climate. The study included an interpretation of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) time series data at the continental spatial scale. Data collected over a period of two decades was used to study and monitor Canada's boreal ecosystem activity and to observe recent climatic change. The study involved the use of classical parameters associated with remote sensing in the visible and thermal infrared spectra for vegetation activity and land-surface temperatures. Problems associated with instrumental drift and inter-satellite adjustment were minimized by choosing indicators for the length of the growing season, annual growing degree-days and ecotone displacement. Climate variations over the past twenty years were compared with daily meteorological data of temperature, precipitation and snow cover. Rapid cycle climatic phenomena such as the El Nino and La Nina appear to have influenced the central region of Canada. The North Atlantic Oscillation and Arctic Oscillation also influenced the climate regime of Canada and annual growing degree-days. Indicators for vegetation activity and land-surface temperature suggest that a North-South disparity exists over Canada. A warming trend with an increased growing season was observed for the region north of the 55 parallel, while southern regions appear to be cooling. This study also used remote sensing to validate the Canadian Regional Climate Model (CRCM) through a comparison of ground temperature values modelled by the CRCM with composite satellite temperatures. The results indicate a small under-estimation of the CRCM ground temperature during the summer due to an overestimation of the precipitation rate. It was concluded that climate models such as the CRCM are useful in making reliable predictions of future climate trends.

Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

Directory of Open Access Journals (Sweden)

M. Trail

2013-09-01

Full Text Available Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US, one region during summer (Texas, and one region where changes potentially would lead to better air quality during spring (Northeast. Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

Science.gov (United States)

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

Very high resolution regional climate model simulations over Greenland: Identifying added value

DEFF Research Database (Denmark)

Lucas-Picher, P.; Wulff-Nielsen, M.; Christensen, J.H.

2012-01-01

models. However, the bias between the simulations and the few available observations does not reduce with higher resolution. This is partly explained by the lack of observations in regions where the higher resolution is expected to improve the simulated climate. The RCM simulations show......This study presents two simulations of the climate over Greenland with the regional climate model (RCM) HIRHAM5 at 0.05° and 0.25° resolution driven at the lateral boundaries by the ERA-Interim reanalysis for the period 1989–2009. These simulations are validated against observations from...... that the temperature has increased the most in the northern part of Greenland and at lower elevations over the period 1989–2009. Higher resolution increases the relief variability in the model topography and causes the simulated precipitation to be larger on the coast and smaller over the main ice sheet compared...

Current climate and climate change over India as simulated by the Canadian Regional Climate Model

Science.gov (United States)

Alexandru, Adelina; Sushama, Laxmi

2015-08-01

The performance of the fifth generation of the Canadian Regional Climate Model (CRCM5) in reproducing the main climatic characteristics over India during the southwest (SW)-, post- and pre-monsoon seasons are presented in this article. To assess the performance of CRCM5, European Centre for Medium- Range Weather Forecasts (ECMWF) Re- Analysis (ERA- 40) and Interim re-analysis (ERA-Interim) driven CRCM5 simulation is compared against independent observations and reanalysis data for the 1971-2000 period. Projected changes for two future periods, 2041-2070 and 2071-2100, with respect to the 1971-2000 current period are assessed based on two transient climate change simulations of CRCM5 spanning the 1950-2100 period. These two simulations are driven by the Canadian Earth System Model version 2 (CanESM2) and the Max Planck Institute for Meteorology's Earth System Low Resolution Model (MPI-ESM-LR), respectively. The boundary forcing errors associated with errors in the driving global climate models are also studied by comparing the 1971-2000 period of the CanESM2 and MPI-ESM-LR driven simulations with that of the CRCM5 simulation driven by ERA-40/ERA-Interim. Results show that CRCM5 driven by ERA-40/ERA-Interim is in general able to capture well the temporal and spatial patterns of 2 m-temperature, precipitation, wind, sea level pressure, total runoff and soil moisture over India in comparison with available reanalysis and observations. However, some noticeable differences between the model and observational data were found during the SW-monsoon season within the domain of integration. CRCM5 driven by ERA-40/ERA-Interim is 1-2 °C colder than CRU observations and generates more precipitation over the Western Ghats and central regions of India, and not enough in the northern and north-eastern parts of India and along the Konkan west coast in comparison with the observed precipitation. The monsoon onset seems to be relatively well captured over the southwestern coast of

Wind climate from the regional climate model REMO

DEFF Research Database (Denmark)

Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

2010-01-01

Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that......, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis pressure data. The spatial correlation of REMO surface winds in Europe...

Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

Energy Technology Data Exchange (ETDEWEB)

Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

2010-06-15

We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

Science.gov (United States)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Modeling of Regional Climate over Red Sea and Arabian Peninsula

KAUST Repository

Stenchikov, Georgiy L.

2011-04-09

Observations, re-analyses, and climate model simulations show strong surface temperature trends in Middle East and Arabian Peninsula in the last 30 years. Trends are especially pronounced in summer exceeding +1K/decade. However, some regions, e.g., the So

Strategies for Teaching Regional Climate Modeling: Online Professional Development for Scientists and Decision Makers

Science.gov (United States)

Walton, P.; Yarker, M. B.; Mesquita, M. D. S.; Otto, F. E. L.

2014-12-01

There is a clear role for climate science in supporting decision making at a range of scales and in a range of contexts: from Global to local, from Policy to Industry. However, clear a role climate science can play, there is also a clear discrepancy in the understanding of how to use the science and associated tools (such as climate models). Despite there being a large body of literature on the science there is clearly a need to provide greater support in how to apply appropriately. However, access to high quality professional development courses can be problematic, due to geographic, financial and time constraints. In attempt to address this gap we independently developed two online professional courses that focused on helping participants use and apply two regional climate models, WRF and PRECIS. Both courses were designed to support participants' learning through tutor led programs that covered the basic climate scientific principles of regional climate modeling and how to apply model outputs. The fundamental differences between the two courses are: 1) the WRF modeling course expected participants to design their own research question that was then run on a version of the model, whereas 2) the PRECIS course concentrated on the principles of regional modeling and how the climate science informed the modeling process. The two courses were developed to utilise the cost and time management benefits associated with eLearning, with the recognition that this mode of teaching can also be accessed internationally, providing professional development courses in countries that may not be able to provide their own. The development teams saw it as critical that the courses reflected sound educational theory, to ensure that participants had the maximum opportunity to learn successfully. In particular, the role of reflection is central to both course structures to help participants make sense of the science in relation to their own situation. This paper details the different

Implementation of a parallel version of a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Gerstengarbe, F.W. [ed.; Kuecken, M. [Potsdam-Institut fuer Klimafolgenforschung (PIK), Potsdam (Germany); Schaettler, U. [Deutscher Wetterdienst, Offenbach am Main (Germany). Geschaeftsbereich Forschung und Entwicklung

1997-10-01

A regional climate model developed by the Max Planck Institute for Meterology and the German Climate Computing Centre in Hamburg based on the `Europa` and `Deutschland` models of the German Weather Service has been parallelized and implemented on the IBM RS/6000 SP computer system of the Potsdam Institute for Climate Impact Research including parallel input/output processing, the explicit Eulerian time-step, the semi-implicit corrections, the normal-mode initialization and the physical parameterizations of the German Weather Service. The implementation utilizes Fortran 90 and the Message Passing Interface. The parallelization strategy used is a 2D domain decomposition. This report describes the parallelization strategy, the parallel I/O organization, the influence of different domain decomposition approaches for static and dynamic load imbalances and first numerical results. (orig.)

Observational uncertainty and regional climate model evaluation: A pan-European perspective

Science.gov (United States)

Kotlarski, Sven; Szabó, Péter; Herrera, Sixto; Räty, Olle; Keuler, Klaus; Soares, Pedro M.; Cardoso, Rita M.; Bosshard, Thomas; Pagé, Christian; Boberg, Fredrik; Gutiérrez, José M.; Jaczewski, Adam; Kreienkamp, Frank; Liniger, Mark. A.; Lussana, Cristian; Szepszo, Gabriella

2017-04-01

Local and regional climate change assessments based on downscaling methods crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling via regional climate models (RCMs) observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. Focusing on the evaluation of RCMs, we here analyze the influence of uncertainties in observational reference data on evaluation results in a well-defined performance assessment framework and on a European scale. For this purpose we employ three different gridded observational reference grids, namely (1) the well-established EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. In terms of climate models five reanalysis-driven experiments carried out by five different RCMs within the EURO-CORDEX framework are used. Two variables (temperature and precipitation) and a range of evaluation metrics that reflect different aspects of RCM performance are considered. We furthermore include an illustrative model ranking exercise and relate observational spread to RCM spread. The results obtained indicate a varying influence of observational uncertainty on model evaluation depending on the variable, the season, the region and the specific performance metric considered. Over most parts of the continent, the influence of the choice of the reference dataset for temperature is rather small for seasonal mean values and inter-annual variability. Here, model uncertainty (as measured by the spread between the five RCM simulations considered) is typically much larger than reference data uncertainty. For

Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

Science.gov (United States)

Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

2017-04-01

The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

Ensemble-based Regional Climate Prediction: Political Impacts

Science.gov (United States)

Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

2008-12-01

Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?

Science.gov (United States)

For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated met...

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

Science.gov (United States)

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

Performance of ALADIN-Climate/CZ over the area of the Czech Republic in comparison with ENSEMBLES regional climate models

Czech Academy of Sciences Publication Activity Database

Crhová, L.; Holtanova, E.; Kalvová, J.; Farda, Aleš

2014-01-01

Roč. 58, č. 1 (2014), s. 148-169 ISSN 0039-3169 R&D Projects: GA MŽP(CZ) SP/1A6/108/07 Institutional support: RVO:67179843 Keywords : regional climate model * climate model performance * Taylor diagram * skill score Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.806, year: 2014

Quantifying uncertainty due to internal variability using high-resolution regional climate model simulations

Science.gov (United States)

Gutmann, E. D.; Ikeda, K.; Deser, C.; Rasmussen, R.; Clark, M. P.; Arnold, J. R.

2015-12-01

The uncertainty in future climate predictions is as large or larger than the mean climate change signal. As such, any predictions of future climate need to incorporate and quantify the sources of this uncertainty. One of the largest sources comes from the internal, chaotic, variability within the climate system itself. This variability has been approximated using the 30 ensemble members of the Community Earth System Model (CESM) large ensemble. Here we examine the wet and dry end members of this ensemble for cool-season precipitation in the Colorado Rocky Mountains with a set of high-resolution regional climate model simulations. We have used the Weather Research and Forecasting model (WRF) to simulate the periods 1990-2000, 2025-2035, and 2070-2080 on a 4km grid. These simulations show that the broad patterns of change depicted in CESM are inherited by the high-resolution simulations; however, the differences in the height and location of the mountains in the WRF simulation, relative to the CESM simulation, means that the location and magnitude of the precipitation changes are very different. We further show that high-resolution simulations with the Intermediate Complexity Atmospheric Research model (ICAR) predict a similar spatial pattern in the change signal as WRF for these ensemble members. We then use ICAR to examine the rest of the CESM Large Ensemble as well as the uncertainty in the regional climate model due to the choice of physics parameterizations.

Med-CORDEX: a first coordinated inter-comparison of high-resolution and fully coupled regional climate models for the Mediterranean

Science.gov (United States)

Somot, Samuel

2015-04-01

Due to its geographical, meteorological and oceanographic features, the Mediterranean region can be considered as one of the best place to test and use regional climate modelling tools. It has been chosen as one of the CORDEX sub-domain (MED) leading to the Med-CORDEX initiative. This open and voluntary initiative, financially supported by MISTRALS/HyMeX, has been proposed by the Mediterranean climate modelling research community as a follow-up of previous initiatives. In addition to the CORDEX-like simulations (Atmosphere-RCM, 50 km, ERA-Interim and GCM driven runs), Med-CORDEX includes additional simulations to experiment some of the regional climate modelling current challenges. We present here the status and results of these additional simulations dedicated to the use of (1) very high-resolution Regional Climate Models (RCM, up to 10 km) and (2) fully coupled Regional Climate System Models (RCSM), coupling the various components of the regional climate (atmosphere, land surface and hydrology, river and ocean). Today, Med-CORDEX gathers 23 different modelling groups from 9 different countries (France, Italy, Spain, Serbia, Turkey, Greece, Tunisia, Germany, Hungary) in Europe, Middle-East and North-Africa. They use 12 different atmosphere RCMs including land-surface representation, 4 river models, 10 regional ocean models and 12 different Regional Climate System Models. Almost all the simulations planned (Evaluation, Historical and Scenarios modes) have been completed by the modelling teams. More than half of the runs are archived and freely available for non-commercial use through a dedicated database hosted at ENEA at www.medcordex.eu in common and standardized netcdf format (265,000 files and 3.6 Tb uploaded). This includes atmosphere-only, ocean-only and fully coupled regional climate models. In particular multi-model regional ocean simulations have been archived in a common and standardized format for the first time in the history of the Mediterranean Sea

Does Nudging Squelch the Extremes in Regional Climate Modeling?

Science.gov (United States)

An important question in regional climate downscaling is whether to constrain (nudge) the interior of the limited-area domain toward the larger-scale driving fields. Prior research has demonstrated that interior nudging can increase the skill of regional climate predictions origin...

Application of regional climate models to the Indian winter monsoon over the western Himalayas.

Science.gov (United States)

Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

2013-12-01

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of the regional climate response in Australia to large-scale climate modes in the historical NARCliM simulations

Science.gov (United States)

Fita, L.; Evans, J. P.; Argüeso, D.; King, A.; Liu, Y.

2017-10-01

NARCliM (New South Wales (NSW)/Australian Capital Territory (ACT) Regional Climate Modelling project) is a regional climate modeling project for the Australian area. It is providing a comprehensive dynamically downscaled climate dataset for the CORDEX-AustralAsia region at 50-km resolution, and south-East Australia at a resolution of 10 km. The first phase of NARCliM produced 60-year long reanalysis driven regional simulations to allow evaluation of the regional model performance. This long control period (1950-2009) was used so that the model ability to capture the impact of large scale climate modes on Australian climate could be examined. Simulations are evaluated using a gridded observational dataset. Results show that using model independence as a criteria for choosing atmospheric model configuration from different possible sets of parameterizations may contribute to the regional climate models having different overall biases. The regional models generally capture the regional climate response to large-scale modes better than the driving reanalysis, though no regional model improves on all aspects of the simulated climate.

Use of regional climate models data for groundwater recharge modelling in Baltic artesian basin

Science.gov (United States)

Timuhins, A.; Klints, I.; Sennikovs, J.; Virbulis, J.

2012-04-01

Baltic artesian basin (BAB) covers about 480000 square kilometres. BAB includes territory of Latvia, Lithuania, Estonia, parts of Poland, Russia, Belarus and Baltic Sea. The closed hydrogeological mathematical model for the BAB is developed in University of Latvia and reference calculations made in steady state mode. No-flow boundary condition is applied on the bottom and side boundaries of BAB. Hydraulic head is fixed on the seabed and largest lakes, and along the main river lines. Main water supply wells also are presented in the model as a pointwise water extraction. Precipitation is the main source of the groundwater recharge in the BAB region. Infiltration parameterization is responsible for this water source in BAB model. During the early stage of calibration of BAB hydrogeological model an automatic calibration for the hydraulic conductivities of permeable layers and single infiltration rate was attempted. Performing BAB model calibration it was noted that the differences of calculated and observed hydraulic heads (used for calculating the calibration penalty function) can be reduced by introducing a spatially distributed infiltration model. The aim of the present study is improving of the infiltration model, as well as preserving a short computation time (several minutes) for the piezometric head. Direct solution of improvement of the infiltration would be a usage of the advanced hydrological models. However, an accurate hydrological model requires a lot of computational power. It should couple meteorological and hydrological parameters and requires additional calibration. The regional climate model (KNMI-RACMO2 25 km resolution) results from ENSEMBLES project are used for the spatially distributed infiltration field calculation. The infiltration field is constructed as weighted difference of 30 year averaged precipitation and evaporation fields. The weight value is calibrated and a considerable decrease of the value of penalty function of the groundwater

Preliminary evaluation of techniques for transforming regional climate model output to the potential repository site in support of Yucca Mountain future climate synthesis

International Nuclear Information System (INIS)

Church, H.W.; Zak, B.D.; Behl, Y.K.

1995-06-01

The report describes a preliminary evaluation of models for transforming regional climate model output from a regional to a local scale for the Yucca Mountain area. Evaluation and analysis of both empirical and numerical modeling are discussed which is aimed at providing site-specific, climate-based information for use by interfacing activities. Two semiempirical approaches are recommended for further analysis

A review on vegetation models and applicability to climate simulations at regional scale

Science.gov (United States)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Regional decadal predictions of coupled climate-human systems

Science.gov (United States)

Curchitser, E. N.; Lawrence, P.; Felder, F.; Large, W.; Bacmeister, J. T.; Andrews, C.; Kopp, R. E.

2016-12-01

We present results from a project to develop a framework for investigating the interactions between human activity and the climate system using state-of-the-art multi-scale, climate and economic models. The model is applied to the highly industrialized and urbanized coastal region of the northeast US with an emphasis on New Jersey. The framework is developed around the NCAR Community Earth System Model (CESM). The CESM model capabilities are augmented with enhanced resolution of the atmosphere (25 km), land surface (I km) and ocean models (7 km) in our region of interest. To the climate model, we couple human activity models for the utility sector and a 300-equation econometric model with sectorial details of an input-output model for the New Jersey economy. We will present results to date showing the potential impact of climate change on electricity markets on its consequences on economic activity in the region.

The influence of spectral nudging on typhoon formation in regional climate models

Science.gov (United States)

Feser, Frauke; Barcikowska, Monika

2012-03-01

Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden-Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model

The influence of spectral nudging on typhoon formation in regional climate models

International Nuclear Information System (INIS)

Feser, Frauke; Barcikowska, Monika

2012-01-01

Regional climate models can successfully simulate tropical cyclones and typhoons. This has been shown and was evaluated for hindcast studies of the past few decades. But often global and regional weather phenomena are not simulated at the observed location, or occur too often or seldom even though the regional model is driven by global reanalysis data which constitute a near-realistic state of the global atmosphere. Therefore, several techniques have been developed in order to make the regional model follow the global state more closely. One is spectral nudging, which is applied for horizontal wind components with increasing strength for higher model levels in this study. The aim of this study is to show the influence that this method has on the formation of tropical cyclones (TC) in regional climate models. Two ensemble simulations (each with five simulations) were computed for Southeast Asia and the Northwestern Pacific for the typhoon season 2004, one with spectral nudging and one without. First of all, spectral nudging reduced the overall TC number by about a factor of 2. But the number of tracks which are similar to observed best track data (BTD) was greatly increased. Also, spatial track density patterns were found to be more similar when using spectral nudging. The tracks merge after a short time for the spectral nudging simulations and then follow the BTD closely; for the no nudge cases the similarity is greatly reduced. A comparison of seasonal precipitation, geopotential height, and temperature fields at several height levels with observations and reanalysis data showed overall a smaller ensemble spread, higher pattern correlations and reduced root mean square errors and biases for the spectral nudged simulations. Vertical temperature profiles for selected TCs indicate that spectral nudging is not inhibiting TC development at higher levels. Both the Madden–Julian Oscillation and monsoonal precipitation are reproduced realistically by the regional model

Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

Energy Technology Data Exchange (ETDEWEB)

Koca, D.; Smith, B.; Sykes, M.T. [Centre for GeoBiosphere Science, Department of Physical Geography and Ecosystems Analysis, Lund University, Soelvegatan 12, S-223 62 Lund (Sweden)

2006-10-15

This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

International Nuclear Information System (INIS)

Koca, D.; Smith, B.; Sykes, M.T.

2006-01-01

This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO2 change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) - HadAM3H and ECHAM4/OPYC3 - were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st

Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

Science.gov (United States)

Pankatz, Klaus; Kerkweg, Astrid

2015-04-01

The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

Science.gov (United States)

Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

2015-12-01

Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

Science.gov (United States)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2016-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

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

Science.gov (United States)

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 due to greenhouse effects in China as simulated by a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Gao, X.J.; Zhao, Z.C.; Ding, Y.H.; Huang, R.H.; Giorgi, F. [National Climate Centre, Beijing (China)

2001-07-01

Impacts of greenhouse effects (2 x CO{sub 2}) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 x CO{sub 2}) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 x CO{sub 2} showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO{sub 2} doubling.

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

Science.gov (United States)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and

The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability

Energy Technology Data Exchange (ETDEWEB)

Deque, M.; Somot, S. [Meteo-France, Centre National de Recherches Meteorologiques, CNRS/GAME, Toulouse Cedex 01 (France); Sanchez-Gomez, E. [Cerfacs/CNRS, SUC URA1875, Toulouse Cedex 01 (France); Goodess, C.M. [University of East Anglia, Climatic Research Unit, Norwich (United Kingdom); Jacob, D. [Max Planck Institute for Meteorology, Hamburg (Germany); Lenderink, G. [KNMI, Postbus 201, De Bilt (Netherlands); Christensen, O.B. [Danish Meteorological Institute, Copenhagen Oe (Denmark)

2012-03-15

Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021-2050 and the 1961-1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM x GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021-2050 response which shows a similar pattern to the one obtained for 2071-2100 in PRUDENCE. The uncertainty

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

Science.gov (United States)

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

2009-04-01

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

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

Science.gov (United States)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Modelling the regional climate and isotopic composition of Svalbard precipitation using REMOiso

DEFF Research Database (Denmark)

Divine..[], D.V.; Sjolte, Jesper; Isaksson, E.

2011-01-01

Simulations of a regional (approx. 50 km resolution) circulation model REMOiso with embedded stable water isotope module covering the period 1958-2001 are compared with the two instrumental climate and four isotope series (d18O) from western Svalbard. We examine the data from ice cores drilled...... than summer. The simulated and measured Holtedahlfonna d18O series agree reasonably well, whereas no significant correlation has been observed between the modelled and measured Lomonosovfonna ice core isotopic series. It is shown that sporadic nature as well as variability in the amount inherent...... in reproducing the local climate. The model successfully captures the climate variations on the daily to multidecadal times scales although it tends to systematically underestimate the winter SAT. Analysis suggests that REMOiso performs better at simulating isotope compositions of precipitation in the winter...

The regional climate model as a tool for long-term planning of Quebec water resources

International Nuclear Information System (INIS)

Frigon, A.

2008-01-01

'Full text': In recent years, important progress has been made in downscaling GCM (Global Climate Model) projections to a resolution where hydrological studies become feasible. Climate change simulations performed with RCMs (Regional Climate Models) have reached a level of confidence that allows us to take advantage of this information in long-term planning of water resources. The RCMs' main advantage consist in their construction based on balanced land as well as atmosphere water and energy budgets, and on their inclusion of feedbacks between the surface and the atmosphere. Such models therefore generate sequences of weather events, providing long time series of hydro-climatic variables that are internally consistent, allowing the analysis of hydrologic regimes. At OURANOS, special attention is placed on the hydrological cycle, given its key role on socioeconomic activities. The Canadian Regional Climate Model (CRCM) was developed as a potential tool to provide climate projections at the watershed scale. Various analyses performed over small basins in Quebec provide information on the level of confidence we have in the CRCM for use in hydrological studies. Even though this approach is not free of uncertainty, it was found useful by some water resource managers and hence this information should be considered. One of the keys to retain usefulness, despite the associated uncertainties, is to make use of more than a single regional climate projection. This approach will allow for the evaluation of the climate change signal and its associated level of confidence. Such a methodology is already applied by Hydro-Quebec in the long-term planning of its water resources for hydroelectric generation over the Quebec territory. (author)

Representation of aerosol particles and associated transport pathways in regional climate modelling in Africa

CSIR Research Space (South Africa)

Garland, Rebecca M

2016-11-01

Full Text Available Aerosol particles can have large impacts on air quality and on the climate system. Regional climate models for Africa have not been well-tested and validated for their representation and simulation of aerosol particles. This study aimed to validate...

Climate change impact on shallow groundwater conditions in Hungary: Conclusions from a regional modelling study

Science.gov (United States)

Kovács, Attila; Marton, Annamária; Tóth, György; Szöcs, Teodóra

2016-04-01

A quantitative methodology has been developed for the calculation of groundwater table based on measured and simulated climate parameters. The aim of the study was to develop a toolset which can be used for the calculation of shallow groundwater conditions for various climate scenarios. This was done with the goal of facilitating the assessment of climate impact and vulnerability of shallow groundwater resources. The simulated groundwater table distributions are representative of groundwater conditions at the regional scale. The introduced methodology is valid for modelling purposes at various scales and thus represents a versatile tool for the assessment of climate vulnerability of shallow groundwater bodies. The calculation modules include the following: 1. A toolset to calculate climate zonation from climate parameter grids, 2. Delineation of recharge zones (Hydrological Response Units, HRUs) based on geology, landuse and slope conditions, 3. Calculation of percolation (recharge) rates using 1D analytical hydrological models, 4. Simulation of the groundwater table using numerical groundwater flow models. The applied methodology provides a quantitative link between climate conditions and shallow groundwater conditions, and thus can be used for assessing climate impacts. The climate data source applied in our calculation comprised interpolated daily climate data of the Central European CARPATCLIM database. Climate zones were determined making use of the Thorntwaite climate zonation scheme. Recharge zones (HRUs) were determined based on surface geology, landuse and slope conditions. The HELP hydrological model was used for the calculation of 1D water balance for hydrological response units. The MODFLOW numerical groundwater modelling code was used for the calculation of the water table. The developed methodology was demonstrated through the simulation of regional groundwater table using spatially averaged climate data and hydrogeological properties for various time

Capturing flood-to-drought transitions in regional climate model simulations

Science.gov (United States)

Anders, Ivonne; Haslinger, Klaus; Hofstätter, Michael; Salzmann, Manuela; Resch, Gernot

2017-04-01

In previous studies atmospheric cyclones have been investigated in terms of related precipitation extremes in Central Europe. Mediterranean (Vb-like) cyclones are of special relevance as they are frequently related to high atmospheric moisture fluxes leading to floods and landslides in the Alpine region. Another focus in this area is on droughts, affecting soil moisture and surface and sub-surface runoff as well. Such events develop differently depending on available pre-saturation of water in the soil. In a first step we investigated two time periods which encompass a flood event and a subsequent drought on very different time scales, one long lasting transition (2002/2003) and a rather short one between May and August 2013. In a second step we extended the investigation to the long time period 1950-2016. We focused on high spatial and temporal scales and assessed the currently achievable accuracy in the simulation of the Vb-events on one hand and following drought events on the other hand. The state-of-the-art regional climate model CCLM is applied in hindcast-mode simulating the single events described above, but also the time from 1948 to 2016 to evaluate the results from the short runs to be valid for the long time period. Besides the conventional forcing of the regional climate model at its lateral boundaries, a spectral nudging technique is applied. The simulations covering the European domain have been varied systematically different model parameters. The resulting precipitation amounts have been compared to E-OBS gridded European precipitation data set and a recent high spatially resolved precipitation data set for Austria (GPARD-6). For the drought events the Standardized Precipitation Evapotranspiration Index (SPEI), soil moisture and runoff has been investigated. Varying the spectral nudging setup helps us to understand the 3D-processes during these events, but also to identify model deficiencies. To improve the simulation of such events in the past

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

Science.gov (United States)

This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Pro...

Projecting regional climate and cropland changes using a linked biogeophysical-socioeconomic modeling framework: 1. Model description and an equilibrium application over West Africa

Science.gov (United States)

Wang, Guiling; Ahmed, Kazi Farzan; You, Liangzhi; Yu, Miao; Pal, Jeremy; Ji, Zhenming

2017-03-01

Agricultural land use alters regional climate through modifying the surface mass, energy, and momentum fluxes; climate influences agricultural land use through their impact on crop yields. These interactions are not well understood and have not been adequately considered in climate projections. This study tackles the critical linkages within the coupled natural-human system of West Africa in a changing climate based on an equilibrium application of a modeling framework that asynchronously couples models of regional climate, crop yield, multimarket agricultural economics, and cropland expansion. Using this regional modeling framework driven with two global climate models, we assess the contributions of land use change (LUC) and greenhouse gas (GHGs) concentration changes to regional climate changes and assess the contribution of climate change and socioeconomic factors to agricultural land use changes. For future cropland expansion in West Africa, our results suggest that socioeconomic development would be the dominant driver in the east (where current cropland coverage is already high) and climate changes would be the primary driver in the west (where future yield drop is severe). For future climate, it is found that agricultural expansion would cause a dry signal in the west and a wet signal in the east downwind, with an east-west contrast similar to the GHG-induced changes. Over a substantial portion of West Africa, the strength of the LUC-induced climate signals is comparable to the GHG-induced changes. Uncertainties originating from the driving global models are small; human decision making related to land use and international trade is a major source of uncertainty.

Tropospheric aerosols radiation feedback on the climate of Pearl River Delta Region using an air quality model

Science.gov (United States)

Nduka, I. C.

2016-12-01

The Pearl River Delta (PRD) region, one of the most vibrant economic regions in China has been witnessing rapid population, economic and structural growth and development. It is also one of the regions mostly polluted with trace gases and particulates. Recent reviews show large uncertainties in climate modification studies, indicating the need for further investigations, such as the role of tropospheric aerosols on direct and indirect climate modification. The aim of this research is to appraise the impacts of tropospheric aerosols on the climate of PRD region. An integrated air quality downscale meteorology and air quality from regional scale (27km) to local scale (3km). The model will be evaluated for both meteorology and air quality by comparing model results with measurements. The radiative forcing of tropospheric aerosols will also be determined so as to estimate the feedbacks and impacts on the climate. This research, when completed, is expected to improve our understanding of tropospheric aerosol-cloud thermodynamic interactions at regional and local scales, thus enhancing our knowledge of the regional and local climate system, which is anticipated to provide critical references for formulating sustainable environment and air quality policies.

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

Science.gov (United States)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were

Future Changes in Surface Runoff over Korea Projected by a Regional Climate Model under A1B Scenario

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Ji-Woo Lee

2014-01-01

Full Text Available This study assesses future change of surface runoff due to climate change over Korea using a regional climate model (RCM, namely, the Global/Regional Integrated Model System (GRIMs, Regional Model Program (RMP. The RMP is forced by future climate scenario, namely, A1B of Intergovernmental Panel on Climate Change (IPCC Fourth Assessment Report (AR4. The RMP satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation. The distribution of monsoonal precipitation-related runoff is adequately captured by the RMP. In the future (2040–2070 simulation, it is shown that the increasing trend of temperature has significant impacts on the intra-annual runoff variation. The variability of runoff is increased in summer; moreover, the strengthened possibility of extreme occurrence is detected in the future climate. This study indicates that future climate projection, including surface runoff and its variability over Korea, can be adequately addressed on the RMP testbed. Furthermore, this study reflects that global warming affects local hydrological cycle by changing major water budget components. This study adduces that the importance of runoff should not be overlooked in regional climate studies, and more elaborate presentation of fresh-water cycle is needed to close hydrological circulation in RCMs.

Comparing regional precipitation and temperature extremes in climate model and reanalysis products

Directory of Open Access Journals (Sweden)

Oliver Angélil

2016-09-01

Full Text Available A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.

Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

Science.gov (United States)

Lyra, Andre; Tavares, Priscila; Chou, Sin Chan; Sueiro, Gustavo; Dereczynski, Claudine; Sondermann, Marcely; Silva, Adan; Marengo, José; Giarolla, Angélica

2018-04-01

The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961-1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

Science.gov (United States)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for

Inflated Uncertainty in Multimodel-Based Regional Climate Projections

Science.gov (United States)

Madsen, Marianne Sloth; Langen, Peter L.; Boberg, Fredrik; Christensen, Jens Hesselbjerg

2017-11-01

Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

Does Dynamical Downscaling Introduce Novel Information in Climate Model Simulations of Recipitation Change over a Complex Topography Region?

Science.gov (United States)

Tselioudis, George; Douvis, Costas; Zerefos, Christos

2012-01-01

Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

Energy Technology Data Exchange (ETDEWEB)

Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

2012-07-15

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

Extreme temperature events on Greenland in observations and the MAR regional climate model

Science.gov (United States)

Leeson, Amber A.; Eastoe, Emma; Fettweis, Xavier

2018-03-01

Meltwater from the Greenland Ice Sheet contributed 1.7-6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20-110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.

Regional Climate Models as a Tool for Assessing Changes in the Laurentian Great Lakes Net Basin Supply

Science.gov (United States)

Music, B.; Mailhot, E.; Nadeau, D.; Irambona, C.; Frigon, A.

2017-12-01

Over the last decades, there has been growing concern about the effects of climate change on the Great Lakes water supply. Most of the modelling studies focusing on the Laurentian Great Lakes do not allow two-way exchanges of water and energy between the atmosphere and the underlying surface, and therefore do not account for important feedback mechanisms. Moreover, energy budget constraint at the land surface is not usually taken into account. To address this issue, several recent climate change studies used high resolution Regional Climate Models (RCMs) for evaluating changes in the hydrological regime of the Great Lakes. As RCMs operate on the concept of water and energy conservation, an internal consistency of the simulated energy and water budget components is assured. In this study we explore several recently generated Regional Climate Model (RCM) simulations to investigate the Great Lakes' Net Basin Supply (NBS) in a changing climate. These include simulations of the Canadian Regional Climate Model (CRCM5) supplemented by simulations from several others RCMs participating to the North American CORDEX project (CORDEX-NA). The analysis focuses on the NBS extreme values under nonstationary conditions. The results are expected to provide useful information to the industries in the Great Lakes that all need to include accurate climate change information in their long-term strategy plans to better anticipate impacts of low and/or high water levels.

California Wintertime Precipitation in Regional and Global Climate Models

Energy Technology Data Exchange (ETDEWEB)

Caldwell, P M

2009-04-27

In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins.

Science.gov (United States)

Gampe, David; Nikulin, Grigory; Ludwig, Ralf

2016-12-15

Climate change will likely increase pressure on the water balances of Mediterranean basins due to decreasing precipitation and rising temperatures. To overcome the issue of data scarcity the hydrological relevant variables total runoff, surface evaporation, precipitation and air temperature are taken from climate model simulations. The ensemble applied in this study consists of 22 simulations, derived from different combinations of four General Circulation Models (GCMs) forcing different Regional Climate Models (RCMs) and two Representative Concentration Pathways (RCPs) at ~12km horizontal resolution provided through the EURO-CORDEX initiative. Four river basins (Adige, Ebro, Evrotas and Sava) are selected and climate change signals for the future period 2035-2065 as compared to the reference period 1981-2010 are investigated. Decreased runoff and evaporation indicate increased water scarcity over the Ebro and the Evrotas, as well as the southern parts of the Adige and the Sava, resulting from a temperature increase of 1-3° and precipitation decrease of up to 30%. Most severe changes are projected for the summer months indicating further pressure on the river basins already at least partly characterized by flow intermittency. The widely used Falkenmark indicator is presented and confirms this tendency and shows the necessity for spatially distributed analysis and high resolution projections. Related uncertainties are addressed by the means of a variance decomposition and model agreement to determine the robustness of the projections. The study highlights the importance of high resolution climate projections and represents a feasible approach to assess climate impacts on water scarcity also in regions that suffer from data scarcity. Copyright © 2016. Published by Elsevier B.V.

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

Science.gov (United States)

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

2010-12-01

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

Evaluation of an ensemble of Arctic regional climate models

DEFF Research Database (Denmark)

Rinke, A.; Dethloff, K.; Cassano, J. J.

2006-01-01

Simulations of eight different regional climate models (RCMs) have been performed for the period September 1997-September 1998, which coincides with the Surface Heat Budget of the Arctic Ocean (SHEBA) project period. Each of the models employed approximately the same domain covering the western......, temperature, cloud cover, and long-/shortwave downward radiation between the individual model simulations are investigated. With this work, we quantify the scatter among the models and therefore the magnitude of disagreement and unreliability of current Arctic RCM simulations. Even with the relatively...... constrained experimental design we notice a considerable scatter among the different RCMs. We found the largest across-model scatter in the 2 m temperature over land, in the surface radiation fluxes, and in the cloud cover which implies a reduced confidence level for these variables....

Extreme winds over Europe in the ENSEMBLES regional climate models

Directory of Open Access Journals (Sweden)

S. D. Outten

2013-05-01

Full Text Available Extreme winds cause vast amounts of damage every year and represent a major concern for numerous industries including construction, afforestation, wind energy and many others. Under a changing climate, the intensity and frequency of extreme events are expected to change, and accurate projections of these changes will be invaluable to decision makers and society as a whole. This work examines four regional climate model downscalings over Europe following the SRES A1B scenario from the "ENSEMBLE-based Predictions of Climate Changes and their Impacts" project (ENSEMBLES. It investigates the projected changes in the 50 yr return wind speeds and the associated uncertainties. This is accomplished by employing the peaks-over-threshold method with the use of the generalised Pareto distribution. The models show that, for much of Europe, the 50 yr return wind is projected to change by less than 2 m s−1, while the uncertainties associated with the statistical estimates are larger than this. In keeping with previous works in this field, the largest source of uncertainty is found to be the inter-model spread, with some locations showing differences in the 50 yr return wind of over 20 m s−1 between two different downscalings.

Evaluation of uncertainties in regional climate change simulations

DEFF Research Database (Denmark)

Pan, Z.; Christensen, J. H.; Arritt, R. W.

2001-01-01

, an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over...... to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all...... regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2x3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial...

Multi-model Ensemble Regional Climate Projection of the Maritime Continent using the MIT Regional Climate Model

Science.gov (United States)

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

2016-12-01

In this study, the future change in precipitation due to global warming is investigated over the Maritime Continent using the MIT Regional Climate Model (MRCM). A total of nine 30-year projections under multi-GCMs (CCSM, MPI, ACCESS) and multi-scenarios of emissions (Control, RCP4.5, RCP8.5) are dynamically downscaled using the MRCM with 12km horizontal resolution. Since downscaled results tend to systematically overestimate the precipitation regardless of GCM used as lateral boundary conditions, the Parametric Quantile Mapping (PQM) is applied to reduce this wet bias. The cross validation for the control simulation shows that the PQM method seems to retain the spatial pattern and temporal variability of raw simulation, however it effectively reduce the wet bias. Based on ensemble projections produced by dynamical downscaling and statistical bias correction, a reduction of future precipitation is discernible, in particular during dry season (June-July-August). For example, intense precipitation in Singapore is expected to be reduced in RCP8.5 projection compared to control simulation. However, the geographical patterns and magnitude of changes still remain uncertain, suffering from statistical insignificance and a lack of model agreement. Acknowledgements This research is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology

Detection and Attribution of Regional Climate Change

Energy Technology Data Exchange (ETDEWEB)

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and ocean circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.

Consistency of climate change projections from multiple global and regional model intercomparison projects

Science.gov (United States)

Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

2018-03-01

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

Modeling climate change impacts on overwintering of Spodoptera exigua Hübner in regions of China

Directory of Open Access Journals (Sweden)

Xia-Lin Zheng

2015-09-01

Full Text Available Inferential models are usually used to evaluate the effect of winter warming on range expansion of insects. Generally, correlative approaches used to predict changes in the distributions of organisms are based on the assumption that climatic boundaries are fixed. Spodoptera exigua Htibner (Lepidoptera: Noctuidae overwinters as larvae or pupae in China regions. To understand the climate change impacts on overwintering of this species in regions of China, CLIMEX and Arc-GIS models were used to predict possible changes of distribution based on temperature. The climate change projection clearly indicated that the northern boundary of overwintering for S. exigua will shift northward from current distribution. Thus, the ongoing winter warming is likely to increase the frequency of S. exigua outbreaks.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States)

2016-10-17

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

Adapting crop rotations to climate change in regional impact modelling assessments.

Science.gov (United States)

Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

2018-03-01

The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Science.gov (United States)

Marengo, Jose A.; Ambrizzi, Tercio; Da Rocha, Rosmeri P.; Alves, Lincoln M.; Cuadra, Santiago V.; Valverde, Maria C.; Torres, Roger R.; Santos, Daniel C.; Ferraz, Simone E. T.

2010-11-01

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N-15°S band, both in summer and especially in winter, reaching up to 6-8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of

Regional emission metrics for short-lived climate forcers from multiple models

Directory of Open Access Journals (Sweden)

B. Aamaas

2016-06-01

Full Text Available For short-lived climate forcers (SLCFs, the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF values calculated in four different (chemical-transport or coupled chemistry–climate models. We distinguish between emissions during summer (May–October and winter (November–April for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3, as well as ozone precursors (NOx, CO, VOCs, which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP and global temperature change potential (GTP, based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation

Spectral nudging in regional climate modelling: How strongly should we nudge?

OpenAIRE

Omrani , Hiba; Drobinski , Philippe; Dubos , Thomas

2012-01-01

International audience; Spectral nudging is a technique consisting in driving regional climate models (RCMs) on selected spatial scales corresponding to those produced by the driving global circulation model (GCM). This technique prevents large and unrealistic departures between the GCM driving fields and the RCM fields at the GCM spatial scales. Theoretically, the relaxation of the RCM towards the GCM should be infinitely strong provided thre are perfect large-scale fields. In practice, the ...

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Energy Technology Data Exchange (ETDEWEB)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

2017-01-04

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

Determination of clouds in MSG data for the validation of clouds in a regional climate model

OpenAIRE

Huckle, Roger

2009-01-01

Regional climate models (e.g. CLM) can help to asses the influence of the antropogenic climate change on the different regions of the earth. Validation of these models is very important. Satellite data are of great benefit, as data on a global scale and high temporal resolution is available. In this thesis a cloud detection and object based cloud classification for Meteosat Second Generation (MSG) was developed and used to validate CLM clouds. Results show sometimes too many clouds in the CLM.

Investigating added value of regional climate modeling in North American winter storm track simulations

Science.gov (United States)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given

An evaluation of temperature and precipitation from global and regional climate models over Scandinavia

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

Precipitation and temperature from global (GCMs) and regional (RCMs) climate models are compared with reanalysis and observations over Scandinavia. Also projections for the next 50-100 years are considered. The climate development is visualised as moving averages (1920-2100). Box plots are used to illuminate how well GCM runs capture the observed seasonal cycle. Maps show the seasonal difference between results from control runs (RCM) and observations (E-OBS dataset) for the reference period 1981-2000. Plots illustrate the RCM-representation of seasonal temperature and precipitations cycle for five locations in Norway and Sweden: Oslo, Bergen, Trondheim, Tromsoe and Oestersund. The results show rather large differences between control runs and observations, demonstrating the need for bias correction of results from climate models. To get an indicator of which GC M-RCM-combination give the best representation of present climate over Scandinavia, a model ranking is provided. The performance measure used is the root-mean-square deviation of mean monthly and seasonal values. The data is compared both in an area-weighted spatial average of the whole domain as well as for the selected locations. The results indicate that the regional models RACMO2 and RCA show the smallest deviations from observed climate. Among the top ranking GCM-RCM combinations, most were driven by the global model ECHAM5 and some by a version of HadCM3. These two GCMs are also present among the worst performing GCM-RCM combinations indicating that selection of RCMs is crucial. (Author)

Regional climate model downscaling may improve the prediction of alien plant species distributions

Science.gov (United States)

Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

2014-12-01

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

Energy Technology Data Exchange (ETDEWEB)

Gutowski, William J.

2013-02-07

The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

Energy Technology Data Exchange (ETDEWEB)

Di Luca, Alejandro; Laprise, Rene [Universite du Quebec a Montreal (UQAM), Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Departement des Sciences de la Terre et de l' Atmosphere, PK-6530, Succ. Centre-ville, B.P. 8888, Montreal, QC (Canada); De Elia, Ramon [Universite du Quebec a Montreal, Ouranos Consortium, Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal (Canada)

2012-03-15

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions. (orig.)

Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

Science.gov (United States)

Wanders, N.; Van Lanen, H. A. J.

2015-03-01

Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model

Energy Technology Data Exchange (ETDEWEB)

Heikkilae, U. [Bjerknes Centre for Climate Research, Uni Bjerknes Centre, Bergen (Norway); Sandvik, A. [Bjerknes Centre for Climate Research, Institute for Marine Research (IMR), Bergen (Norway); Sorteberg, A. [University of Bergen, Geophysical Institute, Bergen (Norway)

2011-10-15

Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1 ) has been downscaled to a horizontal resolution of 30 and 10 km for the period of 1961-1990. This model setup includes the whole North Atlantic in the 30 km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10 km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies. (orig.)

A Regional Climate Model Evaluation System

Data.gov (United States)

National Aeronautics and Space Administration — Develop a packaged data management infrastructure for the comparison of generated climate model output to existing observational datasets that includes capabilities...

Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

NARCIS (Netherlands)

Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

2012-01-01

Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

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

Science.gov (United States)

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

Regional climate change for the Pacific Northwest

International Nuclear Information System (INIS)

McBean, G.A.; Thomas, G.

1991-01-01

The Pacific Northwest climate is dominated by topography and the Pacific Ocean; the forests have become adapted to the present climate. Within short distances there are large changes in precipitation and temperature, with resultant changes in ecosystems. As the atmospheric concentrations of greenhouse gases increase, global climate is expected to warm and precipitation to increase. Global climate model simulations show enhanced warming at high northern latitudes. For the Pacific Northwest, models show 2-6 degree C warming and increased precipitation in the winter for doubled atmospheric CO 2 concentration. However, the regional details of these models are presently not very reliable. The results and limitations of present global climate models are reviewed. The roles of the oceans, clouds, and other feedback mechanisms are described along with some of the possible impacts of climate change on forest resources. 24 refs., 2 figs., 1 tab

Integrated climate and hydrology modelling - Coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model

Energy Technology Data Exchange (ETDEWEB)

Dahl Larsen, M.A. [Technical Univ. of Denmark. DTU Management Engineering, DTU Risoe Campus, Roskilde (Denmark)

2013-10-15

To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface. The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model (LSM), which is superior to the LSM in HIRHAM. A wider range of processes are included at the land surface, subsurface flow is distributed in three dimensions and the temporal and spatial resolution is higher. Secondly, the feedback mechanisms of e.g. soil moisture and precipitation between the two models are included. The preparation of the HIRHAM and MIKE SHE models for the coupled study revealed several findings. The performance of HIRHAM was highly affected by the domain size, domain

The increased atmospheric greenhouse effect and regional climate change

Energy Technology Data Exchange (ETDEWEB)

Groenaas, S. [Bergen Univ. (Norway)

1996-03-01

This paper was read at the workshop ``The Norwegian Climate and Ozone Research Programme`` held on 11-12 March 1996. The main information for predicting future climate changes comes from integrating coupled climate models of the atmosphere, ocean and cryosphere. Regional climate change may be studied from the global integrations, however, resolution is coarse because of insufficient computer power. Attempts are being made to get more regional details out of the global integrations by ``downscaling`` the latter. This can be done in two ways. Firstly, limited area models with high resolution are applied, driven by the global results as boundary values. Secondly, statistical relationships have been found between observed meteorological parameters, like temperature and precipitation, and analyzed large scale gridded fields. The derived relations are then used on similar data from climate runs to give local interpretations. A review is given of literature on recent observations of climate variations and on predicted regional climate change. 18 refs., 4 figs.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Science.gov (United States)

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

An integrated framework to address climate change (ESCAPE) and further developments of the global and regional climate modules (MAGICC)

International Nuclear Information System (INIS)

Hulme, M.; Raper, S.C.B.

1995-01-01

ESCAPE (the Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions) is an integrated climate change assessment model constructed between 1990 and 1992 for DG XI of the Commission of the European Community by a consortium of research institutes headed by the Climatic Research Unit (CRU). It has been designed to enable the user to generate future scenarios of greenhouse gas emissions (through an energy-economic model), examine their impact on global climate and sea level (through two independent global climate models), and illustrate some of the consequences of this global climate change at a regional scale for the European Community (through a regional climate scenario generator and impact models). We provide a very brief overview of the ESCAPE model which, although innovative, suffers from a number of major limitations. Subsequent work in the CRU has concentrated on improvements to the global climate module and work has also commenced on an improved regional climate scenario generating module. These improvements will lead to a new integrated climate change assessment model, MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) which can easily be incorporated into new larger integrated frameworks developed by other institutes. (Author)

The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

Energy Technology Data Exchange (ETDEWEB)

Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

2000-06-01

A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

Producing an integrated climate-land-energy-water (CLEW) model for glaciated regions in the developing world

Science.gov (United States)

Delman, E. M.; Thomas, B. F.; Famiglietti, J. S.

2013-12-01

Growing concern over the impact of climate change on global freshwater resources has spurred a demand for practical, basin-specific adaptation tools. The potential for water stress is particularly inflated in the glaciated watersheds of the developing world; widespread and rapid glacial retreat has forced regional resource managers to reconcile the reality of a diminishing supply with an overall increase in demand, while accounting for the underlying geopolitical and cultural context. An integrated approach, such as the development of a Climate-Land-Energy-Water (CLEW) model that examines relationships among climate, land-use, and the energy and water sectors, can be used to assess the impact of different climate change scenarios on basin sustainability and vulnerability. This study will first constrain the hydrologic budget in the Río Santa Watershed of Peru using satellite imagery, historical and contemporary stream discharge data, hydrologic modeling, climatic data analysis, and isotopic and chemical tracers. Ultimately, glacier retreat will be examined at the watershed scale and be used as an input in the CLEW model framework to assess hydrologic budget scenarios and the subsequent impact on regional economic and environmental sustainability.

Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

NARCIS (Netherlands)

Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.

2015-01-01

Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield

Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

Energy Technology Data Exchange (ETDEWEB)

Cassano, John [Principal Investigator

2013-06-30

The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

The application of a dynamic OpenMI coupling between a regional climate model and a distributed surface water-groundwater model

DEFF Research Database (Denmark)

Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

2014-01-01

To support climate adaptation measures for water resources, we have developed and evaluated a dynamic coupling between a comprehensive distributed hydrological modelling system, MIKE SHE, and a regional climate modelling system, HIRHAM. The coupled model enables two-way interaction between the at......, including local measurements of energy fluxes. The results presented here suggest that there may be important differences in the simulated water balances for this catchment created by introducing an alternative hydrological model into the RCM....

ARCAS (ACACIA Regional Climate-data Access System) -- a Web Access System for Climate Model Data Access, Visualization and Comparison

Science.gov (United States)

Hakkarinen, C.; Brown, D.; Callahan, J.; hankin, S.; de Koningh, M.; Middleton-Link, D.; Wigley, T.

2001-05-01

A Web-based access system to climate model output data sets for intercomparison and analysis has been produced, using the NOAA-PMEL developed Live Access Server software as host server and Ferret as the data serving and visualization engine. Called ARCAS ("ACACIA Regional Climate-data Access System"), and publicly accessible at http://dataserver.ucar.edu/arcas, the site currently serves climate model outputs from runs of the NCAR Climate System Model for the 21st century, for Business as Usual and Stabilization of Greenhouse Gas Emission scenarios. Users can select, download, and graphically display single variables or comparisons of two variables from either or both of the CSM model runs, averaged for monthly, seasonal, or annual time resolutions. The time length of the averaging period, and the geographical domain for download and display, are fully selectable by the user. A variety of arithmetic operations on the data variables can be computed "on-the-fly", as defined by the user. Expansions of the user-selectable options for defining analysis options, and for accessing other DOD-compatible ("Distributed Ocean Data System-compatible") data sets, residing at locations other than the NCAR hardware server on which ARCAS operates, are planned for this year. These expansions are designed to allow users quick and easy-to-operate web-based access to the largest possible selection of climate model output data sets available throughout the world.

Wildfire potential evaluation during a drought event with a regional climate model and NDVI

Science.gov (United States)

Y. Liu; J. Stanturf; S. Goodrick

2010-01-01

Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional...

Modelling regional cropping patterns under scenarios of climate and socio-economic change in Hungary.

Science.gov (United States)

Li, Sen; Juhász-Horváth, Linda; Pintér, László; Rounsevell, Mark D A; Harrison, Paula A

2018-05-01

Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local-level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural

Regionalization of climate model results for the North Sea

Energy Technology Data Exchange (ETDEWEB)

Kauker, F.

1999-07-01

A dynamical downscaling is presented that allows an estimation of potential effects of climate change on the North Sea. Therefore, the ocean general circulation model OPYC is adapted for application on a shelf by adding a lateral boundary formulation and a tide model. In this set-up the model is forced, first, with data from the ECMWF reanalysis for model validation and the study of the natural variability, and, second, with data from climate change experiments to estimate the effects of climate change on the North Sea. (orig.)

Regional climate service in Southern Germany

Science.gov (United States)

Schipper, Janus; Hackenbruch, Julia

2013-04-01

Climate change challenges science, politics, business and society at the international, national and regional level. The South German Climate Office at the Karlsruhe Institute of Technology (KIT) is a contact for the structuring and dissemination of information on climate and climate change in the South German region. It provides scientifically based and user-oriented climate information. Thereby it builds a bridge between the climate sciences and society and provides scientific information on climate change in an understandable way. The expertise of KIT, in which several institutions operate on fundamental and applied climate research, and of partner institutions is the basis for the work in the climate office. The regional focus is on the south of Germany. Thematic focuses are e.g. regional climate modeling, trends in extreme weather events such as heavy rain and hail event, and issues for energy and water management. The South German Climate Office is one of four Regional Helmholtz Climate Offices, of which each has a regional and thematic focus. The users of the Climate Office can be summarized into three categories. First, there is the general public. This category consists mainly of non-professionals. Here, special attention is on an understandable translation of climate information. Attention is paid to application-related aspects, because each individual is affected in a different way by climate change. Typical examples of this category are school groups, citizens and the media. The second category consists of experts of other disciplines. Unlike the first category they are mainly interested in the exchange of results and data. It is important to the climate office to provide support for the use of climatological results. Typical representatives of this category are ministries, state offices, and companies. In the third and final category are scientists. In addition to the climatologists, this category also holds representatives from other scientific

Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

Science.gov (United States)

Leckebusch, G. C.; Ulbrich, U.

2003-04-01

More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

Evaluation of skill at simulating heatwave and heat-humidity indices in Global and Regional Climate Models

Science.gov (United States)

Goldie, J. K.; Alexander, L. V.; Lewis, S. C.; Sherwood, S. C.

2017-12-01

A wide body of literature now establishes the harm of extreme heat on human health, and work is now emerging on the projection of future health impacts. However, heat-health relationships vary across different populations (Gasparrini et al. 2015), so accurate simulation of regional climate is an important component of joint health impact projection. Here, we evaluate the ability of nine Global Climate Models (GCMs) from CMIP5 and the NARCliM Regional Climate Model to reproduce a selection of 15 health-relevant heatwave and heat-humidity indices over the historical period (1990-2005) using the Perkins skill score (Perkins et al. 2007) in five Australian cities. We explore the reasons for poor model skill, comparing these modelled distributions to both weather station observations and gridded reanalysis data. Finally, we show changes in the modelled distributions from the highest-performing models under RCP4.5 and RCP8.5 greenhouse gas scenarios and discuss the implications of simulated heat stress for future climate change adaptation. ReferencesGasparrini, Antonio, Yuming Guo, Masahiro Hashizume, Eric Lavigne, Antonella Zanobetti, Joel Schwartz, Aurelio Tobias, et al. "Mortality Risk Attributable to High and Low Ambient Temperature: A Multicountry Observational Study." The Lancet 386, no. 9991 (July 31, 2015): 369-75. doi:10.1016/S0140-6736(14)62114-0. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney. "Evaluation of the AR4 Climate Models' Simulated Daily Maximum Temperature, Minimum Temperature, and Precipitation over Australia Using Probability Density Functions." Journal of Climate 20, no. 17 (September 1, 2007): 4356-76. doi:10.1175/JCLI4253.1.

A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

Science.gov (United States)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

Simulation of Lake Surface Heat Fluxes by the Canadian Small Lake Model: Offline Performance Assessment for Future Coupling with a Regional Climate Model

Science.gov (United States)

Pernica, P.; Guerrero, J. L.; MacKay, M.; Wheater, H. S.

2014-12-01

Lakes strongly influence local and regional climate especially in regions where they are abundant. Development of a lake model for the purpose of integration within a regional climate model is therefore a subject of scientific interest. Of particular importance are the heat flux predictions provided by the lake model since they function as key forcings in a fully coupled atmosphere-land-lake system. The first step towards a coupled model is to validate and characterize the accuracy of the lake model over a range of conditions and to identify limitations. In this work, validation results from offline tests of the Canadian Small Lake Model; a deterministic, computationally efficient, 1D integral model, are presented. Heat fluxes (sensible and latent) and surface water temperatures simulated by the model are compared with in situ observations from two lakes; Landing Lake (NWT, Canada) and L239 (ELA, Canada) for the 2007-2009 period. Sensitivity analysis is performed to identify key parameters important for heat flux predictions. The results demonstrate the ability of the 1-D lake model to reproduce both diurnal and seasonal variations in heat fluxes and surface temperatures for the open water period. These results, in context of regional climate modelling are also discussed.

Regional climate assessment of precipitation and temperature in Southern Punjab (Pakistan) using SimCLIM climate model for different temporal scales

Science.gov (United States)

Amin, Asad; Nasim, Wajid; Mubeen, Muhammad; Sarwar, Saleem; Urich, Peter; Ahmad, Ashfaq; Wajid, Aftab; Khaliq, Tasneem; Rasul, Fahd; Hammad, Hafiz Mohkum; Rehmani, Muhammad Ishaq Asif; Mubarak, Hussani; Mirza, Nosheen; Wahid, Abdul; Ahamd, Shakeel; Fahad, Shah; Ullah, Abid; Khan, Mohammad Nauman; Ameen, Asif; Amanullah; Shahzad, Babar; Saud, Shah; Alharby, Hesham; Ata-Ul-Karim, Syed Tahir; Adnan, Muhammad; Islam, Faisal; Ali, Qazi Shoaib

2018-01-01

Unbalanced climate during the last decades has created spatially alarming and destructive situations in the world. Anomalies in temperature and precipitation enhance the risks for crop production in large agricultural region (especially the Southern Punjab) of Pakistan. Detailed analysis of historic weather data (1980-2011) record helped in creating baseline data to compare with model projection (SimCLIM) for regional level. Ensemble of 40 GCMs used for climatic projections with greenhouse gas (GHG) representative concentration pathways (RCP-4.5, 6.0, 8.5) was selected on the baseline comparison and used for 2025 and 2050 climate projection. Precipitation projected by ensemble and regional weather observatory at baseline showed highly unpredictable nature while both temperature extremes showed 95 % confidence level on a monthly projection. Percentage change in precipitation projected by model with RCP-4.5, RCP-6.0, and RCP-8.5 showed uncertainty 3.3 to 5.6 %, 2.9 to 5.2 %, and 3.6 to 7.9 % for 2025 and 2050, respectively. Percentage change of minimum temperature from base temperature showed that 5.1, 4.7, and 5.8 % for 2025 and 9.0, 8.1, and 12.0 % increase for projection year 2050 with RCP-4.5, 6.0, and 8.5 and maximum temperature 2.7, 2.5, and 3.0 % for 2025 and 4.7, 4.4, and 6.4 % for 2050 will be increased with RCP-4.5, 6.0, and 8.5, respectively. Uneven increase in precipitation and asymmetric increase in temperature extremes in future would also increase the risk associated with management of climatic uncertainties. Future climate projection will enable us for better risk management decisions.

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

NARCIS (Netherlands)

Giesen, R.H.|info:eu-repo/dai/nl/304831603; Oerlemans, J.|info:eu-repo/dai/nl/06833656X

2013-01-01

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century

Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology - a comparison between two regional climate models (REMO and CLM)

Science.gov (United States)

Endler, Christina; Matzarakis, Andreas

2011-03-01

An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971-2000 that represents the twentieth century climate and 2021-2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes - that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere-ocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists' demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

DEFF Research Database (Denmark)

Xia, Jianyang; McGuire, A. David; Lawrence, David

2017-01-01

productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m−2 yr−1), most models produced higher NPP (309 ± 12 g C m−2 yr−1) over...... and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost...... regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change....

Zooming in on cirrus with the Canadian Regional Climate Model

Science.gov (United States)

Stefanof, C.; Stefanof, A.; Beaulne, A.; Munoz Alpizar, R.; Szyrmer, W.; Blanchet, J.

2004-05-01

The Canadian Regional Climate Model plus a microphysical scheme: two-moments microphysics with three hydrometeor categories (cloud liquid water, pristine ice crystals and larger precipitation crystals) is used to test the simulation in forecast mode using ECMWF data at 0.4 X 0.4 degree. We are zooming in on cirrus at higher resolutions (9, 1.8, 0.36 km). We are currently using the data set measured in APEX-E3, measurements of radar, lidar, passive instruments and interpreted microphysics for some flights (G-II, C404, B200). The radar and lidar data are available for high level cirrus. The south west of Japon is the flight region. The dates are March 20, March 27 and April 2, 2003. We first focus on the March 27 frontal system. We did a rigorous synoptical analysis for the cases. The cirrus at 360 m resolution are simulated. The cloud structure and some similarities between model simulation and observations will be presented.

Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

Science.gov (United States)

Kara, Fatih; Yucel, Ismail

2015-09-01

This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.

Paleoclimate validation of a numerical climate model

International Nuclear Information System (INIS)

Schelling, F.J.; Church, H.W.; Zak, B.D.; Thompson, S.L.

1994-01-01

An analysis planned to validate regional climate model results for a past climate state at Yucca Mountain, Nevada, against paleoclimate evidence for the period is described. This analysis, which will use the GENESIS model of global climate nested with the RegCM2 regional climate model, is part of a larger study for DOE's Yucca Mountain Site Characterization Project that is evaluating the impacts of long term future climate change on performance of the potential high level nuclear waste repository at Yucca Mountain. The planned analysis and anticipated results are presented

The Alpine snow-albedo feedback in regional climate models

Science.gov (United States)

Winter, Kevin J.-P. M.; Kotlarski, Sven; Scherrer, Simon C.; Schär, Christoph

2017-02-01

The effect of the snow-albedo feedback (SAF) on 2m temperatures and their future changes in the European Alps is investigated in the ENSEMBLES regional climate models (RCMs) with a focus on the spring season. A total of 14 re-analysis-driven RCM experiments covering the period 1961-2000 and 10 GCM-driven transient climate change projections for 1950-2099 are analysed. A positive springtime SAF is found in all RCMs, but the range of the diagnosed SAF is large. Results are compared against an observation-based SAF estimate. For some RCMs, values very close to this estimate are found; other models show a considerable overestimation of the SAF. Net shortwave radiation has the largest influence of all components of the energy balance on the diagnosed SAF and can partly explain its spatial variability. Model deficiencies in reproducing 2m temperatures above snow and ice and associated cold temperature biases at high elevations seem to contribute to a SAF overestimation in several RCMs. The diagnosed SAF in the observational period strongly influences the estimated SAF contribution to twenty first century temperature changes in the European Alps. This contribution is subject to a clear elevation dependency that is governed by the elevation-dependent change in the number of snow days. Elevations of maximum SAF contribution range from 1500 to 2000 m in spring and are found above 2000 m in summer. Here, a SAF contribution to the total simulated temperature change between 0 and 0.5 °C until 2099 (multi-model mean in spring: 0.26 °C) or 0 and 14 % (multi-model mean in spring: 8 %) is obtained for models showing a realistic SAF. These numbers represent a well-funded but only approximate estimate of the SAF contribution to future warming, and a remaining contribution of model-specific SAF misrepresentations cannot be ruled out.

Analysis of regional climate strategies in the Barents region

Energy Technology Data Exchange (ETDEWEB)

Himanen, S.; Inkeroeinen, J.; Latola, K.; Vaisanen, T.; Alasaarela, E.

2012-11-15

Climate change is a global phenomenon with especially harsh effects on the Arctic and northern regions. The Arctic's average temperature has risen at almost twice the rate as elsewhere in the past few decades. Since 1966, the Arctic land area covered by snow in early summer has shrunk by almost a fifth. The Barents Region consists of the northern parts of Norway, Sweden, Finland and Russia (i.e. the European part of Russia). Climate change will cause serious impacts in the Barents Region because of its higher density of population living under harsh climatic conditions, thus setting it apart from other Arctic areas. In many cases, economic activities, like tourism, rely on certain weather conditions. For this reason, climate change and adaptation to it is of special urgency for the region. Regional climate change strategies are important tools for addressing mitigation and adaptation to climate change as they can be used to consolidate the efforts of different stakeholders of the public and private sectors. Regional strategies can be important factors in achieving the national and international goals. The study evaluated how the national climate change goals were implemented in the regional and local strategies and programmes in northern Finland. The specific goal was to describe the processes by which the regional strategies were prepared and implemented, and how the work was expanded to include the whole of northern Finland. Finally, the Finnish preparatory processes were compared to case examples of processes for preparing climate change strategies elsewhere in the Barents Region. This analysis provides examples of good practices in preparing a climate change strategy and implementing it. (orig.)

Influences of subtropical jet and Tibetan Plateau on precipitation pattern in Asia : Insights from regional climate modeling

NARCIS (Netherlands)

Sato, Tomonori

2009-01-01

Large topographic features, like the Tibetan Plateau (TP) and the Rocky Mountains, have significant impacts on Earth's climate. Numerical experiments were carried out using a regional climate model in order to study the sensitivity of rainfall distribution to the TP's thermal/dynamic effects and

Climate Impacts of Deforestation/Land-Use Changes in Central South America in the PRECIS Regional Climate Model: Mean Precipitation and Temperature Response to Present and Future Deforestation Scenarios

OpenAIRE

Pablo O. Canziani; Gerardo Carbajal Benitez

2012-01-01

Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961–2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated....

Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic

Directory of Open Access Journals (Sweden)

P. Berg

2013-06-01

Full Text Available The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX (COordinated Regional climate Downscaling EXperiment region, with an emphasis on its suitability to be coupled to a regional ocean and sea ice model. Large biases in mean sea level pressure (MSLP are identified, with pronounced too-high pressure centred over the North Pole in summer of over 5 hPa, and too-low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea ice biases in a future coupled system. The large-scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large-scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables, such as surface radiative components, two-metre temperature and precipitation.

Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

International Nuclear Information System (INIS)

Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

2015-01-01

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

Science.gov (United States)

Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

2018-03-01

Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models

DEFF Research Database (Denmark)

Butts, M.; Rasmussen, S.H.; Ridler, M.

2013-01-01

Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....

Methodological challenges to bridge the gap between regional climate and hydrology models

Science.gov (United States)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph; Felder, Guido

2017-04-01

The frequency and severity of floods worldwide, together with their impacts, are expected to increase under climate change scenarios. It is therefore very important to gain insight into the physical mechanisms responsible for such events in order to constrain the associated uncertainties. Model simulations of the climate and hydrological processes are important tools that can provide insight in the underlying physical processes and thus enable an accurate assessment of the risks. Coupled together, they can provide a physically consistent picture that allows to assess the phenomenon in a comprehensive way. However, climate and hydrological models work at different temporal and spatial scales, so there are a number of methodological challenges that need to be carefully addressed. An important issue pertains the presence of biases in the simulation of precipitation. Climate models in general, and Regional Climate models (RCMs) in particular, are affected by a number of systematic biases that limit their reliability. In many studies, prominently the assessment of changes due to climate change, such biases are minimised by applying the so-called delta approach, which focuses on changes disregarding absolute values that are more affected by biases. However, this approach is not suitable in this scenario, as the absolute value of precipitation, rather than the change, is fed into the hydrological model. Therefore, bias has to be previously removed, being this a complex matter where various methodologies have been proposed. In this study, we apply and discuss the advantages and caveats of two different methodologies that correct the simulated precipitation to minimise differences with respect an observational dataset: a linear fit (FIT) of the accumulated distributions and Quantile Mapping (QM). The target region is Switzerland, and therefore the observational dataset is provided by MeteoSwiss. The RCM is the Weather Research and Forecasting model (WRF), driven at the

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

Science.gov (United States)

Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

2011-03-01

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

Scalability of regional climate change in Europe for high-end scenarios

DEFF Research Database (Denmark)

Christensen, O. B.; Yang, S.; Boberg, F.

2015-01-01

With the help of a simulation using the global circulation model (GCM) EC-Earth, downscaled over Europe with the regional model DMI-HIRHAM5 at a 25 km grid point distance, we investigated regional climate change corresponding to 6°C of global warming to investigate whether regional climate change...... are close to the RCP8.5 emission scenario. We investigated the extent to which pattern scaling holds, i.e. the approximation that the amplitude of any climate change will be approximately proportional to the amount of global warming. We address this question through a comparison of climate change results...... from downscaling simulations over the same integration domain, but for different driving and regional models and scenarios, mostly from the EU ENSEMBLES project. For almost all quantities investigated, pattern scaling seemed to apply to the 6° simulation. This indicates that the single 6° simulation...

Regional impacts of climate change and atmospheric CO2 on future ocean carbon uptake: a multi model linear feedback analysis

International Nuclear Information System (INIS)

Roy, Tilla; Bopp, Laurent; Gehlen, Marion; Cadule, Patricia; Schneider, Birgit; Frolicher, Thomas L.; Segschneider, Joachim; Tjiputra, Jerry; Heinze, Christoph; Joos, Fortunat

2011-01-01

The increase in atmospheric CO 2 over this century depends on the evolution of the oceanic air-sea CO 2 uptake, which will be driven by the combined response to rising atmospheric CO 2 itself and climate change. Here, the future oceanic CO 2 uptake is simulated using an ensemble of coupled climate-carbon cycle models. The models are driven by CO 2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010-2100) oceanic CO 2 uptake into a CO 2 -induced component, due to rising atmospheric CO 2 concentrations, and a climate-induced component, due to global warming. The models capture the observation based magnitude and distribution of anthropogenic CO 2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO 2 uptake in the sub polar Southern Ocean and the equatorial regions, owing to decreased CO 2 solubility; and reduced CO 2 uptake in the mid-latitudes, owing to decreased CO 2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extra-tropics, to large freshwater fluxes in the extra-tropical North Atlantic Ocean, and to small changes in the CO 2 solubility in the equatorial regions. In key anthropogenic CO 2 uptake regions, the climate-induced component offsets the CO 2 - induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extra-tropics and 25% in the southern extra-tropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO 2 uptake may be difficult without monitoring additional tracers, such as oxygen. (authors)

Regional impacts of climate change and atmospheric CO2 on future ocean carbon uptake: a multi model linear feedback analysis

International Nuclear Information System (INIS)

Roy, Tilla; Bopp, Laurent; Gehlen, Marion; Cadule, Patricia

2011-01-01

The increase in atmospheric CO 2 over this century depends on the evolution of the oceanic air-sea CO 2 uptake, which will be driven by the combined response to rising atmospheric CO 2 itself and climate change. Here, the future oceanic CO 2 uptake is simulated using an ensemble of coupled climate-carbon cycle models. The models are driven by CO 2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010-2100) oceanic CO 2 uptake into a CO 2 -induced component, due to rising atmospheric CO 2 concentrations, and a climate-induced component, due to global warming. The models capture the observation based magnitude and distribution of anthropogenic CO 2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO 2 uptake in the sub-polar Southern Ocean and the equatorial regions, owing to decreased CO 2 solubility; and reduced CO 2 uptake in the mid latitudes, owing to decreased CO 2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extra tropics, to large freshwater fluxes in the extra tropical North Atlantic Ocean, and to small changes in the CO 2 solubility in the equatorial regions. In key anthropogenic CO 2 uptake regions, the climate-induced component offsets the CO 2 - induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extra tropics and 25% in the southern extra tropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO 2 uptake may be difficult without monitoring additional tracers, such as oxygen. (authors)

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

Science.gov (United States)

Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

2018-03-01

The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

Heat waves over Central Europe in regional climate model simulations

Science.gov (United States)

Lhotka, Ondřej; Kyselý, Jan

2014-05-01

Regional climate models (RCMs) have become a powerful tool for exploring impacts of global climate change on a regional scale. The aim of the study is to evaluate the capability of RCMs to reproduce characteristics of major heat waves over Central Europe in their simulations of the recent climate (1961-2000), with a focus on the most severe and longest Central European heat wave that occurred in 1994. We analyzed 7 RCM simulations with a high resolution (0.22°) from the ENSEMBLES project, driven by the ERA-40 reanalysis. In observed data (the E-OBS 9.0 dataset), heat waves were defined on the basis of deviations of daily maximum temperature (Tmax) from the 95% quantile of summer Tmax distribution in grid points over Central Europe. The same methodology was applied in the RCM simulations; we used corresponding 95% quantiles (calculated for each RCM and grid point) in order to remove the bias of modelled Tmax. While climatological characteristics of heat waves are reproduced reasonably well in the RCM ensemble, we found major deficiencies in simulating heat waves in individual years. For example, METNOHIRHAM simulated very severe heat waves in 1996, when no heat wave was observed. Focusing on the major 1994 heat wave, considerable differences in simulated temperature patterns were found among the RCMs. The differences in the temperature patterns were clearly linked to the simulated amount of precipitation during this event. The 1994 heat wave was almost absent in all RCMs that did not capture the observed precipitation deficit, while it was by far most pronounced in KNMI-RACMO that simulated virtually no precipitation over Central Europe during the 15-day period of the heat wave. By contrast to precipitation, values of evaporative fraction in the RCMs were not linked to severity of the simulated 1994 heat wave. This suggests a possible major contribution of other factors such as cloud cover and associated downward shortwave radiation. Therefore, a more detailed

Alpine snow cover in a changing climate: a regional climate model perspective

Science.gov (United States)

Steger, Christian; Kotlarski, Sven; Jonas, Tobias; Schär, Christoph

2013-08-01

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951-2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971-2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40-80 % by mid century relative to 1971-2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000-2,500 m, SWE reductions amount to 10-60 % by mid century and to 30-80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

Science.gov (United States)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

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

Science.gov (United States)

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

2018-06-01

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

An investigation of tropical Atlantic bias in a high-resolution coupled regional climate model

Energy Technology Data Exchange (ETDEWEB)

Patricola, Christina M.; Saravanan, R.; Hsieh, Jen-Shan [Texas A and M University, Department of Atmospheric Sciences, College Station, TX (United States); Li, Mingkui; Xu, Zhao [Texas A and M University, Department of Oceanography, College Station, TX (United States); Ocean University of China, Key Laboratory of Physical Oceanography of Ministry of Education, Qingdao (China); Chang, Ping [Texas A and M University, Department of Oceanography, College Station, TX (United States); Ocean University of China, Key Laboratory of Physical Oceanography of Ministry of Education, Qingdao (China); Second Institute of Oceanography, State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou, Zhejiang (China)

2012-11-15

Coupled atmosphere-ocean general circulation models (AOGCMs) commonly fail to simulate the eastern equatorial Atlantic boreal summer cold tongue and produce a westerly equatorial trade wind bias. This tropical Atlantic bias problem is investigated with a high-resolution (27-km atmosphere represented by the Weather Research and Forecasting Model, 9-km ocean represented by the Regional Ocean Modeling System) coupled regional climate model. Uncoupled atmospheric simulations test climate sensitivity to cumulus, land-surface, planetary boundary layer, microphysics, and radiation parameterizations and reveal that the radiation scheme has a pronounced impact in the tropical Atlantic. The CAM radiation simulates a dry precipitation (up to -90%) and cold land-surface temperature (up to -8 K) bias over the Amazon related to an over-representation of low-level clouds and almost basin-wide westerly trade wind bias. The Rapid Radiative Transfer Model and Goddard radiation simulates doubled Amazon and Congo Basin precipitation rates and a weak eastern Atlantic trade wind bias. Season-long high-resolution coupled regional model experiments indicate that the initiation of the warm eastern equatorial Atlantic sea surface temperature (SST) bias is more sensitive to the local rather than basin-wide trade wind bias and to a wet Congo Basin instead of dry Amazon - which differs from AOGCM simulations. Comparisons between coupled and uncoupled simulations suggest a regional Bjerknes feedback confined to the eastern equatorial Atlantic amplifies the initial SST, wind, and deepened thermocline bias, while barrier layer feedbacks are relatively unimportant. The SST bias in some CRCM simulations resembles the typical AOGCM bias indicating that increasing resolution is unlikely a simple solution to this problem. (orig.)

Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme

Energy Technology Data Exchange (ETDEWEB)

Eum, Hyung-Il; Laprise, Rene [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Gachon, Philippe [University of Quebec at Montreal, ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Environment Canada, Adaptation and Impacts Research Section, Climate Research Division, Montreal, QC (Canada); Ouarda, Taha [University of Quebec, INRS-ETE (Institut National de la Recherche Scientifique, Centre Eau-Terre-Environnement), Quebec, QC (Canada)

2012-04-15

This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23 years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates

Climatic Effects of Regional Nuclear War

Science.gov (United States)

Oman, Luke D.

2011-01-01

We use a modern climate model and new estimates of smoke generated by fires in contemporary cities to calculate the response of the climate system to a regional nuclear war between emerging third world nuclear powers using 100 Hiroshima-size bombs (less than 0.03% of the explosive yield of the current global nuclear arsenal) on cities in the subtropics. We find significant cooling and reductions of precipitation lasting years, which would impact the global food supply. The climate changes are large and longlasting because the fuel loadings in modern cities are quite high and the subtropical solar insolation heats the resulting smoke cloud and lofts it into the high stratosphere, where removal mechanisms are slow. While the climate changes are less dramatic than found in previous "nuclear winter" simulations of a massive nuclear exchange between the superpowers, because less smoke is emitted, the changes seem to be more persistent because of improvements in representing aerosol processes and microphysical/dynamical interactions, including radiative heating effects, in newer global climate system models. The assumptions and calculations that go into these conclusions will be described.

An efficient regional energy-moisture balance model for simulation of the Greenland Ice Sheet response to climate change

Directory of Open Access Journals (Sweden)

A. Robinson

2010-04-01

Full Text Available In order to explore the response of the Greenland ice sheet (GIS to climate change on long (centennial to multi-millennial time scales, a regional energy-moisture balance model has been developed. This model simulates seasonal variations of temperature and precipitation over Greenland and explicitly accounts for elevation and albedo feedbacks. From these fields, the annual mean surface temperature and surface mass balance can be determined and used to force an ice sheet model. The melt component of the surface mass balance is computed here using both a positive degree day approach and a more physically-based alternative that includes insolation and albedo explicitly. As a validation of the climate model, we first simulated temperature and precipitation over Greenland for the prescribed, present-day topography. Our simulated climatology compares well to observations and does not differ significantly from that of a simple parameterization used in many previous simulations. Furthermore, the calculated surface mass balance using both melt schemes falls within the range of recent regional climate model results. For a prescribed, ice-free state, the differences in simulated climatology between the regional energy-moisture balance model and the simple parameterization become significant, with our model showing much stronger summer warming. When coupled to a three-dimensional ice sheet model and initialized with present-day conditions, the two melt schemes both allow realistic simulations of the present-day GIS.

Which complexity of regional climate system models is essential for downscaling anthropogenic climate change in the Northwest European Shelf?

Science.gov (United States)

Mathis, Moritz; Elizalde, Alberto; Mikolajewicz, Uwe

2018-04-01

Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production.

Modeling framework for estimating impacts of climate change on electricity demand at regional level: Case of Greece

International Nuclear Information System (INIS)

Mirasgedis, S.; Sarafidis, Y.; Georgopoulou, E.; Kotroni, V.; Lagouvardos, K.; Lalas, D.P.

2007-01-01

This paper focuses on the potential upcoming impacts of climate change in the 21st century on electricity demand at regional/national levels for regions where topography and location result in large differences in local climate. To address this issue, a regional climate model, PRECIS, has been used to predict future climatic conditions under different emissions scenarios (namely A2 and B2 of the IPCC special report on emissions scenarios (SRES)) as an input to a multiple regression model of the sensitivity of electricity demand in the Greek interconnected power system to climate and socio-economic factors. The economic development input to the multiple regression model follows the same storylines of the SRES scenarios upto 2100 and includes sub-scenarios to cover larger and smaller economic development rates. The results of the analysis indicate an increase of the annual electricity demand attributable solely to climate change of 3.6-5.5% under all scenarios examined, most of which results from increased annual variability with substantial increases during the summer period that outweighs moderate declines estimated for the winter period. This becomes more pronounced if inter-annual variability, especially of summer months, is taken into consideration. It was also found that in the long run, economic development will have a strong effect on future electricity demand, thus increasing substantially the total amount of energy consumed for cooling and heating purposes. This substantial increase in energy demand with strong annual variability will lead to the need for inordinate increases of installed capacity, a large percentage of which will be under utilized. Thus, appropriate adaptation strategies (e.g. new investments, interconnections with other power systems, energy saving programmes, etc.) need to be developed at the state level in order to ensure the security of energy supply. (author)

Deriving user-informed climate information from climate model ensemble results

Science.gov (United States)

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

2017-07-01

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

World Regionalization of Climate Change(1961–2010)

Institute of Scientific and Technical Information of China (English)

Peijun; Shi; Shao; Sun; Daoyi; Gong; Tao; Zhou

2016-01-01

Traditional climate classification or regionalization characterizes the mean state of climate condition, which cannot meet the demand of addressing climate change currently. We have developed a climate change classification method, as well as the fundamental principles, an indicator system, and mapping techniques of climate change regionalization. This study used annual mean temperature and total precipitation as climatic indices, and linear trend and variation change as change indices to characterize climate change quantitatively. The study has proposed a scheme for world climate change regionalization based on a half century of climate data(1961–2010). Level-I regionalization divides the world into 12 tendency zones based on the linear trend of climate, level-II regionalization resulted in 28 fluctuation regions based on the variation change of climate. Climate change regionalization provides a scientific basis for countries and regions to develop plans for adapting to climate change, especially for managing climate-related disaster or environmental risks.

Future projections of the climate and surface mass balance of Svalbard with the regional climate model MAR

Science.gov (United States)

Lang, C.; Fettweis, X.; Erpicum, M.

2015-01-01

We have performed future projections of the climate and surface mass balance (SMB) of Svalbard with the MAR regional climate model forced by the MIROC5 global model, following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of the melt around 2050, with a larger melt increase in the south compared to the north of the archipelago and the ice caps. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a strong winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. At the end of the century (2070-2099 mean), SMB is projected to be negative over the entire Svalbard and, by 2085, all glaciated regions of Svalbard are predicted to undergo net ablation, meaning that, under the RCP8.5 scenario, all the glaciers and ice caps are predicted to start their irreversible retreat before the end of the 21st century.

Mediterranean climate modelling: variability and climate change scenarios

International Nuclear Information System (INIS)

Somot, S.

2005-12-01

Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

A synthesis of regional climate change simulations - A Scandinavian perspective

DEFF Research Database (Denmark)

Christensen, J. H.; Räinsänen, J.; Iversen, T.

2001-01-01

Four downscaling experiments of regional climate change for the Nordic countries have been conducted with three different regional climate models (RCMs). A short synthesis of the outcome of the suite of experiments is presented as an ensemble, reflecting the different driving atmosphere-ocean...... general circulation model (AOGCM) conditions, RCM model resolution and domain size, and choice of emission scenarios. This allows the sources of uncertainties in the projections to be assessed. At the same time analysis of the climate change signal for temperature and precipitation over the period 1990......-2050 reveals strong similarities. In particular, all experiments in the suite simulate changes in the precipitation distribution towards a higher frequency of heavy precipitation....

Impacts of climate change on mangrove ecosystems: A region by region overview

Science.gov (United States)

Ward, Raymond D.; Friess, Daniel A.; Day, Richard H.; MacKenzie, Richard A.

2016-01-01

Inter-related and spatially variable climate change factors including sea level rise, increased storminess, altered precipitation regime and increasing temperature are impacting mangroves at regional scales. This review highlights extreme regional variation in climate change threats and impacts, and how these factors impact the structure of mangrove communities, their biodiversity and geomorphological setting. All these factors interplay to determine spatially variable resiliency to climate change impacts, and because mangroves are varied in type and geographical location, these systems are good models for understanding such interactions at different scales. Sea level rise is likely to influence mangroves in all regions although local impacts are likely to be more varied. Changes in the frequency and intensity of storminess are likely to have a greater impact on N and Central America, Asia, Australia, and East Africa than West Africa and S. America. This review also highlights the numerous geographical knowledge gaps of climate change impacts, with some regions particularly understudied (e.g., Africa and the Middle East). While there has been a recent drive to address these knowledge gaps especially in South America and Asia, further research is required to allow researchers to tease apart the processes that influence both vulnerability and resilience to climate change. A more globally representative view of mangroves would allow us to better understand the importance of mangrove type and landscape setting in determining system resiliency to future climate change.

Reconstruction of regional climate and climate change in past decades

Science.gov (United States)

von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.

2009-12-01

Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.

Regional Climate Change Impact on Agricultural Land Use in West Africa

Science.gov (United States)

Ahmed, K. F.; Wang, G.; You, L.

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

Science.gov (United States)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing

Economy-Energy-Climate Interaction. The Model Wiagem

International Nuclear Information System (INIS)

Kemfert, C.

2001-09-01

This paper presents an integrated economy-energy-climate model WIAGEM (World Integrated Assessment General Equilibrium Model) which incorporates economic, energetic and climatic modules in an integrated assessment approach. In order to evaluate market and non-market costs and benefits of climate change WIAGEM combines an economic approach with a special focus on the international energy market and integrates climate interrelations by temperature changes and sea level variations. WIAGEM bases on 25 world regions which are aggregated to 11 trading regions and 14 sectors within each region. The representation of the economic relations is based on an intertemporal general equilibrium approach and contains the international markets for oil, coal and gas. The model incorporates all greenhouse gases (GHG) which influence the potential global temperature, the sea level variation and the assessed probable impacts in terms of costs and benefits of climate change. Market and non market damages are evaluated due to the damage costs approaches of Tol (2001). Additionally, this model includes net changes in GHG emissions from sources and removals by sinks resulting from land use change and forest activities. This paper describes the model structure in detail and outlines some general results, especially the impacts of climate change. As a result, climate change impacts do matter within the next 50 years, developing regions face high economic losses in terms of welfare and GDP losses. The inclusion of sinks and other GHG changes results significantly

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

Modeling aquifer behaviour under climate change and high consumption: Case study of the Sfax region, southeast Tunisia

Science.gov (United States)

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.

Hydrological processes in regional climate model simulations of the central United States flood of June-July 1993

DEFF Research Database (Denmark)

Anderson, Christopher J.; Arritt, Raymond W.; Takle, Eugene S.

2003-01-01

Thirteen regional climate model (RCM) simulations of June-July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° X 10° subregion of the upper Mississippi River basin, containing the region of maximum...

Regional aerosol emissions and temperature response: Local and remote climate impacts of regional aerosol forcing

Science.gov (United States)

Lewinschal, Anna; Ekman, Annica; Hansson, Hans-Christen

2017-04-01

Emissions of anthropogenic aerosols vary substantially over the globe and the short atmospheric residence time of aerosols leads to a highly uneven radiative forcing distribution, both spatially and temporally. Regional aerosol radiative forcing can, nevertheless, exert a large influence on the temperature field away from the forcing region through changes in heat transport or the atmospheric or ocean circulation. Moreover, the global temperature response distribution to aerosol forcing may vary depending on the geographical location of the forcing. In other words, the climate sensitivity in one region can vary depending on the location of the forcing. The surface temperature distribution response to changes in sulphate aerosol forcing caused by sulphur dioxide (SO2) emission perturbations in four different regions is investigated using the Norwegian Earth System Model (NorESM). The four regions, Europe, North America, East and South Asia, are all regions with historically high aerosol emissions and are relevant from both an air-quality and climate policy perspective. All emission perturbations are defined relative to the year 2000 emissions provided for the Coupled Model Intercomparison Project phase 5. The global mean temperature change per unit SO2 emission change is similar for all four regions for similar magnitudes of emissions changes. However, the global temperature change per unit SO2 emission in simulations where regional SO2 emission were removed is substantially higher than that obtained in simulations where regional SO2 emissions were increased. Thus, the climate sensitivity to regional SO2 emissions perturbations depends on the magnitude of the emission perturbation in NorESM. On regional scale, on the other hand, the emission perturbations in different geographical locations lead to different regional temperature responses, both locally and in remote regions. The results from the model simulations are used to construct regional temperature potential

A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period

Directory of Open Access Journals (Sweden)

Florence Sevault

2014-11-01

Full Text Available A fully coupled regional climate system model (CNRM-RCSM4 dedicated to the Mediterranean region is described and evaluated using a multidecadal hindcast simulation (1980–2012 driven by global atmosphere and ocean reanalysis. CNRM-RCSM4 includes the regional representation of the atmosphere (ALADIN-Climate model, land surface (ISBA model, rivers (TRIP model and the ocean (NEMOMED8 model, with a daily coupling by the OASIS coupler. This model aims to reproduce the regional climate system with as few constraints as possible: there is no surface salinity, temperature relaxation, or flux correction; the Black Sea budget is parameterised and river runoffs (except for the Nile are fully coupled. The atmospheric component of CNRM-RCSM4 is evaluated in a companion paper; here, we focus on the air–sea fluxes, river discharges, surface ocean characteristics, deep water formation phenomena and the Mediterranean thermohaline circulation. Long-term stability, mean seasonal cycle, interannual variability and decadal trends are evaluated using basin-scale climatologies and in-situ measurements when available. We demonstrate that the simulation shows overall good behaviour in agreement with state-of-the-art Mediterranean RCSMs. An overestimation of the shortwave radiation and latent heat loss as well as a cold Sea Surface Temperature (SST bias and a slight trend in the bottom layers are the primary current deficiencies. Further, CNRM-RCSM4 shows high skill in reproducing the interannual to decadal variability for air–sea fluxes, river runoffs, sea surface temperature and salinity as well as open-sea deep convection, including a realistic simulation of the Eastern Mediterranean Transient. We conclude that CNRM-RCSM4 is a mature modelling tool allowing the climate variability of the Mediterranean regional climate system to be studied and understood. It is used in hindcast and scenario modes in the HyMeX and Med-CORDEX programs.

Regional Climate Modelling of the Western Iberian Low-Level Wind Jet

Science.gov (United States)

Soares, Pedro M. M.; Lima, Daniela C. A.; Cardoso, Rita M.; Semedo, Álvaro

2016-04-01

The Iberian coastal low-level jet (CLLJ) is one the less studied boundary layer wind jet features in the Eastern Boundary Currents Systems (EBCS). These regions are amongst the most productive ocean ecosystems, where the atmosphere-land-ocean feedbacks, which include marine boundary layer clouds, coastal jets, upwelling and inland soil temperature and moisture, play an important role in defining the regional climate along the sub-tropical mid-latitude western coastal areas. Recently, the present climate western Iberian CLLJ properties were extensively described using a high resolution regional climate hindcast simulation. A summer maximum frequency of occurrence above 30% was found, with mean maximum wind speeds around 15 ms-1, between 300 and 400m heights (at the jet core). Since the 1990s the climate change impact on the EBCS is being studied, nevertheless some lack of consensus still persists regarding the evolution of upwelling and other components of the climate system in these areas. However, recently some authors have shown that changes are to be expected concerning the timing, intensity and spatial homogeneity of coastal upwelling and of CLLJs, in response to future warming, especially at higher latitudes, namely in Iberia and Canaries. In this study, the first climate change assessment study regarding the Western Iberian CLLJ, using a high resolution (9km) regional climate simulation, is presented. The properties of this CLLJ are studied and compared using two 30 years simulations: one historical simulation for the 1971-2000 period, and another simulation for future climate, in agreement with the RCP8.5 scenario, for the 2071-2100 period. Robust and consistent changes are found: 1) the hourly frequency of occurrence of the CLLJ is expected to increase in summer along the western Iberian coast, from mean maximum values of around 35% to approximately 50%; 2) the relative increase of the CLLJ frequency of occurrence is higher in the north off western Iberia

Climate in Context - How partnerships evolve in regions

Science.gov (United States)

Parris, A. S.

2014-12-01

In 2015, NOAA's RISA program will celebrate its 20th year of exploration in the development of usable climate information. In the mid-1990s, a vision emerged to develop interdisciplinary research efforts at the regional scale for several important reasons. Recognizable climate patterns, such as the El Nino Southern Oscillation (ENSO), emerge at the regional level where our understanding of observations and models coalesce. Critical resources for society are managed in a context of regional systems, such as water supply and human populations. Multiple scales of governance (local, state, and federal) with complex institutional relationships can be examined across a region. Climate information (i.e. data, science, research etc) developed within these contexts has greater potential for use. All of this work rests on a foundation of iterative engagement between scientists and decision makers. Throughout these interactions, RISAs have navigated diverse politics, extreme events and disasters, socio-economic and ecological disruptions, and advances in both science and technology. Our understanding of information needs is evolving into a richer understanding of complex institutional, legal, political, and cultural contexts within which people can use science to make informed decisions. The outcome of RISA work includes both cases where climate information was used in decisions and cases where capacity for using climate information and making climate resilient decisions has increased over time. In addition to balancing supply and demand of scientific information, RISAs are engaged in a social process of reconciling climate information use with important drivers of society. Because partnerships are critical for sustained engagement, and because engagement is critically important to the use of science, the rapid development of new capacity in regionally-based science programs focused on providing climate decision support is both needed and challenging. New actors can bolster

CARICOF - The Caribbean Regional Climate Outlook Forum

Science.gov (United States)

Van Meerbeeck, Cedric

2013-04-01

Regional Climate Outlook Forums (RCOFs) are viewed as a critical building block in the Global Framework for Climate Services (GFCS) of the World Meteorological Organization (WMO). The GFCS seeks to extend RCOFs to all vulnerable regions of the world such as the Caribbean, of which the entire population is exposed to water- and heat-related natural hazards. An RCOF is initially intended to identify gaps in information and technical capability; facilitate research cooperation and data exchange within and between regions, and improve coordination within the climate forecasting community. A focus is given on variations in climate conditions on a seasonal timescale. In this view, the relevance of a Caribbean RCOF (CARICOF) is the following: while the seasonality of the climate in the Caribbean has been well documented, major gaps in knowledge exist in terms of the drivers in the shifts of amplitude and phase of seasons (as evidenced from the worst region-wide drought period in recent history during 2009-2010). To address those gaps, CARICOF has brought together National Weather Services (NWSs) from 18 territories under the coordination of the Caribbean Institute for Meteorology and Hydrology (CIMH), to produce region-wide, consensus, seasonal climate outlooks since March 2012. These outlooks include tercile rainfall forecasts, sea and air surface temperature forecasts as well as the likely evolution of the drivers of seasonal climate variability in the region, being amongst others the El Niño Southern Oscillation or tropical Atlantic and Caribbean Sea temperatures. Forecasts for both the national-scale forecasts made by the NWSs and CIMH's regional-scale forecast amalgamate output from several forecasting tools. These currently include: (1) statistical models such as Canonical Correlation Analysis run with the Climate Predictability Tool, providing tercile rainfall forecasts at weather station scale; (2) a global outlooks published by the WMO appointed Global Producing

Evaluation of high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

Science.gov (United States)

Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

2009-04-01

Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

Science.gov (United States)

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

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

Science.gov (United States)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.

Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models

NARCIS (Netherlands)

Rae, J.G.L.; Aðalgeirsdóttir, G.; Edwards, T.L.; Fettweis, X.; Gregory, J.M.; Hewitt, H.T.; Lowe, J.A.; Lucas-Picher, P.; Mottram, R.H.; Payne, A.J.; Ridley, J.K.; Shannon, S.R.; van de Berg, W.J.; van de Wal, R.S.W.; van den Broeke, M.R.

2012-01-01

Four high-resolution regional climate models (RCMs) have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB), and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution

Continuously on-­going regional climate hindcast simulations for impact applications

Science.gov (United States)

Anders, Ivonne; Piringer, Martin; Kaufmann, Hildegard; Knauder, Werner; Resch, Gernot; Andre, Konrad

2017-04-01

Observational data for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation performed with the regional climate model COSMO-CLM is forced by ERAinterim and optimized for the Alpine Region. The simulation available for the period of 1979-2015 in a spatial resolution of about 10km is prolonged ongoing and fullfils the customer's needs with respect of output variables, levels, intervals and statistical measures. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the Northeast. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure or the calculation the separation distances between livestock

Greenhouse Gas Induced Changes in the Seasonal Cycle of the Amazon Basin in Coupled Climate-Vegetation Regional Model

Directory of Open Access Journals (Sweden)

Flavio Justino

2016-01-01

Full Text Available Previous work suggests that changes in seasonality could lead to a 70% reduction in the extent of the Amazon rainforest. The primary cause of the dieback of the rainforest is a lengthening of the dry season due to a weakening of the large-scale tropical circulation. Here we examine these changes in the seasonal cycle. Under present day conditions the Amazon climate is characterized by a zonal separation of the dominance of the annual and semi-annual seasonal cycles. This behavior is strongly modified under greenhouse warming conditions, with the annual cycle becoming dominant throughout the Amazon basin, increasing differences between the dry and wet seasons. In particular, there are substantial changes in the annual cycle of temperature due to the increase in the temperature of the warmest month, but the lengthening of the dry season is believed to be particularly important for vegetation-climate feedbacks. Harmonic analysis performed to regional climate model simulations yields results that differ from the global climate model that it is forced from, with the regional model being more sensitive to changes in the seasonal cycle.

Winter precipitation and cyclones in the Mediterranean region: future climate scenarios in a regional simulation

Directory of Open Access Journals (Sweden)

P. Lionello

2007-11-01

Full Text Available Future climate projections show higher/lower winter (Dec-Jan-Feb precipitation in the northern/southern Mediterranean region than in present climate conditions. This paper analyzes the results of regional model simulations of the A2 and B2 scenarios, which confirm this opposite precipitation change and link it to the change of cyclone activity. The increase of the winter cyclone activity in future climate scenarios over western Europe is responsible for the larger precipitation at the northern coast of the basin, though the bulk of the change is located outside the Mediterranean region. The reduction of cyclone activity inside the Mediterranean region in future scenarios is responsible for the lower precipitation at the southern and eastern Mediterranean coast.

Evaluating the impact of climate policies on regional food availability and accessibility using an Integrated Assessment Model

Science.gov (United States)

Gilmore, E.; Cui, Y. R.; Waldhoff, S.

2015-12-01

Beyond 2015, eradicating hunger will remain a critical part of the global development agenda through the Sustainable Development Goals (SDG). Efforts to limit climate change through both mitigation of greenhouse gas emissions and land use policies may interact with food availability and accessibility in complex and unanticipated ways. Here, we develop projections of regional food accessibility to 2050 under the alternative futures outlined by the Shared Socioeconomic Pathways (SSPs) and under different climate policy targets and structures. We use the Global Change Assessment Model (GCAM), an integrated assessment model (IAM), for our projections. We calculate food access as the weighted average of consumption of five staples and the portion of income spend on those commodities and extend the GCAM calculated universal global producer price to regional consumer prices drawing on historical relationships of these prices. Along the SSPs, food access depends largely on expectations of increases in population and economic status. Under a more optimistic scenario, the pressures on food access from increasing demand and rising prices can be counterbalanced by faster economic development. Stringent climate policies that increase commodity prices, however, may hinder vulnerable regions, namely Sub-Saharan Africa, from achieving greater food accessibility.

Climate impacts of deforestation/land-use changes in Central South America in the PRECIS regional climate model: mean precipitation and temperature response to present and future deforestation scenarios.

Science.gov (United States)

Canziani, Pablo O; Carbajal Benitez, Gerardo

2012-01-01

Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961-2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated. Current 2002 and estimated 2030 land-use scenarios are used to assess PRECIS's response during 1960-2000. ERA-40 and ECHAM4 Baseline driven runs yield similar results. Precipitation changes for 2002 and 2030 land-use scenarios, while significant within deforested areas, do not result in significant regional changes. For temperature significant changes are found within deforested areas and beyond, with major temperature enhancements during winter and spring. Given the current climate, primary effects of deforestation/land-use changes remain mostly confined to the tropical latitudes of Gran Chaco, and Amazonia.

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

Science.gov (United States)

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

2012-04-01

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

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

Science.gov (United States)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

Regional analysis of ground and above-ground climate

Science.gov (United States)

1981-12-01

The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of Earth tempering as a practice and of specific Earth sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermal advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground are included. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 20 locations in the United States.

Regional analysis of ground and above-ground climate

Energy Technology Data Exchange (ETDEWEB)

1981-12-01

The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long-term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of earth tempering as a practice and of specific earth-sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermal advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Also contained in the report are reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 29 locations in the United States.

CLIMATE CHANGE AND ORIENTAL SPRUCE (PICEA ORIENTALIS ECOSYSTEMS IN EASTERN BLACKSEA REGION OF TURKEY

Directory of Open Access Journals (Sweden)

Aydın Tüfekçioğlu

2008-04-01

Full Text Available Climate change has been getting more attention from scientific community recently. Eastern Black Sea Region of Turkey will get significant influences from the climate change according to regional climate model (RegCM3. Oriental spruce (Picea orientalis L. is an important tree species of Turkey and it only grows in the Eastern Black Sea Region of Turkey. With the increase in global warming, spruce forests started to have serious bark beetle problems. More than 200 000 trees died in the region recently due to bark beetle attack. We used existing literature related to oriental spruce and future climate of the region and field observations done in the different times to assess current status of the spruce stands. Future climate of the region has been predicted using RegCM3 regional climate model. Climate change could significantly influence distribution, diversity, structure and stability of the oriental spruce ecosystems. According to RegCM3 regional climate model, the temperatures will increase 2-4 °C in the region in the next century. Future climate scenarios predict 200-300 mm increases in precipitation in the eastern part of the region while the western part won't have any increase in precipitation in the next century. Temperature increases in the western part of the region can cause more stress on spruce trees and would probably increase bark beetle attacks. Also, fire could become an important threat in the western part of the region. It is possible to observe 400-800 m upward shift in the spruce belt in the western part. Treeline of spruce stands would probably move upward both in western and eastern part of the North-eastern Blacksea Region.

Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR

NARCIS (Netherlands)

Fettweis, X.; Franco, B.; Tedesco, M.; van Angelen, J.H.; Lenaerts, J.T.M.; van den Broeke, M.R.; Gallée, H.

2013-01-01

To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Mod`ele Atmosph´erique R´egional), forced by output of three CMIP5 (Coupled Model

Use of variability modes to evaluate AR4 climate models over the Euro-Atlantic region

Energy Technology Data Exchange (ETDEWEB)

Casado, M.J.; Pastor, M.A. [Agencia Estatal de Meteorologia (AEMET), Madrid (Spain)

2012-01-15

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others. (orig.)

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

Science.gov (United States)

Tariku, Tebikachew Betru; Gan, Thian Yew

2018-06-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

Science.gov (United States)

Tariku, Tebikachew Betru; Gan, Thian Yew

2017-08-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

Modeling lakes and reservoirs in the climate system

Science.gov (United States)

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

2009-01-01

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

A regional climate simulation over the Iberian Peninsula for the last millennium

Directory of Open Access Journals (Sweden)

J. J. Gómez-Navarro

2011-04-01

Full Text Available A high-resolution (30 km regional paleoclimate simulation of the last millennium over the Iberian Peninsula (IP is presented. The simulation was performed with a climate version of the mesoscale model MM5 driven by the global model ECHO-G. Both models were driven by the same reconstructions of several external forcing factors. The high spatial resolution of the regional model allows climatologists to realistically simulate many aspects of the climate in the IP, as compared to an observational data set in the reference period 1961–1990. Although the spatial-averaged values developed by the regional model are tightly driven by the boundary conditions, it is capable to develop a different realisation of the past climate at regional scales, especially in the high-frequency domain and for precipitation. This has to be considered when comparing the results of climate simulations versus proxy reconstructions. A preliminary comparison of the simulation results with reconstructions of temperature and precipitation over the IP shows good agreement in the warming trends in the last century of the simulation, although there are large disagreements in key periods such as the precipitation anomalies in the Maunder Minimum.

Modelling the energy and exergy utilisation of the Mexican non-domestic sector: A study by climatic regions

International Nuclear Information System (INIS)

García Kerdan, Iván; Morillón Gálvez, David; Raslan, Rokia; Ruyssevelt, Paul

2015-01-01

This paper presents the development of a bottom-up stock model to perform a holistic energy study of the Mexican non-domestic sector. The current energy and exergy flows are shown based on a categorisation by climatic regions with the aim of understanding the impact of local characteristics on regional efficiencies. Due to the limited data currently available, the study is supported by the development of a detailed archetype-based stock model using EnergyPlus as a first law analysis tool combined with an existing exergy analysis method. Twenty-one reference models were created to estimate the electric and gas use in the sector. The results indicate that sectoral energy and exergy annual input are 95.37 PJ and 94.28 PJ, respectively. Regional exergy efficiencies were found to be 17.8%, 16.6% and 23.2% for the hot-dry, hot-humid and temperate climates, respectively. The study concludes that significant potential for improvements still exists, especially in the cases of space conditioning, lighting, refrigeration, and cooking where most exergy destructions occur. Additionally, this work highlights that the method described may be further used to study the impact of large-scale refurbishments and promote national regulations and standards for sustainable buildings that takes into consideration energy and exergy indicators. - Highlights: • A bottom-up physics model was developed to analyse the Mexican commercial stock. • A detailed energy analysis by climate, buildings and end-uses is presented. • The Mexican non-domestic sector as a whole has an exergy efficiency of 19.7%. • The lowest regional exergy efficiency is found at the hot-humid region with 16.6%. • By end use, the highest exergy destructions are caused by HVAC and lighting

Validation of EURO-CORDEX regional climate models in reproducing the variability of precipitation extremes in Romania

Science.gov (United States)

Dumitrescu, Alexandru; Busuioc, Aristita

2016-04-01

EURO-CORDEX is the European branch of the international CORDEX initiative that aims to provide improved regional climate change projections for Europe. The main objective of this paper is to document the performance of the individual models in reproducing the variability of precipitation extremes in Romania. Here three EURO-CORDEX regional climate models (RCMs) ensemble (scenario RCP4.5) are analysed and inter-compared: DMI-HIRHAM5, KNMI-RACMO2.2 and MPI-REMO. Compared to previous studies, when the RCM validation regarding the Romanian climate has mainly been made on mean state and at station scale, a more quantitative approach of precipitation extremes is proposed. In this respect, to have a more reliable comparison with observation, a high resolution daily precipitation gridded data set was used as observational reference (CLIMHYDEX project). The comparison between the RCM outputs and observed grid point values has been made by calculating three extremes precipitation indices, recommended by the Expert Team on Climate Change Detection Indices (ETCCDI), for the 1976-2005 period: R10MM, annual count of days when precipitation ≥10mm; RX5DAY, annual maximum 5-day precipitation and R95P%, precipitation fraction of annual total precipitation due to daily precipitation > 95th percentile. The RCMs capability to reproduce the mean state for these variables, as well as the main modes of their spatial variability (given by the first three EOF patterns), are analysed. The investigation confirms the ability of RCMs to simulate the main features of the precipitation extreme variability over Romania, but some deficiencies in reproducing of their regional characteristics were found (for example, overestimation of the mea state, especially over the extra Carpathian regions). This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian

The effect of a giant wind farm on precipitation in a regional climate model

International Nuclear Information System (INIS)

Fiedler, B H; Bukovsky, M S

2011-01-01

The Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to study the effect of a giant wind farm on warm-season precipitation in the eastern two-thirds of the USA. The boundary conditions for WRF are supplied by 62 years of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) global reanalysis. In the model, the presence of a mid-west wind farm, either giant or small, can have an enormous impact on the weather and the amount of precipitation for one season, which is consistent with the known sensitivity of long-term weather forecasts to initial conditions. The effect on climate is less strong. In the average precipitation of 62 warm seasons, there is a statistically significant 1.0% enhancement of precipitation in a multi-state area surrounding and to the south-east of the wind farm.

The new WMO RA VI Regional Climate Centre on Climate Monitoring

Science.gov (United States)

Rapp, J.; Nitsche, H.

2010-09-01

Regional Climate Centres (RCCs) are institutions with the capacity and mandate by WMO to develop high quality regional-scale products using global products and incorporating regional information. Recently a pilot network of three RCC consortia was established for the WMO region RA VI (Europe and Middle East): • RCC node on climate data, • RCC node on climate monitoring, • RCC node on long-range forecasting. DWD/Germany has taken the responsibility of the RCC node on climate monitoring (RRC-CM). Further consortium members are Armstatehydromet/Armenia, Météo-France/France, KNMI/The Netherlands, RHMS/Serbia, and TSMS/Turkey. RCCs provide online access to their products and services to national meteorological and hydrological services and to other regional users. Vice versa, RCCs receive data, products, know-how and feedbacks from the meteorological services as a main source for regional information. By the same time, they provide regional data, products and feedbacks to Global Production Centres and Lead Centres for respective verification and product optimisation of the global-scale information. The RCC-CM will perform basic functions covering the domain of climate monitoring: • Annual and monthly climate diagnostic bulletins, • Monthly monitoring maps: global, RAVI, Eastern Mediterranean, South Caucasus, • Reference climatologies and trend maps, • RA VI climate monitoring WebPortal, • Climate watches, • Training; Research and Development (R&D). The poster shows the current stage of development of the RCC-CM by means of example products.

A Bayesian posterior predictive framework for weighting ensemble regional climate models

Directory of Open Access Journals (Sweden)

Y. Fan

2017-06-01

Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

Applicability of ranked Regional Climate Models (RCM) to assess the impact of climate change on Ganges: A case study.

Science.gov (United States)

Anand, Jatin; Devak, Manjula; Gosain, Ashvani Kumar; Khosa, Rakesh; Dhanya, Ct

2017-04-01

The negative impact of climate change is felt over wide range of spatial scales, ranging from small basins to large watershed area, which can possibly outweighs the benefits of natural water system. General Circulation Models (GCMs) has been widely used as an input to a hydrological models (HMs), to simulate different hydrological components of a river basin. However, the coarser scale of GCMs and spatio-temporal biases, restricted its use at finer resolution. If downscaled, adds one more level of uncertainty i.e., downscaling uncertainty together with model and scenario uncertainty. The outputs computed from Regional Climate Models (RCM) may aid the uncertainties arising from GCMs, as the RCMs are the miniatures of GCMs. However, the RCMs do have some inherent systematic biases, hence bias correction is a prerequisite process before it is fed to HMs. RCMs, together with the input from GCMs at later boundaries also takes topography of the area into account. Hence, RCMs need to be ranked a priori. In this study, impact of climate change on the Ganga basin, India, is assessed using the ranked RCMs. Firstly, bias correction of 14 RCM models are done using Quantile-Quantile mapping and Equidistant cumulative distribution method, for historic (1990-2004) and future scenario (2021-2100), respectively. The runoff simulations from Soil Water Assessment Tool (SWAT), for historic scenario is used for ranking of RCMs. Entropy and PROMETHEE-2 method is employed to rank the RCMs based on five performance indicators namely, Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), normalised root mean square error (NRMSE), absolute normalised mean bias error (ANMBE) and average absolute relative error (AARE). The results illustrated that each of the performance indicators behaves differently for different RCMs. RCA 4 (CNRM-CERFACS) is found as the best model with the highest value of  (0.85), followed by RCA4 (MIROC) and RCA4 (ICHEC) with  values of 0.80 and 0

Assessing climate change impacts on water resources in remote mountain regions

Science.gov (United States)

Buytaert, Wouter; De Bièvre, Bert

2013-04-01

From a water resources perspective, remote mountain regions are often considered as a basket case. They are often regions where poverty is often interlocked with multiple threats to water supply, data scarcity, and high uncertainties. In these environments, it is paramount to generate locally relevant knowledge about water resources and how they impact local livelihoods. This is often problematic. Existing environmental data collection tends to be geographically biased towards more densely populated regions, and prioritized towards strategic economic activities. Data may also be locked behind institutional and technological barriers. These issues create a "knowledge trap" for data-poor regions, which is especially acute in remote and hard-to-reach mountain regions. We present lessons learned from a decade of water resources research in remote mountain regions of the Andes, Africa and South Asia. We review the entire tool chain of assessing climate change impacts on water resources, including the interrogation and downscaling of global circulation models, translating climate variables in water availability and access, and assessing local vulnerability. In global circulation models, mountain regions often stand out as regions of high uncertainties and lack of agreement of future trends. This is partly a technical artifact because of the different resolution and representation of mountain topography, but it also highlights fundamental uncertainties in climate impacts on mountain climate. This problem also affects downscaling efforts, because regional climate models should be run in very high spatial resolution to resolve local gradients, which is computationally very expensive. At the same time statistical downscaling methods may fail to find significant relations between local climate properties and synoptic processes. Further uncertainties are introduced when downscaled climate variables such as precipitation and temperature are to be translated in hydrologically

Future directions in climate modeling: A climate impacts perspective

International Nuclear Information System (INIS)

Mearns, L.O.

1990-01-01

One of the most serious impediments to further progress on the determination of specific impacts of climate change on relevant earth systems is the lack of precise and accurate scenarios of regional change. Spatial resolution of models is generally coarse (5-10 degree, corresponding to 550-1,100 km), and the modeling of physical processes is quite crude. Three main areas in which improvements in the modeling of physical processes are being made are modeling of surface processes, modeling of oceans and coupling of oceans and atmospheric models, and modeling of clouds. Improvements are required in the modeling of surface hydrology and vegetative effects, which have significant impact on the albedo scheme used. Oceans are important in climate modeling for the following reasons: delay of warming due to oceanic heat absorption; effect of mean meridional circulation; control of regional patterns of sea surface temperatures and sea ice by wind driven currents; absorption of atmospheric carbon dioxide by the oceans; and determination of interannual climatic variability via variability in sea surface temperature. The effects of clouds on radiation balance is highly significant. Clouds both reflect shortwave radiation and trap longwave radiation. Most cloud properties are sub-grid scale and thus difficult to include explicitly in models. 25 refs., 1 tab

Global and regional health effects of future food production under climate change: a modelling study.

Science.gov (United States)

Springmann, Marco; Mason-D'Croz, Daniel; Robinson, Sherman; Garnett, Tara; Godfray, H Charles J; Gollin, Douglas; Rayner, Mike; Ballon, Paola; Scarborough, Peter

2016-05-07

One of the most important consequences of climate change could be its effects on agriculture. Although much research has focused on questions of food security, less has been devoted to assessing the wider health impacts of future changes in agricultural production. In this modelling study, we estimate excess mortality attributable to agriculturally mediated changes in dietary and weight-related risk factors by cause of death for 155 world regions in the year 2050. For this modelling study, we linked a detailed agricultural modelling framework, the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT), to a comparative risk assessment of changes in fruit and vegetable consumption, red meat consumption, and bodyweight for deaths from coronary heart disease, stroke, cancer, and an aggregate of other causes. We calculated the change in the number of deaths attributable to climate-related changes in weight and diets for the combination of four emissions pathways (a high emissions pathway, two medium emissions pathways, and a low emissions pathway) and three socioeconomic pathways (sustainable development, middle of the road, and more fragmented development), which each included six scenarios with variable climatic inputs. The model projects that by 2050, climate change will lead to per-person reductions of 3·2% (SD 0·4%) in global food availability, 4·0% (0·7%) in fruit and vegetable consumption, and 0·7% (0·1%) in red meat consumption. These changes will be associated with 529,000 climate-related deaths worldwide (95% CI 314,000-736,000), representing a 28% (95% CI 26-33) reduction in the number of deaths that would be avoided because of changes in dietary and weight-related risk factors between 2010 and 2050. Twice as many climate-related deaths were associated with reductions in fruit and vegetable consumption than with climate-related increases in the prevalence of underweight, and most climate-related deaths were projected to

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

Science.gov (United States)

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

2017-04-01

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

Regional climate response collaboratives: Multi-institutional support for climate resilience

Science.gov (United States)

Averyt, Kristen; Derner, Justin D.; Dilling, Lisa; Guerrero, Rafael; Joyce, Linda A.; McNeeley, Shannon; McNie, Elizabeth; Morisette, Jeffrey T.; Ojima, Dennis; O'Malley, Robin; Peck, Dannele; Ray, Andrea J.; Reeves, Matt; Travis, William

2018-01-01

Federal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally-supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable research that informs climate-related decisions for stakeholders and ultimately enhances climate resilience at regional scales.

Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model MAR forced by MIROC5

Science.gov (United States)

Lang, C.; Fettweis, X.; Erpicum, M.

2015-05-01

We have performed a future projection of the climate and surface mass balance (SMB) of Svalbard with the MAR (Modèle Atmosphérique Régional) regional climate model forced by MIROC5 (Model for Interdisciplinary Research on Climate), following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of melt around 2050, with a larger melt increase in the south compared to the north of the archipelago. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to a cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a stronger winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. By 2085, SMB is projected to become negative over all of Svalbard's glaciated regions, leading to the rapid degradation of the firn layer.

Spatio-temporal modelling of heat stress and climate change implications for the Murray dairy region, Australia

Science.gov (United States)

Nidumolu, Uday; Crimp, Steven; Gobbett, David; Laing, Alison; Howden, Mark; Little, Stephen

2014-08-01

The Murray dairy region produces approximately 1.85 billion litres of milk each year, representing about 20 % of Australia's total annual milk production. An ongoing production challenge in this region is the management of the impacts of heat stress during spring and summer. An increase in the frequency and severity of extreme temperature events due to climate change may result in additional heat stress and production losses. This paper assesses the changing nature of heat stress now, and into the future, using historical data and climate change projections for the region using the temperature humidity index (THI). Projected temperature and relative humidity changes from two global climate models (GCMs), CSIRO MK3.5 and CCR-MIROC-H, have been used to calculate THI values for 2025 and 2050, and summarized as mean occurrence of, and mean length of consecutive high heat stress periods. The future climate scenarios explored show that by 2025 an additional 12-15 days (compared to 1971 to 2000 baseline data) of moderate to severe heat stress are likely across much of the study region. By 2050, larger increases in severity and occurrence of heat stress are likely (i.e. an additional 31-42 moderate to severe heat stress days compared with baseline data). This increasing trend will have a negative impact on milk production among dairy cattle in the region. The results from this study provide useful insights on the trends in THI in the region. Dairy farmers and the dairy industry could use these results to devise and prioritise adaptation options to deal with projected increases in heat stress frequency and severity.

Analyzing Multidecadal Trends in Cloudiness Over the Subtropical Andes Mountains of South America Using a Regional Climate Model.

Science.gov (United States)

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.

Climate and chemistry effects of a regional scale nuclear conflict

OpenAIRE

Stenke A.; Hoyle C. R.; Luo B.; Rozanov E.; Groebner J.; Maag L.; Broennimann S.; Peter T.

2013-01-01

Previous studies have highlighted the severity of detrimental effects for life on Earth after an assumed regionally limited nuclear war. These effects are caused by climatic, chemical and radiative changes persisting for up to one decade. However, so far only a very limited number of climate model simulations have been performed, giving rise to the question how realistic previous computations have been. This study uses the coupled chemistry climate model (CCM) SOCOL, which belongs to a...

The regionalization of climate scenarios: towards impact studies

International Nuclear Information System (INIS)

Cariolle, D.

1999-01-01

This article describes the different types of climate numerical models and their use to obtain scenarios for climate change due to the greenhouse gas increase. Results from global or meso-scale models are given. They illustrate the existing ways of representing climatic conditions at global and regional scales. Combined with statistical approaches based for example on the techniques of analogues, their use gives a coherent strategy going from global scale numerical simulations to the study of impacts at a local scale. In the future the increase of computer power should allow a better description of the small processes and a wider range of impact studies on natural ecosystems and various economic sectors. The results of these studies will be very useful to define a coherent policy in response to observed or predicted climate changes. (author)

The Integration of Climate Science and Collaborative Processes in Building Regional Climate Resiliency in Southeast Florida

Science.gov (United States)

Jurado, J.

2016-12-01

Southeast Florida is widely recognized as one of the most vulnerable regions in the United States to the impacts of climate change, especially sea level rise. Dense urban populations, low land elevations, flat topography, complex shorelines and a porous geology all contribute to the region's challenges. Regional and local governments have been working collaboratively to address shared climate mitigation and adaptation concerns as part of the four-county Southeast Florida Regional Climate Change Compact (Compact). This partnership has emphasized, in part, the use of climate data and the development of advanced technical tools and visualizations to help inform decision-making, improve communications, and guide investments. Prominent work products have included regional vulnerability maps and assessments, a unified sea level rise projection for southeast Florida, the development and application of hydrologic models in scenario planning, interdisciplinary resilient redesign planning workshops, and the development of regional climate indicators. Key to the Compact's efforts has been the engagement and expertise of academic and agency partners, including a formal collaboration between the Florida Climate Institute and the Compact to improve research and project collaborations focused on southeast Florida. This presentation will focus on the collaborative processes and work products that have served to accelerate resiliency planning and investments in southeast Florida, with specific examples of how local governments are using these work products to modernize agency processes, and build support among residents and business leaders.

Regional climate projections for Northeast India: an appraisal from CORDEX South Asia experiment

Science.gov (United States)

Kumar, D.; Dimri, A. P.

2017-11-01

An appraisal of the recent changes in the present climate (1970-2005) followed by the possible future (2006-2100) changes in the climate has been carried out in the current study using the observations and regional climate model (REMO) over the Northeast Indian region. The regional climate model simulation has been used from the COordinated Regional climate Downscaling EXperiment (CORDEX) South Asia framework. A consistent warming for the winter (December, January, and February (DJF)) and post-monsoon (October and November (ON)) has been observed for the present climate especially in the northern and eastern parts of the region. The changes in the near future (2020-2049) and far future (2070-2099) temperature climatology suggest a rise in temperature by 3-8 °C across different representative concentration pathways (RCPs). The rate of long-term (1970-2099) increase in temperature has been found ranging between 0.01 and 0.07 °C/year across the region in the least emission (RCP2.6) to strongest emission (RCP8.5) scenarios. The daily mean precipitation statistics suggests an overall increasing trends of precipitation during the pre-monsoon (March, April, and May (MAM)) for the present across the region with a mixed trend in other seasons. A change in daily mean precipitation ranging from - 60% (during winter) to + 40% during post-monsoon has been projected by the model across different RCPs. RCP4.5 and RCP8.5 show a strong deficit in precipitation in the warmer climate across the region as compared to RCP2.6. This fact is also confirmed from the long-term trend of precipitation where a consistent decreasing trend dominates in the RCP4.5- and RCP8.5-simulated precipitations by the end of the twenty-first century. A large model bias in temperature and precipitation along with high amount of uncertainty is associated with the model simulations; thus, in order to use the projections, a more careful approach to improve the utility of downscaled product should be adopted.

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

Science.gov (United States)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

Near-surface wind pattern in regional climate projections over the broader Adriatic region

Science.gov (United States)

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

2017-04-01

The Adriatic region is characterized by the complex coastline, strong topographic gradients and specific wind regimes. This represents excellent test area for the latest generation of the regional climate models (RCMs) applied over the European domain. The most famous wind along the Adriatic coast is bora, which due to its strength, has a strong impact on all types of human activities in the Adriatic region. The typical bora wind is a severe gusty downslope flow perpendicular to the mountains. Besides bora, in the Adriatic region, typical winds are sirocco (mostly during the wintertime) and sea/land breezes (dominantly in the warm part of the year) as a part of the regional Mediterranean wind system. Thus, it is substantial to determine future changes in the wind filed characteristics (e.g., changes in strength and frequencies). The first step was the evaluation of a suite of ten EURO- and MED-CORDEX models (at 50 km and 12.5 km resolution), and two additional high resolution models from the Swiss Federal Institute of Technology in Zürich (ETHZ, at 12.5 km and 2.2. km resolution) in the present climate. These results provided a basis for the next step where wind field features, in an ensemble of RCMs forced by global climate models (GCMs) in historical and future runs are examined. Our aim is to determine the influence of the particular combination of RCMs and GCMs, horizontal resolution and emission scenario on the future changes in the near-surface wind field. The analysis reveals strong sensitivity of the simulated wind flow and its statistics to both season and location analyzed, to the horizontal resolution of the RCM and on the choice of the particular GCM that provides boundary conditions.

Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

Science.gov (United States)

Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

2012-12-01

We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical

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

Science.gov (United States)

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

Sensitivity of regional climate to global temperature and forcing

International Nuclear Information System (INIS)

Tebaldi, Claudia; O’Neill, Brian; Lamarque, Jean-François

2015-01-01

The sensitivity of regional climate to global average radiative forcing and temperature change is important for setting global climate policy targets and designing scenarios. Setting effective policy targets requires an understanding of the consequences exceeding them, even by small amounts, and the effective design of sets of scenarios requires the knowledge of how different emissions, concentrations, or forcing need to be in order to produce substantial differences in climate outcomes. Using an extensive database of climate model simulations, we quantify how differences in global average quantities relate to differences in both the spatial extent and magnitude of climate outcomes at regional (250–1250 km) scales. We show that differences of about 0.3 °C in global average temperature are required to generate statistically significant changes in regional annual average temperature over more than half of the Earth’s land surface. A global difference of 0.8 °C is necessary to produce regional warming over half the land surface that is not only significant but reaches at least 1 °C. As much as 2.5 to 3 °C is required for a statistically significant change in regional annual average precipitation that is equally pervasive. Global average temperature change provides a better metric than radiative forcing for indicating differences in regional climate outcomes due to the path dependency of the effects of radiative forcing. For example, a difference in radiative forcing of 0.5 W m −2 can produce statistically significant differences in regional temperature over an area that ranges between 30% and 85% of the land surface, depending on the forcing pathway. (letter)

Regional hydrological impacts of climate change: implications for water management in India

Directory of Open Access Journals (Sweden)

A. Mondal

2015-04-01

Full Text Available Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

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

Science.gov (United States)

Beranová, Romana; Kyselý, Jan; Hanel, Martin

2018-04-01

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

THE EVOLUTION OF ANNUAL MEAN TEMPERATURE AND PRECIPITATION QUANTITY VARIABILITY BASED ON ESTIMATED CHANGES BY THE REGIONAL CLIMATIC MODELS

Directory of Open Access Journals (Sweden)

Paula Furtună

2013-03-01

Full Text Available Climatic changes are representing one of the major challenges of our century, these being forcasted according to climate scenarios and models, which represent plausible and concrete images of future climatic conditions. The results of climate models comparison regarding future water resources and temperature regime trend can become a useful instrument for decision makers in choosing the most effective decisions regarding economic, social and ecologic levels. The aim of this article is the analysis of temperature and pluviometric variability at the closest grid point to Cluj-Napoca, based on data provided by six different regional climate models (RCMs. Analysed on 30 year periods (2001-2030,2031-2060 and 2061-2090, the mean temperature has an ascending general trend, with great varability between periods. The precipitation expressed trough percentage deviation shows a descending general trend, which is more emphazied during 2031-2060 and 2061-2090.

Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

International Nuclear Information System (INIS)

Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

2012-01-01

This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA and D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA and D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA and D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA and D dataset in the context of regional climate research in the Euro-Mediterranean region. (letter)

Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations

DEFF Research Database (Denmark)

Arnbjerg-Nielsen, Karsten; Leonardsen, L.; Madsen, Henrik

2015-01-01

Climate change adaptation studies on urban flooding are often based on a model chain approach from climate forcing scenarios to analysis of adaptation measures. Previous analyses of climate change impacts in Copenhagen, Denmark, were supplemented by 2 high-end scenario simulations. These include...... a regional climate model projection forced to a global temperature increase of 6 degrees C in 2100 as well as a projection based on a high radiative forcing scenario (RCP8.5). With these scenarios, projected impacts of extreme precipitation increase significantly. For extreme sea surges, the impacts do...... by almost 4 and 8 times the current EAD for the RCP8.5 and 6 degrees C scenario, respectively. For both hazards, business-as-usual is not a possible scenario, since even in the absence of policy-driven changes, significant autonomous adaptation is likely to occur. Copenhagen has developed an adaptation plan...

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

Energy Technology Data Exchange (ETDEWEB)

Brunsell, Nathaniel [Univ. of Kansas, Lawrence, KS (United States); Mechem, David [Univ. of Kansas, Lawrence, KS (United States); Ma, Chunsheng [Wichita State Univ., KS (United States)

2015-02-20

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive to alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the

Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS

Science.gov (United States)

Gianotti, R. L.; Zhang, D.; Eltahir, E. A.

2010-12-01

Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and

Regional air quality management aspects of climate change: impact of climate mitigation options on regional air emissions.

Science.gov (United States)

Rudokas, Jason; Miller, Paul J; Trail, Marcus A; Russell, Armistead G

2015-04-21

We investigate the projected impact of six climate mitigation scenarios on U.S. emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxides (NOX) associated with energy use in major sectors of the U.S. economy (commercial, residential, industrial, electricity generation, and transportation). We use the EPA U.S. 9-region national database with the MARKet Allocation energy system model to project emissions changes over the 2005 to 2050 time frame. The modeled scenarios are two carbon tax, two low carbon transportation, and two biomass fuel choice scenarios. In the lower carbon tax and both biomass fuel choice scenarios, SO2 and NOX achieve reductions largely through pre-existing rules and policies, with only relatively modest additional changes occurring from the climate mitigation measures. The higher carbon tax scenario projects greater declines in CO2 and SO2 relative to the 2050 reference case, but electricity sector NOX increases. This is a result of reduced investments in power plant NOX controls in earlier years in anticipation of accelerated coal power plant retirements, energy penalties associated with carbon capture systems, and shifting of NOX emissions in later years from power plants subject to a regional NOX cap to those in regions not subject to the cap.

A regional approach to climate adaptation in the Nile Basin

Directory of Open Access Journals (Sweden)

M. B. Butts

2016-10-01

Full Text Available The Nile Basin is one of the most important shared basins in Africa. Managing and developing the water resources within the basin must not only address different water uses but also the trade-off between developments upstream and water use downstream, often between different countries. Furthermore, decision-makers in the region need to evaluate and implement climate adaptation measures. Previous work has shown that the Nile flows can be highly sensitive to climate change and that there is considerable uncertainty in climate projections in the region with no clear consensus as to the direction of change. Modelling current and future changes in river runoff must address a number of challenges; including the large size of the basin, the relative scarcity of data, and the corresponding dramatic variety of climatic conditions and diversity in hydrological characteristics. In this paper, we present a methodology, to support climate adaptation on a regional scale, for assessing climate change impacts and adaptation potential for floods, droughts and water scarcity within the basin.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

Science.gov (United States)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

Science.gov (United States)

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Climate Prediction Center - Monitoring and Data - Regional Climate Maps:

Science.gov (United States)

National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site government Web resources and services. HOME > Monitoring and Data > U.S. Climate Data > ; Precipitation & Temperature > Regional Climate Maps: USA Menu Weekly 1-Month 3-Month 12-Month Weekly

Assessment of future extreme climate events over the Porto wine Region

Science.gov (United States)

Viceto, Carolina; Cardoso, Susana; Marta-Almeida, Martinho; Gorodetskaya, Irina; Rocha, Alfredo

2017-04-01

The Douro Demarcated Region (DDR) is a wine region, in the northern Portugal, recognized for the Porto wine, which is responsible for more than 60% of the total value of national wine exportations. Since the viticulture is highly dependent on weather/climate patterns, the global warming is expected to affect the areas suitable to the growth of a certain variety of grape, its production and quality. This highlights the need of regional studies that assess the future climate changes effects in the vineyard, which might allow an early adjustment. We explore future climate change in the DDR region using a high-resolution regional climate model for Weather Research and Forecasting (WRF) forced by the Max Planck Institute Earth System Model - low resolution (MPI-ESM-LR). Two future periods have been simulated using the emission scenario RCP8.5 - for the mid- (2046-2065) and late 21st century (2081-2100) - and compared to a reference period (1986-2005). The RCP8.5 is a "baseline" scenario without any climate mitigation and corresponds to the pathway with the highest greenhouse gas emissions compared to other scenarios developed by the Intergovernmental Panel for Climate Change. Our regional WRF implementation uses three online-nested domains with increasing resolution at a downscaling ratio of three. The coarser domain of 81-km resolution covers part of the North Atlantic Ocean and most of the Europe. The innermost 9-km horizontal resolution domain includes the Iberian Peninsula, a portion of Northern Africa and the adjacent part of the Atlantic Ocean and Mediterranean Sea. Our study uses this 9-km resolution domain and focuses on a confined area, which comprises the DDR. Such dynamical downscaling approach gives an advantage to assess climate effects on the DDR region, where the high horizontal resolution allows including effects of the oceanic coastline, local riverbeds and complex topography. The climatology of the DDR region determines the more suitable wine variety

Assessing the impact of climatic change in cold regions

Energy Technology Data Exchange (ETDEWEB)

Parry, M L; Carter, T R [eds.

1984-01-01

The report describes the use of models to predict the consequences of global warming in particular (cold) regions. The workshop focused on two related issues: (a) the current sensitivity of ecosystems and farming systems to climatic variability, and (b) the range of impacts likely for certain changes of climate. This report addresses four broad themes: (1) the nature of the research problem; (2) methods of evaluating sensitivity to climatic variability; (3) methods of measuring the impact of climate change; and (4) how these methods might be refined. (ACR)

Late Cenozoic climate and the phylogenetic structure of regional conifer floras worldwide

NARCIS (Netherlands)

Eiserhardt, W.L.; Borchsenius, F.; Sandel, B.; Kissling, W.D.; Svenning, J.-C.

2015-01-01

Aim Using conifers as a model system, we aim to test four hypotheses. H1: the processes that shape the phylogenetic structure of regional species assemblages depend on climate. H2: apparent effects of current climate can be equally well explained by past climate. H3: strong Quaternary climate

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

Science.gov (United States)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

Science.gov (United States)

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus

Directory of Open Access Journals (Sweden)

Farzin Shabani

2018-03-01

Full Text Available Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i regions with suitable non-climatic factors, and (ii regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF, together with six geographical conditioning factors (raster data layers, to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs, Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically

Regional Climate Change and Development of Public Health Decision Aids

Science.gov (United States)

Hegedus, A. M.; Darmenova, K.; Grant, F.; Kiley, H.; Higgins, G. J.; Apling, D.

2011-12-01

According to the World Heath Organization (WHO) climate change is a significant and emerging threat to public health, and changes the way we must look at protecting vulnerable populations. Worldwide, the occurrence of some diseases and other threats to human health depend predominantly on local climate patterns. Rising average temperatures, in combination with changing rainfall patterns and humidity levels, alter the lifecycle and regional distribution of certain disease-carrying vectors, such as mosquitoes, ticks and rodents. In addition, higher surface temperatures will bring heat waves and heat stress to urban regions worldwide and will likely increase heat-related health risks. A growing body of scientific evidence also suggests an increase in extreme weather events such as floods, droughts and hurricanes that can be destructive to human health and well-being. Therefore, climate adaptation and health decision aids are urgently needed by city planners and health officials to determine high risk areas, evaluate vulnerable populations and develop public health infrastructure and surveillance systems. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. WRF model is initialized with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model simulations forced with the Special Report on Emissions (SRES) A1B emissions scenario. Our methodology involves development of climatological indices of extreme weather, quantifying the risk of occurrence of water/rodent/vector-borne diseases as well as developing various heat stress related decision aids. Our results indicate that the downscale simulations provide the necessary

Developing climatic scenarios for pesticide fate modelling in Europe

International Nuclear Information System (INIS)

Blenkinsop, S.; Fowler, H.J.; Dubus, I.G.; Nolan, B.T.; Hollis, J.M.

2008-01-01

A climatic classification for Europe suitable for pesticide fate modelling was constructed using a 3-stage process involving the identification of key climatic variables, the extraction of the dominant modes of spatial variability in those variables and the use of k-means clustering to identify regions with similar climates. The procedure identified 16 coherent zones that reflect the variability of climate across Europe whilst maintaining a manageable number of zones for subsequent modelling studies. An analysis of basic climatic parameters for each zone demonstrates the success of the scheme in identifying distinct climatic regions. Objective criteria were used to identify one representative 26-year daily meteorological series from a European dataset for each zone. The representativeness of each series was then verified against the zonal classifications. These new FOOTPRINT climate zones provide a state-of-the-art objective classification of European climate complete with representative daily data that are suitable for use in pesticide fate modelling. - The FOOTPRINT climatic zones provide an objective climatic classification and daily climate series that may be used for the modelling of pesticide fate across Europe

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

Czech Academy of Sciences Publication Activity Database

Beranová, Romana; Kyselý, Jan; Hanel, M.

2018-01-01

Roč. 132, 1-2 (2018), s. 515-527 ISSN 0177-798X R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : sub-daily precipitation * regional climate models * extremes * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 2.640, year: 2016 https://link.springer.com/article/10.1007/s00704-017-2102-0

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

Science.gov (United States)

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

2003-12-01

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

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

Science.gov (United States)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

Regionální klimatický model ALARO-CLIMATE, validace experimentu s rozlišením 25 km

Czech Academy of Sciences Publication Activity Database

Pokorná, Lucie; Kliegrová, S.; Brožková, R.; Štěpánek, Petr; Skalák, Petr; Belda, M.; Farda, Aleš; Metelka, L.; Huth, Radan

2015-01-01

Roč. 68, č. 2 (2015), s. 33-43 ISSN 0026-1173 R&D Projects: GA ČR(CZ) GAP209/11/2405 Institutional support: RVO:68378289 ; RVO:67179843 Keywords : ALARO-Climate * regional climate model * precipitation * temperature * validation Subject RIV: DG - Athmosphere Sciences, Meteorology http://www.chmi.cz/files/portal/docs/reditel/SIS/casmz/2015_2.pdf

An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe

Science.gov (United States)

Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro

2018-04-01

Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

Energy Technology Data Exchange (ETDEWEB)

Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Cassano, John J. [Univ. of Colorado, Boulder, CO (United States); Gutowski, Jr., William J. [Iowa State Univ., Ames, IA (United States); Lipscomb, William H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nijssen, Bart [Univ. of Washington, Seattle, WA (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States). Dept. of Oceanography; Robertson, William [Univ. of Texas, El Paso, TX (United States); Tulaczyk, Slawek [Univ. of California, Santa Cruz, CA (United States); Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States)

2011-05-15

The primary outcome of the project was the development of the Regional Arctic System Model (RASM) and evaluation of its individual model components, coupling among them and fully coupled model results. Overall, we have demonstrated that RASM produces realistic mean and seasonal surface climate as well as its interannual and decadal variability and trends.

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

Science.gov (United States)

Qin, P.; Xie, Z.

2017-12-01

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

Improvement of snowpack simulations in a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Jin, J.; Miller, N.L.

2011-01-10

To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the

A statistical adjustment approach for climate projections of snow conditions in mountain regions using energy balance land surface models

Science.gov (United States)

Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu

2017-04-01

Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the

Regional Energy Demand Responses To Climate Change. Methodology And Application To The Commonwealth Of Massachusetts

International Nuclear Information System (INIS)

Amato, A.D.; Ruth, M.; Kirshen, P.; Horwitz, J.

2005-01-01

Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles. In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand