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Author: Marzia Tamanna Publisher: ISBN: Category : Climatic changes Languages : en Pages : 114
Book Description
"In order to make informed decisions in response to future climate change, researches, policy-makers, and the public need climate projections at the scale of few kilometers, rather than the scales provided by Global climate Models. The North American Regional Climate Change Assessment Program (NARCCAP) is such a recent effort that addresses this necessity. As the climate models contain various levels of uncertainty, it is essential to evaluate the performance of such models and their representativeness of regional climate characteristics. When assessing climate change impacts, precipitation is a crucial variable, due to its direct influence on many aspects of our natural-human ecosystems such as freshwater resources, agriculture and energy production, and health and infrastructure. The current study performs an evaluation analysis of precipitation simulations produced by a set of dynamically downscaled climate models provided by the NARCCAP program. The Assessment analysis is implemented for a period that covers 20 to 30 years (1970-1999), depending on joint availability of both the observational and the NARCCAP datasets. In addition to direct comparison versus observations, the hindcast NARCCAP simulations are used within a hydrologic modeling analysis for a regional ecosystem in coastal Louisiana (Chenier Plain). The study concludes the NARCCAP simulations have systematic biases in representing average precipitation amounts, but are successful at capturing some of the characteristics on spatial and temporal variability. The study also reveals the effect of precipitation on salinity concentrations in the Chenier Plain as a result of using different precipitation forcing fields. In the future, special efforts should be made to reduce biases in the NARCCAP simulations, which can then lead to a better presentation of regional climate scenarios for use by decision makers and resource managers." -Abstract.
Author: Marzia Tamanna Publisher: ISBN: Category : Climatic changes Languages : en Pages : 114
Book Description
"In order to make informed decisions in response to future climate change, researches, policy-makers, and the public need climate projections at the scale of few kilometers, rather than the scales provided by Global climate Models. The North American Regional Climate Change Assessment Program (NARCCAP) is such a recent effort that addresses this necessity. As the climate models contain various levels of uncertainty, it is essential to evaluate the performance of such models and their representativeness of regional climate characteristics. When assessing climate change impacts, precipitation is a crucial variable, due to its direct influence on many aspects of our natural-human ecosystems such as freshwater resources, agriculture and energy production, and health and infrastructure. The current study performs an evaluation analysis of precipitation simulations produced by a set of dynamically downscaled climate models provided by the NARCCAP program. The Assessment analysis is implemented for a period that covers 20 to 30 years (1970-1999), depending on joint availability of both the observational and the NARCCAP datasets. In addition to direct comparison versus observations, the hindcast NARCCAP simulations are used within a hydrologic modeling analysis for a regional ecosystem in coastal Louisiana (Chenier Plain). The study concludes the NARCCAP simulations have systematic biases in representing average precipitation amounts, but are successful at capturing some of the characteristics on spatial and temporal variability. The study also reveals the effect of precipitation on salinity concentrations in the Chenier Plain as a result of using different precipitation forcing fields. In the future, special efforts should be made to reduce biases in the NARCCAP simulations, which can then lead to a better presentation of regional climate scenarios for use by decision makers and resource managers." -Abstract.
Author: U.S. Department of the Interior Publisher: CreateSpace ISBN: 9781497353619 Category : Reference Languages : en Pages : 70
Book Description
We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs.
Author: Zhongqi Yu Publisher: ISBN: Category : Languages : en Pages :
Book Description
Global climate models (GCMs) are widely used to study climate change. Due to their coarse resolutions, GCMs cannot resolve some microscale and mesoscale processes such as topographical effects. Dynamic downscaling simulations using Regional Climate Models (RCMs) are often required to provide higher spatial- and temporal-resolution climate variabilities in specific regions. Uncertainties in dynamic downscaling simulations due to errors in the atmospheric state and models need to be understood first in the present climate simulations. Then the reliability for future projections can be inferred. This research contains three parts. The first part gives an assessment of temperature and precipitation over Ontario based on the North American Regional Climate Change Assessment Program (NARCCAP) RCM simulation data. In part two, five 8-year downscaling simulations using the Weather Research and Forecasting (WRF) model driven by five NARCCAP model data over Ontario are studied. Each of these simulation results and their mean are analyzed to address the dynamic downscaling effect on temperature and precipitation and their variabilities. Lastly in the third part, a 14-member perturbed ensemble simulation using the WRF model was conducted. The ensemble means of temperature and precipitation are evaluated and the uncertainties in regional climate modeling are discussed. The temperature and precipitation in seven NARCCAP RCM simulations from 1979 to 2004 are compared to the observations over Ontario. The observed annual area mean temperature has a remarkable rising trend in the late 1990s after decades of fluctuation. It is mainly due to a significant rise of winter area mean temperature during that period. This rising trend has been revealed in all seven models. For the annual area mean precipitation, the observed values fluctuate during this period, and the NARCCAP RCM model simulations show larger discrepancies. One focus of this thesis is to assess the impact of increased model resolution on regional climate simulations. Five NARCCAP RCM (MM5I, RCM3, HRM3, CRCM and WRFG) simulation data with 50-km horizontal resolution are downscaled to 10-km horizontal grid over Ontario to provide initial and boundary conditions for the WRF downscaling simulations in the period from 1991 to 1998. The model results show that the high resolution has great impact on regional climate simulations. Three sets of ensembles, the seven-member NARCCAP RCM simulations, the five-member WRF downscaling simulations, and a 14-member perturbed ensemble simulations using WRF model with the stochastic kinetic energy backscatter scheme are analyzed to assess the performance of the ensemble approach in regional climate simulations. The ensemble mean temperature and precipitation are compared to reanalysis data and the observations. The root mean square errors (RMSE) and the correlations are calculated. The results show that the ensemble method improves the accuracy of simulations, for both temperature and precipitation.
Author: Jean-Yves Djamen-Kepaou Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
"Global climate models represent major climate system components of the planet in order to generate long term, sparse, accurate realizations of future climatic events across the entire globe. Downscaling is the method by which these low resolution realizations are converted into high resolution simulations of climate events which can then be used by stakeholders and policy makers. Regional climate models dynamically downscale simulated climate by conditioning global climate models on location-specific physical processes. Although these models are robust and reliable, they are computationally expensive when compared to statistical approaches for modeling a general relationship between global climate behaviour and local climate behavior. Therefore, there is need for downscaling methods that leverage the computational efficiency of statistical models while maintaining the performance of regional climate models.In this thesis, we build upon previously proposed deep learning methods for dynamical downscaling through estimation of a regional climate model. Our proposed model is a generative adversarial network that leverages the effects of temporal dependencies within spatio-temporal climate events"--
Author: Rao Kotamarthi Publisher: Cambridge University Press ISBN: 1108587062 Category : Science Languages : en Pages : 213
Book Description
Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.
Author: Andrew Jason Halmstad Publisher: ISBN: Category : Climatic changes Languages : en Pages : 50
Book Description
One important aspect related to the management of water resources under future climate variation is the occurrence of extreme precipitation events. In order to prepare for extreme events, namely floods and droughts, it is important to understand how future climate variability will influence the occurrence of such events. Recent advancements in regional climate modeling efforts provide additional resources for investigating the occurrence of extreme events at scales that are appropriate for regional hydrologic modeling. This study utilizes data from three Regional Climate Models (RCMs), each driven by the same General Circulation Model (GCM) as well as a reanalysis dataset, all of which was made available by the North American Regional Climate Change Assessment Program (NARCCAP). A comparison between observed historical precipitation events and NARCCAP modeled historical conditions over Oregon's Willamette River basin was performed. This comparison is required in order to investigate the reliability of regional climate modeling efforts. Datasets representing future climate signal scenarios, also provided by NARCCAP, were then compared to historical data to provide an estimate of the variability in extreme event occurrence and severity within the basin. Analysis determining magnitudes of two, five, ten and twenty-five year return level estimates, as well as parameters corresponding to a representative Generalized Extreme Value (GEV) distribution, were determined. The results demonstrate the importance of the applied initial/boundary driving conditions, the need for multi-model ensemble analysis due to RCM variability, and the need for further downscaling and bias correction methods to RCM datasets when investigating watershed scale phenomena.
Author: Rasmus E. Benestad Publisher: World Scientific ISBN: 9812819126 Category : Science Languages : en Pages : 228
Book Description
Empirical-statistical downscaling (ESD) is a method for estimating how local climatic variables are affected by large-scale climatic conditions. ESD has been applied to local climate/weather studies for years, but there are few ? if any ? textbooks on the subject. It is also anticipated that ESD will become more important and commonplace in the future, as anthropogenic global warming proceeds. Thus, a textbook on ESD will be important for next-generation climate scientists.
Author: Rao Kotamarthi Publisher: Cambridge University Press ISBN: 110847375X Category : Nature Languages : en Pages : 213
Book Description
A practical guide to understanding, using and producing downscaled climate data, for researchers, graduate students, policy makers and practitioners.
Author: Publisher: ISBN: Category : Languages : en Pages : 19
Book Description
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.
Author: Marzia Tamanna
Author: Marzia Tamanna
Author: U.S. Department of the Interior
Author: Zhongqi Yu
Author: Jean-Yves Djamen-Kepaou
Author: Rao Kotamarthi
Author: Andrew Jason Halmstad
Author: S. W. Hostetler
Author: Rasmus E. Benestad
Author: Rao Kotamarthi
Author: