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

Regional Modeling of Dust Mass Balance and Radiative Forcing over East Asia using WRF-Chem

Energy Technology Data Exchange (ETDEWEB)

Chen, Siyu; Zhao, Chun; Qian, Yun; Leung, Lai-Yung R.; Huang, J.; Huang, Zhongwei; Bi, Jianrong; Zhang, Wu; Shi, Jinsen; Yang, Lei; Li, Deshuai; Li, Jinxin

2014-12-01

The Weather Research and Forecasting model with Chemistry (WRF-Chem) is used to investigate the seasonal and annual variations of mineral dust over East Asia during 2007-2011, with a focus on the dust mass balance and radiative forcing. A variety of measurements from in-stu and satellite observations have been used to evaluate simulation results. Generally, WRF-Chem reproduces not only the column variability but also the vertical profile and size distribution of mineral dust over and near the dust source regions of East Asia. We investigate the dust lifecycle and the factors that control the seasonal and spatial variations of dust mass balance and radiative forcing over the seven sub-regions of East Asia, i.e. source regions, the Tibetan Plateau, Northern China, Southern China, the ocean outflow region, and Korea-Japan regions. Results show that, over the source regions, transport and dry deposition are the two dominant sinks. Transport contributes to ~30% of the dust sink over the source regions. Dust results in a surface cooling of up to -14 and -10 W m-2, atmospheric warming of up to 20 and 15 W m-2, and TOA cooling of -5 and -8 W m-2 over the two major dust source regions of East Asia, respectively. Over the Tibetan Plateau, transport is the dominant source with a peak in summer. Over identified outflow regions, maximum dust mass loading in spring is contributed by the transport. Dry and wet depositions are the comparably dominant sinks, but wet deposition is larger than dry deposition over the Korea-Japan region, particularly in spring (70% versus 30%). The WRF-Chem simulations can generally capture the measured features of dust aerosols and its radaitve properties and dust mass balance over East Asia, which provides confidence for use in further investigation of dust impact on climate over East Asia.

Downscaling CESM1 climate change projections for the MENA-CORDEX domain using WRF

Science.gov (United States)

Zittis, George; Hadjinicolaou, Panos; Lelieveld, Jos

2017-04-01

According to analysis of observations and global climate model projections, the broader Middle East, North Africa and Mediterranean region is found to be a climate change hotspot. Substantial changes in precipitation amounts and patterns and strong summer warming (including an intensification of heat extremes) is a likely future scenario for the region, but a recent uncertainty analysis indicated good model agreement for temperature but much less for precipitation. Although the horizontal resolution of global models has increased over the last years, it is still not adequate for impact and adaptation assessments of regional or national level and further downscaling of the climate information is required. The region is now studied within the CORDEX initiative (Coordinated Regional Climate Downscaling Experiment) with the establishment of a domain covering the Middle East - North Africa (MENA-CORDEX) region (http://mena-cordex.cyi.ac.cy/). In this study, we present the first climate change projections for the MENA produced by dynamically downscaling a bias-corrected output of the CESM1 global earth system model. For the downscaling, we use a climate configuration of the Weather, Research and Forecasting model (WRF). Our simulations use a standard CORDEX Phase I 50-km grid in three simulations, a historical (1950-2005) and two scenario runs (2006-2100) with the greenhouse gas forcing following the RCP 4.5 and 8.5. We evaluate precipitation, temperature and other surface meteorological variables from the historical using gridded and station observational datasets. Maps of projected changes are constructed for different periods in the future as differences of the two scenarios model output against the data from the historical run. The main spatial and temporal patterns of change are discussed, especially in the context of the United Nations Framework Convention on Climate Change agreement in Paris to limit the global average temperature increase to 1.5 degrees above pre

Weather Research and Forecasting (WRF) Regional Atmospheric Model: CNMI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Commonwealth of the Northern...

Weather Research and Forecasting (WRF) Regional Atmospheric Model: Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the islands of Samoa at...

Weather Research and Forecasting (WRF) Regional Atmospheric Model: Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the island of Guam at...

WRF4G project: Adaptation of WRF Model to Distributed Computing Infrastructures

Science.gov (United States)

Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García Díez, Markel; Blanco Real, Jose C.; Fernández, Jesús

2013-04-01

Nowadays Grid Computing is powerful computational tool which is ready to be used for scientific community in different areas (such as biomedicine, astrophysics, climate, etc.). However, the use of this distributed computing infrastructures (DCI) is not yet common practice in climate research, and only a few teams and applications in this area take advantage of this infrastructure. Thus, the first objective of this project is to popularize the use of this technology in the atmospheric sciences area. In order to achieve this objective, one of the most used applications has been taken (WRF; a limited- area model, successor of the MM5 model), that has a user community formed by more than 8000 researchers worldwide. This community develop its research activity on different areas and could benefit from the advantages of Grid resources (case study simulations, regional hind-cast/forecast, sensitivity studies, etc.). The WRF model is been used as input by many energy and natural hazards community, therefore those community will also benefit. However, Grid infrastructures have some drawbacks for the execution of applications that make an intensive use of CPU and memory for a long period of time. This makes necessary to develop a specific framework (middleware). This middleware encapsulates the application and provides appropriate services for the monitoring and management of the jobs and the data. Thus, the second objective of the project consists on the development of a generic adaptation of WRF for Grid (WRF4G), to be distributed as open-source and to be integrated in the official WRF development cycle. The use of this WRF adaptation should be transparent and useful to face any of the previously described studies, and avoid any of the problems of the Grid infrastructure. Moreover it should simplify the access to the Grid infrastructures for the research teams, and also to free them from the technical and computational aspects of the use of the Grid. Finally, in order to

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.

An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

NARCIS (Netherlands)

Stegehuis, A.I.; Vautard, R.; Ciais, P.; Teuling, A.J.; Gonzalez Miralles, D.; Wild, M.

2015-01-01

Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface

Weather Research and Forecasting (WRF) Regional Atmospheric Model: Oahu

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 3.5-day hourly forecast for the region surrounding the Hawaiian island of Oahu at...

An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

NARCIS (Netherlands)

Stegehuis, A.I.; Vautard, R.; Ciais, P.; Teuling, A.J.; Miralles, D.G.; Wild, M.

2015-01-01

Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface

Spatiotemporal characteristics of heat waves over China in regional climate simulations within the CORDEX-EA project

Science.gov (United States)

Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang

2018-03-01

Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances.

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

Mean and extreme temperatures in a warming climate: EURO CORDEX and WRF regional climate high-resolution projections for Portugal

Science.gov (United States)

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

2018-02-01

Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8.5. An additional WRF simulation with even higher resolution (9 km) for RCP8.5 scenario is also examined. All simulations for the historical period (1971-2000) are evaluated against the available station observations and the EURO-CORDEX model results are ranked in order to build multi-model ensembles. In present climate models are able to reproduce the main topography/coast related temperature gradients. Although there are discernible differences between models, most present a cold bias. The multi-model ensembles improve the overall representation of the temperature. The ensembles project a significant increase of the maximum and minimum temperatures in all seasons and scenarios. Maximum increments of 8 °C in summer and autumn and between 2 and 4 °C in winter and spring are projected in RCP8.5. The temperature distributions for all models show a significant increase in the upper tails of the PDFs. In RCP8.5 more than half of the extended summer (MJJAS) has maximum temperatures exceeding the historical 90th percentile and, on average, 60 tropical nights are projected for the end of the century, whilst there are only 7 tropical nights in the historical period. Conversely, the number of cold days almost disappears. The yearly average number of heat waves increases by seven to ninefold by 2100 and the most frequent length rises from 5 to 22 days throughout the twenty-first century. 5% of the longest events will last for more than one month. The amplitude is overwhelming

Weather Research and Forecasting (WRF) Regional Atmospheric Model: Maui-Oahu

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Hawaiian islands of Oahu,...

High-resolution regional climate model evaluation using variable-resolution CESM over California

Science.gov (United States)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

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)

Influences of Regional Climate Change on Air Quality Across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations. Chapter 2

Science.gov (United States)

Nolte, Christopher; Otte, Tanya; Pinder, Robert; Bowden, J.; Herwehe, J.; Faluvegi, Gregory; Shindell, Drew

2013-01-01

Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture regional-scale changes in temperatures and precipitation. We use a regional climate model (RCM) to dynamically downscale the GCM's large-scale signal to investigate the changes in regional and local extremes of temperature and precipitation that may result from a changing climate. In this paper, we show preliminary results from downscaling the NASA/GISS ModelE IPCC AR5 Representative Concentration Pathway (RCP) 6.0 scenario. We use the Weather Research and Forecasting (WRF) model as the RCM to downscale decadal time slices (1995-2005 and 2025-2035) and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0. The regional climate change scenario is further processed using the Community Multiscale Air Quality modeling system to explore influences of regional climate change on air quality.

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.

Weather Research and Forecasting (WRF) Regional Atmospheric Model: Main Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Main Hawaiian Islands (MHI)...

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

Evaluation of the WRF model for precipitation downscaling on orographic complex islands

Science.gov (United States)

Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

2010-05-01

General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong

Evaluation of Optimized WRF Precipitation Forecast over a Complex Topography Region during Flood Season

Directory of Open Access Journals (Sweden)

Yuan Li

2016-11-01

Full Text Available In recent years, the Weather Research and Forecast (WRF model has been utilized to generate quantitative precipitation forecasts with higher spatial and temporal resolutions. However, factors including horizontal resolution, domain size, and the physical parameterization scheme have a strong impact on the dynamic downscaling ability of the WRF model. In this study, the influence of these factors has been analyzed in precipitation forecasting for the Xijiang Basin, southern China—a region with complex topography. The results indicate that higher horizontal resolutions always result in higher Critical Success Indexes (CSI, but higher biases as well. Meanwhile, the precipitation forecast skills are also influenced by the combination of microphysics parameterization scheme and cumulus convective parameterization scheme. On the basis of these results, an optimized configuration of the WRF model is built in which the horizontal resolution is 10 km, the microphysics parameterization is the Lin scheme, and the cumulus convective parameterization is the Betts–Miller–Janjic scheme. This configuration is then evaluated by simulating the daily weather during the 2013–2014 flood season. The high Critical Success Index scores and low biases at various thresholds and lead times confirm the high accuracy of the optimized WRF model configuration for Xijiang Basin. However, the performance of the WRF model varies from different sub-basins due to the complexity of the mesoscale convective system (MCS over this region.

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.

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.

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

Regional and urban downscaling of global climate scenarios for health impact assessments

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J.L.; Perez, L.; Gonzalez, R.M.; Pecci, J.; Garzon, A.; Palacios, M.

2015-07-01

In this contribution we have used global climate RCP IPCC scenarios to produce climate and air pollution maps at regional (25 km resolution) and urban scale with 200 m spatial resolution over Europe and five European cities in order to investigate the impact on meteorological variables and pollutant concentrations . We have used the very well known mesoscale meeorological model WRF-Chem (NOAA, US). We have used 2011 as control past year and two RCP scenarios from CCSM global climate model with 4.5 W/m2 and 8.5 W/m2 for 2030, 2050 and 2100 years. After running WRF-Chem model, using the boundary conditions provided by RCP scenarios with the emissions of 2011, we have performed a detailed downscaling process using CALMET diagnostic model to obtain a full 200 m spatial resolution map of five European cities (London, Antwerp, Madrid, Milan, and Helsinki). We will show the results and the health impacts for future RCP IPCC climate scenarios in comparison with the 2011 control year information for climate and health indicators. Finnally, we have also investigated the impact of the aerosol effects in the short wave radiation mean value. Two simulations with the WRF-Chem model have been performed over Europe in 2010. A baseline simulation without any feedback effects and a second simulation including the direct effects affecting the solar radiation reaching the surface as well as the indirect aerosol effect with potential impacts on increasing or decreasing the precipitation rates. Aerosol effects produce an increase of incoming radiation over Atlantic Ocean (up to 70%) because the prescribed aerosol concentrations in the WRF-Chem without feedbacks is substantially higher than the aerosol concentrations produced when we activate the feedback effects. The decrease in solar radiation in the Sahara area (10%) is found to be produced because the prescribed aerosol concentration in the {sup n}o feedback{sup s}imulation is lower than when we activate the feedback effects. (Author)

Numberical Calculations of Atmospheric Conditions over Tibetan Plateau by Using WRF Model

International Nuclear Information System (INIS)

Qian, Xuan; Yao, Yongqiang; Wang, Hongshuai; Liu, Liyong; Li, Junrong; Yin, Jia

2015-01-01

The wind field, precipitable water vapor are analyzed by using the mesoscale numerical model WRF over Tibetan Plateau, and the aerosol is analyzed by using WRF- CHEM model. The spatial and vertical distributions of the relevant atmospheric factors are summarized, providing truth evidence for selecting and further evaluating an astronomical site. It has been showed that this method could provide good evaluation of atmospheric conditions. This study serves as a further demonstration towards astro-climate regionalization, and provides with essential database for astronomical site survey over Tibetan Plateau. (paper)

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

Science.gov (United States)

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

2010-12-01

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

Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin

Directory of Open Access Journals (Sweden)

Xiaoduo Pan

2017-09-01

Full Text Available Individually, ground-based, in situ observations, remote sensing, and regional climate modeling cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrains. Data assimilation techniques can be used to bridge the gap between observations and models by assimilating ground observations and remote sensing products into models to improve precipitation simulation and forecasting. However, only a small portion of satellite-retrieved precipitation products assimilation research has been implemented over complex terrains in an arid region. Here, we used the weather research and forecasting (WRF model to assimilate two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM 3B42 and Fengyun-2D: FY-2D using the 4D-Var data assimilation method for a typical inland river basin in northwest China’s arid region, the Heihe River Basin, where terrains are very complex. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly over regions with complex terrains.

WRF high resolution dynamical downscaling of ERA-Interim for Portugal

Energy Technology Data Exchange (ETDEWEB)

Soares, Pedro M.M. [University of Lisbon, Instituto Dom Luiz, Lisbon (Portugal); Faculdade de Ciencias da Universidade de Lisboa, Lisbon (Portugal); Cardoso, Rita M.; Miranda, Pedro M.A.; Medeiros, Joana de [University of Lisbon, Instituto Dom Luiz, Lisbon (Portugal); Belo-Pereira, Margarida; Espirito-Santo, Fatima [Instituto de Meteorologia, Lisbon (Portugal)

2012-11-15

This study proposes a dynamically downscaled climatology of Portugal, produced by a high resolution (9 km) WRF simulation, forced by 20 years of ERA-Interim reanalysis (1989-2008), nested in an intermediate domain with 27 km of resolution. The Portuguese mainland is characterized by large precipitation gradients, with observed mean annual precipitation ranging from about 400 to over 2,200 mm, with a very wet northwest and rather dry southeast, largely explained by orographic processes. Model results are compared with all available stations with continuous records, comprising daily information in 32 stations for temperature and 308 for precipitation, through the computation of mean climatologies, standard statistical errors on daily to seasonally timescales, and distributions of extreme events. Results show that WRF at 9 km outperforms ERA-Interim in all analyzed variables, with good results in the representation of the annual cycles in each region. The biases of minimum and maximum temperature are reduced, with improvement of the description of temperature variability at the extreme range of its distribution. The largest gain of the high resolution simulations is visible in the rainiest regions of Portugal, where orographic enhancement is crucial. These improvements are striking in the high ranking percentiles in all seasons, describing extreme precipitation events. WRF results at 9 km compare favorably with published results supporting its use as a high-resolution regional climate model. This higher resolution allows a better representation of extreme events that are of major importance to develop mitigation/adaptation strategies by policy makers and downstream users of regional climate models in applications such as flash floods or heat waves. (orig.)

WRF-Hydro Simulated Spatiotemporal Characteristics of Streamflow Extremes over the CONUS during 1993-2016 and Possible Connections with Climate Variability

Science.gov (United States)

Dugger, A. L.; Zhang, Y.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L.; Rafieeinasab, A.; Sampson, K. M.; Salas, F.; Read, L.; Pan, L.; Yates, D. N.; Cosgrove, B.; Clark, E. P.

2017-12-01

Streamflow extremes (lows and peaks) tend to have disproportionately higher impacts on the human and natural systems compared to mean streamflow. Examining and understanding the spatiotemporal distributions of streamflow extremes is of significant interests to both the research community and the water resources management. In this work, the output from the 24-year (1993 through 2016) retrospective runs of the National Water Model (NWM) version of WRF-Hydro will be analyzed for streamflow extremes over the CONUS domain. The CONUS domain was configured at 1-km resolution for land surface grid and 250-m resolution for terrain routing. The WRF-Hydro runs were forced by the regridded and downscaled NLDAS2 data. The analyses focus on daily mean streamflow values over the full water year and within the summer and winter seasons. Connections between NWM streamflow and other hydrologic variables (e.g. snowpack, soil moisture/saturation and ET) with variations in large-scale climate phenomena, e.g., El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and North American monsoon are examined. The CONUS domain has a diverse environment and is characterized by complex terrain, heterogeneous land surfaces and ecosystems, and numerous hydrological basins. The potential dependence of streamflow extremes on regional terrain character, climatic conditions, and ecologic zones will also be investigated.

Quantifying the effects of LUCCs on local temperatures, precipitation, and wind using the WRF model.

Science.gov (United States)

Lian, Lishu; Li, Baofu; Chen, Yaning; Chu, Cuicui; Qin, Yanhua

2017-09-11

Land use/cover changes (LUCCs) are an important cause of regional climate changes, but the contribution of LUCCs to regional climate changes is not clear. In this study, the Weather Research and Forecasting (WRF) model and statistical methods were used to investigate changes in meteorologic variables in January, April, July, and October 2013 due to local LUCCs from 1990 to 2010 in southern Shandong province, China. The results indicate that the WRF model simulates temperatures in the region well, with high correlation coefficients (0.86-0.97, p wind speed and direction substantially during these four months: average wind speeds increased by 0.02 and 0.01 m/s in January and October, respectively, and decreased by 0.02 and 0.05 m/s in April and July, respectively. Overall, The LUCCs affected spring temperatures the least and summer precipitation the most.

Regional and urban down scaling of global climate scenarios for health impact assessments

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Garzon, A.; Palacios, M.

2015-07-01

In this contribution we have used global climate RCP IPCC scenarios to produce climate and air pollution maps at regional (25 km resolution) and urban scale with 200 m spatial resolution over Europe and five European cities in order to investigate the impact on meteorological variables and pollutant concentrations . We have used the very well known mesoscale meteorological model WRF-Chem (NOAA, US). We have used 2011 as control past year and two RCP scenarios from CCSM global climate model with 4.5 W/m2 and 8.5 W/m2 for 2030, 2050 and 2100 years. After running WRF-Chem model, using the boundary conditions provided by RCP scenarios with the emissions of 2011, we have performed a detailed down scaling process using CALMET diagnostic model to obtain a full 200 m spatial resolution map of five European cities (London, Antwerp, Madrid, Milan, and Helsinki). We will show the results and the health impacts for future RCP IPCC climate scenarios in comparison with the 2011 control year information for climate and health indicators. Finally, we have also investigated the impact of the aerosol effects in the short wave radiation mean value. Two simulations with the WRF-Chem model have been performed over Europe in 2010. A baseline simulation without any feedback effects and a second simulation including the direct effects affecting the solar radiation reaching the surface as well as the indirect aerosol effect with potential impacts on increasing or decreasing the precipitation rates. Aerosol effects produce an increase of incoming radiation over Atlantic Ocean (up to 70%) because the prescribed aerosol concentrations in the WRF-Chem without feedbacks is substantially higher than the aerosol concentrations produced when we activate the feedback effects. The decrease in solar radiation in the Sahara area (10%) is found to be produced because the prescribed aerosol concentration in the no feedback simulation is lower than when we activate the feedback effects. (Author)

Potential impacts on regional climate due to land degradation in the Guizhou Karst Plateau of China

International Nuclear Information System (INIS)

Gao, Jiangbo; Wu, Shaohong; Xue, Yongkang

2013-01-01

The possible regional climatic effects of land condition change in the Guizhou Karst Plateau (GKP), which has experienced serious Karst Rocky Desertification (KRD) in the past decades, were investigated in this study using the Weather Research and Forecasting (WRF) regional climate model. It was shown that when compared with validation datasets, the WRF showed a high ability to downscale NCEP-DOE Reanalysis-2, which provided the initial and lateral boundary conditions for WRF, especially for the precipitation simulation. After land degradation over the GKP, the net radiation and evaporation were reduced mainly within the desertification area, consistent with the reduction in rainfall and the increase in surface temperature there. The southwest monsoon flow from the Bay of Bengal was weakened over the adjacent area to the northeast, influencing the East Asian summer monsoon. Meanwhile, the weaker low-layer anti-cyclone and the stronger horizontal convergence enhanced vertical motion in the southeastern coastal areas. Furthermore, owing to the decreased surface heating in the degradation experiment, the lifting over the GKP and neighboring regions to the east was limited, which resulted in a reduced rainfall within the GKP and strengthened the ascending motion downstream over 114°–122° E. Such circulation differences favored an increase in moisture flux and clouds, thereby causing more precipitation in coastal areas of southeast China. (letter)

An Observation-base investigation of nudging in WRF for downscaling surface climate information to 12-km Grid Spacing

Science.gov (United States)

Previous research has demonstrated the ability to use the Weather Research and Forecast (WRF) model and contemporary dynamical downscaling methods to refine global climate modeling results to a horizontal resolution of 36 km. Environmental managers and urban planners have expre...

Updated vegetation information in high resolution WRF simulations

DEFF Research Database (Denmark)

Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.

2013-01-01

modify the energy distribution at the land surface. In weather and climate models it is important to represent the vegetation variability accurately to obtain reliable results. The weather research and forecasting (WRF) model uses green vegetation fraction (GVF) time series to represent vegetation...... seasonality. The GVF of each grid cell is additionally used to scale other parameters such as LAI, roughness, emissivity and albedo within predefined intervals. However, the default GYP used by WRF does not reflect recent climatic changes or change in management practices since it was derived more than 20...

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

Science.gov (United States)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

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.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

Science.gov (United States)

S. Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter Caldwell; K. Duan; Y. Zhang

2015-01-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model)...

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

Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies

Science.gov (United States)

Mu, Qing; Lammel, Gerhard; Gencarelli, Christian N.; Hedgecock, Ian M.; Chen, Ying; Přibylová, Petra; Teich, Monique; Zhang, Yuxuan; Zheng, Guangjie; van Pinxteren, Dominik; Zhang, Qiang; Herrmann, Hartmut; Shiraiwa, Manabu; Spichtinger, Peter; Su, Hang; Pöschl, Ulrich; Cheng, Yafang

2017-10-01

Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.

On the Dependence of Cloud Feedbacks on Physical Parameterizations in WRF Aquaplanet Simulations

Science.gov (United States)

Cesana, Grégory; Suselj, Kay; Brient, Florent

2017-10-01

We investigate the effects of physical parameterizations on cloud feedback uncertainty in response to climate change. For this purpose, we construct an ensemble of eight aquaplanet simulations using the Weather Research and Forecasting (WRF) model. In each WRF-derived simulation, we replace only one parameterization at a time while all other parameters remain identical. By doing so, we aim to (i) reproduce cloud feedback uncertainty from state-of-the-art climate models and (ii) understand how parametrizations impact cloud feedbacks. Our results demonstrate that this ensemble of WRF simulations, which differ only in physical parameterizations, replicates the range of cloud feedback uncertainty found in state-of-the-art climate models. We show that microphysics and convective parameterizations govern the magnitude and sign of cloud feedbacks, mostly due to tropical low-level clouds in subsidence regimes. Finally, this study highlights the advantages of using WRF to analyze cloud feedback mechanisms owing to its plug-and-play parameterization capability.

Impact of anthropogenic aerosols on regional climate change in Beijing, China

Science.gov (United States)

Zhao, B.; Liou, K. N.; He, C.; Lee, W. L.; Gu, Y.; Li, Q.; Leung, L. R.

2015-12-01

Anthropogenic aerosols affect regional climate significantly through radiative (direct and semi-direct) and indirect effects, but the magnitude of these effects over megacities are subject to large uncertainty. In this study, we evaluated the effects of anthropogenic aerosols on regional climate change in Beijing, China using the online-coupled Weather Research and Forecasting/Chemistry Model (WRF/Chem) with the Fu-Liou-Gu radiation scheme and a spatial resolution of 4km. We further updated this radiation scheme with a geometric-optics surface-wave (GOS) approach for the computation of light absorption and scattering by black carbon (BC) particles in which aggregation shape and internal mixing properties are accounted for. In addition, we incorporated in WRF/Chem a 3D radiative transfer parameterization in conjunction with high-resolution digital data for city buildings and landscape to improve the simulation of boundary-layer, surface solar fluxes and associated sensible/latent heat fluxes. Preliminary simulated meteorological parameters, fine particles (PM2.5) and their chemical components agree well with observational data in terms of both magnitude and spatio-temporal variations. The effects of anthropogenic aerosols, including BC, on radiative forcing, surface temperature, wind speed, humidity, cloud water path, and precipitation are quantified on the basis of simulation results. With several preliminary sensitivity runs, we found that meteorological parameters and aerosol radiative effects simulated with the incorporation of improved BC absorption and 3-D radiation parameterizations deviate substantially from simulation results using the conventional homogeneous/core-shell configuration for BC and the plane-parallel model for radiative transfer. Understanding of the aerosol effects on regional climate change over megacities must consider the complex shape and mixing state of aerosol aggregates and 3D radiative transfer effects over city landscape.

Differences between downscaling with spectral and grid nudging using WRF

Directory of Open Access Journals (Sweden)

P. Liu

2012-04-01

Full Text Available Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields and the small-scale features (from the RCMs has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF Model. The simulations are compared against the results with North America Regional Reanalysis (NARR data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

Joint atmospheric-terrestrial water balances for East Africa: a WRF-Hydro case study for the upper Tana River basin

Science.gov (United States)

Kerandi, Noah; Arnault, Joel; Laux, Patrick; Wagner, Sven; Kitheka, Johnson; Kunstmann, Harald

2018-02-01

For an improved understanding of the hydrometeorological conditions of the Tana River basin of Kenya, East Africa, its joint atmospheric-terrestrial water balances are investigated. This is achieved through the application of the Weather Research and Forecasting (WRF) and the fully coupled WRF-Hydro modeling system over the Mathioya-Sagana subcatchment (3279 km2) and its surroundings in the upper Tana River basin for 4 years (2011-2014). The model setup consists of an outer domain at 25 km (East Africa) and an inner one at 5-km (Mathioya-Sagana subcatchment) horizontal resolution. The WRF-Hydro inner domain is enhanced with hydrological routing at 500-m horizontal resolution. The results from the fully coupled modeling system are compared to those of the WRF-only model. The coupled WRF-Hydro slightly reduces precipitation, evapotranspiration, and the soil water storage but increases runoff. The total precipitation from March to May and October to December for WRF-only (974 mm/year) and coupled WRF-Hydro (940 mm/year) is closer to that derived from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data (989 mm/year) than from the TRMM (795 mm/year) precipitation product. The coupled WRF-Hydro-accumulated discharge (323 mm/year) is close to that observed (333 mm/year). However, the coupled WRF-Hydro underestimates the observed peak flows registering low but acceptable NSE (0.02) and RSR (0.99) at daily time step. The precipitation recycling and efficiency measures between WRF-only and coupled WRF-Hydro are very close and small. This suggests that most of precipitation in the region comes from moisture advection from the outside of the analysis domain, indicating a minor impact of potential land-precipitation feedback mechanisms in this case. The coupled WRF-Hydro nonetheless serves as a tool in quantifying the atmospheric-terrestrial water balance in this region.

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

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.

Evaluating hourly rainfall characteristics over the U.S. Great Plains in dynamically downscaled climate model simulations using NASA-Unified WRF

Science.gov (United States)

Lee, Huikyo; Waliser, Duane E.; Ferraro, Robert; Iguchi, Takamichi; Peters-Lidard, Christa D.; Tian, Baijun; Loikith, Paul C.; Wright, Daniel B.

2017-07-01

Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall characteristics simulated by the NASA-Unified Weather Research and Forecasting (NU-WRF) regional climate model at horizontal resolutions of 4, 12, and 24 km over the Great Plains of the United States. We also examined the sensitivity of the simulated precipitation to different spectral nudging approaches and the cumulus parameterizations. The rainfall characteristics in the observations and simulations were defined as an hourly diurnal cycle of precipitation and a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. We calculated a JPDF for each data set and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. Comparison of the diurnal precipitation cycles between observations and simulations does not reveal the added value of high-resolution simulations. However, the performance of NU-WRF simulations measured by the JPDF metric strongly depends on horizontal resolution. The simulation with the highest resolution of 4 km shows the best agreement with the observations in simulating duration and intensity of wet spells. Spectral nudging does not affect the JPDF significantly. The effect of cumulus parameterizations on the JPDFs is considerable but smaller than that of horizontal resolution. The simulations with lower resolutions of 12 and 24 km show reasonable agreement but only with the high-resolution observational data that are aggregated into coarse resolution and spatially averaged.

A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

Energy Technology Data Exchange (ETDEWEB)

Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.; Fast, Jerome D.; Chapman, Elaine G.; Liu, Ying

2015-01-01

A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have been implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they

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.

Burgundy regional climate change and its potential impact on grapevines

Energy Technology Data Exchange (ETDEWEB)

Xu, Yiwen [University of Burgundy, Center for Climate Research, UMR 5210 CNRS, Dijon (France); G.C. Rieber Climate Institute at the Nansen Environment and Remote Sensing Center, Bergen (Norway); Castel, Thierry [University of Burgundy, Center for Climate Research, UMR 5210 CNRS, Dijon (France); AgroSup, Department of Agriculture and Environment, Dijon (France); Richard, Yves; Cuccia, Cedric [University of Burgundy, Center for Climate Research, UMR 5210 CNRS, Dijon (France); Bois, Benjamin [University of Burgundy, Center for Climate Research, UMR 5210 CNRS, Dijon (France); IUVV, University of Burgundy, Dijon (France)

2012-10-15

ARPEGE general circulation model simulations were dynamically downscaled by The Weather Research and Forecasting Model (WRF) for the study of climate change and its impact on grapevine growth in Burgundy region in France by the mid twenty-first century. Two time periods were selected: 1970-1979 and 2031-2040. The WRF model driven by ERA-INTERIM reanalysis data was validated against in situ surface temperature observations. The daily maximum and minimum surface temperature (T{sub max} and T{sub min}) were simulated by the WRF model at 8 x 8 km horizontal resolution. The averaged daily T{sub max} for each month during 1970-1979 have good agreement with observations, the averaged daily T{sub min} have a warm bias about 1-2 K. The daily T{sub max} and T{sub min} for each month (domain averaged) during 2031-2040 show a general increase. The largest increment ({proportional_to}3 K) was found in summer. The smallest increments (<1 K) were found in spring and fall. The spatial distribution of temperature increment shows a strong meridional gradient, high in south in summer, reversing in winter. The resulting potential warming rate in summer is equivalent to 4.7 K/century under the IPCC A2 emission scenario. The dynamically downscaled T{sub max} and T{sub min} were used to simulate the grape (Pinot noir grape variety) flowering and veraison dates. For 2031-2040, the projected dates are 8 and 12 days earlier than those during 1970-1979, respectively. The simulated hot days increase more than 50% in the two principal grapevine regions. They show strong impact on Pinot noir development. (orig.)

Improving Regional Forecast by Assimilating Atmospheric InfraRed Sounder (AIRS) Profiles into WRF Model

Science.gov (United States)

Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.

2009-01-01

In data sparse regions, remotely-sensed observations can be used to improve analyses and produce improved forecasts. One such source comes from the Atmospheric InfraRed Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The purpose of this paper is to describe a procedure to optimally assimilate high resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background type, and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics. The AIRS thermodynamic profiles are derived from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators were used to select the highest quality temperature and moisture data for each profile location and pressure level. The analyses were then used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impacts of AIRS profiles on forecast were assessed against verifying NAM analyses and stage IV precipitation data.

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.

WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

Science.gov (United States)

Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

2014-05-01

Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are

Contribution of lateral terrestrial water flows to the regional hydrological cycle: A joint soil-atmospheric moisture tagging procedure with WRF-Hydro

Science.gov (United States)

Arnault, Joel; Wei, Jianhui; Zhang, Zhenyu; Wagner, Sven; Kunstmann, Harald

2017-04-01

Water resources management requires an accurate knowledge of the behavior of the regional hydrological cycle components, including precipitation, evapotranspiration, river discharge and soil water storage. Atmospheric models such as the Weather Research and Forecasting (WRF) model provide a tool to evaluate these components. The main drawback of these atmospheric models, however, is that the terrestrial segment of the hydrological cycle is reduced to vertical infiltration, and that lateral terrestrial water flows are neglected. Recent model developments have focused on coupled atmospheric-hydrological modeling systems, such as WRF-hydro, in order to take into account subsurface, overland and river flow. The aim of this study is to investigate the contribution of lateral terrestrial water flows to the regional hydrological cycle, with the help of a joint soil-atmospheric moisture tagging procedure. This procedure is the extended version of an existing atmospheric moisture tagging method developed in WRF and WRF-Hydro (Arnault et al. 2017). It is used to quantify the partitioning of precipitation into water stored in the soil, runoff, evapotranspiration, and potentially subsequent precipitation through regional recycling. An application to a high precipitation event on 23 June 2009 in the upper Danube river basin, Germany and Austria, is presented. Precipitating water during this day is tagged for the period 2009-2011. Its contribution to runoff and evapotranspiration decreases with time, but is still not negligible in the summer 2011. At the end of the study period, less than 5 % of the precipitating water on 23 June 2009 remains in the soil. The additionally resolved lateral terrestrial water flows in WRF-Hydro modify the partitioning between surface and underground runoff, in association with a slight increase of evapotranspiration and recycled precipitation. Reference: Arnault, J., R. Knoche, J. Wei, and H. Kunstmann (2016), Evaporation tagging and atmospheric

Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

Science.gov (United States)

Yahya, Khairunnisa; Glotfelty, Timothy; Wang, Kai; Zhang, Yang; Nenes, Athanasios

2017-06-01

Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem) version 3.7.1. The existing Volatility Basis Set (VBS) treatments for organic aerosol (OA) formation in WRF/Chem are improved by considering the following: the secondary OA (SOA) formation from semi-volatile primary organic aerosol (POA), a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010) are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex) campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05) and the VBS SOA module with semivolatile POA treatment, 25 % fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07) used, CB05 gives the best performance for surface ozone and PM2. 5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA) compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC) predictions (normalized mean biases from -40.8 % to a range of -34.6 to -27.7 %), with large differences between CB05-CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation parameterization based on the Fountoukis and Nenes

Impact of Desiccation of Aral Sea on the Regional Climate of Central Asia Using WRF Model

Science.gov (United States)

Sharma, Ashish; Huang, Huei-Ping; Zavialov, Peter; Khan, Valentina

2018-01-01

This study explores the impacts of the desiccation of the Aral Sea and large-scale climate change on the regional climate of Central Asia in the post-1960 era. A series of climate downscaling experiments for the 1960's and 2000's decades were performed using the Weather Research and Forecast model at 12-km horizontal resolution. To quantify the impacts of the changing surface boundary condition, a set of simulations with an identical lateral boundary condition but different extents of the Aral Sea were performed. It was found that the desiccation of the Aral Sea leads to more snow (and less rain) as desiccated winter surface is relatively much colder than water surface. In summer, desiccation led to substantial warming over the Aral Sea. These impacts were largely confined to within the area covered by the former Aral Sea and its immediate vicinity, although desiccation of the Sea also led to minor cooling over the greater Central Asia in winter. A contrasting set of simulations with an identical surface boundary condition but different lateral boundary conditions produced more identifiable changes in regional climate over the greater Central Asia which was characterized by a warming trend in both winter and summer. Simulations also showed that while the desiccation of the Aral Sea has significant impacts on the local climate over the Sea, the climate over the greater Central Asia on inter-decadal time scale was more strongly influenced by the continental or global-scale climate change on that time scale.

Air Quality Modeling for the Urban Jackson, Mississippi Region Using a High Resolution WRF/Chem Model

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Shelton J. Swanier

2011-06-01

Full Text Available In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi region using an online WRF/Chem (Weather Research and Forecasting–Chemistry model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators.

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

"Application, evaluation and sensitivity analysis of the coupled WRF-CMAQ system from regional to urban scales"

Science.gov (United States)

Appel, W.; Gilliam, R. C.; Mathur, R.; Roselle, S. J.; Pleim, J. E.; Hogrefe, C.; Pouliot, G.

2017-12-01

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science chemical transport model (CTM) capable of simulating the emission, transport and fate of numerous air pollutants. Similarly, the Weather Research and Forecasting (WRF) model is a state-of-the-science meteorological model capable of simulating meteorology at many scales (e.g. global to urban). The coupled WRF-CMAQ system integrates these two models in a "two-way" configuration which allows feedback effects between the chemical (e.g. aerosols) and physical (e.g. solar radiation) states of the atmosphere. In addition, the coupled modeling system allows for more frequent communication between the CTM and meteorological model than is typically done in uncoupled WRF-CMAQ simulations. The goal of this modeling exercise is to assess the ability of the coupled WRF-CMAQ system at fine-scales (e.g. 4km to 1km) through comparison with high space and time resolution field measurements, and comparing those results to the traditional regional scale (e.g. 12km) simulation. This work will specifically examine several fine-scale simulations over the Eastern United States and the Baltimore, MD/Washington D.C. region for 2011, with special emphasis on the period of the DISCOVERAQ field campaign. In addition to evaluating the model performance at the various scales, the impact of the more frequent time coupling of the CTM and meteorology, aerosol feedback effects and lightning generated NO at the finer spatial resolutions will be assessed. The effect of simulating sub-grid clouds using several different options (i.e. explicit, parameterized or assimilated) will also be examined, since clouds are particularly important as they can have a large impact on both the meteorology (beyond the clouds themselves) and air quality, and are notoriously difficult to simulate accurately.

The 2010 Pakistan floods: high-resolution simulations with the WRF model

Science.gov (United States)

Viterbo, Francesca; Parodi, Antonio; Molini, Luca; Provenzale, Antonello; von Hardenberg, Jost; Palazzi, Elisa

2013-04-01

Estimating current and future water resources in high mountain regions with complex orography is a difficult but crucial task. In particular, the French-Italian project PAPRIKA is focused on two specific regions in the Hindu-Kush -- Himalaya -- Karakorum (HKKH)region: the Shigar basin in Pakistan, at the feet of K2, and the Khumbu valley in Nepal, at the feet of Mount Everest. In this framework, we use the WRF model to simulate precipitation and meteorological conditions with high resolution in areas with extreme orographic slopes, comparing the model output with station and satellite data. Once validated the model, we shall run a set of three future time-slices at very high spatial resolution, in the periods 2046-2050, 2071-2075 and 2096-2100, nested in different climate change scenarios (EXtreme PREcipitation and Hydrological climate Scenario Simulations -EXPRESS-Hydro project). As a prelude to this study, here we discuss the simulation of specific, high-intensity rainfall events in this area. In this paper we focus on the 2010 Pakistan floods which began in late July 2010, producing heavy monsoon rains in the Khyber Pakhtunkhwa, Sindh, Punjab and Balochistan regions of Pakistan and affecting the Indus River basin. Approximately one-fifth of Pakistan's total land area was underwater, with a death toll of about 2000 people. This event has been simulated with the WRF model (version 3.3.) in cloud-permitting mode (d01 14 km and d02 3.5 km): different convective closures and microphysics parameterization have been used. A deeper understanding of the processes responsible for this event has been gained through comparison with rainfall depth observations, radiosounding data and geostationary/polar satellite images.

WRF and WRF-Chem v3.5.1 simulations of meteorology and black carbon concentrations in the Kathmandu Valley

Directory of Open Access Journals (Sweden)

A. Mues

2018-06-01

Full Text Available An evaluation of the meteorology simulated using the Weather Research and Forecast (WRF model for the region of south Asia and Nepal with a focus on the Kathmandu Valley is presented. A particular focus of the model evaluation is placed on meteorological parameters that are highly relevant to air quality such as wind speed and direction, boundary layer height and precipitation. The same model setup is then used for simulations with WRF including chemistry and aerosols (WRF-Chem. A WRF-Chem simulation has been performed using the state-of-the-art emission database, EDGAR HTAP v2.2, which is the Emission Database for Global Atmospheric Research of the Joint Research Centre (JRC of the European Commission, in cooperation with the Task Force on Hemispheric Transport of Air Pollution (TF HTAP organized by the United Nations Economic Commission for Europe, along with a sensitivity simulation using observation-based black carbon emission fluxes for the Kathmandu Valley. The WRF-Chem simulations are analyzed in comparison to black carbon measurements in the valley and to each other.The evaluation of the WRF simulation with a horizontal resolution of 3×3 km2 shows that the model is often able to capture important meteorological parameters inside the Kathmandu Valley and the results for most meteorological parameters are well within the range of biases found in other WRF studies especially in mountain areas. But the evaluation results also clearly highlight the difficulties of capturing meteorological parameters in such complex terrain and reproducing subgrid-scale processes with a horizontal resolution of 3×3 km2. The measured black carbon concentrations are typically systematically and strongly underestimated by WRF-Chem. A sensitivity study with improved emissions in the Kathmandu Valley shows significantly reduced biases but also underlines several limitations of such corrections. Further improvements of the model and of the emission data are

High-resolution dynamical downscaling of re-analysis data over the Kerguelen Islands using the WRF model

Science.gov (United States)

Fonseca, Ricardo; Martín-Torres, Javier

2018-03-01

We have used the Weather Research and Forecasting (WRF) model to simulate the climate of the Kerguelen Islands (49° S, 69° E) and investigate its inter-annual variability. Here, we have dynamically downscaled 30 years of the Climate Forecast System Reanalysis (CFSR) over these islands at 3-km horizontal resolution. The model output is found to agree well with the station and radiosonde data at the Port-aux-Français station, the only location in the islands for which observational data is available. An analysis of the seasonal mean WRF data showed a general increase in precipitation and decrease in temperature with elevation. The largest seasonal rainfall amounts occur at the highest elevations of the Cook Ice Cap in winter where the summer mean temperature is around 0 °C. Five modes of variability are considered: conventional and Modoki El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Subtropical IOD (SIOD) and Southern Annular Mode (SAM). It is concluded that a key mechanism by which these modes impact the local climate is through interaction with the diurnal cycle in particular in the summer season when it has a larger magnitude. One of the most affected regions is the area just to the east of the Cook Ice Cap extending into the lower elevations between the Gallieni and Courbet Peninsulas. The WRF simulation shows that despite the small annual variability, the atmospheric flow in the Kerguelen Islands is rather complex which may also be the case for the other islands located in the Southern Hemisphere at similar latitudes.

The Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: A Case Study over the Continental U.S. using the GISS-ModelE2 and WRF Models

Science.gov (United States)

Racherla, P. N.; Shindell, D. T.; Faluvegi, G. S.

2012-01-01

Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

PREDIKSI SEBARAN ASAP KEBAKARAN HUTAN/LAHAN MENGGUNAKAN WRF/CHEM (Studi Kasus: Tanggal 14 dan 20 Juni 2012, Pekanbaru-Riau

Directory of Open Access Journals (Sweden)

Eko Heriyanto

2015-01-01

Full Text Available Penelitian ini bertujuan mengembangkan prediksi sebaran asap kebakaran hutan/lahan di wilayah Indonesia. Simulasi prediksi sebaran  asap (hindcast menggunakan model Weather Research and Forecasting with CHEMistry (WRF/CHEM pada kasus kebakaran hutan/lahan tanggal 14 dan 20 Juni 2012 di wilayah Pekanbaru-Riau. Dalam penelitian ini digunakan data luaran WRF resolusi 25 km dan emisi global . Hasil simulasi  konsentrasi Carbon Monoxide (CO luaran WRF/CHEM menggambarkan pola yang identik dengan hasil luaran Monitoring Atmospheric Composition and Climate (MACC-Reanalysis 1.10. Dilakukan juga analisis kualitatif terhadap hasil simulasi kedua model dengan citra satelit Aqua-Terra MODIS, NOAA-18, dan total column CO Atmospheric Infrared Sounder (AIRS dari NASA. Korelasi simulasi kedua model menunjukkan nilai yang baik antara 0.55 – 0.83. Secara umum dapat disimpulkan bahwa WRF/CHEM mampu mensimulasikan sebaran asap kebakaran hutan/lahan secara akurat. Hasil penelitian ini bisa menjadi salah satu langkah awal dalam pengembangan sistem peringatan dini sebaran asap kebakaran hutan/lahan di wilayah Indonesia.   This study aims to develop a predictive distribution of forest fire smoke/land in the territory of Indonesia. The simulation of smoke spread prediction (hindcast is using the Weather Research and Forecasting Model with CHEMistry (WRF/CHEM in the case of forest fires/land dated June 14, 2012 in Pekanbaru-Riau region. This study uses the WRF data output resolution 25 km and global emissions. Carbon Monoxide concentration simulation results (CO which is the WRF/CHEM output describes patterns that are identical to the results of Monitoring Atmospheric Composition and Climate (MACC-Reanalysis 1.1250 outcomes. a qualitative analysis of the results of the both simulation models with satellite imagery MODIS Aqua-Terra,NOAA-18 and the Total column CO Atmospheric Infrared Sounder (Airs from NASA has  been conducted as well. Both simulation models show a

Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas

Science.gov (United States)

Karki, Ramchandra; Hasson, Shabeh ul; Gerlitz, Lars; Schickhoff, Udo; Scholten, Thomas; Böhner, Jürgen

2017-07-01

Mesoscale dynamical refinements of global climate models or atmospheric reanalysis have shown their potential to resolve intricate atmospheric processes, their land surface interactions, and subsequently, realistic distribution of climatic fields in complex terrains. Given that such potential is yet to be explored within the central Himalayan region of Nepal, we investigate the skill of the Weather Research and Forecasting (WRF) model with different spatial resolutions in reproducing the spatial, seasonal, and diurnal characteristics of the near-surface air temperature and precipitation as well as the spatial shifts in the diurnal monsoonal precipitation peak over the Khumbu (Everest), Rolwaling, and adjacent southern areas. Therefore, the ERA-Interim (0.75°) reanalysis has been dynamically refined to 25, 5, and 1 km (D1, D2, and D3) for one complete hydrological year (October 2014-September 2015), using the one-way nested WRF model run with mild nudging and parameterized convection for the outer but explicitly resolved convection for the inner domains. Our results suggest that D3 realistically reproduces the monsoonal precipitation, as compared to its underestimation by D1 but overestimation by D2. All three resolutions, however, overestimate precipitation from the westerly disturbances, owing to simulating anomalously higher intensity of few intermittent events. Temperatures are generally reproduced well by all resolutions; however, winter and pre-monsoon seasons feature a high cold bias for high elevations while lower elevations show a simultaneous warm bias. Unlike higher resolutions, D1 fails to realistically reproduce the regional-scale nocturnal monsoonal peak precipitation observed in the Himalayan foothills and its diurnal shift towards high elevations, whereas D2 resolves these characteristics but exhibits a limited skill in reproducing such a peak on the river valley scale due to the limited representation of the narrow valleys at 5 km resolution

Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas

Directory of Open Access Journals (Sweden)

R. Karki

2017-07-01

Full Text Available Mesoscale dynamical refinements of global climate models or atmospheric reanalysis have shown their potential to resolve intricate atmospheric processes, their land surface interactions, and subsequently, realistic distribution of climatic fields in complex terrains. Given that such potential is yet to be explored within the central Himalayan region of Nepal, we investigate the skill of the Weather Research and Forecasting (WRF model with different spatial resolutions in reproducing the spatial, seasonal, and diurnal characteristics of the near-surface air temperature and precipitation as well as the spatial shifts in the diurnal monsoonal precipitation peak over the Khumbu (Everest, Rolwaling, and adjacent southern areas. Therefore, the ERA-Interim (0.75° reanalysis has been dynamically refined to 25, 5, and 1 km (D1, D2, and D3 for one complete hydrological year (October 2014–September 2015, using the one-way nested WRF model run with mild nudging and parameterized convection for the outer but explicitly resolved convection for the inner domains. Our results suggest that D3 realistically reproduces the monsoonal precipitation, as compared to its underestimation by D1 but overestimation by D2. All three resolutions, however, overestimate precipitation from the westerly disturbances, owing to simulating anomalously higher intensity of few intermittent events. Temperatures are generally reproduced well by all resolutions; however, winter and pre-monsoon seasons feature a high cold bias for high elevations while lower elevations show a simultaneous warm bias. Unlike higher resolutions, D1 fails to realistically reproduce the regional-scale nocturnal monsoonal peak precipitation observed in the Himalayan foothills and its diurnal shift towards high elevations, whereas D2 resolves these characteristics but exhibits a limited skill in reproducing such a peak on the river valley scale due to the limited representation of the narrow valleys at 5

A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations

Energy Technology Data Exchange (ETDEWEB)

Wiersema, David John [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of California, Berkeley, CA (United States); Lundquist, Katherine A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chow, Fotini Katapodes [Univ. of California, Berkeley, CA (United States)

2016-09-29

With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscale simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.

Application of WRF - SWAT OpenMI 2.0 based models integration for real time hydrological modelling and forecasting

Science.gov (United States)

Bugaets, Andrey; Gonchukov, Leonid

2014-05-01

Intake of deterministic distributed hydrological models into operational water management requires intensive collection and inputting of spatial distributed climatic information in a timely manner that is both time consuming and laborious. The lead time of the data pre-processing stage could be essentially reduced by coupling of hydrological and numerical weather prediction models. This is especially important for the regions such as the South of the Russian Far East where its geographical position combined with a monsoon climate affected by typhoons and extreme heavy rains caused rapid rising of the mountain rivers water level and led to the flash flooding and enormous damage. The objective of this study is development of end-to-end workflow that executes, in a loosely coupled mode, an integrated modeling system comprised of Weather Research and Forecast (WRF) atmospheric model and Soil and Water Assessment Tool (SWAT 2012) hydrological model using OpenMI 2.0 and web-service technologies. Migration SWAT into OpenMI compliant involves reorganization of the model into a separate initialization, performing timestep and finalization functions that can be accessed from outside. To save SWAT normal behavior, the source code was separated from OpenMI-specific implementation into the static library. Modified code was assembled into dynamic library and wrapped into C# class implemented the OpenMI ILinkableComponent interface. Development of WRF OpenMI-compliant component based on the idea of the wrapping web-service clients into a linkable component and seamlessly access to output netCDF files without actual models connection. The weather state variables (precipitation, wind, solar radiation, air temperature and relative humidity) are processed by automatic input selection algorithm to single out the most relevant values used by SWAT model to yield climatic data at the subbasin scale. Spatial interpolation between the WRF regular grid and SWAT subbasins centroid (which are

Assessing the Impact of Oil and Natural Gas Activities on Regional Air Quality in the Colorado Northern Front Range using WRF-Chem

Science.gov (United States)

Abdioskouei, M.; Carmichael, G. R.

2017-12-01

Recent increases in the Natural Gas (NG) production through hydraulic fracturing have questioned the climate benefit of switching from coal-fired to natural gas-fired power plants. Higher than expected levels of methane, VOCs, and NOx have been observed in areas close to oil and NG (OnG) operation facilities. High uncertainty in the OnG emission inventories and methane budget challenge the assessment of OnG impact on air quality and climate and consequently development of effective mitigation policies and control regulations. In this work, we focus on reducing the uncertainties around the OnG emissions by using high resolution (4x4 km2) WRF-Chem simulations coupled with detailed observation from the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ 2014) field campaign. First, we identified the optimal WRF-Chem configurations in the NFR area. We compared the performance of local and non-local Planetary Boundary Layer (PBL) schemes in predicting the PBL height and vertical mixing in the domain. We evaluated the impact of different meteorological and chemical initial and boundary conditions on the model performance. Next, simulations based on optimal configurations were used to assess the performance of the emission inventory (NEI-2011v2). To evaluate the impact of OnG emission on regional air quality and performance of NEI-2011 we tested the sensitivity of the model to the OnG emission. Comparison between simulated values and ground-based and airborne measurements shows a low bias of OnG emission in NEI-2011. Finally, inverse modeling techniques based on emission sensitivity simulations are being used to optimal scaling the OnG emission from the NEI-2011.

Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

Directory of Open Access Journals (Sweden)

K. Yahya

2017-06-01

Full Text Available Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem version 3.7.1. The existing Volatility Basis Set (VBS treatments for organic aerosol (OA formation in WRF/Chem are improved by considering the following: the secondary OA (SOA formation from semi-volatile primary organic aerosol (POA, a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010 are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05 and the VBS SOA module with semivolatile POA treatment, 25 % fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07 used, CB05 gives the best performance for surface ozone and PM2. 5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC predictions (normalized mean biases from −40.8 % to a range of −34.6 to −27.7 %, with large differences between CB05–CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation

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.

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

. Specifics of the importance of the scientific methodology e.g. RCM ensemble modeling (using OLAM, RAMS and WRF); combining RCM runs with agriculture modeling system (specifically APSIM); bringing different RCM setups to as close as possible common framework, etc., and important science results (e.g. the significance of Gulf of CA SST for precipitation over dry regions; the AR landfall impacts on precipitation; etc.) are described in our work. We emphasize that the methodology is significant in order to advance the state of the art climate change impacts at regional levels; and to implement our methodology for realistic impact analysis on the natural and managed (agriculture) ecosystems, beyond the SW US.

An evaluation of the performance of a WRF multi-physics ensemble for heatwave events over the city of Melbourne in southeast Australia

Science.gov (United States)

Imran, H. M.; Kala, J.; Ng, A. W. M.; Muthukumaran, S.

2018-04-01

Appropriate choice of physics options among many physics parameterizations is important when using the Weather Research and Forecasting (WRF) model. The responses of different physics parameterizations of the WRF model may vary due to geographical locations, the application of interest, and the temporal and spatial scales being investigated. Several studies have evaluated the performance of the WRF model in simulating the mean climate and extreme rainfall events for various regions in Australia. However, no study has explicitly evaluated the sensitivity of the WRF model in simulating heatwaves. Therefore, this study evaluates the performance of a WRF multi-physics ensemble that comprises 27 model configurations for a series of heatwave events in Melbourne, Australia. Unlike most previous studies, we not only evaluate temperature, but also wind speed and relative humidity, which are key factors influencing heatwave dynamics. No specific ensemble member for all events explicitly showed the best performance, for all the variables, considering all evaluation metrics. This study also found that the choice of planetary boundary layer (PBL) scheme had largest influence, the radiation scheme had moderate influence, and the microphysics scheme had the least influence on temperature simulations. The PBL and microphysics schemes were found to be more sensitive than the radiation scheme for wind speed and relative humidity. Additionally, the study tested the role of Urban Canopy Model (UCM) and three Land Surface Models (LSMs). Although the UCM did not play significant role, the Noah-LSM showed better performance than the CLM4 and NOAH-MP LSMs in simulating the heatwave events. The study finally identifies an optimal configuration of WRF that will be a useful modelling tool for further investigations of heatwaves in Melbourne. Although our results are invariably region-specific, our results will be useful to WRF users investigating heatwave dynamics elsewhere.

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.

Analysis of climate change indices in relation to wine production: A case study in the Douro region (Portugal

Directory of Open Access Journals (Sweden)

Blanco-Ward Daniel

2017-01-01

Full Text Available Climate change is of major relevance to wine production as most of the wine-growing regions of the world, in particular the Douro region, are located within relatively narrow latitudinal bands with average growing season temperatures limited to 13–21°C. This study focuses on the incidence of climate variables and indices that are relevant both for climate change detection and for grape production with particular emphasis on extreme events (e.g. cold waves, storms, heat waves. Dynamical downscaling of MPI-ESM-LR global data forced with RCP8.5 climatic scenario is performed with the Weather Research and Forecast (WRF model to a regional scale including the Douro valley of Portugal for recent-past (1986–2005 and future periods (2046–2065; 2081–2100. The number, duration and intensity of events are superimposed over critical phenological phases of the vine (dormancy, bud burst, flowering, véraison, and maturity in order to assess their positive or negative implications on wine production in the region. An assessment on the statistical significance of climatic indices, their differences between the recent-past and the future scenarios and the potential impact on wine production is performed. Preliminary results indicate increased climatic stress on the Douro region wine production and increased vulnerability of its vine varieties. These results will provide evidence for future strategies aimed to preserve the high-quality wines in the region and their typicality in a sustainable way.

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

Science.gov (United States)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the

Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

Science.gov (United States)

Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

2008-01-01

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

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. 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. Monthly temperature 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. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. 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

Using High Resolution Simulations with WRF/SSiB Regional Climate Model Constrained by In Situ Observations to Assess the Impacts of Dust in Snow in the Upper Colorado River Basin

Science.gov (United States)

Oaida, C. M.; Skiles, M.; Painter, T. H.; Xue, Y.

2015-12-01

The mountain snowpack is an essential resource for both the environment as well as society. Observational and energy balance modeling work have shown that dust on snow (DOS) in western U.S. (WUS) is a major contributor to snow processes, including snowmelt timing and runoff amount in regions like the Upper Colorado River Basin (UCRB). In order to accurately estimate the impact of DOS to the hydrologic cycle and water resources, now and under a changing climate, we need to be able to (1) adequately simulate the snowpack (accumulation), and (2) realistically represent DOS processes in models. Energy balance models do not capture the impact on a broader local or regional scale, nor the land-atmosphere feedbacks, while GCM studies cannot resolve orographic-related precipitation processes, and therefore snowpack accumulation, owing to coarse spatial resolution and smoother terrain. All this implies the impacts of dust on snow on the mountain snowpack and other hydrologic processes are likely not well captured in current modeling studies. Recent increase in computing power allows for RCMs to be used at higher spatial resolutions, while recent in situ observations of dust in snow properties can help constrain modeling simulations. Therefore, in the work presented here, we take advantage of these latest resources to address the some of the challenges outlined above. We employ the newly enhanced WRF/SSiB regional climate model at 4 km horizontal resolution. This scale has been shown by others to be adequate in capturing orographic processes over WUS. We also constrain the magnitude of dust deposition provided by a global chemistry and transport model, with in situ measurements taken at sites in the UCRB. Furthermore, we adjust the dust absorptive properties based on observed values at these sites, as opposed to generic global ones. This study aims to improve simulation of the impact of dust in snow on the hydrologic cycle and related water resources.

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

Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

Science.gov (United States)

Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

2017-10-01

This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

Comparison of Thunderstorm Simulations from WRF-NMM and WRF-ARW Models over East Indian Region

Directory of Open Access Journals (Sweden)

A. J. Litta

2012-01-01

Full Text Available The thunderstorms are typical mesoscale systems dominated by intense convection. Mesoscale models are essential for the accurate prediction of such high-impact weather events. In the present study, an attempt has been made to compare the simulated results of three thunderstorm events using NMM and ARW model core of WRF system and validated the model results with observations. Both models performed well in capturing stability indices which are indicators of severe convective activity. Comparison of model-simulated radar reflectivity imageries with observations revealed that NMM model has simulated well the propagation of the squall line, while the squall line movement was slow in ARW. From the model-simulated spatial plots of cloud top temperature, we can see that NMM model has better captured the genesis, intensification, and propagation of thunder squall than ARW model. The statistical analysis of rainfall indicates the better performance of NMM than ARW. Comparison of model-simulated thunderstorm affected parameters with that of the observed showed that NMM has performed better than ARW in capturing the sharp rise in humidity and drop in temperature. This suggests that NMM model has the potential to provide unique and valuable information for severe thunderstorm forecasters over east Indian region.

Evaluation of cumulus cloud – radiation interaction effects on air quality –relevant meteorological variables from WRF, from a regional climate perspective

Science.gov (United States)

Aware only of the resolved, grid-scale clouds, the Weather Research & Forecasting model (WRF) does not consider the interactions between subgrid-scale convective clouds and radiation. One consequence of this omission may be WRF’s overestimation of surface precipitation during sum...

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

Science.gov (United States)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

Science.gov (United States)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

Science.gov (United States)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

Science.gov (United States)

Li, Xia; Mitra, Chandana; Dong, Li; Yang, Qichun

2018-02-01

To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.

Future Midwest Heat Waves in WRF

Science.gov (United States)

Huber, M.; Buzan, J. R.; Yoo, J.

2017-12-01

We present heat stress results for the upper Midwest derived from convection resolving Weather Research and Forecasting (WRF) model simulations carried out for the RCP 8.5 Scenario and driven by Community Earth System Model (CESM) boundary conditions as part of the Indiana Climate Change Assessment. Using this modeling system we find widespread and severe increases in moist heat stress metrics in the Midwest by end of century. We detail scaling arguments that suggest our results are robust and not model dependent and describe potential health, welfare, and productivity implications of these results.

WRF nested large-eddy simulations of deep convection during SEAC4RS

Science.gov (United States)

Heath, Nicholas K.; Fuelberg, Henry E.; Tanelli, Simone; Turk, F. Joseph; Lawson, R. Paul; Woods, Sarah; Freeman, Sean

2017-04-01

Large-eddy simulations (LES) and observations are often combined to increase our understanding and improve the simulation of deep convection. This study evaluates a nested LES method that uses the Weather Research and Forecasting (WRF) model and, specifically, tests whether the nested LES approach is useful for studying deep convection during a real-world case. The method was applied on 2 September 2013, a day of continental convection that occurred during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. Mesoscale WRF output (1.35 km grid length) was used to drive a nested LES with 450 m grid spacing, which then drove a 150 m domain. Results reveal that the 450 m nested LES reasonably simulates observed reflectivity distributions and aircraft-observed in-cloud vertical velocities during the study period. However, when examining convective updrafts, reducing the grid spacing to 150 m worsened results. We find that the simulated updrafts in the 150 m run become too diluted by entrainment, thereby generating updrafts that are weaker than observed. Lastly, the 450 m simulation is combined with observations to study the processes forcing strong midlevel cloud/updraft edge downdrafts that were observed on 2 September. Results suggest that these strong downdrafts are forced by evaporative cooling due to mixing and by perturbation pressure forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested LES approach, with further development and evaluation, could potentially provide an effective method for studying deep convection in real-world cases.

Urban effects on regional climate: a case study in the Phoenix and Tucson ‘sun’ corridor

Science.gov (United States)

Zhao Yang,; Francina Dominguez,; Hoshin Gupta,; Xubin Zeng,; Norman, Laura M.

2016-01-01

Land use and land cover change (LULCC) due to urban expansion alter the surface albedo, heat capacity, and thermal conductivity of the surface. Consequently, the energy balance in urban regions is different from that of natural surfaces. To evaluate the changes in regional climate that could arise due to projected urbanization in the Phoenix-Tucson corridor, Arizona, we applied the coupled WRF-NOAH-UCM (which includes a detailed urban radiation scheme) to this region. Land cover changes were represented using land cover data for 2005 and projections to 2050, and historical North American Regional Reanalysis (NARR) data were used to specify the lateral boundary conditions. Results suggest that temperature changes will be well defined, reflecting the urban heat island (UHI) effect within areas experiencing LULCC. Changes in precipitation are less robust, but seem to indicate reductions in precipitation over the mountainous regions northeast of Phoenix and decreased evening precipitation over the newly-urbanized area.

WRF-Fire Applied in Bulgaria

OpenAIRE

Dobrinkova, Nina; Jordanov, Georgi; Mandel, Jan

2010-01-01

WRF-Fire consists of the WRF (Weather Research and Forecasting Model) coupled with a fire spread model, based on the level-set method. We describe a preliminary application of WRF-Fire to a forest fire in Bulgaria, oportunities for research of forest fire models for Bulgaria, and plans for the development of an Environmental Decision Support Systems which includes computational modeling of fire behavior.

Using nudging to improve global-regional dynamic consistency in limited-area climate modeling: What should we nudge?

Science.gov (United States)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2015-03-01

Regional climate modelling sometimes requires that the regional model be nudged towards the large-scale driving data to avoid the development of inconsistencies between them. These inconsistencies are known to produce large surface temperature and rainfall artefacts. Therefore, it is essential to maintain the synoptic circulation within the simulation domain consistent with the synoptic circulation at the domain boundaries. Nudging techniques, initially developed for data assimilation purposes, are increasingly used in regional climate modeling and offer a workaround to this issue. In this context, several questions on the "optimal" use of nudging are still open. In this study we focus on a specific question which is: What variable should we nudge? in order to maintain the consistencies between the regional model and the driving fields as much as possible. For that, a "Big Brother Experiment", where a reference atmospheric state is known, is conducted using the weather research and forecasting (WRF) model over the Euro-Mediterranean region. A set of 22 3-month simulations is performed with different sets of nudged variables and nudging options (no nudging, indiscriminate nudging, spectral nudging) for summer and winter. The results show that nudging clearly improves the model capacity to reproduce the reference fields. However the skill scores depend on the set of variables used to nudge the regional climate simulations. Nudging the tropospheric horizontal wind is by far the key variable to nudge to simulate correctly surface temperature and wind, and rainfall. To a lesser extent, nudging tropospheric temperature also contributes to significantly improve the simulations. Indeed, nudging tropospheric wind or temperature directly impacts the simulation of the tropospheric geopotential height and thus the synoptic scale atmospheric circulation. Nudging moisture improves the precipitation but the impact on the other fields (wind and temperature) is not significant. As

GPU-Accelerated Stony-Brook University 5-class Microphysics Scheme in WRF

Science.gov (United States)

Mielikainen, J.; Huang, B.; Huang, A.

2011-12-01

The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. Microphysics plays an important role in weather and climate prediction. Several bulk water microphysics schemes are available within the WRF, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University scheme (SBU-YLIN) is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In the past few years, co-processing on Graphics Processing Units (GPUs) has been a disruptive technology in High Performance Computing (HPC). GPUs use the ever increasing transistor count for adding more processor cores. Therefore, GPUs are well suited for massively data parallel processing with high floating point arithmetic intensity. Thus, it is imperative to update legacy scientific applications to take advantage of this unprecedented increase in computing power. CUDA is an extension to the C programming language offering programming GPU's directly. It is designed so that its constructs allow for natural expression of data-level parallelism. A CUDA program is organized into two parts: a serial program running on the CPU and a CUDA kernel running on the GPU. The CUDA code consists of three computational phases: transmission of data into the global memory of the GPU, execution of the CUDA kernel, and transmission of results from the GPU into the memory of CPU. CUDA takes a bottom-up point of view of parallelism is which thread is an atomic unit of parallelism. Individual threads are part of groups called warps, within which every thread executes exactly the same sequence of instructions. To test SBU-YLIN, we used a CONtinental United States (CONUS) benchmark data set for 12 km resolution domain for October 24, 2001. A WRF domain is a geographic region of interest discretized into a 2-dimensional grid parallel to the ground. Each grid point has

The WASCAL high-resolution regional climate simulation ensemble for West Africa: concept, dissemination and assessment

Science.gov (United States)

Heinzeller, Dominikus; Dieng, Diarra; Smiatek, Gerhard; Olusegun, Christiana; Klein, Cornelia; Hamann, Ilse; Salack, Seyni; Bliefernicht, Jan; Kunstmann, Harald

2018-04-01

Climate change and constant population growth pose severe challenges to 21st century rural Africa. Within the framework of the West African Science Service Center on Climate Change and Adapted Land Use (WASCAL), an ensemble of high-resolution regional climate change scenarios for the greater West African region is provided to support the development of effective adaptation and mitigation measures. This contribution presents the overall concept of the WASCAL regional climate simulations, as well as detailed information on the experimental design, and provides information on the format and dissemination of the available data. All data are made available to the public at the CERA long-term archive of the German Climate Computing Center (DKRZ) with a subset available at the PANGAEA Data Publisher for Earth & Environmental Science portal (https://doi.pangaea.de/10.1594/PANGAEA.880512" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.880512). A brief assessment of the data are presented to provide guidance for future users. Regional climate projections are generated at high (12 km) and intermediate (60 km) resolution using the Weather Research and Forecasting Model (WRF). The simulations cover the validation period 1980-2010 and the two future periods 2020-2050 and 2070-2100. A brief comparison to observations and two climate change scenarios from the Coordinated Regional Downscaling Experiment (CORDEX) initiative is presented to provide guidance on the data set to future users and to assess their climate change signal. Under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, the results suggest an increase in temperature by 1.5 °C at the coast of Guinea and by up to 3 °C in the northern Sahel by the end of the 21st century, in line with existing climate projections for the region. They also project an increase in precipitation by up to 300 mm per year along the coast of Guinea, by up to 150 mm per year in the Soudano region adjacent in the north and

Water Resources Sustainability in Northwest Mexico: Analysis of Regional Infrastructure Plans under Historical and Climate Change Scenarios

Science.gov (United States)

Che, D.; Robles-Morua, A.; Mayer, A. S.; Vivoni, E. R.

2012-12-01

The arid state of Sonora, Mexico, has embarked on a large water infrastructure project to provide additional water supply and improved sanitation to the growing capital of Hermosillo. The main component of the Sonora SI project involves an interbasin transfer from rural to urban water users that has generated conflicts over water among different social sectors. Through interactions with regional stakeholders from agricultural and water management agencies, we ascertained the need for a long-term assessment of the water resources of one of the system components, the Sonora River Basin (SRB). A semi-distributed, daily watershed model that includes current and proposed reservoir infrastructure was applied to the SRB. This simulation framework allowed us to explore alternative scenarios of water supply from the SRB to Hermosillo under historical (1980-2010) and future (2031-2040) periods that include the impact of climate change. We compared three precipitation forcing scenarios for the historical period: (1) a network of ground observations from Mexican water agencies; (2) gridded fields from the North America Land Data Assimilation System (NLDAS) at 12 km resolution; and (3) gridded fields from the Weather Research and Forecasting (WRF) model at 10 km resolution. These were compared to daily historical observations at two stream gauging stations and two reservoirs to generate confidence in the simulation tools. We then tested the impact of climate change through the use of the A2 emissions scenario and HadCM3 boundary forcing on the WRF simulations of a future period. Our analysis is focused on the combined impact of existing and proposed reservoir infrastructure at two new sites on the water supply management in the SRB under historical and future climate conditions. We also explore the impact of climate variability and change on the bimodal precipitation pattern from winter frontal storms and the summertime North American monsoon and its consequences on water

Ensemble simulations to study the impact of land use change of Atlanta to regional climate

Science.gov (United States)

Liu, P.; Hu, Y.; Stone, B.; Vargo, J.; Nenes, A.; Russell, A.; Trail, M.; Tsimpidi, A.

2012-12-01

Studies show that urban areas may be the "first responders" to climate change (Rosenzweig et al., 2010). Of particular interest is the potential increased temperatures in urban areas, due to use of structures and surfaces that increase local heating, and how that may impact health, air quality and other environmental factors. In response, interest has grown as to how the modification of land use in urban areas, in order to mitigate the adverse effects of urbanization can serve to reduce local temperatures, and how climate is impacted more regionally. Studies have been conducted to investigate the impact of land use change on local or regional climate by dynamic downscaling using regional climate models (RCMs), the boundary conditions (BCs) and initial conditions (ICs) of which result from coarser-resolution reanalysis data or general circulation models (GCMs). However, few studies have focused on demonstrating whether the land use change in local areas significantly impacts the climate of the larger region of the domain, and the spatial scale of the impact from urban-scale changes. This work investigated the significance of the impact of land use change in the Atlanta city area on different scales, using a range of modeling resolutions, including the contiguous US (with 36km resolution), the southeastern US (with 12km resolution) and the state of Georgia (with 4km resolution). We used WRF version 3.1.1 with and ran continuous from June to August of a simulated year 2050, driven by GISS ModelE with inputs corresponding to RCP4.5. During the simulation, spectral nudging is used in the 36km resolution domain to maintain the climate patterns with scales larger than 2000km. Two-way nesting is also used in order to take into account the feedback of nesting domains across model domains. Two land use cases over the Atlanta city are chosen. For the base case, most of the urban area of Atlanta is covered with forest; while for the second, "impervious" case, all the urban

Numerical simulation for regional ozone concentrations: A case study by weather research and forecasting/chemistry (WRF/Chem) model

Energy Technology Data Exchange (ETDEWEB)

Habib Al Razi, Khandakar Md; Hiroshi, Moritomi [Environmental and Renewable Energy System, Graduate School of Engineering, Gifu University, 1-1 Yanagido, Gifu City, 501-1193 (Japan)

2013-07-01

The objective of this research is to better understand and predict the atmospheric concentration distribution of ozone and its precursor (in particular, within the Planetary Boundary Layer (Within 110 km to 12 km) over Kasaki City and the Greater Tokyo Area using fully coupled online WRF/Chem (Weather Research and Forecasting/Chemistry) model. In this research, a serious and continuous high ozone episode in the Greater Tokyo Area (GTA) during the summer of 14–18 August 2010 was investigated using the observation data. We analyzed the ozone and other trace gas concentrations, as well as the corresponding weather conditions in this high ozone episode by WRF/Chem model. The simulation results revealed that the analyzed episode was mainly caused by the impact of accumulation of pollution rich in ozone over the Greater Tokyo Area. WRF/Chem has shown relatively good performance in modeling of this continuous high ozone episode, the simulated and the observed concentrations of ozone, NOx and NO2 are basically in agreement at Kawasaki City, with best correlation coefficients of 0.87, 0.70 and 0.72 respectively. Moreover, the simulations of WRF/Chem with WRF preprocessing software (WPS) show a better agreement with meteorological observations such as surface winds and temperature profiles in the ground level of this area. As a result the surface ozone simulation performances have been enhanced in terms of the peak ozone and spatial patterns, whereas WRF/Chem has been succeeded to generate meteorological fields as well as ozone, NOx, NO2 and NO.

High Resolution Forecasting System for Mountain area based on KLAPS-WRF

Science.gov (United States)

Chun, Ji Min; Rang Kim, Kyu; Lee, Seon-Yong; Kang, Wee Soo; Park, Jong Sun; Yi, Chae Yeon; Choi, Young-jean; Park, Eun Woo; Hong, Soon Sung; Jung, Hyun-Sook

2013-04-01

This paper reviews the results of recent observations and simulations on the thermal belt and cold air drainage, which are outstanding in local climatic phenomena in mountain areas. In a mountain valley, cold air pool and thermal belt were simulated with the Weather and Research Forecast (WRF) model and the Korea Local Analysis and Prediction System (KLAPS) to determine the impacts of planetary boundary layer (PBL) schemes and topography resolution on model performance. Using the KLAPS-WRF models, an information system was developed for 12 hour forecasting of cold air damage in orchard. This system was conducted on a three level nested grid from 1 km to 111 m horizontal resolution. Results of model runs were verified by the data from automated weather stations, which were installed at twelve sites in a valley at Yeonsuri, Yangpyeonggun, Gyeonggido to measure temperature and wind speed and direction during March to May 2012. The potential of the numerical model to simulate these local features was found to be dependent on the planetary boundary layer schemes. Statistical verification results indicate that Mellor-Yamada-Janjic (MYJ) PBL scheme was in good agreement with night time temperature, while the no-PBL scheme produced predictions similar to the day time temperature observation. Although the KLAPS-WRF system underestimates temperature in mountain areas and overestimates wind speed, it produced an accurate description of temperature, with an RMSE of 1.67 ˚C in clear daytime. Wind speed and direction were not forecasted well in precision (RMSE: 5.26 m/s and 10.12 degree). It might have been caused by the measurement uncertainty and spatial variability. Additionally, the performance of KLAPS-WRF was performed to evaluate for different terrain resolution: Topography data were improved from USGS (United States Geological Survey) 30" to NGII (National Geographic Information Institute) 10 m. The simulated results were quantitatively compared to observations and

WRF-Chem simulations in the Amazon region during wet and dry season transitions: evaluation of methane models and wetland inundation maps

Science.gov (United States)

Beck, V.; Gerbig, C.; Koch, T.; Bela, M. M.; Longo, K. M.; Freitas, S. R.; Kaplan, J. O.; Prigent, C.; Bergamaschi, P.; Heimann, M.

2013-08-01

The Amazon region, being a large source of methane (CH4), contributes significantly to the global annual CH4 budget. For the first time, a forward and inverse modelling framework on regional scale for the purpose of assessing the CH4 budget of the Amazon region is implemented. Here, we present forward simulations of CH4 as part of the forward and inverse modelling framework based on a modified version of the Weather Research and Forecasting model with chemistry that allows for passive tracer transport of CH4, carbon monoxide, and carbon dioxide (WRF-GHG), in combination with two different process-based bottom-up models of CH4 emissions from anaerobic microbial production in wetlands and additional datasets prescribing CH4 emissions from other sources such as biomass burning, termites, or other anthropogenic emissions. We compare WRF-GHG simulations on 10 km horizontal resolution to flask and continuous CH4 observations obtained during two airborne measurement campaigns within the Balanço Atmosférico Regional de Carbono na Amazônia (BARCA) project in November 2008 and May 2009. In addition, three different wetland inundation maps, prescribing the fraction of inundated area per grid cell, are evaluated. Our results indicate that the wetland inundation maps based on remote-sensing data represent the observations best except for the northern part of the Amazon basin and the Manaus area. WRF-GHG was able to represent the observed CH4 mixing ratios best at days with less convective activity. After adjusting wetland emissions to match the averaged observed mixing ratios of flights with little convective activity, the monthly CH4 budget for the Amazon basin obtained from four different simulations ranges from 1.5 to 4.8 Tg for November 2008 and from 1.3 to 5.5 Tg for May 2009. This corresponds to an average CH4 flux of 9-31 mg m-2 d-1 for November 2008 and 8-36 mg m-2 d-1 for May 2009.

The WASCAL high-resolution regional climate simulation ensemble for West Africa: concept, dissemination and assessment

Directory of Open Access Journals (Sweden)

D. Heinzeller

2018-04-01

Full Text Available Climate change and constant population growth pose severe challenges to 21st century rural Africa. Within the framework of the West African Science Service Center on Climate Change and Adapted Land Use (WASCAL, an ensemble of high-resolution regional climate change scenarios for the greater West African region is provided to support the development of effective adaptation and mitigation measures. This contribution presents the overall concept of the WASCAL regional climate simulations, as well as detailed information on the experimental design, and provides information on the format and dissemination of the available data. All data are made available to the public at the CERA long-term archive of the German Climate Computing Center (DKRZ with a subset available at the PANGAEA Data Publisher for Earth & Environmental Science portal (https://doi.pangaea.de/10.1594/PANGAEA.880512. A brief assessment of the data are presented to provide guidance for future users. Regional climate projections are generated at high (12 km and intermediate (60 km resolution using the Weather Research and Forecasting Model (WRF. The simulations cover the validation period 1980–2010 and the two future periods 2020–2050 and 2070–2100. A brief comparison to observations and two climate change scenarios from the Coordinated Regional Downscaling Experiment (CORDEX initiative is presented to provide guidance on the data set to future users and to assess their climate change signal. Under the RCP4.5 (Representative Concentration Pathway 4.5 scenario, the results suggest an increase in temperature by 1.5 °C at the coast of Guinea and by up to 3 °C in the northern Sahel by the end of the 21st century, in line with existing climate projections for the region. They also project an increase in precipitation by up to 300 mm per year along the coast of Guinea, by up to 150 mm per year in the Soudano region adjacent in the north and almost no change in

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal).

Science.gov (United States)

Rafael, S; Martins, H; Marta-Almeida, M; Sá, E; Coelho, S; Rocha, A; Borrego, C; Lopes, M

2017-05-01

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability. In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were applied for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of the WRF-CO2 4D-Var assimilation system v1.0

Science.gov (United States)

Zheng, Tao; French, Nancy H. F.; Baxter, Martin

2018-05-01

Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var) assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF) modeling system, including the system coupled to chemistry (WRF-Chem), with tangent linear and adjoint codes (WRFPLUS), and with data assimilation (WRFDA), all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimization algorithm (L-BFGS-B) and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

Development of the WRF-CO2 4D-Var assimilation system v1.0

Directory of Open Access Journals (Sweden)

T. Zheng

2018-05-01

Full Text Available Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF modeling system, including the system coupled to chemistry (WRF-Chem, with tangent linear and adjoint codes (WRFPLUS, and with data assimilation (WRFDA, all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS minimization algorithm (L-BFGS-B and the second uses the Lanczos conjugate gradient (CG in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km  ×  48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

Development of extended WRF variational data assimilation system (WRFDA) for WRF non-hydrostatic mesoscale model

Science.gov (United States)

Pattanayak, Sujata; Mohanty, U. C.

2018-06-01

The paper intends to present the development of the extended weather research forecasting data assimilation (WRFDA) system in the framework of the non-hydrostatic mesoscale model core of weather research forecasting system (WRF-NMM), as an imperative aspect of numerical modeling studies. Though originally the WRFDA provides improved initial conditions for advanced research WRF, we have successfully developed a unified WRFDA utility that can be used by the WRF-NMM core, as well. After critical evaluation, it has been strategized to develop a code to merge WRFDA framework and WRF-NMM output. In this paper, we have provided a few selected implementations and initial results through single observation test, and background error statistics like eigenvalues, eigenvector and length scale among others, which showcase the successful development of extended WRFDA code for WRF-NMM model. Furthermore, the extended WRFDA system is applied for the forecast of three severe cyclonic storms: Nargis (27 April-3 May 2008), Aila (23-26 May 2009) and Jal (4-8 November 2010) formed over the Bay of Bengal. Model results are compared and contrasted within the analysis fields and later on with high-resolution model forecasts. The mean initial position error is reduced by 33% with WRFDA as compared to GFS analysis. The vector displacement errors in track forecast are reduced by 33, 31, 30 and 20% to 24, 48, 72 and 96 hr forecasts respectively, in data assimilation experiments as compared to control run. The model diagnostics indicates successful implementation of WRFDA within the WRF-NMM system.

Wind climate estimation using WRF model output: method and model sensitivities over the sea

DEFF Research Database (Denmark)

Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo

2015-01-01

setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface...... temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce...... a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast....

The Development of a Customization Framework for the WRF Model over the Lake Victoria Basin, Eastern Africa on Seasonal Timescales

Directory of Open Access Journals (Sweden)

R. Argent

2015-01-01

Full Text Available Lake Victoria, Africa, supports millions of people. To produce reliable climate projections, it is desirable to successfully model the rainfall over the lake accurately. An initial step is taken here with customization of the Weather, Research, and Forecast (WRF model. Of particular interest is an asymmetrical rainfall pattern across the lake basin, due to a diurnal land-lake breeze. The main aim is to present a customization framework for use over the lake. This framework is developed by conducting several series of model runs to investigate aspects of the customization. The runs are analyzed using Tropical Rainfall Measuring Mission rainfall data and Climatic Research Unit temperature data. The study shows that the choice of parameters and lake surface temperature initialization can significantly alter the results. Also, the optimal physics combinations for the climatology may not necessarily be suitable for all circumstances, such as extreme years. The study concludes that WRF is unable to reproduce the pattern across the lake. The temperature of the lake is too cold and this prevents the diurnal land-lake breeze reversal. Overall, this study highlights the importance of customizing a model to the region of research and presents a framework through which this may be achieved.

A Study of Precipitation Climatology and Its Variability over Europe Using an Advanced Regional Model (WRF)

KAUST Repository

Dasari, Hari Prasad

2015-03-06

In recent years long-term precipitation trends on a regional scale have been given emphasis due to the impacts of global warming on regional hydrology. In this study, regional precipitation trends are simulated over the Europe continent for a 60-year period in 1950-2010 using an advanced regional model, WRF, to study extreme precipitation events over Europe. The model runs continuously for each year during the period at a horizontal resolution of 25 km with initial/ boundary conditions derived from the National Center for Environmental Prediction (NCEP) 2.5 degree reanalysis data sets. The E-OBS 0.25 degree rainfall observation analysis is used for model validation. Results indicate that the model could reproduce the spatial annual rainfall pattern over Europe with low amounts (250 - 750 mm) in Iberian Peninsula, moderate to large amounts (750 - 1500 mm) in central, eastern and northeastern parts of Europe and extremely heavy falls (1500 - 2000 mm) in hilly areas of Alps with a slight overestimation in Alps and underestimation in other parts of Europe. The regional model integrations showed increasing errors (mean absolute errors) and decreasing correlations with increasing time scale (daily to seasonal). Rainfall is simulated relatively better in Iberian Peninsula, northwest and central parts of Europe. A large spatial variability with the highest number of wet days over eastern, central Europe and Alps (~200 days/year) and less number of wet days over Iberian Peninsula (≤150 days/year) is also found in agreement with observations. The model could simulate the spatial rainfall climate variability reasonably well with low rainfall days (1 - 10 mm/days) in almost all zones, heavy rainfall events in western, northern, southeastern hilly and coastal zones and extremely heavy rainfall events in northern coastal zones. An increasing trend of heavy rainfall in central, southern and southeastern parts, a decreasing trend in Iberian Peninsula and a steady trend in other

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

Science.gov (United States)

Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew

2012-01-01

Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

Simulation of CO2 concentrations at Tsukuba tall tower using WRF ...

Indian Academy of Sciences (India)

1School of Environmental Studies, Jadavpur University, Kolkata 700 032, India. ... nental or coastal sites is challenging because of coarse horizontal resolution of ... Here the regional Weather Research and Forecasting (WRF) model coupled .... at nine-towers regional networks during North ..... ond case, it falls to ≥0.57.

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal)

Energy Technology Data Exchange (ETDEWEB)

Rafael, S., E-mail: sandra.rafael@ua.pt [CESAM & Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro (Portugal); Martins, H. [CESAM & Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro (Portugal); Rossby Centre, Swedish Meteorological and Hydrological Institute (SMHI), SE-60176 Norrköping (Sweden); Marta-Almeida, M. [Centro Oceanográfico A Coruña, Instituto Español de Oceanografía, A Coruña (Spain); Sá, E.; Coelho, S. [CESAM & Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro (Portugal); Rocha, A. [CESAM & Department of Physics, University of Aveiro, 3810-193 Aveiro (Portugal); Borrego, C.; Lopes, M. [CESAM & Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro (Portugal)

2017-05-15

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability. In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were applied for two climatological scenarios: a present (or reference, 1986–2005) scenario and a future scenario (2046–2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation. - Highlights: • Assessment of energy fluxes behaviour under past period and medium-term climate change projection. • Evaluation of climate change at urban scale. • Meteorological variables alters the partitioning of the energy fluxes. • Changes in the partition of the annual energy balance are found between the two analysed periods. • Increase in the magnitude of sensible and storage heat fluxes.

Improved simulation of precipitation in the tropics using a modified BMJ scheme in the WRF model

Science.gov (United States)

Fonseca, R. M.; Zhang, T.; Yong, K.-T.

2015-09-01

The successful modelling of the observed precipitation, a very important variable for a wide range of climate applications, continues to be one of the major challenges that climate scientists face today. When the Weather Research and Forecasting (WRF) model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR) over the Indo-Pacific region, with analysis (grid-point) nudging, it is found that the cumulus scheme used, Betts-Miller-Janjić (BMJ), produces excessive rainfall suggesting that it has to be modified for this region. Experimentation has shown that the cumulus precipitation is not very sensitive to changes in the cloud efficiency but varies greatly in response to modifications of the temperature and humidity reference profiles. A new version of the scheme, denoted "modified BMJ" scheme, where the humidity reference profile is more moist, was developed. In tropical belt simulations it was found to give a better estimate of the observed precipitation as given by the Tropical Rainfall Measuring Mission (TRMM) 3B42 data set than the default BMJ scheme for the whole tropics and both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.

Comparison of Spatial and Temporal Rainfall Characteristics in WRF-Simulated Precipitation to Gauge and Radar Observations

Science.gov (United States)

Weather Research and Forecasting (WRF) meteorological data are used for USEPA multimedia air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hi...

The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part 1: African Wave Circulation

Science.gov (United States)

Noble, Erik; Druyan, Leonard M.; Fulakeza, Matthew

2014-01-01

The performance of the NCAR Weather Research and Forecasting Model (WRF) as a West African regional-atmospheric model is evaluated. The study tests the sensitivity of WRF-simulated vorticity maxima associated with African easterly waves to 64 combinations of alternative parameterizations in a series of simulations in September. In all, 104 simulations of 12-day duration during 11 consecutive years are examined. The 64 combinations combine WRF parameterizations of cumulus convection, radiation transfer, surface hydrology, and PBL physics. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP/Department of Energy Global Reanalysis 2. Precipitation is considered in a second part of this two-part paper. A wide range of 700-hPa vorticity validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year while a parallel-benchmark simulation by the NASA Regional Model-3 (RM3) achieves higher correlations, but less realistic spatiotemporal variability. The largest favorable impact on WRF-vorticity validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact, although WRF configurations incorporating one surface model and PBL scheme consistently performed poorly. A comparison of reanalysis circulation against two NASA radiosonde stations confirms that both reanalyses represent observations well enough to validate the WRF results. Validation statistics for optimized WRF configurations simulating the parallel period during 10 additional years are less favorable than for 2006.

An Online Approach for Training International Climate Scientists to Use Computer Models

Science.gov (United States)

Yarker, M. B.; Mesquita, M. D.; Veldore, V.

2013-12-01

that engages the learners with the subject matter, in a way that is meaningful for their region. A number of science-education courses are being conducted online within a capacity building project called 'The Future of Climate Extremes in the Caribbean (XCUBE)'. If accepted, this presentation will explore a case study related to the online training courses provided via the website m2lab.org for the XCUBE project: 'Regional Climate Modeling using WRF'. The course relates to teaching participants how to run WRF for climate simulations using a special version of the model called e-WRF (WRF for Educational purposes). This version of WRF does not require installation so that student learning can be focused on using the model itself. In order to explore the effectiveness of the course, data will be collected from the participants as they complete it. There are currently over 200 participants registered for the course and are made up of graduate students, professors, and researchers from many different science fields. Preliminary results indicate that many students enrolled in this course have previously taken a WRF tutorial, but do not feel confident enough to use it. Despite having taken a tutorial previously, for some participants the basic design of the model was a new concept to them. If accepted, a statistical analysis will be performed as more students complete the course.

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

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.)

A Dynamic Evaluation Of A Model And An Estimate Of The Air Quality And Regional Climate Impacts Of Enhanced Solar Power Generation

Science.gov (United States)

Millstein, D.; Brown, N. J.; Zhai, P.; Menon, S.

2012-12-01

We use the WRF/Chem model (Weather Research and Forecasting model with chemistry) and pollutant emissions based on the EPA National Emission Inventories from 2005 and 2008 to model regional climate and air quality over the continental United States. Additionally, 2030 emission scenarios are developed to investigate the effects of future enhancements to solar power generation. Modeling covered 6 summer and 6 winter weeks each year. We model feedback between aerosols and meteorology and thus capture direct and indirect aerosol effects. The grid resolution is 25 km and includes no nesting. Between 2005 and 2008 significant emission reductions were reported in the National Emission Inventory. The 2008 weekday emissions over the continental U.S. of SO2 and NO were reduced from 2005 values by 28% and 16%, respectively. Emission reductions of this magnitude are similar in scale to the potential emission reductions from various energy policy initiatives. By evaluating modeled and observed air quality changes from 2005 to 2008, we analyze how well the model represents the effects of historical emission changes. We also gain insight into how well the model might predict the effects of future emission changes. In addition to direct comparisons of model outputs to ground and satellite observations, we compare observed differences between 2005 and 2008 to corresponding modeled differences. Modeling was extended to future scenarios (2030) to simulate air quality and regional climate effects of large-scale adoption of solar power. The 2030-year was selected to allow time for development of solar generation infrastructure. The 2030 emission scenario was scaled, with separate factors for different economic sectors, from the 2008 National Emissions Inventory. The changes to emissions caused by the introduction of large-scale solar power (here assumed to be 10% of total energy generation) are based on results from a parallel project that used an electricity grid model applied over

Deciphering the contrasting climatic trends between the central Himalaya and Karakoram with 36 years of WRF simulations

Science.gov (United States)

Norris, Jesse; Carvalho, Leila M. V.; Jones, Charles; Cannon, Forest

2018-02-01

Glaciers over the central Himalaya have retreated at particularly rapid rates in recent decades, while glacier mass in the Karakoram appears stable. To address the meteorological factors associated with this contrast, 36 years of Climate Forecast System Reanalyses (CFSR) are dynamically downscaled from 1979 to 2015 with the Weather Research and Forecasting (WRF) model over High Mountain Asia at convection permitting grid spacing (6.7 km). In all seasons, CFSR shows an anti-cyclonic warming trend over the majority of High Mountain Asia, but distinctive differences are observed between the central Himalaya and Karakoram in winter and summer. In winter and summer, the central Himalaya has been under the influence of an anti-cyclonic trend, which in summer the downscaling shows has reduced cloud cover, leading to significant warming and reduced snowfall in recent years. Contrastingly, the Karakoram has been near the boundary between large-scale cyclonic and anti-cyclonic trends and has not experienced significant snowfall or temperature changes in winter or summer, despite significant trends in summer of increasing cloud cover and decreasing shortwave radiation. This downscaling does not identify any trends over glaciers in closer neighboring regions to the Karakoram (e.g., Hindu Kush and the western Himalaya) where glaciers have retreated as over the central Himalaya, indicating that there are other factors driving glacier mass balance that this downscaling is unable to capture. While this study does not fully explain the Karakoram anomaly, the identified trends detail important meteorological contributions to the observed differences between central Himalaya and Karakoram glacier evolution in recent decades.

WRF model sensitivity to choice of parameterization: a study of the `York Flood 1999'

Science.gov (United States)

Remesan, Renji; Bellerby, Tim; Holman, Ian; Frostick, Lynne

2015-10-01

Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the `1999 York Flood' event, which occurred over North Yorkshire, UK, 1st-14th March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

Science.gov (United States)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns.

NARCIS (Netherlands)

Jiménez, P.A.; Dudhia, J.; González-Rouco, J.F.; Montávez, J.P.; Garcia-Bustamante, E.; Navarro, J.; Vilà-Guerau de Arellano, J.; Munoz-Roldán, A.

2013-01-01

[1] The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13¿year period (1992 to 2005) over a complex terrain region

Coupled Regional Ocean-Atmosphere Modeling of the Mount Pinatubo Impact on the Red Sea

Science.gov (United States)

Stenchikov, G. L.; Osipov, S.

2017-12-01

The 1991 eruption of Mount Pinatubo had dramatic effects on the regional climate in the Middle East. Though acknowledged, these effects have not been thoroughly studied. To fill this gap and to advance understanding of the mechanisms that control variability in the Middle East's regional climate, we simulated the impact of the 1991 Pinatubo eruption using a regional coupled ocean-atmosphere modeling system set for the Middle East and North Africa (MENA) domain. We used the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) framework, which couples the Weather Research and Forecasting Model (WRF) model with the Regional Oceanic Modeling System (ROMS). We modified the WRF model to account for the radiative effect of volcanic aerosols. Our coupled ocean-atmosphere simulations verified by available observations revealed strong perturbations in the energy balance of the Red Sea, which drove thermal and circulation responses. Our modeling approach allowed us to separate changes in the atmospheric circulation caused by the impact of the volcano from direct regional radiative cooling from volcanic aerosols. The atmospheric circulation effect was significantly stronger than the direct volcanic aerosols effect. We found that the Red Sea response to the Pinatubo eruption was stronger and qualitatively different from that of the global ocean system. Our results suggest that major volcanic eruptions significantly affect the climate in the Middle East and the Red Sea and should be carefully taken into account in assessments of long-term climate variability and warming trends in MENA and the Red Sea.

Methane in the Amazon: A forward and inverse regional modeling approach

Science.gov (United States)

Beck, V.; Gerbig, C.; Koch, F. T.; Karstens, U.; Chen, H.; Bela, M. M.; Longo, K.; Freitas, S.; Bergamaschi, P. M.; Kaplan, J. O.; Prigent, C.

2011-12-01

The Amazon region is an important player in the global methane (CH4) cycle, the second most important greenhouse gas after CO2. Different major CH4 sources in the Amazon region such as anaerobic microbial production in wetlands and biomass burning will be affected by changing climate. Therefore, a thorough understanding of the processes is required. Within the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) project, airborne measurements of greenhouse gases, associated tracers and aerosols were taken during the end of the dry season in November 2008 as well as during the end of the wet season in May 2009. These aircraft measurements and additional ground based measurements provide a test bed for high resolution transport simulation of CH4. Here we present a comparison of WRF-Chem passive tracer simulations of CH4 to airborne CH4 observations obtained from the BARCA campaigns in November 2008 and May 2009 using the newly established WRF Greenhouse Gas Model (WRF-GHG) in combination with two different process-based bottom-up models for the calculation of CH4 emissions from anaerobic microbial production in wetlands (Kaplan and Walter-Heimann) and three different wetland inundation maps (Kaplan, JERS-1SAR, Prigent). The comparison illustrates the importance of a wetland inundation map with inundated area changing in time, and the quality of the representation of atmospheric transport in regional models in tropical regions. In addition, we demonstrate a comparison of WRF-GHG CH4 simulations to TT34 tower observations (35 m above ground; located 60 km north-west of Manaus, Brazil) for August 2009, evaluating the performance of WRF-GHG in representing CH4 observations in the planetary boundary layer in tropical regions. Finally, we present preliminary results of a regional inversion using the TM3-STILT model together with the above mentioned observations for the estimation of the CH4 budget of the Amazon region.

Transforming the representation of the boundary layer and low clouds for high-resolution regional climate modeling: Final report

Energy Technology Data Exchange (ETDEWEB)

Hall, Alex [University of California, Los Angeles, CA (United States). Joint Institute for Regional Earth System Science and Engineering

2013-07-24

Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while

Evaluation and Improvement of Polar WRF simulations using the observed atmospheric profiles in the Arctic seasonal ice zone

Science.gov (United States)

Liu, Z.; Schweiger, A. J. B.

2016-12-01

We use the Polar Weather Research and Forecasting (WRF) model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) over the Beaufort Sea in the summer since 2013. With the 119 SIZRS dropsondes in the18 cross sections along the 150W and 140W longitude lines, we evaluate the performance of WRF simulations and two forcing data sets, the ERA-Interim reanalysis and the Global Forecast System (GFS) analysis, and explore the improvement of the Polar WRF performance when the dropsonde data are assimilated using observation nudging. Polar WRF, ERA-Interim, and GFS can reproduce the general features of the observed mean atmospheric profiles, such as low-level temperature inversion, low-level jet (LLJ) and specific humidity inversion. The Polar WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing, which is likely related to the lower values of the boundary layer diffusion in WRF than in the global models such as ECMWF and GFS. The Polar WRF simulated relative humidity closely resembles the forcing datasets while having large biases compared to observations. This suggests that the performance of Polar WRF and its forecasts in this region are limited by the quality of the forcing dataset and that the assimilation of more and better-calibrated observations, such as humidity data, is critical for their improvement. We investigate the potential of assimilating the SIZRS dropsonde dataset in improving the weather forecast over the Beaufort Sea. A simple local nudging approach is adopted. Along SIZRS flight cross sections, a set of Polar WRF simulations are performed with varying number of variables and dropsonde profiles assimilated. Different model physics are tested to examine the sensitivity of different aspects of model physics, such as boundary layer schemes, cloud microphysics, and radiation parameterization, to data assimilation. The comparison of the Polar WRF runs with

Regional Effects of the Mount Pinatubo Eruption on the Middle East and the Red Sea

KAUST Repository

Osipov, Sergey

2017-10-26

The 1991 eruption of Mount Pinatubo had dramatic effects on the regional climate in the Middle East. Though acknowledged, these effects have not been thoroughly studied. To fill this gap and to advance understanding of the mechanisms that control variability in the Middle East\\'s regional climate, we simulated the impact of the 1991 Pinatubo eruption using a regional coupled ocean-atmosphere modeling system set for the Middle East and North Africa (MENA) domain. We used the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) framework, which couples the Weather Research and Forecasting Model (WRF) model with the Regional Oceanic Modeling System (ROMS). We modified the WRF model to account for the radiative effect of volcanic aerosols. Our coupled ocean-atmosphere simulations verified by available observations revealed strong perturbations in the energy balance of the Red Sea, which drove thermal and circulation responses. Our modeling approach allowed us to separate changes in the atmospheric circulation caused by the impact of the volcano from direct regional radiative cooling from volcanic aerosols. The atmospheric circulation effect was significantly stronger than the direct volcanic aerosols effect. We found that the Red Sea response to the Pinatubo eruption was stronger and qualitatively different from that of the global ocean system. Our results suggest that major volcanic eruptions significantly affect the climate in the Middle East and the Red Sea and should be carefully taken into account in assessments of long-term climate variability and warming trends in MENA and the Red Sea.

Regional Effects of the Mount Pinatubo Eruption on the Middle East and the Red Sea

Science.gov (United States)

Osipov, Sergey; Stenchikov, Georgiy

2017-11-01

The 1991 eruption of Mount Pinatubo had dramatic effects on the regional climate in the Middle East. Though acknowledged, these effects have not been thoroughly studied. To fill this gap and to advance understanding of the mechanisms that control variability in the Middle East's regional climate, we simulated the impact of the 1991 Pinatubo eruption using a regional coupled ocean-atmosphere modeling system set for the Middle East and North Africa (MENA) domain. We used the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) framework, which couples the Weather Research and Forecasting Model (WRF) model with the Regional Oceanic Modeling System (ROMS). We modified the WRF model to account for the radiative effect of volcanic aerosols. Our coupled ocean-atmosphere simulations verified by available observations revealed strong perturbations in the energy balance of the Red Sea, which drove thermal and circulation responses. Our modeling approach allowed us to separate changes in the atmospheric circulation caused by the impact of the volcano from direct regional radiative cooling from volcanic aerosols. The atmospheric circulation effect was significantly stronger than the direct volcanic aerosols effect. We found that the Red Sea response to the Pinatubo eruption was stronger and qualitatively different from that of the global ocean system. Our results suggest that major volcanic eruptions significantly affect the climate in the Middle East and the Red Sea and should be carefully taken into account in assessments of long-term climate variability and warming trends in MENA and the Red Sea.

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

Energy Technology Data Exchange (ETDEWEB)

Campbell, Patrick; Zhang, Yang; Wang, Kai; Leung, Ruby; Fan, Jiwen; Zheng, Bo; Zhang, Qiang; He, Kebin

2017-11-01

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improve performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32N and 42N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. Results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.

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.

Improved Near Real Time WRF-Chem Volcanic Emission Prediction and Impacts of Ash Aerosol on Weather.

Science.gov (United States)

Stuefer, M.; Webley, P. W.; Hirtl, M.

2017-12-01

We use the numerical Weather Research Forecasting (WRF) model with online Chemistry (WRF-Chem) to investigate the regional effects of volcanic aerosol on weather. A lot of observational data have become available since the Icelandic eruption of Eyjafjallajökull in spring 2010. The observed plume characteristics and meteorological data have been exploited for volcanic WRF-Chem case studies. We concluded that the Eyjafjallajökull ash plume resulted in significant direct aerosol effects altering the state of the atmosphere over large parts of Europe. The WRF-Chem model runs show near surface temperature differences up to 3ºC, altered vertical stability, changed pressure- and wind fields within the atmosphere loaded with ash aerosol. The modeled results have been evaluated with lidar network data, and ground and balloon based observations all over Europe. Besides case studies, we use WRF-Chem to build an improved volcanic ash decision support system that NOAA can use within the Volcanic Ash Advisory Center (VAAC) system. Realistic eruption source parameter (ESP) estimates are a main challenge in predicting volcanic emission dispersion in near real time. We implemented historic ESP into the WRF-Chem preprocessing routine, which can be used as a first estimate to assess a volcanic plume once eruption activity is reported. In a second step, a range of varying plume heights has been associated with the different ash variables within WRF-Chem, resulting in an assembly of different plume scenarios within one WRF-Chem model run. Once there is plume information available from ground or satellite observations, the forecaster has the option to select the corresponding ash variable that best matches the observations. In addition we added an automatic domain generation tool to create near real time WRF-Chem model runs anywhere on the globe by reducing computing expenses at the same time.

Regional climate consequences of large-scale cool roof and photovoltaic array deployment

International Nuclear Information System (INIS)

Millstein, Dev; Menon, Surabi

2011-01-01

Modifications to the surface albedo through the deployment of cool roofs and pavements (reflective materials) and photovoltaic arrays (low reflection) have the potential to change radiative forcing, surface temperatures, and regional weather patterns. In this work we investigate the regional climate and radiative effects of modifying surface albedo to mimic massive deployment of cool surfaces (roofs and pavements) and, separately, photovoltaic arrays across the United States. We use a fully coupled regional climate model, the Weather Research and Forecasting (WRF) model, to investigate feedbacks between surface albedo changes, surface temperature, precipitation and average cloud cover. With the adoption of cool roofs and pavements, domain-wide annual average outgoing radiation increased by 0.16 ± 0.03 W m -2 (mean ± 95% C.I.) and afternoon summertime temperature in urban locations was reduced by 0.11-0.53 deg. C, although some urban areas showed no statistically significant temperature changes. In response to increased urban albedo, some rural locations showed summer afternoon temperature increases of up to + 0.27 deg. C and these regions were correlated with less cloud cover and lower precipitation. The emissions offset obtained by this increase in outgoing radiation is calculated to be 3.3 ± 0.5 Gt CO 2 (mean ± 95% C.I.). The hypothetical solar arrays were designed to be able to produce one terawatt of peak energy and were located in the Mojave Desert of California. To simulate the arrays, the desert surface albedo was darkened, causing local afternoon temperature increases of up to + 0.4 deg. C. Due to the solar arrays, local and regional wind patterns within a 300 km radius were affected. Statistically significant but lower magnitude changes to temperature and radiation could be seen across the domain due to the introduction of the solar arrays. The addition of photovoltaic arrays caused no significant change to summertime outgoing radiation when averaged

Improved cyberinfrastructure for integrated hydrometeorological predictions within the fully-coupled WRF-Hydro modeling system

Science.gov (United States)

gochis, David; hooper, Rick; parodi, Antonio; Jha, Shantenu; Yu, Wei; Zaslavsky, Ilya; Ganapati, Dinesh

2014-05-01

The community WRF-Hydro system is currently being used in a variety of flood prediction and regional hydroclimate impacts assessment applications around the world. Despite its increasingly wide use certain cyberinfrastructure bottlenecks exist in the setup, execution and post-processing of WRF-Hydro model runs. These bottlenecks result in wasted time, labor, data transfer bandwidth and computational resource use. Appropriate development and use of cyberinfrastructure to setup and manage WRF-Hydro modeling applications will streamline the entire workflow of hydrologic model predictions. This talk will present recent advances in the development and use of new open-source cyberinfrastructure tools for the WRF-Hydro architecture. These tools include new web-accessible pre-processing applications, supercomputer job management applications and automated verification and visualization applications. The tools will be described successively and then demonstrated in a set of flash flood use cases for recent destructive flood events in the U.S. and in Europe. Throughout, an emphasis on the implementation and use of community data standards for data exchange is made.

Regionalizing global climate models

NARCIS (Netherlands)

Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

2012-01-01

Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US

Science.gov (United States)

Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo

2016-01-01

Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.

WRF Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset contains WRF model output. There are three months of data: July 2012, July 2013, and January 2013. For each month, several simulations were made: A...

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

Science.gov (United States)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far

Hydrological Modeling in Alaska with WRF-Hydro

Science.gov (United States)

Elmer, N. J.; Zavodsky, B.; Molthan, A.

2017-12-01

The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Science.gov (United States)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

Science.gov (United States)

Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

2014-12-01

Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

Science.gov (United States)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF

Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts

Science.gov (United States)

Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert

2017-08-01

Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.

Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

Science.gov (United States)

Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

2015-12-01

An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

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.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

Science.gov (United States)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2018-06-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

Science.gov (United States)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2017-08-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute

A Climate Statistics Tool and Data Repository

Science.gov (United States)

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

2017-12-01

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

Potential regulation on the climatic effect of Tibetan Plateau heating by tropical air-sea coupling in regional models

Science.gov (United States)

Wang, Ziqian; Duan, Anmin; Yang, Song

2018-05-01

Based on the conventional weather research and forecasting (WRF) model and the air-sea coupled mode WRF-OMLM, we investigate the potential regulation on the climatic effect of Tibetan Plateau (TP) heating by the air-sea coupling over the tropical Indian Ocean and western Pacific. Results indicate that the TP heating significantly enhances the southwesterly monsoon circulation over the northern Indian Ocean and the South Asia subcontinent. The intensified southwesterly wind cools the sea surface mainly through the wind-evaporation-SST (sea surface temperature) feedback. Cold SST anomaly then weakens monsoon convective activity, especially that over the Bay of Bengal, and less water vapor is thus transported into the TP along its southern slope from the tropical oceans. As a result, summer precipitation decreases over the TP, which further weakens the TP local heat source. Finally, the changed TP heating continues to influence the summer monsoon precipitation and atmospheric circulation. To a certain extent, the air-sea coupling over the adjacent oceans may weaken the effect of TP heating on the mean climate in summer. It is also implied that considerations of air-sea interaction are necessary in future simulation studies of the TP heating effect.

Sensitivity analysis of ground level ozone in India using WRF-CMAQ models

NARCIS (Netherlands)

Sharma, Sumit; Chatani, Satoru; Mahtta, Richa; Goel, Anju; Kumar, Atul

2016-01-01

Ground level ozone is emerging as a pollutant of concern in India. Limited surface monitoring data reveals that ozone concentrations are well above the prescribed national standards. This study aims to simulate the regional and urban scale ozone concentrations in India using WRF-CMAQ models.

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.

Forecasting Lightning Threat Using WRF Proxy Fields

Science.gov (United States)

McCaul, E. W., Jr.

2010-01-01

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

Dust modeling over East Asia during the summer of 2010 using the WRF-Chem model

Science.gov (United States)

Zhang, B.; Huang, J.; Chen, S.

2017-12-01

An intense summer dust storm over East Asia during June 24-27, 2010, was systematically analyzed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and a variety of in situ measurements and satellite retrievals. The results showed that the WRF-Chem model captured the spatial and temporal distributions of meteorological factors and dust aerosols over East Asia. This summer dust storm was initiated by the approach of a transverse trough in the northwestern Xinjiang. Because of the passage of the cutoff-low, a large amount of cold air was transported southward and further enhanced in the narrow valleys of the Altai and Tianshan Mountains, which resulted in higher wind speeds and huge dust emissions over the Taklimakan Desert (TD). Dust emission fluxes over the TD were as high as 54 μg m-2 s-1 on June 25th. The dust aerosols from the TD then swept across Inner Mongolia, Ningxia and Mongolia, and some were also transported eastward to Beijing, Tianjin, the Hebei region, and even South Korea and Japan. The simulations further showed that summer dust over East Asia exerts an important influence on the radiation budget in the Earth-atmosphere system. Dust heat the atmosphere at a maximum heating rate of 0.14 k day-1, effectively changing the vertical stability of the atmosphere and affecting climate change at regional and even global scales. The dust event-averaged direct radiative forcing induced by dust particles over the TD at all-sky was -6.0, -16.8 and 10.8 W m-2 at the top of the atmosphere, the surface, and in the atmosphere, respectively.

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)

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

Science.gov (United States)

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

2014-12-01

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

Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation

NARCIS (Netherlands)

Jiménez, P.A.; González-Rouco, J.F.; García-Bustamante, E.; Navarro, J.; Montávez, J.P.; Vilà-Guerau de Arellano, J.; Dudhia, J.; Muñoz-Roldan, A.

2010-01-01

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the

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

Science.gov (United States)

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

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

Science.gov (United States)

Ran, L.; Cooter, E. J.; Gilliam, R. C.; Foroutan, H.; Kang, D.; Appel, W.; Wong, D. C.; Pleim, J. E.; Benson, V.; Pouliot, G.

2017-12-01

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteorology, climate, and chemical transport. The Environmental Policy Integrated Climate (EPIC) is a cropping model which has long been used in a range of applications related to soil erosion, crop productivity, climate change, and water quality around the world. We have integrated WRF/CMAQ with EPIC using the Fertilizer Emission Scenario Tool for CMAQ (FEST-C) to estimate daily soil N information with fertilization for CMAQ bi-directional ammonia flux modeling. Driven by the weather and N deposition from WRF/CMAQ, FEST-C EPIC simulations are conducted on 22 different agricultural production systems ranging from managed grass lands (e.g. hay and alfalfa) to crop lands (e.g. corn grain and soybean) with rainfed and irrigated information across any defined conterminous United States (U.S.) CMAQ domain and grid resolution. In recent years, this integrated system has been enhanced and applied in many different air quality and ecosystem assessment projects related to land-water-atmosphere interactions. These enhancements have advanced this system to become a valuable tool for integrated assessments of air, land and water quality in light of social drivers and human and ecological outcomes. This presentation will focus on evaluating the sensitivity of precipitation and N deposition in the integrated system to MODIS vegetation input and lightning assimilation and their impacts on agricultural production and fertilization. We will describe the integrated modeling system and evaluate simulated precipitation and N deposition along with other weather information (e.g. temperature, humidity) for 2011 over the conterminous U.S. at 12 km grids from a coupled WRF/CMAQ with MODIS and lightning assimilation

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

Sensitivity of Sahelian Precipitation to Desert Dust under ENSO variability: a regional modeling study

Science.gov (United States)

Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.

2016-12-01

Mineral dust is estimated to comprise over half the total global aerosol burden, with a majority coming from the Sahara and Sahel region. Bounded by the Sahara Desert to the north and the Sahelian Savannah to the south, the Sahel experiences high interannual rainfall variability and a short rainy season during the boreal summer months. Observation-based data for the past three decades indicates a reduced dust emission trend, together with an increase in greening and surface roughness within the Sahel. Climate models used to study regional precipitation changes due to Saharan dust yield varied results, both in sign convention and magnitude. Inconsistency of model estimates drives future climate projections for the region that are highly varied and uncertain. We use the NASA-Unified Weather Research and Forecasting (NU-WRF) model to quantify the interaction and feedback between desert dust aerosol and Sahelian precipitation. Using nested domains at fine spatial resolution we resolve changes to mesoscale atmospheric circulation patterns due to dust, for representative phases of El Niño-Southern Oscillation (ENSO). The NU-WRF regional earth system model offers both advanced land surface data and resolvable detail of the mechanisms of the impact of Saharan dust. Results are compared to our previous work assessed over the Western Sahel using the Geophysical Fluid Dynamics Laboratory (GFDL) CM2Mc global climate model, and to other previous regional climate model studies. This prompts further research to help explain the dust-precipitation relationship and recent North African dust emission trends. This presentation will offer a quantitative analysis of differences in radiation budget, energy and moisture fluxes, and atmospheric dynamics due to desert dust aerosol over the Sahel.

Confronting the WRF and RAMS mesoscale models with innovative observations in the Netherlands: Evaluating the boundary layer heat budget

Science.gov (United States)

Steeneveld, G. J.; Tolk, L. F.; Moene, A. F.; Hartogensis, O. K.; Peters, W.; Holtslag, A. A. M.

2011-12-01

The Weather Research and Forecasting Model (WRF) and the Regional Atmospheric Mesoscale Model System (RAMS) are frequently used for (regional) weather, climate and air quality studies. This paper covers an evaluation of these models for a windy and calm episode against Cabauw tower observations (Netherlands), with a special focus on the representation of the physical processes in the atmospheric boundary layer (ABL). In addition, area averaged sensible heat flux observations by scintillometry are utilized which enables evaluation of grid scale model fluxes and flux observations at the same horizontal scale. Also, novel ABL height observations by ceilometry and of the near surface longwave radiation divergence are utilized. It appears that WRF in its basic set-up shows satisfactory model results for nearly all atmospheric near surface variables compared to field observations, while RAMS needed refining of its ABL scheme. An important inconsistency was found regarding the ABL daytime heat budget: Both model versions are only able to correctly forecast the ABL thermodynamic structure when the modeled surface sensible heat flux is much larger than both the eddy-covariance and scintillometer observations indicate. In order to clarify this discrepancy, model results for each term of the heat budget equation is evaluated against field observations. Sensitivity studies and evaluation of radiative tendencies and entrainment reveal that possible errors in these variables cannot explain the overestimation of the sensible heat flux within the current model infrastructure.

A parallel calibration utility for WRF-Hydro on high performance computers

Science.gov (United States)

Wang, J.; Wang, C.; Kotamarthi, V. R.

2017-12-01

A successful modeling of complex hydrological processes comprises establishing an integrated hydrological model which simulates the hydrological processes in each water regime, calibrates and validates the model performance based on observation data, and estimates the uncertainties from different sources especially those associated with parameters. Such a model system requires large computing resources and often have to be run on High Performance Computers (HPC). The recently developed WRF-Hydro modeling system provides a significant advancement in the capability to simulate regional water cycles more completely. The WRF-Hydro model has a large range of parameters such as those in the input table files — GENPARM.TBL, SOILPARM.TBL and CHANPARM.TBL — and several distributed scaling factors such as OVROUGHRTFAC. These parameters affect the behavior and outputs of the model and thus may need to be calibrated against the observations in order to obtain a good modeling performance. Having a parameter calibration tool specifically for automate calibration and uncertainty estimates of WRF-Hydro model can provide significant convenience for the modeling community. In this study, we developed a customized tool using the parallel version of the model-independent parameter estimation and uncertainty analysis tool, PEST, to enabled it to run on HPC with PBS and SLURM workload manager and job scheduler. We also developed a series of PEST input file templates that are specifically for WRF-Hydro model calibration and uncertainty analysis. Here we will present a flood case study occurred in April 2013 over Midwest. The sensitivity and uncertainties are analyzed using the customized PEST tool we developed.

Ensemble using different Planetary Boundary Layer schemes in WRF model for wind speed and direction prediction over Apulia region

Science.gov (United States)

Tateo, Andrea; Marcello Miglietta, Mario; Fedele, Francesca; Menegotto, Micaela; Monaco, Alfonso; Bellotti, Roberto

2017-04-01

The Weather Research and Forecasting mesoscale model (WRF) was used to simulate hourly 10 m wind speed and direction over the city of Taranto, Apulia region (south-eastern Italy). This area is characterized by a large industrial complex including the largest European steel plant and is subject to a Regional Air Quality Recovery Plan. This plan constrains industries in the area to reduce by 10 % the mean daily emissions by diffuse and point sources during specific meteorological conditions named wind days. According to the Recovery Plan, the Regional Environmental Agency ARPA-PUGLIA is responsible for forecasting these specific meteorological conditions with 72 h in advance and possibly issue the early warning. In particular, an accurate wind simulation is required. Unfortunately, numerical weather prediction models suffer from errors, especially for what concerns near-surface fields. These errors depend primarily on uncertainties in the initial and boundary conditions provided by global models and secondly on the model formulation, in particular the physical parametrizations used to represent processes such as turbulence, radiation exchange, cumulus and microphysics. In our work, we tried to compensate for the latter limitation by using different Planetary Boundary Layer (PBL) parameterization schemes. Five combinations of PBL and Surface Layer (SL) schemes were considered. Simulations are implemented in a real-time configuration since our intention is to analyze the same configuration implemented by ARPA-PUGLIA for operational runs; the validation is focused over a time range extending from 49 to 72 h with hourly time resolution. The assessment of the performance was computed by comparing the WRF model output with ground data measured at a weather monitoring station in Taranto, near the steel plant. After the analysis of the simulations performed with different PBL schemes, both simple (e.g. average) and more complex post-processing methods (e.g. weighted average

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

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.

Reduction of systematic biases in regional climate downscaling through ensemble forcing

Energy Technology Data Exchange (ETDEWEB)

Yang, Hongwei; Wang, Bin [Chinese Academy of Sciences, LASG, Institute of Atmospheric Physics, Beijing (China); Wang, Bin [University of Hawaii at Manoa, Department of Meteorology, Honolulu, Hawaii (United States); University of Hawaii at Manoa, International Pacific Research Center, Honolulu, Hawaii (United States)

2012-02-15

Simulations of the East Asian summer monsoon for the period of 1979-2001 were carried out using the Weather Research and Forecast (WRF) model forced by three reanalysis datasets (NCEP-R2, ERA-40, and JRA-25). The experiments forced by different reanalysis data exhibited remarkable differences, primarily caused by uncertainties in the lateral boundary (LB) moisture fluxes over the Bay of Bengal and the Philippine Sea. The climatological mean water vapor convergence into the model domain computed from ERA-40 was about 24% higher than that from the NCEP-R2 reanalysis. We demonstrate that using the ensemble mean of NCEP-R2, ERA-40, and JRA-25 as LB forcing considerably reduced the biases in the model simulation. The use of ensemble forcing improved the performance in simulated mean circulation and precipitation, inter-annual variation in seasonal precipitation, and daily precipitation. The model simulated precipitation was superior to that in the reanalysis in both climatology and year-to-year variations, indicating the added value of dynamic downscaling. The results suggest that models having better performance under one set of LB forcing might worsen when another set of reanalysis data is used as LB forcing. Use of ensemble mean LB forcing for assessing regional climate model performance is recommended. (orig.)

Importance of transboundary transport of biomass burning emissions to regional air quality in Southeast Asia during a high fire event

NARCIS (Netherlands)

Aouizerats, B.; van der Werf, G.R.; Balasubramanian, R.; Betha, R.

2015-01-01

Smoke from biomass and peat burning has a notable impact on ambient air quality and climate in the Southeast Asia (SEA) region. We modeled a large fire-induced haze episode in 2006 stemming mostly from Indonesia using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). We

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.

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

Science.gov (United States)

Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos

2017-07-01

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

Nested High Resolution Modeling of the Impact of Urbanization on Regional Climate in Three Vast Urban Agglomerations in China

Science.gov (United States)

Wang, Jun; Feng, Jinming; Yan, Zhongwei; Hu, Yonghong; Jia, Gensuo

2013-04-01

In this paper, the Weather Research and Forecasting (WRF) model coupled to the Urban Canopy Model (UCM) is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high resolution land use and land cover data, two scenarios are designed to represent the non-urban and current urban land use distributions. By comparing the results of two nested, high resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1? and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban area mainly in summer and change the regional precipitation pattern to a certain extent.

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

Science.gov (United States)

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

2004-06-01

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

Application, evaluation and sensitivity analysis of the coupled WRF-CMAQ system from regional to urban scales

Science.gov (United States)

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science chemical transport model (CTM) capable of simulating the emission, transport and fate of numerous air pollutants. Similarly, the Weather Research and Forecasting (WRF) model is a state-of-the-science mete...

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

Web-GIS platform for monitoring and forecasting of regional climate and ecological changes

Science.gov (United States)

Gordov, E. P.; Krupchatnikov, V. N.; Lykosov, V. N.; Okladnikov, I.; Titov, A. G.; Shulgina, T. M.

2012-12-01

presented. Platform software developed (Shulgina et al, 2012, Okladnikov et al, 2012) includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also data preprocessing, run and visualization of modeling results of models WRF and «Planet Simulator» integrated into the platform is provided. All functions of the center are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of visualization of processing results, selection of geographical region of interest (pan and zoom) and data layers manipulation (order, enable/disable, features extraction). Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches (Shulgina et al, 2011). Using it even unskilled user without specific knowledge can perform computational processing and visualization of large meteorological, climatological and satellite monitoring datasets through unified graphical web-interface.

An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations

KAUST Repository

Xu, Zhongfeng

2012-09-01

An improved dynamical downscaling method (IDD) with general circulation model (GCM) bias corrections is developed and assessed over North America. A set of regional climate simulations is performed with the Weather Research and Forecasting Model (WRF) version 3.3 embedded in the National Center for Atmospheric Research\\'s (NCAR\\'s) Community Atmosphere Model (CAM). The GCM climatological means and the amplitudes of interannual variations are adjusted based on the National Centers for Environmental Prediction (NCEP)-NCAR global reanalysis products (NNRP) before using them to drive WRF. In this study, the WRF downscaling experiments are identical except the initial and lateral boundary conditions derived from the NNRP, original GCM output, and bias-corrected GCM output, respectively. The analysis finds that the IDD greatly improves the downscaled climate in both climatological means and extreme events relative to the traditional dynamical downscaling approach (TDD). The errors of downscaled climatological mean air temperature, geopotential height, wind vector, moisture, and precipitation are greatly reduced when the GCM bias corrections are applied. In the meantime, IDD also improves the downscaled extreme events characterized by the reduced errors in 2-yr return levels of surface air temperature and precipitation. In comparison with TDD, IDD is also able to produce a more realistic probability distribution in summer daily maximum temperature over the central U.S.-Canada region as well as in summer and winter daily precipitation over the middle and eastern United States. © 2012 American Meteorological Society.

Spatial scale separation in regional climate modelling

Energy Technology Data Exchange (ETDEWEB)

Feser, F.

2005-07-01

In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

The air quality and regional climate effects of widespread solar power generation under a changing regulatory environment

Science.gov (United States)

Millstein, D.; Zhai, P.; Menon, S.

2011-12-01

Over the past decade significant reductions of NOx and SOx emissions from coal burning power plants in the U.S. have been achieved due to regulatory action and substitution of new generation towards natural gas and wind power. Low natural gas prices, ever decreasing solar generation costs, and proposed regulatory changes, such as to the Cross State Air Pollution Rule, promise further long-run coal power plant emission reductions. Reduced power plant emissions have the potential to affect ozone and particulate air quality and influence regional climate through aerosol cloud interactions and visibility effects. Here we investigate, on a national scale, the effects on future (~2030) air quality and regional climate of power plant emission regulations in contrast to and combination with policies designed to aggressively promote solar electricity generation. A sophisticated, economic and engineering based, hourly power generation dispatch model is developed to explore the integration of significant solar generation resources (>10% on an energy basis) at various regions across the county, providing detailed estimates of substitution of solar generation for fossil fuel generation resources. Future air pollutant emissions from all sectors of the economy are scaled based on the U.S. Environmental Protection Agency's National Emission Inventory to account for activity changes based on population and economic projections derived from county level U.S. Census data and the Energy Information Administration's Annual Energy Outlook. Further adjustments are made for technological and regulatory changes applicable within various sectors, for example, emission intensity adjustments to on-road diesel trucking due to exhaust treatment and improved engine design. The future year 2030 is selected for the emissions scenarios to allow for the development of significant solar generation resources. A regional climate and air quality model (Weather Research and Forecasting, WRF model) is

Multi-year application of WRF-CAM5 over East Asia-Part I: Comprehensive evaluation and formation regimes of O 3 and PM 2.5

Energy Technology Data Exchange (ETDEWEB)

He, Jian; Zhang, Yang; Wang, Kai; Chen, Ying; Leung, L. Ruby; Fan, Jiwen; Li, Meng; Zheng, Bo; Zhang, Qiang; Duan, Fengkui; He, Kebin

2017-09-01

Accurate simulations of air quality and climate require robust model parameterizations on regional and global scales. The Weather Research and Forecasting model with Chemistry version 3.4.1 has been coupled with physics packages from the Community Atmosphere Model version 5 (CAM5) (WRF-CAM5) to assess the robustness of the CAM5 physics package for regional modeling at higher grid resolutions than typical grid resolutions used in global modeling. In this two-part study, Part I describes the application and evaluation of WRF-CAM5 over East Asia at a horizontal resolution of 36-km for six years: 2001, 2005, 2006, 2008, 2010, and 2011. The simulations are evaluated comprehensively with a variety of datasets from surface networks, satellites, and aircraft. The results show that meteorology is relatively well simulated by WRF-CAM5. However, cloud variables are largely or moderately underpredicted, indicating uncertainties in the model treatments of dynamics, thermodynamics, and microphysics of clouds/ices as well as aerosol-cloud interactions. For chemical predictions, the tropospheric column abundances of CO, NO2, and O3 are well simulated, but those of SO2 and HCHO are moderately overpredicted, and the column HCHO/NO2 indicator is underpredicted. Large biases exist in the surface concentrations of CO, NO2, and PM10 due to uncertainties in the emissions as well as vertical mixing. The underpredictions of NO lead to insufficient O3 titration, thus O3 overpredictions. The model can generally reproduce the observed O3 and PM indicators. These indicators suggest to control NOx emissions throughout the year, and VOCs emissions in summer in big cities and in winter over North China Plain, North/South Korea, and Japan to reduce surface O3, and to control SO2, NH3, and NOx throughout the year to reduce inorganic surface PM.

Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system

International Nuclear Information System (INIS)

Gao, Y; Fu, J S; Drake, J B; Liu, Y; Lamarque, J-F

2012-01-01

This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year). (letter)

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

Regional-Scale Climate Change: Observations and Model Simulations

Energy Technology Data Exchange (ETDEWEB)

Bradley, Raymond S; Diaz, Henry F

2010-12-14

This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, and we conducted studies of changes in phonological indicators based on various climatic thresholds.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

Science.gov (United States)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Abilities and limitations in the use of regional climate models

Energy Technology Data Exchange (ETDEWEB)

Koeltzov, Morten Andreas Oedegaard

2012-11-01

In order to say something about the effect of climate change at the regional level, one takes in use regional climate models. In these models the thesis introduce regional features, which are not included in the global climate models (which are basically in climate research). Regional models can provide good and useful climate projections that add more value than the global climate models, but also introduces an uncertainty in the calculations. How should this uncertainty affect the use of regional climate models?The most common methodology for calculating potential future climate developments are based on different scenarios of possible emissions of greenhouse gases. These scenarios operates as global climate models using physical laws and calculate possible future developments. This is considered mathematical complexed and processes with limited supercomputing capacity calculates the global models for the larger scale of the climate system. To study the effects of climate change are regional details required and the regional models used therefore in a limited area of the climate system. These regional models are driven by data from the global models and refines and improves these data. Impact studies can then use the data from the regional models or data which are further processed to provide more local details using geo-statistical methods. In the preparation of the climate projections is there a minimum of 4 sources of uncertainty. This uncertainty is related to the provision of emission scenarios of greenhouse gases, uncertainties related to the use of global climate models, uncertainty related to the use of regional climate models and the uncertainty of internal variability in the climate system. This thesis discusses the use of regional climate models, and illustrates how the regional climate model adds value to climate projections, and at the same time introduce uncertainty in the calculations. It discusses in particular the importance of the choice of

Impact of spectral nudging on the downscaling of tropical cyclones in regional climate simulations

Science.gov (United States)

Choi, Suk-Jin; Lee, Dong-Kyou

2016-06-01

This study investigated the simulations of three months of seasonal tropical cyclone (TC) activity over the western North Pacific using the Advanced Research WRF Model. In the control experiment (CTL), the TC frequency was considerably overestimated. Additionally, the tracks of some TCs tended to have larger radii of curvature and were shifted eastward. The large-scale environments of westerly monsoon flows and subtropical Pacific highs were unreasonably simulated. The overestimated frequency of TC formation was attributed to a strengthened westerly wind field in the southern quadrants of the TC center. In comparison with the experiment with the spectral nudging method, the strengthened wind speed was mainly modulated by large-scale flow that was greater than approximately 1000 km in the model domain. The spurious formation and undesirable tracks of TCs in the CTL were considerably improved by reproducing realistic large-scale atmospheric monsoon circulation with substantial adjustment between large-scale flow in the model domain and large-scale boundary forcing modified by the spectral nudging method. The realistic monsoon circulation took a vital role in simulating realistic TCs. It revealed that, in the downscaling from large-scale fields for regional climate simulations, scale interaction between model-generated regional features and forced large-scale fields should be considered, and spectral nudging is a desirable method in the downscaling method.

Tropospheric ozone using an emission tagging technique in the CAM-Chem and WRF-Chem models

Science.gov (United States)

Lupascu, A.; Coates, J.; Zhu, S.; Butler, T. M.

2017-12-01

Tropospheric ozone is a short-lived climate forcing pollutant. High concentration of ozone can affect human health (cardiorespiratory and increased mortality due to long-term exposure), and also it damages crops. Attributing ozone concentrations to the contributions from different sources would indicate the effects of locally emitted or transported precursors on ozone levels in specific regions. This information could be used as an important component of the design of emissions reduction strategies by indicating which emission sources could be targeted for effective reductions, thus reducing the burden of ozone pollution. Using a "tagging" approach within the CAM-Chem (global) and WRF-Chem (regional) models, we can quantify the contribution of individual emission of NOx and VOC precursors on air quality. Hence, when precursor emissions of NOx are tagged, we have seen that the largest contributors on ozone levels are the anthropogenic sources, while in the case of precursor emissions of VOCs, the biogenic sources and methane account for more than 50% of ozone levels. Further, we have extended the NOx tagging method in order to investigate continental source region contributions to concentrations of ozone over various receptor regions over the globe, with a zoom over Europe. In general, summertime maximum ozone in most receptor regions is largely attributable to local emissions of anthropogenic NOx and biogenic VOC. During the rest of the year, especially during springtime, ozone in most receptor regions shows stronger influences from anthropogenic emissions of NOx and VOC in remote source regions.

Etude Climat no. 36 'Regional Climate - Air - Energy Plans: a tool for guiding the energy and climate transition in French regions'

International Nuclear Information System (INIS)

De Charentenay, Jeremie; Leseur, Alexia; Bordier, Cecile

2012-01-01

Among the publications of CDC Climat Research, 'Climate Reports' offer in-depth analyses on a given subject. This issue addresses the following points: The Regional Climate-Air-Energy Plan (SRCAE - Schema Regional Climat-Air-Energie) was introduced by the Grenelle II legislation. The Plans are co-authored by the State through its decentralised services and the 'Conseil Regionaux' (regional councils) with the objective to guide climate and energy policy in the 26 French regions through to 2020 and 2050. Starting from an assessment of regional greenhouse gas (GHG) emissions, the SRCAE establishes energy transition scenarios based on the sectoral and structural guidelines that constitute the principal framework of the regional strategy. This report offers a detailed analysis of the strategies chosen by the various Regions for a successful transition to low-carbon energy sources, via the study of eleven SRCAEs that were opened to public consultation before the end of July 2012 (Alsace, Aquitaine, Auvergne, Bourgogne, Centre, Champagne-Ardenne, Ile-de-France, Midi-Pyrenees, Nord-Pas de Calais, Picardie and Rhone-Alpes regions). The wide range of methodologies used by the Regions, both to draw up their inventories of GHG emissions and for their scenarios, means that a quantitative comparison between regions or against the national objectives is not possible. Nevertheless, the report establishes a typology of regions and identifies policies that are common to all regions and those chosen in response to local characteristics. Certain guidelines could be applied by other regions of the same type, or could feed into discussions at national level. The report also indicates that the SRCAEs go beyond the competencies of the Regions, highlighting the role of local, national and European decision-making in the success of a regional energy transition. Particular attention was paid to the building and transport sectors, often identified as having the largest potential for reducing

Water resources management using the WRF-Hydro modelling system: Case-study of the Tono dam in West Africa

Directory of Open Access Journals (Sweden)

E. Naabil

2017-08-01

Full Text Available Water resources are a major source of economic development for most West African (WA countries. There is, however inadequate information on these resources for the purposes of planning, decision-making and management. This paper explores the potential for using a state of the art hydrological model (WRF-Hydro in a fully coupled (i.e. land surface hydrology-atmosphere mode to assess these water resources, particularly the Tono basin in Ghana. The WRF-Hydro model is an enhanced version of the Weather Research and Forecasting model (WRF which allows simulating river discharge. A 2-domain configuration is chosen: an outer domain at 25 km horizontal resolution encompassing the West African Region and an inner domain at 5 km horizontal resolution centered on the Tono basin. The infiltration partition parameter and Manning’s roughness parameter were calibrated to fit the WRF-Hydro simulated discharge with the observed data. The simulations were done from 1999 to 2003, using 1999 as a spin-up period. The results were compared with TRMM precipitation, CRU temperature and available observed hydrological data. The WRF-Hydro model captured the attributes of the “observed” streamflow estimate; with Nash-Sutcliff efficiency (NSE of 0.78 and Pearson’s correlation of 0.89. Further validation of model results is based on using the output from the WRF-Hydro model as input into a water balance model to simulate the dam levels. WRF-Hydro has shown the potential for use in water resource planning (i.e. with respect to streamflow and dam level estimation. However, the model requires further improvement with respect to calibration of model parameters (e.g. baseflow and saturated hydraulic conductivity considering the effect of the accumulation of model bias in dam level estimation.

How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

Directory of Open Access Journals (Sweden)

Claas Teichmann

2013-06-01

Full Text Available Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs. The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming

Climate Change Impacts at Department of Defense Installations

Science.gov (United States)

2017-06-16

Most stakeholders were not comfortable addressing issues related to 8 FIGURE 2 (a) Model Domain Used for the WRF Model Dynamic Downscaling...and NARCCAP-WRFG at 50 km and (b) between PRISM and WRF at 12 km during all months in 1980–2004 (The student t-test result at the 0.005 [and lower...Alavez, A., T. Cavazos, and C. Turrent, 2014: Land–sea thermal contrast and intensity of the North American Monsoon under climate change conditions

Regional climate services: A regional partnership between NOAA and USDA

Science.gov (United States)

Climate services in the Midwest and Northern Plains regions have been enhanced by a recent addition of the USDA Climate Hubs to NOAA’s existing network of partners. This new partnership stems from the intrinsic variability of intra and inter-annual climatic conditions, which makes decision-making fo...

How reliable is the offline couple of WRF and VIC model? And how does high quality land cover data impact the VIC model simulation?

Science.gov (United States)

Tang, C.; Dennis, R. L.

2012-12-01

First, the ability of the offline coupling of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological and climate variables was evaluated. The performance of the offline couple of WRF and VIC was assessed with respect to key simulated variables through a comparison with the calibrated VIC model simulation. A spatiotemporal comparison of the simulated evaporation (ET), soil moisture (SM), runoff, and baseflow produced by the VIC calibrated run (base data) and by the offline coupling run was conducted. The results showed that the offline couple of VIC with WRF was able to achieve good agreement in the simulation of monthly and daily soil moisture, and monthly evaporation. This suggests the VIC coupling should function without causing a large change in the moisture budget. However, the offline coupling showed most disagreement in daily and monthly runoff, and baseflow which is related to errors in WRF precipitation. Second, the sensitivity of the VIC model to the land cover was assessed by performing a sensitivity simulation using the National Land Cover Database (NLCD) instead of the older NLDAS/AVHRR data. Improved land cover is shown to achieve more accurate simulation of the streamflow.

Assessing NARCCAP climate model effects using spatial confidence regions

Directory of Open Access Journals (Sweden)

J. P. French

2017-07-01

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

Meteorological Modeling Using the WRF-ARW Model for Grand Bay Intensive Studies of Atmospheric Mercury

Directory of Open Access Journals (Sweden)

Fong Ngan

2015-02-01

Full Text Available Measurements at the Grand Bay National Estuarine Research Reserve support a range of research activities aimed at improving the understanding of the atmospheric fate and transport of mercury. Routine monitoring was enhanced by two intensive measurement periods conducted at the site in summer 2010 and spring 2011. Detailed meteorological data are required to properly represent the weather conditions, to determine the transport and dispersion of plumes and to understand the wet and dry deposition of mercury. To describe the mesoscale features that might influence future plume calculations for mercury episodes during the Grand Bay Intensive campaigns, fine-resolution meteorological simulations using the Weather Research and Forecasting (WRF model were conducted with various initialization and nudging configurations. The WRF simulations with nudging generated reasonable results in comparison with conventional observations in the region and measurements obtained at the Grand Bay site, including surface and sounding data. The grid nudging, together with observational nudging, had a positive effect on wind prediction. However, the nudging of mass fields (temperature and moisture led to overestimates of precipitation, which may introduce significant inaccuracies if the data were to be used for subsequent atmospheric mercury modeling. The regional flow prediction was also influenced by the reanalysis data used to initialize the WRF simulations. Even with observational nudging, the summer case simulation results in the fine resolution domain inherited features of the reanalysis data, resulting in different regional wind patterns. By contrast, the spring intensive period showed less influence from the reanalysis data.

Future Urban Climate Projection in A Tropical Megacity Based on Global and Regional Scenarios

Science.gov (United States)

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

2017-12-01

Cities in Asian developing countries experience rapid transformation in urban morphology and energy consumption, which correspondingly affects urban climate. Weather Research and Forecasting (WRF) Model coupled with improved single-layer urban canopy model incorporating realistic distribution of urban parameters and anthropogenic heat emission (AHE) in the tropic Jakarta Greater Area was conducted. Simulation was conducted during the dry months from 2006 to 2015 and agreed well with point and satellite observation. The same technology coupled with pseudo global warming (PGW) method based on representative concentration pathways (RCP) scenario 2.6 and 8.5 was conducted to produce futuristic climate condition in 2050. Projected urban morphology and AHE in 2050s were constructed using regional urban growing model with shared socioeconomic pathways (SSP) among its inputs. Compact future urban configuration, based on SSP1, was coupled to RCP2.6. Unrestrained future urban configuration, based on SSP3, was coupled to RCP8.5. Results show that background warming from RCP 2.6 and 8.5 will increase background temperature by 0.55°C and 1.2°C throughout the region, respectively. Future projection of urban sprawl results to an additional 0.3°C and 0.5°C increase on average, with maximum increase of 1.1°C and 1.3°C due to urban effect for RCP2.6/compact and RCP8.5/unrestrained, respectively. Higher moisture content in urban area is indicated in the future due to higher evaporation. Change in urban roughness is likely affect slower wind velocity in urban area and sea breeze front inland penetration the future compare with current condition. Acknowledgement: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

Sensitivity of the Community Multiscale Air Quality (CMAQ model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers

Directory of Open Access Journals (Sweden)

K. W. Appel

2010-02-01

Full Text Available This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5 and the Weather Research and Forecasting (WRF meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ and the other utilized WRF meteorology (WRF-CMAQ, while all other model inputs and options were kept the same. For January, predicted ozone (O₃ mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O₃ mixing ratios are attributed to less dry deposition of O₃ in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO₄²⁻, similar performance for nitrate (NO₃⁻, and slightly worse performance for nitric acid (HNO₃, total carbon (TC and total fine particulate (PM_2.5 mass than the corresponding MM5-CMAQ results. For August, predictions of O₃ were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO₄²⁻ were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u_∗ in the MM5 and WRF model simulations, while

Using Social Media to Expand Peer-to-Peer Discussion in an Online Course about Regional Climate Modeling

Science.gov (United States)

Yarker, M. B.; Mesquita, M. D. S.

2015-12-01

The goal of this project is to make knowledge about regional climate modeling accessible to anyone in any location, regardless of their resources. We accomplish this through the development of a free online course, which introduces novice model users to an educational version of the Weather Research and Forecasting model (e-WRF). These courses are grounded in education theory and have been described in detail at prior AGU meetings (Kelsey et al. 2014, Walton et al. 2014, Yarker & Mesquita 2013). Research indicates that effective dialogue is an important component for successful learning to occur and displays the following elements: asking complex questions, deep discussion, and use of evidence to construct arguments (Benus et al. 2013). These can happen between the student and tutor, but peer-to-peer interaction is especially important as well as the most difficult aspect of social constructivism to meet, especially in an online setting. In our online courses, standard course forums were underutilized and generally only used to ask the tutor clarifying questions or troubleshoot error messages. To rectify this problem, we began using social media to facilitate conversation and notice vast improvement in peer-to-peer communication. Moreover, we created a community of over 700 regional climate modelers from around the world, sharing information, asking questions, and creating research projects relating to climate change. Data was gathered by qualitatively analyzing forum and Facebook posts and quantitatively analyzing survey data from participants in both courses. Facebook participants posted on the group more often about a wider variety of topics than the forum participants. Additionally, there were statistically significant increase ('student' t test and Mann-Whitney test) in the elements of effective dialogue. We conclude that social media can serve as a possible tool in the development of online learning, especially for difficult concepts like regional climate

Implement a Sub-grid Turbulent Orographic Form Drag in WRF and its application to Tibetan Plateau

Science.gov (United States)

Zhou, X.; Yang, K.; Wang, Y.; Huang, B.

2017-12-01

Sub-grid-scale orographic variation exerts turbulent form drag on atmospheric flows. The Weather Research and Forecasting model (WRF) includes a turbulent orographic form drag (TOFD) scheme that adds the stress to the surface layer. In this study, another TOFD scheme has been incorporated in WRF3.7, which exerts an exponentially decaying drag on each model layer. To investigate the effect of the new scheme, WRF with the old and new one was used to simulate the climate over the complex terrain of the Tibetan Plateau. The two schemes were evaluated in terms of the direct impact (on wind) and the indirect impact (on air temperature, surface pressure and precipitation). Both in winter and summer, the new TOFD scheme reduces the mean bias in the surface wind, and clearly reduces the root mean square error (RMSEs) in comparisons with the station measurements (Figure 1). Meanwhile, the 2-m air temperature and surface pressure is also improved (Figure 2) due to the more warm air northward transport across south boundary of TP in winter. The 2-m air temperature is hardly improved in summer but the precipitation improvement is more obvious, with reduced mean bias and RMSEs. This is due to the weakening of water vapor flux (at low-level flow with the new scheme) crossing the Himalayan Mountains from South Asia.

A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations

Directory of Open Access Journals (Sweden)

Hengyue Zhang

2017-09-01

Full Text Available The urban heat island effect (UHI for inner land regions was investigated using satellite data, ground observations, and simulations with an Single-Layer Urban Canopy Parameterization (SLUCP coupled into the regional Weather Research Forecasting model (WRF, http://wrf-model.org/index.php. Specifically, using the satellite-observed surface skin temperatures (Tskin, the intensity of the UHI was first compared for two inland cities (Xi’an City, China, and Oklahoma City (OKC, which have different city populations and building densities. The larger population density and larger building density in Xi’an lead to a stronger skin-level UHI by 2 °C. However, the ground observed 2 m surface air temperature (Tair observations showed an urban cooling island effect (UCI over the downtown region in OKC during the daytime of 19 July 2003, from a DOE field campaign (Joint Urban 2003. To understand this contrast between satellite-based Tskin and ground-based Tair, a sensitivity study using WRF/SLUCP was analyzed. The model reproduced a UCI in OKC. Furthermore, WRF/Noah/SLUCM simulations were also compared with the Joint Urban 2003 ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLUCM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions, and energy fluxes reasonably well.

The regional climate model RegCM3 performances over several regions and climate regimes

Science.gov (United States)

Coppola, E.; Rauscher, S.; Gao, X.; Giorgi, F.; Im, E. S.; Mariotti, L.; Seth, A.; Sylla, M. B.

2009-04-01

Regional Climate models are more and more needed to provide high resolution regional climate information in climate impact studies. Water availability in a future scenario is the main request of policy makers for adaptation and mitigation purposes. However precipitation changes are unlikely to be as spatially coherent as temperature changes and they are closely related to the regional model itself. In addition model skill varies regionally. An example of several ICTP regional climate model (RegCM3) simulations is reported over China, Korea, Africa, Central and Southern America, Europe and Australia. Over China, Australia, and Korea the regional model improves the simulation compared to the driving GCM when compared with CRU observations. In China, for example, the higher resolution of the regional model inhibits the penetration of the monsoon precipitation front from the southern slope of the Himalaya onto the Tibetan Plateau. In Korea the nested domain simulation (20 km) shows an encouraging performance with regard to capturing extreme precipitation episodes and the finer spatial distribution reflects the detailed geography of the Korean Peninsula. Over South America, RegCM captures the annual cycle of precipitation over Northeast Brazil and the South American Monsoon region, although the monsoon onset occurs too early in the model. Precipitation over the Amazon is not well captured, with too little precipitation associated with weak easterlies and reduced moisture transport into the interior of the continent. RegCM simulates the annual cycle of precipitation over Central America and the Caribbean fairly well; in particular, the complex spatial distribution of the Mid-Summer Drought, a decrease in precipitation that occurs during the middle of the rainy season in July and August, is better captured by RegCM than by the GCM. In addition, RegCM simulates the strength and position of the Caribbean low level jet, a mesoscale feature related to precipitation anomalies

Modelling and observing urban climate in the Netherlands

International Nuclear Information System (INIS)

Van Hove, B.; Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B.; Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E.

2011-06-01

The main aims of the present study are: (1) to evaluate the performance of two well-known mesoscale NWP (numerical weather prediction) models coupled to a UCM (Urban Canopy Models), and (2) to develop a proper measurement strategy for obtaining meteorological data that can be used in model evaluation studies. We choose the mesoscale models WRF (Weather Research and Forecasting Model) and RAMS (Regional Atmospheric Modeling System), respectively, because the partners in the present project have a large expertise with respect to these models. In addition WRF and RAMS have been successfully used in the meteorology and climate research communities for various purposes, including weather prediction and land-atmosphere interaction research. Recently, state-of-the-art UCM's were embedded within the land surface scheme of the respective models, in order to better represent the exchange of heat, momentum, and water vapour in the urban environment. Key questions addressed here are: What is the general model performance with respect to the urban environment?; How can useful and observational data be obtained that allow sensible validation and further parameterization of the models?; and Can the models be easily modified to simulate the urban climate under Dutch climatic conditions, urban configuration and morphology? Chapter 2 reviews the available Urban Canopy Models; we discuss their theoretical basis, the different representations of the urban environment, the required input and the output. Much of the information was obtained from the Urban Surface Energy Balance: Land Surface Scheme Comparison project (PILPS URBAN, PILPS stands for Project for Inter-comparison of Land-Surface Parameterization Schemes). This project started in March 2008 and was coordinated by the Department of Geography, King's College London. In order to test the performance of our models we participated in this project. Chapter 3 discusses the main results of the first phase of PILPS URBAN. A first

CARICOF - The Caribbean Regional Climate Outlook Forum

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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

Intercomparison of Streamflow Simulations between WRF-Hydro and Hydrology Laboratory-Research Distributed Hydrologic Model Frameworks

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KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.

Variability of wet troposphere delays over inland reservoirs as simulated by a high-resolution regional climate model

Science.gov (United States)

Clark, E.; Lettenmaier, D. P.

2014-12-01

Satellite radar altimetry is widely used for measuring global sea level variations and, increasingly, water height variations of inland water bodies. Existing satellite radar altimeters measure water surfaces directly below the spacecraft (approximately at nadir). Over the ocean, most of these satellites use radiometry to measure the delay of radar signals caused by water vapor in the atmosphere (also known as the wet troposphere delay (WTD)). However, radiometry can only be used to estimate this delay over the largest inland water bodies, such as the Great Lakes, due to spatial resolution issues. As a result, atmospheric models are typically used to simulate and correct for the WTD at the time of observations. The resolutions of these models are quite coarse, at best about 5000 km2 at 30˚N. The upcoming NASA- and CNES-led Surface Water and Ocean Topography (SWOT) mission, on the other hand, will use interferometric synthetic aperture radar (InSAR) techniques to measure a 120-km-wide swath of the Earth's surface. SWOT is expected to make useful measurements of water surface elevation and extent (and storage change) for inland water bodies at spatial scales as small as 250 m, which is much smaller than current altimetry targets and several orders of magnitude smaller than the models used for wet troposphere corrections. Here, we calculate WTD from very high-resolution (4/3-km to 4-km) simulations of the Weather Research and Forecasting (WRF) regional climate model, and use the results to evaluate spatial variations in WTD. We focus on six U.S. reservoirs: Lake Elwell (MT), Lake Pend Oreille (ID), Upper Klamath Lake (OR), Elephant Butte (NM), Ray Hubbard (TX), and Sam Rayburn (TX). The reservoirs vary in climate, shape, use, and size. Because evaporation from open water impacts local water vapor content, we compare time series of WTD over land and water in the vicinity of each reservoir. To account for resolution effects, we examine the difference in WRF

Coupling West WRF to GSSHA with GSSHApy

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Snow, A. D.

2017-12-01

The West WRF output data is in the gridded NetCDF output format containing the required forcing data needed to run a GSSHA simulation. These data include precipitation, pressure, temperature, relative humidity, cloud cover, wind speed, and solar radiation. Tools to reproject, resample, and reformat the data for GSSHA have recently been added to the open source Python library GSSHApy (https://github.com/ci-water/gsshapy). These tools have created a connection that has made it possible to run forecasts using the West WRF forcing data with GSSHA to produce both streamflow and lake level predictions.

Learning to love the rain in Bergen (Norway) and other lessons from a Climate Services neophyte

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Sobolowski, Stefan; Wakker, Joyce

2014-05-01

A question that is often asked of regional climate modelers generally, and Climate Service providers specifically, is: "What is the added-value of regional climate simulations and how can I use this information?" The answer is, unsurprisingly, not straightforward and depends greatly on what one needs to know. In particular it is important for scientist to communicate directly with the users of this information to determine what kind of information is important for them to do their jobs. This study is part of the ECLISE project (Enabling Climate Information Services for Europe) and involves a user at the municipality of Bergen's (Norway) water and drainage administration and a provider from Uni Research and the Bjerknes Center for Climate Research. The water and drain administration is responsible for communicating potential future changes in extreme precipitation, particularly short-term high-intensity rainfall, which is common in Bergen and making recommendations to the engineering department for changes in design criteria. Thus, information that enables better decision-making is crucial. This study then actually has two relevant components for climate services: 1) is a scientific exercise to evaluate the performance of high resolution regional climate simulations and their ability to reproduce high intensity short duration precipitation and 2) an exercise in communication between a provider community and user community with different concerns, mandates, methodological approaches and even vocabularies. A set of Weather Research and Forecasting (WRF) simulations was run at high resolution (8km) over a large domain covering much of Scandinavia and Northern Europe. One simulation was driven by so-called "perfect" boundary conditions taken from reanalysis data (ERA-interim, 1989-2010) the second and third simulations used Norway's global climate model as boundary forcing (NorESM) and were run for a historical period (1950-2005) and a 30yr. end of the century time

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

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Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human

Trend analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections.

Science.gov (United States)

Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L

2017-08-15

The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.

The regional characteristics of climatic change in China

International Nuclear Information System (INIS)

Chen Longxun

1994-01-01

Using abundant historical records, the Chinese climatologists have analyzed regional climatic change during the past 2,000 years. Recently, more research on regional climatic change has been done by using the data of the instrumental period. The data show that Chinese climatic change has obvious regional characteristics. The average temperature in the whole country has kept increasing since the last century, and reached its highest value in the 1940s, then it decreased. Although there was a warming trend in the 1980s, the temperature declined again. Especially in the area south of 35 degree N and east of 100 degree E in the mainland China, the air temperature decreased continuously from the 1940s. So climatic change in China is not consistent with global warming, but has its own regional characteristics

High-resolution WRF-LES simulations for real episodes: A case study for prealpine terrain

Science.gov (United States)

Hald, Cornelius; Mauder, Matthias; Laux, Patrick; Kunstmann, Harald

2017-04-01

While in most large or regional scale weather and climate models turbulence is parametrized, LES (Large Eddy Simulation) allows for the explicit modeling of turbulent structures in the atmosphere. With the exponential growth in available computing power the technique has become more and more applicable, yet it has mostly been used to model idealized scenarios. It is investigated how well WRF-LES can represent small scale weather patterns. The results are evaluated against different hydrometeorological measurements. We use WRF-LES to model the diurnal cycle for a 48 hour episode in summer over moderately complex terrain in southern Germany. The model setup uses a high resolution digital elevation model, land use and vegetation map. The atmospheric boundary conditions are set by reanalysis data. Schemes for radiation and microphysics and a land-surface model are employed. The biggest challenge in modeling arises from the high horizontal resolution of dx = 30m, since the subgrid-scale model then requires a vertical resolution dz ≈ 10m for optimal results. We observe model instabilities and present solutions like smoothing of the surface input data, careful positioning of the model domain and shortening of the model time step down to a twentieth of a second. Model results are compared to an array of various instruments including eddy covariance stations, LIDAR, RASS, SODAR, weather stations and unmanned aerial vehicles. All instruments are part of the TERENO pre-Alpine area and were employed in the orchestrated measurement campaign ScaleX in July 2015. Examination of the results show reasonable agreement between model and measurements in temperature- and moisture profiles. Modeled wind profiles are highly dependent on the vertical resolution and are in accordance with measurements only at higher wind speeds. A direct comparison of turbulence is made difficult by the purely statistical character of turbulent motions in the model.

Strengthening Climate Services Capabilities and Regional Engagement at NOAA's National Climatic Data Center

Science.gov (United States)

Shea, E.

2008-12-01

The demand for sector-based climate information is rapidly expanding. In order to support this demand, it is crucial that climate information is managed in an effective, efficient, and user-conscious manner. NOAA's National Climatic Data Center is working closely with numerous partners to develop a comprehensive interface that is authoritative, accessible, and responsive to a variety of sectors, stakeholders, and other users. This talk will explore these dynamics and activities, with additional perspectives on climate services derived from the regional and global experiences of the NOAA Integrated Data and Environmental Applications (IDEA) Center in the Pacific. The author will explore the importance of engaging partners and customers in the development, implementation and emergence of a national climate service program. The presentation will draw on the author's experience in climate science and risk management programs in the Pacific, development of regional and national climate services programs and insights emerging from climate services development efforts in NCDC. In this context, the author will briefly discuss some of guiding principles for effective climate services and applications including: - Early and continuous dialogue, partnership and collaboration with users/customers; - Establishing and sustaining trust and credibility through a program of shared learning and joint problem- solving; - Understanding the societal context for climate risk management and using a problem-focused approach to the development of products and services; - Addressing information needs along a continuum of timescales from extreme events to long-term change; and - Embedding education, outreach and communications activities as critical program elements in effective climate services. By way of examples, the author will reference lessons learned from: early Pacific Island climate forecast applications and climate assessment activities; the implementation of the Pacific Climate

High-Resolution WRF Forecasts of Lightning Threat

Science.gov (United States)

Goodman, S. J.; McCaul, E. W., Jr.; LaCasse, K.

2007-01-01

Tropical Rainfall Measuring Mission (TRMM)lightning and precipitation observations have confirmed the existence of a robust relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of the Weather Research and Forecast (WRF) model, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Initial experiments using 6-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. The WRF has been initialized on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data. An array of subjective and objective statistical metrics is employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

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

Natural emissions under future climate condition and their effects on surface ozone in the Yangtze River Delta region, China

Science.gov (United States)

Xie, Min; Shu, Lei; Wang, Ti-jian; Liu, Qian; Gao, Da; Li, Shu; Zhuang, Bing-liang; Han, Yong; Li, Meng-meng; Chen, Pu-long

2017-02-01

The natural emissions of ozone precursors (NOx and VOCs) are sensitive to climate. Future climate change can impact O3 concentrations by perturbing these emissions. To better estimate the variation of natural emissions under different climate conditions and understand its effect on surface O3, we model the present and the future air quality over the Yangtze River Delta (YRD) region by running different simulations with the aid of the WRF-CALGRID model system that contains a natural emission module. Firstly, we estimate the natural emissions at present and in IPCC A1B scenario. The results show that biogenic VOC emission and soil NOx emission over YRD in 2008 is 657 Gg C and 19.1 Gg N, respectively. According to climate change, these emissions in 2050 will increase by 25.5% and 11.5%, respectively. Secondly, the effects of future natural emissions and meteorology on surface O3 are investigated and compared. It is found that the variations in meteorological fields can significantly alter the spatial distribution of O3 over YRD, with the increases of 5-15 ppb in the north and the decreases of -5 to -15 ppb in the south. However, only approximately 20% of the surface O3 increases caused by climate change can be attributed to the natural emissions, with the highest increment up to 2.4 ppb. Finally, Ra (the ratio of impacts from NOx and VOCs on O3 formation) and H2O2/HNO3 (the ratio between the concentrations of H2O2 and HNO3) are applied to study the O3 sensitivity in YRD. The results show that the transition value of H2O2/HNO3 will turn from 0.3 to 0.5 in 2008 to 0.4-0.8 in 2050. O3 formation in the YRD region will be insensitive to VOCs under future climate condition, implying more NOx need to be cut down. Our findings can help us understand O3 variation trend and put forward the reasonable and effective pollution control policies in these famous polluted areas.

South Baltic wind atlas. South Baltic offshore wind energy regions project

Energy Technology Data Exchange (ETDEWEB)

Pena, A.; Hahmann, A.; Hasager, C.B.; Bingoel, F.; Karagali, I.; Badger, J.; Badger, M.; Clausen, Niels-Erik

2011-05-15

A first version of a wind atlas for the South Baltic Sea has been developed using the WRF mesoscale model and verified by data from tall Danish and German masts. Six different boundary-layer parametrization schemes were evaluated by comparing the WRF results to the observed wind profiles at the masts. The WRF modeling was done in a nested domain of high spatial resolution for 4 years. In addition the long-term wind statistics using the NCAR-NCEP reanalysis data were performed during 30 years to provide basis for a long-term adjustment of the results and the final WRF results include a weighting for the long-term trends variability in the South Baltic Sea. Observations from Earth observing satellites were used to evaluate the spatial resolution of the WRF model results near the surface. The QuikSCAT and the WRF results compared well whereas the Envisat ASAR mean wind map showed some variation to the others. The long-term analysis revealed that the South Baltic Sea has a spatially highly variable wind climate during the 30-years. (Author)

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

A changing climate: impacts on human exposures to O3 using ...

Science.gov (United States)

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur

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.

A characteristics of East Asian climate using high-resolution regional climate model

Science.gov (United States)

Yhang, Y.

2013-12-01

Climate research, particularly application studies for water, agriculture, forestry, fishery and energy management require fine scale multi-decadal information of meteorological, oceanographic and land states. Unfortunately, spatially and temporally homogeneous multi-decadal observations of these variables in high horizontal resolution are non-existent. Some long term surface records of temperature and precipitation exist, but the number of observation is very limited and the measurements are often contaminated by changes in instrumentation over time. Some climatologically important variables, such as soil moisture, surface evaporation, and radiation are not even measured over most of East Asia. Reanalysis is one approach to obtaining long term homogeneous analysis of needed variables. However, the horizontal resolution of global reanalysis is of the order of 100 to 200 km, too coarse for many application studies. Regional climate models (RCMs) are able to provide valuable regional finescale information, especially in regions where the climate variables are strongly regulated by the underlying topography and the surface heterogeneity. In this study, we will provide accurately downscaled regional climate over East Asia using the Global/Regional Integrated Model system [GRIMs; Hong et al. 2013]. A mixed layer model is embedded within the GRIMs in order to improve air-sea interaction. A detailed description of the characteristics of the East Asian summer and winter climate will be presented through the high-resolution numerical simulations. The increase in horizontal resolution is expected to provide the high-quality data that can be used in various application areas such as hydrology or environmental model forcing.

Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

2015-05-01

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

Future extreme events in European climate: An exploration of regional climate model projections

DEFF Research Database (Denmark)

Beniston, M.; Stephenson, D.B.; Christensen, O.B.

2007-01-01

-90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

Final Report for Cloud-Aerosol Physics in Super-Parameterized Atmospheric Regional Climate Simulations (CAP-SPARCS)(DE-SC0002003) for 8/15/2009 through 8/14/2012

Energy Technology Data Exchange (ETDEWEB)

Russell, Lynn M; Somerville, Richard C.J.

2012-11-05

Improving the representation of local and non-local aerosol interactions in state-of-the-science regional climate models is a priority for the coming decade (Zhang, 2008). With this aim in mind, we have combined two new technologies that have a useful synergy: (1) an aerosol-enabled regional climate model (Advanced Weather Research and Forecasting Model with Chemistry WRF-Chem), whose primary weakness is a lack of high quality boundary conditions and (2) an aerosol-enabled multiscale modeling framework (PNNL Multiscale Aerosol Climate Model (MACM)), which is global but captures aerosol-convection-cloud feedbacks, and thus an ideal source of boundary conditions. Combining these two approaches has resulted in an aerosol-enabled modeling framework that not only resolves high resolution details in a particular region, but crucially does so within a global context that is similarly faithful to multi-scale aerosol-climate interactions. We have applied and improved the representation of aerosol interactions by evaluating model performance over multiple domains, with (1) an extensive evaluation of mid-continent precipitation representation by multiscale modeling, (2) two focused comparisons to transport of aerosol plumes to the eastern United States for comparison with observations made as part of the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT), with the first being idealized and the second being linked to an extensive wildfire plume, and (3) the extension of these ideas to the development of a new approach to evaluating aerosol indirect effects with limited-duration model runs by nudging to observations. This research supported the work of one postdoc (Zhan Zhao) for two years and contributed to the training and research of two graduate students. Four peer-reviewed publications have resulted from this work, and ground work for a follow-on project was completed.

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-...

WRF Simulation over the Eastern Africa by use of Land Surface Initialization

Science.gov (United States)

Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

2014-12-01

The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order

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

Science.gov (United States)

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

2014-05-01

Volumes of environmental data archives are growing immensely due to recent models, high performance computers and sensors development. It makes impossible their comprehensive analysis in conventional manner on workplace using in house computing facilities, data storage and processing software at hands. One of possible answers to this challenge is creation of virtual research environment (VRE), which should provide a researcher with an integrated access to huge data resources, tools and services across disciplines and user communities and enable researchers to process structured and qualitative data in virtual workspaces. VRE should integrate data, network and computing resources providing interdisciplinary climatic research community with opportunity to get profound understanding of ongoing and possible future climatic changes and their consequences. Presented are first steps and plans for development of VRE prototype element aimed at regional climatic and ecological monitoring and modeling as well as at continuous education and training support. Recently developed experimental software and hardware platform aimed at integrated analysis of heterogeneous georeferenced data "Climate" (http://climate.scert.ru/, Gordov et al., 2013; Shulgina et al., 2013; Okladnikov et al., 2013) is used as a VRE element prototype and approach test bench. VRE under development will integrate on the base of geoportal distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. VRE specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenaria. Currently the VRE element is accessible via developed geoportal at the same link (http://climate.scert.ru/) and integrates the WRF and «Planet Simulator» models, basic reanalysis and instrumental

On the use of nudging techniques for regional climate modeling: application for tropical convection

Science.gov (United States)

Pohl, Benjamin; Crétat, Julien

2014-09-01

Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments.

Coupling of WRF and Building-resolved CFD Simulations for Greenhouse Gas Transport and Dispersion

Science.gov (United States)

Prasad, K.; Hu, H.; McDermott, R.; Lopez-Coto, I.; Davis, K. J.; Whetstone, J. R.; Lauvaux, T.

2014-12-01

The Indianapolis Flux Experiment (INFLUX) aims to use a top-down inversion methodology to quantify sources of Greenhouse Gas (GHG) emissions over an urban domain with high spatial and temporal resolution. Atmospheric transport of tracer gases from an emission source to a tower mounted receptor are usually conducted using the Weather Research and Forecasting (WRF) model. WRF is used extensively in the atmospheric community to simulate mesoscale atmospheric transport. For such simulations, WRF employs a parameterized turbulence model and does not resolve the fine scale dynamics that are generated by the flow around buildings and communities that are part of a large city. Since the model domain includes the city of Indianapolis, much of the flow of interest is over an urban topography. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model to perform large eddy simulations of flow around buildings, but it has not been nested within a larger-scale atmospheric transport model such as WRF. FDS has the potential to evaluate the impact of complex urban topography on near-field dispersion and mixing that cannot be simulated with a mesoscale atmospheric model, and which may be important to determining urban GHG emissions using atmospheric measurements. A methodology has been developed to run FDS as a sub-grid scale model within a WRF simulation. The coupling is based on nudging the FDS flow field towards the one computed by WRF, and is currently limited to one way coupling performed in an off-line mode. Using the coupled WRF / FDS model, NIST will investigate the effects of the urban canopy at horizontal resolutions of 2-10 m. The coupled WRF-FDS simulations will be used to calculate the dispersion of tracer gases in an urban domain and to evaluate the upwind areas that contribute to tower observations, referred to in the inversion community as influence functions. Predicted mixing ratios will be compared with tower measurements and WRF simulations

Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

Science.gov (United States)

Tan, Elcin

A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem

Directory of Open Access Journals (Sweden)

Q. Yang

2011-12-01

Full Text Available This study assesses the ability of the recent chemistry version (v3.3 of the Weather Research and Forecasting (WRF-Chem model to simulate boundary layer structure, aerosols, stratocumulus clouds, and energy fluxes over the Southeast Pacific Ocean. Measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx and satellite retrievals (i.e., products from the MODerate resolution Imaging Spectroradiometer (MODIS, Clouds and Earth's Radiant Energy System (CERES, and GOES-10 are used for this assessment. The Morrison double-moment microphysics scheme is newly coupled with interactive aerosols in the model. The 31-day (15 October–16 November 2008 WRF-Chem simulation with aerosol-cloud interactions (AERO hereafter is also compared to a simulation (MET hereafter with fixed cloud droplet number concentrations in the microphysics scheme and simplified cloud and aerosol treatments in the radiation scheme. The well-simulated aerosol quantities (aerosol number, mass composition and optical properties, and the inclusion of full aerosol-cloud couplings lead to significant improvements in many features of the simulated stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the simulation of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer (MBL depth by 130 m from that of the MET simulation. These differences are associated with weaker entrainment and stronger mean subsidence at the top of the MBL in AERO. Mean top-of-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with

Projected Impacts of Bioenergy-Demand-Induced Land Use and Cover Changes on Regional Climate in Central Europe

Directory of Open Access Journals (Sweden)

Fang Yin

2013-01-01

Full Text Available Energy shortfalls are becoming more and more serious all over the world, and worldwide governments have tried to promote the development of biofuels in order to mitigate the climatic impacts of massive fossil fuel consumption. Since the land is the main input factor of the bioenergy production, the development of biofuels will inevitably lead to change of the land use structure and allocation and thereby affect the climate system. With Central Europe as the study area, this study explored the impacts of land use/land cover change (LUCC on climate under the influence of demand of bioenergy production for land resources. First, the land use structure from 2010 to 2050 is simulated with the Agriculture and Land Use model in MiniCam. The result indicates that the main conversion will be mainly from grassland and forest to cropland and from cropland to grassland. Then the Dynamics of Land System model was used to spatially simulate the LUCC in the future. The impacts of LUCC on the climate were analyzed on the basis of simulation with the Weather Research and Forecasting (WRF model. The climate change will be characterized by the increase of latent heat flux and temperature and the decrease of precipitation.

Precipitation recycling in West Africa - regional modeling, evaporation tagging and atmospheric water budget analysis

Science.gov (United States)

Arnault, Joel; Kunstmann, Harald; Knoche, Hans-Richard

2015-04-01

Many numerical studies have shown that the West African monsoon is highly sensitive to the state of the land surface. It is however questionable to which extend a local change of land surface properties would affect the local climate, especially with respect to precipitation. This issue is traditionally addressed with the concept of precipitation recycling, defined as the contribution of local surface evaporation to local precipitation. For this study the West African monsoon has been simulated with the Weather Research and Forecasting (WRF) model using explicit convection, for the domain (1°S-21°N, 18°W-14°E) at a spatial resolution of 10 km, for the period January-October 2013, and using ERA-Interim reanalyses as driving data. This WRF configuration has been selected for its ability to simulate monthly precipitation amounts and daily histograms close to TRMM (Tropical Rainfall Measuring Mission) data. In order to investigate precipitation recycling in this WRF simulation, surface evaporation tagging has been implemented in the WRF source code as well as the budget of total and tagged atmospheric water. Surface evaporation tagging consists in duplicating all water species and the respective prognostic equations in the source code. Then, tagged water species are set to zero at the lateral boundaries of the simulated domain (no inflow of tagged water vapor), and tagged surface evaporation is considered only in a specified region. All the source terms of the prognostic equations of total and tagged water species are finally saved in the outputs for the budget analysis. This allows quantifying the respective contribution of total and tagged atmospheric water to atmospheric precipitation processes. The WRF simulation with surface evaporation tagging and budgets has been conducted two times, first with a 100 km2 tagged region (11-12°N, 1-2°W), and second with a 1000 km2 tagged region (7-16°N, 6°W -3°E). In this presentation we will investigate hydro

REGIONAL CLIMATE MODELING STUDY FOR THE CARPATHIAN REGION USING REGCM4 EXPERIMENTS

Directory of Open Access Journals (Sweden)

PIECZKA I.

2015-03-01

Full Text Available The newest model version of RegCM is adapted with the ultimate aim of providing climate projection for the Carpathian region with 10 km horizontal resolution. For this purpose, first, coarse resolution reanalysis data and global climate model outputs are used to drive 50 km resolution model experiments, from which the outputs are used to provide necessary boundary conditions for the fine scale model runs. Besides the historical runs (for the period 1981-2010, RCP4.5 scenario is also analyzed in this paper for the 21st century. These experiments are essential since they form the basis of national climate and adaptation strategies by providing detailed regional scale climatic projections and enabling specific impact studies for various sectors.

Study of atmospheric condition during the heavy rain event in Bojonegoro using weather research and forecasting (WRF) model: case study 9 February 2017

Science.gov (United States)

Saragih, I. J. A.; Meygatama, A. G.; Sugihartati, F. M.; Sidauruk, M.; Mulsandi, A.

2018-03-01

During 2016, there are frequent heavy rains in the Bojonegoro region, one of which is rain on 9 February 2016. The occurrence of heavy rainfall can cause the floods that inundate the settlements, rice fields, roads, and public facilities. This makes it important to analyze the atmospheric conditions during the heavy rainfall events in Bojonegoro. One of the analytical methods that can be used is using WRF-Advanced Research WRF (WRF-ARW) model. This study was conducted by comparing the rain analysis from WRF-ARW model with the Himawari-8 satellite imagery. The data used are Final Analysis (FNL) data for the WRF-ARW model and infrared (IR) channel for Himawari-8 satellite imagery. The data are processed into the time-series images and then analyzed descriptively. The meteorological parameters selected to be analyzed are relative humidity, vortices, divergences, air stability index, and precipitation. These parameters are expected to indicate the existence of a convective activity in Bojonegoro during the heavy rainfall event. The Himawari-8 satellite imagery shows that there is a cluster of convective clouds in Bojonegoro during the heavy rainfall event. The lowest value of the cloud top temperature indicates that the cluster of convective clouds is a cluster of Cumulonimbus cloud (CB).

Inception of the Laurentide Ice Sheet using asynchronous coupling of a regional atmospheric model and an ice model

Science.gov (United States)

Birch, L.; Cronin, T.; Tziperman, E.

2017-12-01

The climate over the past 0.8 million years has been dominated by ice ages. Ice sheets have grown about every 100 kyrs, starting from warm interglacials, until they spanned continents. State-of-the-art global climate models (GCMs) have difficulty simulating glacial inception, or the transition of Earth's climate from an interglacial to a glacial state. It has been suggested that this failure may be related to their poorly resolved local mountain topography, due to their coarse spatial resolution. We examine this idea as well as the possible role of ice flow dynamics missing in GCMs. We investigate the growth of the Laurentide Ice Sheet at 115 kya by focusing on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred. We use the Weather Research and Forecasting model (WRF) in a regional, cloud-resolving configuration with resolved mountain terrain to explore how quickly Baffin Island could become glaciated with the favorable yet realizable conditions of 115 kya insolation, cool summers, and wet winters. Using the model-derived mountain glacier mass balance, we force an ice sheet model based on the shallow-ice approximation, capturing the ice flow that may be critical to the spread of ice sheets away from mountain ice caps. The ice sheet model calculates the surface area newly covered by ice and the change in the ice surface elevation, which we then use to run WRF again. Through this type of iterated asynchronous coupling, we investigate how the regional climate responds to both larger areas of ice cover and changes in ice surface elevation. In addition, we use the NOAH-MP Land model to characterize the importance of land processes, like refreezing. We find that initial ice growth on the Penny Ice Cap causes regional cooling that increases the accumulation on the Barnes Ice Cap. We investigate how ice and topography changes on Baffin Island may impact both the regional climate and the large-scale circulation.

Regional climate change and national responsibilities

Science.gov (United States)

Hansen, James; Sato, Makiko

2016-03-01

Global warming over the past several decades is now large enough that regional climate change is emerging above the noise of natural variability, especially in the summer at middle latitudes and year-round at low latitudes. Despite the small magnitude of warming relative to weather fluctuations, effects of the warming already have notable social and economic impacts. Global warming of 2 °C relative to preindustrial would shift the ‘bell curve’ defining temperature anomalies a factor of three larger than observed changes since the middle of the 20th century, with highly deleterious consequences. There is striking incongruity between the global distribution of nations principally responsible for fossil fuel CO2 emissions, known to be the main cause of climate change, and the regions suffering the greatest consequences from the warming, a fact with substantial implications for global energy and climate policies.

Climate Change Assessments for Lakes Region of Turkey

Directory of Open Access Journals (Sweden)

Ayten Erol

2012-07-01

Full Text Available Climate change is one of the most important challenges for forestry. Forests are known to be most efficient natural tools to ensure availability and quality of water in many regions. Besides, planning of forest resources towards water quality and quantity is essential in countries that are expected to face with more frequent drought periods in the next decades due to climate change. Watershed management concept has been supposed as the primary tool to plan natural resources in a more efficient and sustainable way by both academicians and practitioners to mitigate and adapt climate change. Forest cover among other land use types provides the best regulating mechanism to mitigate erosion, sedimentation, desertification, and pollution. In addition, climate change can potentially affect forest stand dynamics by influencing the availability of water resources. Therefore, the amount of forest cover in a watershed is an indicator of climate change mitigation and adaptation. Climate change is a concern and risk for the sustainability of water resources in Lakes Region of Turkey. The objective of this study is to make a comprehensive assessment in lake watersheds of the Lakes region considering the forest cover. For this purpose, the study gives a general view of trends in climatic parameters using Mann Kendall trend test. The results showed that Mann Kendall trend test for temperature and precipitation data is not enough to evaluate the magnitude of potential changes of climate in terms of forest cover. Understanding impacts of changes in temperature and precipitation on forest cover, runoff data should be evaluated with temperature and precipitation for watersheds of forest areas in Lakes Region.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description and evaluation of meteorological predictions

Science.gov (United States)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-02-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget

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.

Comparative Evaluation of the Impact of WRF-NMM and WRF-ARW Meteorology on CMAQ Simulations for O3 and Related Species During the 2006 TexAQS/GoMACCS Campaign

Science.gov (United States)

In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...

Usage of virtual research laboratory "Climate" prototype for Northern Eurasia climatic and ecological studies

Science.gov (United States)

Gordov, Evgeny; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2015-04-01

Reported are some results of Northern Eurasia regional climatic and ecological monitoring and modeling obtained using recently developed prototype of thematic virtual research laboratory (VRL) Climate (http://climate.scert.ru/). The prototype integrates distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. Its specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenario. Currently VRL integrates on the base of geoportal the WRF and «Planet Simulator» models, basic reanalysis, meteorological stations data and support profound statistical analysis of storage and modeled on demand data. In particular, one can run the integrated models, preprocess modeling results data, using dedicated modules for numerical processing perform analysys and visualize obtained results. The prototype can provide specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even a user without programming skills would be able to process and visualize multidimensional observational and model data through unified web-interface using a web-browser. Location, frequency and magnitude of observed in Siberia extremes has been studied using recently added prototype functionality allowing detailed statistical analysis studies of regional climatic extremes. Firstly it was shown that ECMWF ERA Interim Reanalysis data are closest to near surface temperature time series measured at regional meteorological stations. Statistical analysis of ERA Interim daily temperature time series (1979-2012) indicates the asymmetric changes in distribution tails of such extreme indices as warm/cold days/nights. Namely, the

Implementation of a gust front head collapse scheme in the WRF numerical model

Science.gov (United States)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2018-05-01

Gust fronts are thunderstorm-related phenomena usually associated with severe winds which are of great importance in theoretical meteorology, weather forecasting, cloud dynamics and precipitation, and wind engineering. An important feature of gust fronts demonstrated through both theoretical and observational studies is the periodic collapse and rebuild of the gust front head. This cyclic behavior of gust fronts results in periodic forcing of vertical velocity ahead of the parent thunderstorm, which consequently influences the storm dynamics and microphysics. This paper introduces the first gust front pulsation parameterization scheme in the WRF-ARW model (Weather Research and Forecasting-Advanced Research WRF). The influence of this new scheme on model performances is tested through investigation of the characteristics of an idealized supercell cumulonimbus cloud, as well as studying a real case of thunderstorms above the United Arab Emirates. In the ideal case, WRF with the gust front scheme produced more precipitation and showed different time evolution of mixing ratios of cloud water and rain, whereas the mixing ratios of ice and graupel are almost unchanged when compared to the default WRF run without the parameterization of gust front pulsation. The included parameterization did not disturb the general characteristics of thunderstorm cloud, such as the location of updraft and downdrafts, and the overall shape of the cloud. New cloud cells in front of the parent thunderstorm are also evident in both ideal and real cases due to the included forcing of vertical velocity caused by the periodic collapse of the gust front head. Despite some differences between the two WRF simulations and satellite observations, the inclusion of the gust front parameterization scheme produced more cumuliform clouds and seem to match better with real observations. Both WRF simulations gave poor results when it comes to matching the maximum composite radar reflectivity from radar

Megacity impacts on regional ozone formation: observations and WRF-Chem modeling for the MIRAGE-Shanghai field campaign

Directory of Open Access Journals (Sweden)

X. Tie

2013-06-01

Full Text Available The MIRAGE-Shanghai experiment was designed to characterize the factors controlling regional air pollution near a Chinese megacity (Shanghai and was conducted during September 2009. This paper provides information on the measurements conducted for this study. In order to have some deep analysis of the measurements, a regional chemical/dynamical model (version 3 of Weather Research and Forecasting Chemical model – WRF-Chemv3 is applied for this study. The model results are intensively compared with the measurements to evaluate the model capability for calculating air pollutants in the Shanghai region, especially the chemical species related to ozone formation. The results show that the model is able to calculate the general distributions (the level and the variability of air pollutants in the Shanghai region, and the differences between the model calculation and the measurement are mostly smaller than 30%, except the calculations of HONO (nitrous acid at PD (Pudong and CO (carbon monoxide at DT (Dongtan. The main scientific focus is the study of ozone chemical formation not only in the urban area, but also on a regional scale of the surrounding area of Shanghai. The results show that during the experiment period, the ozone photochemical formation was strongly under the VOC (volatile organic compound-limited condition in the urban area of Shanghai. Moreover, the VOC-limited condition occurred not only in the city, but also in the larger regional area. There was a continuous enhancement of ozone concentrations in the downwind of the megacity of Shanghai, resulting in a significant enhancement of ozone concentrations in a very large regional area in the surrounding region of Shanghai. The sensitivity study of the model suggests that there is a threshold value for switching from VOC-limited condition to NOx (nitric oxide and nitrogen dioxide-limited condition. The threshold value is strongly dependent on the emission ratio of NOx / VOCs. When the

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

Science.gov (United States)

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd

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...

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.

Climate Variability and Change in the Mediterranean Region

Science.gov (United States)

Lionello, Piero; Özsoy, Emin; Planton, Serge; Zanchetta, Giovanni

2017-04-01

This special issue collects new research results on the climate of the Mediterranean region. It covers traditional topics of the MedCLIVAR programme (www.medclivar.eu, Lionello et al. 2006, Lionello et al. 2012b) being devoted to papers addressing on-going and future climate changes in the Mediterranean region and their impacts on its environment.

CLIMATIC JUMP IN THE POLAR REGION (I)

OpenAIRE

ヤマモト, リョウザブロウ; イワシマ, タツヤ; ホシアイ, マコト; Ryozaburo, YAMAMOTO; Tatsuya, IWASHIMA; Makoto, HOSHIAI

1987-01-01

From the analysis of the climatic elements over Japan, we can detect the "climatic jumps" around the years 1920 and 1950,which is a new concept in the climatic diagnosis proposed by the present authors (R. YAMAMOTO et al. : J. Meteorol. Soc. Jpn., 63,1157,1985,64,273,1986). Taking account of several results which show the simultaneous occurrence of the climatic jumps of the surface air temperature, precipitation, etc., in the other regions by the other investigators, we may infer the "climati...

(WRFDA) for WRF non-hydrostatic mesoscale model

Indian Academy of Sciences (India)

Sujata Pattanayak

2018-05-22

May 22, 2018 ... Keywords. WRF-NMM; WRFDA; single observation test; eigenvalues; eigenvector; correlation; tropical .... The per- turbation variables here are defined as deviations ..... Synop, Sound, Metar, Pilot, Buoy, Ships, Airep,. Geoamv ...

Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements

Energy Technology Data Exchange (ETDEWEB)

Li, Zhijin [Univ. of California, Los Angeles, CA (United States); Sha, Feng [Univ. of California, Los Angeles, CA (United States); Liu, Yangang [Brookhaven National Lab. (BNL), Upton, NY (United States); Lin, Wuyin [Brookhaven National Lab. (BNL), Upton, NY (United States); Toto, Tami [Brookhaven National Lab. (BNL), Upton, NY (United States); Vogelmann, Andrew [Brookhaven National Lab. (BNL), Upton, NY (United States)

2016-02-02

This five-year award supports the project “Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements (FASTER)”. The goal of this project is to produce accurate, consistent and comprehensive data sets for initializing both single column models (SCMs) and cloud resolving models (CRMs) using data assimilation. A multi-scale three-dimensional variational data assimilation scheme (MS-3DVAR) has been implemented. This MS-3DVAR system is built on top of WRF/GSI. The Community Gridpoint Statistical Interpolation (GSI) system is an operational data assimilation system at the National Centers for Environmental Prediction (NCEP) and has been implemented in the Weather Research and Forecast (WRF) model. This MS-3DVAR is further enhanced by the incorporation of a land surface 3DVAR scheme and a comprehensive aerosol 3DVAR scheme. The data assimilation implementation focuses in the ARM SGP region. ARM measurements are assimilated along with other available satellite and radar data. Reanalyses are then generated for a few selected period of time. This comprehensive data assimilation system has also been employed for other ARM-related applications.

Regional climate change-Science in the Southeast

Science.gov (United States)

Jones, Sonya A.

2010-01-01

Resource managers are at the forefront of a new era of management. They must consider the potential impacts of climate change on the Nation's resources and proactively develop strategies for dealing with those impacts on plants, animals, and ecosystems. This requires rigorous, scientific understanding of environmental change. The role of the U.S. Geological Survey (USGS) in this effort is to analyze climate-change data and develop tools for assessing how changing conditions are likely to impact resources. This information will assist Federal, State, local, and tribal partners manage resources strategically. The 2008 Omnibus Budget Act and Secretarial Order 3289 established a new network of eight Department of Interior Regional Climate Science Centers to provide technical support for resource managers. The Southeast Regional Assessment Project (SERAP) is the first regional assessment to be funded by the USGS National Climate Change and Wildlife Science Center (http://nccw.usgs.gov/). The USGS is working closely with the developing Department of Interior Landscape Conservation Cooperatives to ensure that the project will meet the needs of resource managers in the Southeast. In addition, the U.S. Fish and Wildlife Service is providing resources to the SERAP to expand the scope of the project.

PENGGUNAAN SKEMA KONVEKTIF MODEL CUACA WRF (BETTS MILLER JANJIC, KAIN FRITSCH DAN GRELL 3D ENSEMBLE (Studi kasus: Surabaya dan Jakarta

Directory of Open Access Journals (Sweden)

Roni Kurniawan

2015-01-01

Full Text Available Pada kajian ini dilakukan evaluasi penggunaan beberapa skema konvektif pada model WRF (Weather Research and Forecasting untuk prediksi cuaca di wilayah Indonesia. Terdapat tiga skema konvektif yang akan dievaluasi yaitu; skema konvektif cumulus BMJ (Betts Miller Janjic, KF (Kain Fritsch, dan GD (Grell 3D ensemble. Data yang digunakan untuk evaluasi adalah data curah hujan per 3 jam dan data angin per 12 jam (level ketinggian; permukaan, 850, 500, 250 mb dari hasil pengolahan model WRF dan observasi selama periode bulan Agustus 2011 dan Februari 2012 di stasiun Juanda-Surabaya dan Cengkareng-Jakarta. Hasil verifikasi dari tiga skema konvektif pada model WRF terhadap data observasi menunjukkan bahwa untuk prakiraan curah hujan, penggunaan skema konvektif BMJ lebih baik dari skema KF dan GD, dan untuk prakiraan arah dan kecepatan angin skema BMJ dan GD relatif lebih baik dari skema KF. Berdasarkan analisis hasil verifikasi yang diperoleh, pemilihan skema konvektif cumulus BMJ cenderung lebih baik dari skema konvektif KF dan GD untuk di aplikasikan pada model WRF.   In this study, the use of some convective schemes on the model WRF (Weather Research and Forecasting for weather prediction in Indonesian region has been evaluated. There are two models evaluated; BMJ cumulus convective scheme (Betts Miller Janjic, KF (Kain Fritsch, and GD (Grell 3D ensemble. The data used in the evaluation are the 3 hourly rainfall data, and the 12 hourly wind data (level height; surface, 850, 500, 250mb from the WRF models and observation processing during August 2011 and February 2012 period at the Juanda-Surabaya and Cengkareng-Jakarta stations. The results of the verification of the three convective schemes in WRF models against observation data indicate that for precipitation forecasts, the application of the BMJ convective scheme is better than the KF and GD schemes, and for direction and wind speed forecast, BMJ and GD schemes is relatively better than the KF

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.

Aerosol indirect effects on summer precipitation in a regional climate model for the Euro-Mediterranean region

Science.gov (United States)

Da Silva, Nicolas; Mailler, Sylvain; Drobinski, Philippe

2018-03-01

Aerosols affect atmospheric dynamics through their direct and semi-direct effects as well as through their effects on cloud microphysics (indirect effects). The present study investigates the indirect effects of aerosols on summer precipitation in the Euro-Mediterranean region, which is located at the crossroads of air masses carrying both natural and anthropogenic aerosols. While it is difficult to disentangle the indirect effects of aerosols from the direct and semi-direct effects in reality, a numerical sensitivity experiment is carried out using the Weather Research and Forecasting (WRF) model, which allows us to isolate indirect effects, all other effects being equal. The Mediterranean hydrological cycle has often been studied using regional climate model (RCM) simulations with parameterized convection, which is the approach we adopt in the present study. For this purpose, the Thompson aerosol-aware microphysics scheme is used in a pair of simulations run at 50 km resolution with extremely high and low aerosol concentrations. An additional pair of simulations has been performed at a convection-permitting resolution (3.3 km) to examine these effects without the use of parameterized convection. While the reduced radiative flux due to the direct effects of the aerosols is already known to reduce precipitation amounts, there is still no general agreement on the sign and magnitude of the aerosol indirect forcing effect on precipitation, with various processes competing with each other. Although some processes tend to enhance precipitation amounts, some others tend to reduce them. In these simulations, increased aerosol loads lead to weaker precipitation in the parameterized (low-resolution) configuration. The fact that a similar result is obtained for a selected area in the convection-permitting (high-resolution) configuration allows for physical interpretations. By examining the key variables in the model outputs, we propose a causal chain that links the aerosol

Great plains regional climate assessment technical report

Science.gov (United States)

The Great Plains region (GP) plays important role in providing food and energy to the economy of the United States. Multiple climatic and non-climatic stressors put multiple sectors, livelihoods and communities at risk, including agriculture, water, ecosystems and rural and tribal communities. The G...

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.

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...

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)

WRF-CMAQ simulations of Aerosol Direct Effects

Data.gov (United States)

U.S. Environmental Protection Agency — CMAQ and WRF output files. This dataset is not publicly accessible because: Too Big. It can be accessed through the following means: The data can be accesses from...

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.

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.

Evaluating the performance and utility of regional climate models

DEFF Research Database (Denmark)

Christensen, Jens H.; Carter, Timothy R.; Rummukainen, Markku

2007-01-01

This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective...... of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design...... of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme...

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

Energy Technology Data Exchange (ETDEWEB)

Patricola, C.M. [Cornell University, Department of Earth and Atmospheric Sciences, Ithaca, NY (United States); Texas A and M University, Department of Atmospheric Sciences, College Station, TX (United States); Cook, K.H. [The University of Texas at Austin, Department of Geological Sciences, Jackson School of Geosciences, Austin, TX (United States)

2011-09-15

A regional climate model, the Weather Research and Forecasting (WRF) Model, is forced with increased atmospheric CO{sub 2} and anomalous SSTs and lateral boundary conditions derived from nine coupled atmosphere-ocean general circulation models to produce an ensemble set of nine future climate simulations for northern Africa at the end of the twenty-first century. A well validated control simulation, agreement among ensemble members, and a physical understanding of the future climate change enhance confidence in the predictions. The regional model ensembles produce consistent precipitation projections over much of northern tropical Africa. A moisture budget analysis is used to identify the circulation changes that support future precipitation anomalies. The projected midsummer drought over the Guinean Coast region is related partly to weakened monsoon flow. Since the rainfall maximum demonstrates a southward bias in the control simulation in July-August, this may be indicative of future summer drying over the Sahel. Wetter conditions in late summer over the Sahel are associated with enhanced moisture transport by the West African westerly jet, a strengthening of the jet itself, and moisture transport from the Mediterranean. Severe drought in East Africa during August and September is accompanied by a weakened Indian monsoon and Somali jet. Simulations with projected and idealized SST forcing suggest that overall SST warming in part supports this regional model ensemble agreement, although changes in SST gradients are important over West Africa in spring and fall. Simulations which isolate the role of individual climate forcings suggest that the spatial distribution of the rainfall predictions is controlled by the anomalous SST and lateral boundary conditions, while CO{sub 2} forcing within the regional model domain plays an important secondary role and generally produces wetter conditions. (orig.)

Implementation of a turbulent orographic form drag scheme in WRF and its application to the Tibetan Plateau

Science.gov (United States)

Zhou, Xu; Yang, Kun; Wang, Yan

2018-04-01

Sub-grid-scale orographic variation (smaller than 5 km) exerts turbulent form drag on atmospheric flows and significantly retards the wind speed. The Weather Research and Forecasting model (WRF) includes a turbulent orographic form drag (TOFD) scheme that adds the drag to the surface layer. In this study, another TOFD scheme has been incorporated in WRF3.7, which exerts an exponentially decaying drag from the surface layer to upper layers. To investigate the effect of the new scheme, WRF with the old scheme and with the new one was used to simulate the climate over the complex terrain of the Tibetan Plateau from May to October 2010. The two schemes were evaluated in terms of the direct impact (on wind fields) and the indirect impact (on air temperature and precipitation). The new TOFD scheme alleviates the mean bias in the surface wind components, and clearly reduces the root mean square error (RMSEs) in seasonal mean wind speed (from 1.10 to 0.76 m s-1), when referring to the station observations. Furthermore, the new TOFD scheme also generally improves the simulation of wind profile, as characterized by smaller biases and RMSEs than the old one when referring to radio sounding data. Meanwhile, the simulated precipitation with the new scheme is improved, with reduced mean bias (from 1.34 to 1.12 mm day-1) and RMSEs, which is due to the weakening of water vapor flux at low-level atmosphere with the new scheme when crossing the Himalayan Mountains. However, the simulation of 2-m air temperature is little improved.

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.

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

Science.gov (United States)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

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/

WRF Mesoscale Pre-Run for the Wind Atlas of Mexico

OpenAIRE

Hahmann, Andrea N.; Pena Diaz, Alfredo; Hansen, Jens Carsten

2016-01-01

This report documents the work performed by DTU Wind Energy for the project “Atlas Eólico Mexicano” or the Wind Atlas of Mexico. This document reports on the methods used in “Pre-run” of the windmapping project for Mexico. The interim mesoscale modeling results were calculated from the output of simulations using the Weather, Research and Forecasting (WRF) model. We document the method used to run the mesoscale simulations and to generalize the WRF model wind climatologies. A separate section...

Forecasting summertime surface temperature and precipitation in the Mexico City metropolitan area: sensitivity of the WRF model to land cover changes

Science.gov (United States)

López-Bravo, Clemente; Caetano, Ernesto; Magaña, Víctor

2018-02-01

Changes in the frequency and intensity of severe hydrometeorological events in recent decades in the Mexico City Metropolitan Area have motivated the development of weather warning systems. The weather forecasting system for this region was evaluated in sensitivity studies using the Weather Research and Forecasting Model (WRF) for July 2014, a summer time month. It was found that changes in the extent of the urban area and associated changes in thermodynamic and dynamic variables have induced local circulations that affect the diurnal cycles of temperature, precipitation, and wind fields. A newly implemented configuration (land cover update and Four-Dimensional Data Assimilation (FDDA)) of the WRF model has improved the adjustment of the precipitation field to the orography. However, errors related to the depiction of convection due to parameterizations and microphysics remains a source of uncertainty in weather forecasting in this region.

Regional climate science: lessons and opportunities

Science.gov (United States)

Mote, P. W.; Miles, E. L.; Whitely Binder, L.

2008-12-01

Since its founding in 1995, the Climate Impacts Group (CIG) at the University of Washington (UW) has achieved remarkable success at translating global- and regional-scale science into forms and products that are useful to, and used by, decision-makers. From GCM scenarios to research on the connection between global climate patterns and locally important factors like floods and wildfires, CIG's strong physical science foundation is matched by a vigorous and successful outreach program. As a result, CIG and its partner the Office of Washington State Climatologist at UW have made substantial progress at bridging the gap between climate science and decision-making, and are deeply involved in advising all levels of government and many business interests on adapting to climate variability and change. This talk will showcase some of the specific activities and tools, describe lessons learned, and illustrate how such efforts fit into a "National Climate Service."

Regional Analysis of Energy, Water, Land and Climate Interactions

Science.gov (United States)

Tidwell, V. C.; Averyt, K.; Harriss, R. C.; Hibbard, K. A.; Newmark, R. L.; Rose, S. K.; Shevliakova, E.; Wilson, T.

2014-12-01

Energy, water, and land systems interact in many ways and are impacted by management and climate change. These systems and their interactions often differ in significant ways from region-to-region. To explore the coupled energy-water-land system and its relation to climate change and management a simple conceptual model of demand, endowment and technology (DET) is proposed. A consistent and comparable analysis framework is needed as climate change and resource management practices have the potential to impact each DET element, resource, and region differently. These linkages are further complicated by policy and trade agreements where endowments of one region are used to meet demands in another. This paper reviews the unique DET characteristics of land, energy and water resources across the United States. Analyses are conducted according to the eight geographic regions defined in the 2014 National Climate Assessment. Evident from the analyses are regional differences in resources endowments in land (strong East-West gradient in forest, cropland and desert), water (similar East-West gradient), and energy. Demands likewise vary regionally reflecting differences in population density and endowment (e.g., higher water use in West reflecting insufficient precipitation to support dryland farming). The effect of technology and policy are particularly evident in differences in the energy portfolios across the eight regions. Integrated analyses that account for the various spatial and temporal differences in regional energy, water and land systems are critical to informing effective policy requirements for future energy, climate and resource management. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

A Step towards a Sharable Community Knowledge Base for WRF Settings -Developing a WRF Setting Methodology based on a case study in a Torrential Rainfall Event

Science.gov (United States)

CHU, Q.; Xu, Z.; Zhuo, L.; Han, D.

2016-12-01

Increased requirements for interactions between different disciplines and readily access to the numerical weather forecasting system featured with portability and extensibility have made useful contribution to the increases of downstream model users in WRF over recent years. For these users, a knowledge base classified by the representative events would be much helpful. This is because the determination of model settings is regarded as the most important steps in WRF. However, such a process is generally time-consuming, even if with a high computational platform. As such, we propose a sharable proper lookup table on WRF domain settings and corresponding procedures based on a representative torrential rainfall event in Beijing, China. It has been found that WRF's simulations' drift away from the input lateral boundary conditions can be significantly reduced with the adjustment of the domain settings. Among all the impact factors, the placement of nested domain can not only affect the moving speed and angle of the storm-center, but also the location and amount of heavy-rain-belt which can only be detected with adjusted spatial resolutions. Spin-up time is also considered in the model settings, which is demonstrated to have the most obvious influence on the accuracy of the simulations. This conclusion is made based on the large diversity of spatial distributions of precipitation, in terms of the amount of heavy rain varied from -30% to 58% among each experiment. After following all the procedures, the variations of domain settings have minimal effect on the modeling and show the best correlation (larger than 0.65) with fusion observations. So the model settings, including domain size covering the greater Beijing area, 1:5:5 downscaling ratio, 57 vertical levels with top of 50hpa and 60h spin-up time, are found suitable for predicting the similar convective torrential rainfall event in Beijing area. We hope that the procedure for building the community WRF knowledge

Regional climate change mitigation analysis

Energy Technology Data Exchange (ETDEWEB)

Rowlands, Ian H [UNEP Collaborating Centre on Energy and Environment, and Univ. of Waterloo (Canada)

1998-10-01

The purpose of this paper is to explore some of the key methodological issues that arise from an analysis of regional climate change mitigation options. The rationale for any analysis of regional mitigation activities, emphasising both the theoretical attractiveness and the existing political encouragement and the methodology that has been developed are reviewed. The differences arising from the fact that mitigation analyses have been taken from the level of the national - where the majority of the work has been completed to date - to the level of the international - that is, the `regional` - will be especially highlighted. (EG)

Regional climate change mitigation analysis

International Nuclear Information System (INIS)

Rowlands, Ian H.

1998-01-01

The purpose of this paper is to explore some of the key methodological issues that arise from an analysis of regional climate change mitigation options. The rationale for any analysis of regional mitigation activities, emphasising both the theoretical attractiveness and the existing political encouragement and the methodology that has been developed are reviewed. The differences arising from the fact that mitigation analyses have been taken from the level of the national - where the majority of the work has been completed to date - to the level of the international - that is, the 'regional' - will be especially highlighted. (EG)

NOAA's Regional Climate Services Program: Building Relationships with Partners and Customers to Deliver Trusted Climate Information at Usable Scales

Science.gov (United States)

Mecray, E. L.; Dissen, J.

2016-12-01

Federal agencies across multiple sectors from transportation to health, emergency management and agriculture, are now requiring their key stakeholders to identify and plan for climate-related impacts. Responding to the drumbeat for climate services at the regional and local scale, the National Oceanic and Atmospheric Administration (NOAA) formed its Regional Climate Services (RCS) program to include Regional Climate Services Directors (RCSD), Regional Climate Centers, and state climatologists in a partnership. Since 2010, the RCS program has engaged customers across the country and amongst many of the nation's key economic sectors to compile information requirements, deliver climate-related products and services, and build partnerships among federal agencies and their regional climate entities. The talk will include a sketch from the Eastern Region that may shed light on the interaction of the multiple entities working at the regional scale. Additionally, we will show examples of our interagency work with the Department of Interior, the Department of Agriculture, and others in NOAA to deliver usable and trusted climate information and resources. These include webinars, print material, and face-to-face customer engagements to gather and respond to information requirements. NOAA/National Centers for Environmental Information's RCSDs work on-the-ground to learn from customers about their information needs and their use of existing tools and resources. As regional leads, the RCSDs work within NOAA and with our regional partners to ensure the customer receives a broad picture of the tools and information from across the nation.

Effect of land cover on atmospheric processes and air quality over the continental United States – a NASA Unified WRF (NU-WRF model study

Directory of Open Access Journals (Sweden)

Z. Tao

2013-07-01

Full Text Available The land surface plays a crucial role in regulating water and energy fluxes at the land–atmosphere (L–A interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL evolution, and precipitation through soil-moisture–evapotranspiration coupling. In turn, it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L–A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF modeling system couples NASA's Land Information System (LIS with the community WRF model and allows users to explore the L–A processes and feedbacks. Three commonly used satellite-derived land cover datasets – i.e., from the US Geological Survey (USGS and University of Maryland (UMD, which are based on the Advanced Very High Resolution Radiometer (AVHRR, and from the Moderate Resolution Imaging Spectroradiometer (MODIS – bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g., stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.

Climatic change impacts in Lombardia region

International Nuclear Information System (INIS)

Fiorese, G.; Gatto, M.; De Leo, G.

2008-01-01

Climatic change will change significantly our Country through impacts of natural and physical systems, on human health and the productive sectors. This article describes the expected impacts in Lombardia region [it

Modelling the regional effects of climate change on air quality

International Nuclear Information System (INIS)

Giorgi, F.; Meleux, F.

2007-01-01

The life cycle of pollutants is affected by chemical as well as meteorological factors, such as wind, temperature, precipitation, solar radiation. Therefore, climatic changes induced by anthropogenic emissions of greenhouse gases may be expected to have significant effects on air quality. Because of the spatial variability of the pollutant emissions and climate-change signals, these effects are particularly relevant at the regional to local scales. This paper first briefly reviews modelling tools and methodologies used to study regional climate-change impacts on air quality. Patterns of regional precipitation, temperature, and sea-level changes emerging from the latest set of general circulation model projections are then discussed. Finally, the specific case of climate-change effects on summer ozone concentrations over Europe is presented to illustrate the potential impacts of climate change on pollutant amounts. It is concluded that climate change is an important factor that needs to be taken into account when designing future pollution-reduction policies. (authors)

The Haute-Normandie Climate Air Energy Regional Scheme - Synthesis

International Nuclear Information System (INIS)

2016-01-01

This regional public and planning document (SRCAE) first proposes a regional diagnosis in terms of energetic situation, climatic situation, air quality situation, building condition (in terms of energy), transports (characteristics of regional transport, of person and goods transport), industries and enterprises (important role of oil and chemical activities, low level of renewable and recovery energies), agriculture and forest, renewable energies (biomass and wastes, wind energy, solar photovoltaic, hydroelectricity, renewable heat production), and territory vulnerability in front of climate change. The second part states objectives and orientations: definition of scenarios, and of sector-based objectives (in the building, transport, agricultural, and industrial sectors, in the development of renewable energies, and in terms of adaptation to climate change). Synthetic approaches are then stated in relationship with different challenges related to sustainable behaviours and consumption, promotion of professions related to energy transition, diffusion of good practices in the fields of energy efficiency and emission reduction, sustainable land development, promotion of environmental mutations for the regional economy, innovation to face climate and energy challenges, development of renewable energies, anticipation of the adaptation to climate change, and SRCAE follow-up and assessment. Sheets of definitions of objectives are given for each sector. A synthetic version of this study is provided

Impacts of updated green vegetation fraction data on WRF simulations of the 2006 European heat wave

Science.gov (United States)

Refslund, J.; Dellwik, E.; Hahmann, A. N.; Barlage, M. J.; Boegh, E.

2012-12-01

Climate change studies suggest an increase in heat wave occurrences over Europe in the coming decades. Extreme events with excessive heat and associated drought will impact vegetation growth and health and lead to alterations in the partitioning of the surface energy. In this study, the atmospheric conditions during the heat wave year 2006 over Europe were simulated using the Weather Research and Forecasting (WRF) model. To account for the drought effects on the vegetation, new high-resolution green vegetation fraction (GVF) data were developed for the domain using NDVI data from MODIS satellite observations. Many empirical relationships exist to convert NDVI to GVF and both a linear and a quadratic formulation were evaluated. The new GVF product has a spatial resolution of 1 km2 and a temporal resolution of 8 days. To minimize impacts from low-quality satellite retrievals in the NDVI series, as well as for comparison with the default GVF climatology in WRF, a new background climatology using 10 recent years of observations was also developed. The annual time series of the new GVF climatology was compared to the default WRF GVF climatology at 18 km2 grid resolution for the most common land use classes in the European domain. The new climatology generally has higher GVF levels throughout the year, in particular an extended autumnal growth season. Comparison of 2006 GVF with the climatology clearly indicates vegetation stresses related to heat and drought. The GVF product based on a quadratic NDVI relationship shows the best agreement with the magnitude and annual range of the default input data, in addition to including updated seasonality for various land use classes. The new GVF products were tested in WRF and found to work well for the spring of 2006 where the difference between the default and new GVF products was small. The WRF 2006 heat wave simulations were verified by comparison with daily gridded observations of mean, minimum and maximum temperature and

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.

Building America Best Practices Series: Guide to Determining Climate Regions by County

Energy Technology Data Exchange (ETDEWEB)

Gilbride, Theresa L.

2008-10-01

This document describes the eight climate region designations used by the US Department of Energy Building America Program. In addition to describing the climate zones, the document includes a complete list of every county in the United States and their climate region designations. The county lists are grouped by state. The doucment is intended to assist builders to easily identify what climate region they are building in and therefore which climate-specific Building America best practices guide would be most appropriate for them.

Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?

Science.gov (United States)

Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

2006-01-01

A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

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.

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

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

Science.gov (United States)

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscal...

Developing a Process for Sustained Climate Assessment in the US Southwest Region

Science.gov (United States)

Duncan, B.; Rick, U. K.; McNie, E. C.

2017-12-01

Climate information needs often vary across states, regions, and sectors. While a national assessment provides foundational guidance about the science and impacts of climate change, there is also value in an ongoing climate assessment process with a more targeted regional geographic scale and sectoral focus. Such a process could provide timely and relevant climate information that is sometimes more detailed than what can be included in a national assessment, while also providing a foundation of knowledge and relationships that can be drawn on in larger-scale assessment processes. In the Sustained Climate Assessment in the Southwest project, researchers are investigating opportunities for sustained assessment in the US Southwest National Climate Assessment (NCA) region - an area that consists of Arizona, California, Colorado, Nevada, New Mexico, and Utah. This work is focused on identifying key elements of an ongoing climate assessment process for the region in collaboration with climate service providers and users, with the goal of connecting providers and users to increase access to information and understanding of climate impacts in decision-making contexts. It is focused on four key sectors that represent a range of existing capacity in the region: water, oceans and coasts, agriculture, and transportation. Recommendations for an ongoing assessment process may vary by sector - a reflection of the capacity and opportunity associated with each. In this presentation, we will share case studies of particularly useful or successful existing assessment activities and identify common characteristics across the case studies. We will also share preliminary recommendations for a regional sustained climate assessment process that draws on the broad existing capacity for climate assessment in the region and complements national-scale assessment processes.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

Science.gov (United States)

Shanlei Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter V. Caldwell; Kai Duan; Yang Zhang

2016-01-01

Quantifying the potential impacts of climatechange on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, andecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and StressIndex, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled...

Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme

Science.gov (United States)

Mielikainen, J.; Huang, B.; Huang, A. H.-L.

2014-12-01

The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations

Problems and Ways of Improving the Business Climate in the Regions

Directory of Open Access Journals (Sweden)

Nazym Aminovna Uruzbaeva

2016-03-01

Full Text Available The existence of the specific conditions and development factors of small and medium-sized enterprises (SMEs in the regions of Kazakhstan supposes the differentiated state policy in order to maintain a favorable business climate. The article presents the results of the research whose purpose was to determine the main issues and directions of the improvement of the business climate in the regions. This allows to intensify the activities of local authorities in support of SMEs considering the peculiarities of the territories’ development. The subject matter of this research is the conditions and factors generating the business climate of the region. As a hypothesis, a direct connection between the prevailing regional business climate and the development of the quantitative indicators of active SMEs in the field was assumed. The study used the method of comparative analysis, sociological methods of focus groups, survey research, statistical methods and statistical methods of ranking and grouping. The article theoretically substantiates the correctness of the usage of «business climate» category as a scope of the study in the framework of the project of «Implementation of «Business Climate» as an Independent Rating», which makes possible the argumentation of the used methodology and concretization of the factors affecting the functioning of SMEs in the regions. This research has confirmed the direct correlation between the established business climate in the regions and quantitative indicators of the development of SMEs at the local level. Such factors as “financial resources” and “government support” have been determined as limiting the business development in a greater degree. In conclusion, a set of measures to improve the business climate in the region both at national and regional levels of government has been provided. In addition, it has been concluded that to generate a favorable business environment in the regions of

Integrated regional changes in arctic climate feedbacks: Implications for the global climate system

Science.gov (United States)

McGuire, A.D.; Chapin, F. S.; Walsh, J.E.; Wirth, C.; ,

2006-01-01

The Arctic is a key part of the global climate system because the net positive energy input to the tropics must ultimately be resolved through substantial energy losses in high-latitude regions. The Arctic influences the global climate system through both positive and negative feedbacks that involve physical, ecological, and human systems of the Arctic. The balance of evidence suggests that positive feedbacks to global warming will likely dominate in the Arctic during the next 50 to 100 years. However, the negative feedbacks associated with changing the freshwater balance of the Arctic Ocean might abruptly launch the planet into another glacial period on longer timescales. In light of uncertainties and the vulnerabilities of the climate system to responses in the Arctic, it is important that we improve our understanding of how integrated regional changes in the Arctic will likely influence the evolution of the global climate system. Copyright ?? 2006 by Annual Reviews. All rights reserved.

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

Science.gov (United States)

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

2018-04-01

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

Impacts of Future Grassland Changes on Surface Climate in Mongolia

Directory of Open Access Journals (Sweden)

Fan Zhang

2013-01-01

Full Text Available Climate change caused by land use/cover change (LUCC is becoming a hot topic in current global change, especially the changes caused by the grassland degradation. In this paper, based on the baseline underlying surface data of 1993, the predicted underlying surface data which can be derived through overlaying the grassland degradation information to the map of baseline underlying surface, and the atmospheric forcing data of RCP 6.0 from CMIP5, climatological changes caused by future grassland changes for the years 2010–2020 and 2040–2050 with the Weather Research Forecast model (WRF are simulated. The model-based analysis shows that future grassland degradation will significantly result in regional climate change. The grassland degradation in future could lead to an increasing trend of temperature in most areas and corresponding change range of the annual average temperature of −0.1°C–0.4°C, and it will cause a decreasing trend of precipitation and corresponding change range of the annual average precipitation of 10 mm–50 mm. This study identifies lines of evidence for effects of future grassland degradation on regional climate in Mongolia which provides meaningful decision-making information for the development and strategy plan making in Mongolia.

The Regional Integrated Sciences and Assessments (RISA) Program, Climate Services, and Meeting the National Climate Change Adaptation Challenge

Science.gov (United States)

Overpeck, J. T.; Udall, B.; Miles, E.; Dow, K.; Anderson, C.; Cayan, D.; Dettinger, M.; Hartmann, H.; Jones, J.; Mote, P.; Ray, A.; Shafer, M.; White, D.

2008-12-01

The NOAA-led RISA Program has grown steadily to nine regions and a focus that includes both natural climate variability and human-driven climate change. The RISAs are, at their core, university-based and heavily invested in partnerships, particularly with stakeholders, NOAA, and other federal agencies. RISA research, assessment and partnerships have led to new operational climate services within NOAA and other agencies, and have become important foundations in the development of local, state and regional climate change adaptation initiatives. The RISA experience indicates that a national climate service is needed, and must include: (1) services prioritized based on stakeholder needs; (2) sustained, ongoing regional interactions with users, (3) a commitment to improve climate literacy; (4) support for assessment as an ongoing, iterative process; (5) full recognition that stakeholder decisions are seldom made using climate information alone; (6) strong interagency partnership; (7) national implementation and regional in focus; (8) capability spanning local, state, tribal, regional, national and international space scales, and weeks to millennia time scales; and (9) institutional design and scientific support flexible enough to assure the effort is nimble enough to respond to rapidly-changing stakeholder needs. The RISA experience also highlights the central role that universities must play in national climate change adaptation programs. Universities have a tradition of trusted regional stakeholder partnerships, as well as the interdisciplinary expertise - including social science, ecosystem science, law, and economics - required to meet stakeholder climate-related needs; project workforce can also shift rapidly in universities. Universities have a proven ability to build and sustain interagency partnerships. Universities excel in most forms of education and training. And universities often have proven entrepreneurship, technology transfer and private sector

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

Daily precipitation statistics in regional climate models

DEFF Research Database (Denmark)

Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

2003-01-01

An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

Regional Highlights of Climate Change

Science.gov (United States)

David L. Peterson; J.M. Wolken; Teresa Hollingsworth; Christian Giardina; J.S. Littell; Linda Joyce; Chris Swanston; Stephen Handler; Lindsey Rustad; Steve McNulty

2014-01-01

Climatic extremes, ecological disturbance, and their interactions are expected to have major effects on ecosystems and social systems in most regions of the United States in the coming decades. In Alaska, where the largest temperature increases have occurred, permafrost is melting, carbon is being released, and fire regimes are changing, leading to a...

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

OpenAIRE

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-01-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In t...

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.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

Science.gov (United States)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation

Assessing the impact of aerosol-atmosphere interactions in convection-permitting regional climate simulations: the Rolf medicane in 2011

Science.gov (United States)

José Gómez-Navarro, Juan; María López-Romero, José; Palacios-Peña, Laura; Montávez, Juan Pedro; Jiménez-Guerrero, Pedro

2017-04-01

A critical challenge for assessing regional climate change projections relies on improving the estimate of atmospheric aerosol impact on clouds and reducing the uncertainty associated with the use of parameterizations. In this sense, the horizontal grid spacing implemented in state-of-the-art regional climate simulations is typically 10-25 kilometers, meaning that very important processes such as convective precipitation are smaller than a grid box, and therefore need to be parameterized. This causes large uncertainties, as closure assumptions and a number of parameters have to be established by model tuning. Convection is a physical process that may be strongly conditioned by atmospheric aerosols, although the solution of aerosol-cloud interactions in warm convective clouds remains nowadays a very important scientific challenge, rendering parametrization of these complex processes an important bottleneck that is responsible from a great part of the uncertainty in current climate change projections. Therefore, the explicit simulation of convective processes might improve the quality and reliability of the simulations of the aerosol-cloud interactions in a wide range of atmospheric phenomena. Particularly over the Mediterranean, the role of aerosol particles is very important, being this a crossroad that fuels the mixing of particles from different sources (sea-salt, biomass burning, anthropogenic, Saharan dust, etc). Still, the role of aerosols in extreme events in this area such as medicanes has been barely addressed. This work aims at assessing the role of aerosol-atmosphere interaction in medicanes with the help of the regional chemistry/climate on-line coupled model WRF-CHEM run at a convection-permitting resolution. The analysis is exemplary based on the "Rolf" medicane (6-8 November 2011). Using this case study as reference, four sets of simulations are run with two spatial resolutions: one at a convection-permitting configuration of 4 km, and other at the

Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

Science.gov (United States)

Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

2010-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

Science.gov (United States)

Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPo

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.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

Science.gov (United States)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

Science.gov (United States)

Srikishen, Jayanthi; Case, Jonathan L.; Petersen, Walter A.; Iguchi, Takamichi; Tao, Wei-Kuo; Zavodsky, Bradley T.; Molthan, Andrew

2017-01-01

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment -PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

A WRF sensitivity study for summer ozone and winter PM events in California

Science.gov (United States)

Zhao, Z.; Chen, J.; Mahmud, A.; Di, P.; Avise, J.; DaMassa, J.; Kaduwela, A. P.

2014-12-01

Elevated summer ozone and winter PM frequently occur in the San Joaquin Valley (SJV) and the South Coast Air Basin (SCAB) in California. Meteorological conditions, such as wind, temperature and planetary boundary layer height (PBLH) play crucial roles in these air pollution events. Therefore, accurate representation of these fields from a meteorological model is necessary to successfully reproduce these air pollution events in subsequent air quality model simulations. California's complex terrain and land-sea interface can make it challenging for meteorological models to replicate the atmospheric conditions over the SJV and SCAB during extreme pollution events. In this study, the performance of the Weather Research and Forecasting Model (WRF) over these two regions for a summer month (July 2012) and a winter month (January 2013) is evaluated with different model configurations and forcing. Different land surface schemes (Pleim-Xiu vs. hybrid scheme), the application of observational and soil nudging, two SST datasets (the Global Ocean Data Assimilation Experiment (GODAE) SST vs. the default SST from North American Regional Reanalysis (NARR) reanalysis), and two land use datasets (the National Land Cover Data (NLCD) 2006 40-category vs. USGS 24-category land use data) have been tested. Model evaluation will focus on both surface and vertical profiles for wind, temperature, relative humidity, as well as PBLH. Sensitivity of the Community Multi-scale Air Quality Model (CMAQ) results to different WRF configurations will also be presented and discussed.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

Science.gov (United States)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

[Research on climatic factors of ecology suitability regionalization of atractylodis].

Science.gov (United States)

Tan, Zhe-tian; Wang, Hao; Zhu, Shou-dong; Yan, Yu-ping; Guo, Lan-ping; Zheng, Yu-guang

2015-11-01

Through study on the correlation between atractylodis lactones ingredient content and climatic factors, we research regionalization from climatic of five main producing provinces of the country, in order to provide a scientific basis for atractylodis' conscious cultivation. By sampling from 40 origins which from five main producing provinces of the country, we use SPSS to analysis variation of atractylodis lactones ingredient content in different conditions of climatic factors and the effect of each factors. Then according to the relationship between atractylodis lactones ingredient content and climatic factors, we use ArcGIS to conduct ecological suitability regionalization based on climatic factors. The most suitable climatic condition for cultivation of atractylodis: the wettest month precipitation 220-230 mm, the warmest average temperature 25 degrees C, the average temperature of driest season 10 degrees C.

Unraveling Tropical Mountain Hydroclimatology by Coupling Autonomous Sensor Observations and Climate Modeling: Llanganuco Valley, Cordillera Blanca, Peru.

Science.gov (United States)

Hellstrom, R. A.; Fernandez, A.; Mark, B. G.; Covert, J. M.

2015-12-01

Northern Peru will face critical water resource issues in the near future as permanent ice retreats. Much of current global and regional climate research neglects the meteorological forcing of lapse rates and valley wind dynamics on critical components of the Peruvian Andes' water-cycle. In 2004 and 2005 we installed an autonomous sensor network (ASN) within the glacierized Llanganuco Valley, Cordillera Blanca (9°S), consisting of discrete, cost-effective, automatic temperature loggers located along the valley axis and anchored by two automatic weather stations. Comparisons of these embedded atmospheric measurements from the ASN and climate modeling (CM) by dynamical downscaling using the Weather Research and Forecasting (WRF) model elucidate distinct diurnal and seasonal characteristics of the mountain valley winds and lapse rates. Wind, temperature, humidity, and cloud simulations by WRF suggest that thermally driven valley winds converging with easterly flow aloft enhance late afternoon and evening cloud development which helps explain detected nocturnal precipitation maxima measured by the ASN. We attribute sustained evapotranspiration (ET), as estimated by the FAO-56 Penman-Monteith model, to an abundance of glacial melt-water during the dry season and strong pre-noon solar heating during the wet season. Furthermore, the extreme diurnal variability of along-valley-axis lapse rates and valley wind detected from ground observations and confirmed by dynamical downscaling demonstrate the importance of realistic scale parameterizations of the boundary layer to improve regional CM projections in mountainous regions. Our findings portray ET as an integral yet poorly represented process in Andean hydroclimatology. We show that coupling ASN and CM can improve understanding of multi-scale atmospheric and associated hydrological processes in mountain valleys.

Simulating Climate Change in Ireland

Science.gov (United States)

Nolan, P.; Lynch, P.

2012-04-01

At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

Simulations of the Holuhraun eruption 2014 with WRF-Chem and evaluation with satellite and ground based SO2 measurements

Science.gov (United States)

Hirtl, Marcus; Arnold-Arias, Delia; Flandorfer, Claudia; Maurer, Christian; Mantovani, Simone; Natali, Stefano

2016-04-01

Volcanic eruptions, with gas or/and particle emissions, directly influence our environment, with special significance when they either occur near inhabited regions or are transported towards them. In addition to the well-known affectation of air traffic, with large economic impacts, the ground touching plumes can lead directly to an influence of soil, water and even to a decrease of air quality. The eruption of Holuhraun in August 2014 in central Iceland is the country's largest lava and gas eruption since the Lakagígar eruption in 1783. Nevertheless, very little volcanic ash was produced. The main atmospheric threat from this event was the SO2 pollution that frequently violated the Icelandic National Air Quality Standards in many population centers. However, the SO2 affectation was not limited to Iceland but extended to mainland Europe. The on-line coupled model WRF-Chem is used to simulate the dispersion of SO2 for this event that affected the central European regions. The volcanic emissions are considered in addition to the anthropogenic and biogenic ground sources at European scale. A modified version of WRF-Chem version 4.1 is used in order to use time depending injection heights and mass fluxes which were obtained from in situ observations. WRF-Chem uses complex gas- (RADM2) and aerosol- (MADE-SORGAM) chemistry and is operated on a European domain (12 km resolution), and a nested grid covering the Alpine region (4 km resolution). The study is showing the evaluation of the model simulations with satellite and ground based measurement data of SO2. The analysis is conducted on a data management platform, which is currently developed in the frame of the ESA-funded project TAMP "Technology and Atmospheric Mission Platform": it provides comprehensive functionalities to visualize and numerically compare data from different sources (model, satellite and ground-measurements).

Grid-scale Indirect Radiative Forcing of Climate due to aerosols over the northern hemisphere simulated by the integrated WRF-CMAQ model: Preliminary results

Science.gov (United States)

In this study, indirect aerosol effects on grid-scale clouds were implemented in the integrated WRF3.3-CMAQ5.0 modeling system by including parameterizations for both cloud droplet and ice number concentrations calculated from the CMAQ-predicted aerosol particles. The resulting c...

Climate and climate variability of the wind power resources in the Great Lakes region of the United States

Science.gov (United States)

X. Li; S. Zhong; X. Bian; W.E. Heilman

2010-01-01

The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution...

Projected climatic changes on drought conditions over Spain

Science.gov (United States)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Producing custom regional climate data sets for impact assessment with xarray

Science.gov (United States)

Simcock, J. G.; Delgado, M.; Greenstone, M.; Hsiang, S. M.; Kopp, R. E.; Carleton, T.; Hultgren, A.; Jina, A.; Nath, I.; Rising, J. A.; Rode, A.; Yuan, J.; Chong, T.; Dobbels, G.; Hussain, A.; Song, Y.; Wang, J.; Mohan, S.; Larsen, K.; Houser, T.

2017-12-01

Research in the field of climate impact assessment and valuation frequently requires the pairing of economic observations with historical or projected weather variables. Impact assessments with large geographic scope or spatially aggregated data frequently require climate variables to be prepared for use with administrative/political regions, economic districts such as utility service areas, physical regions such as watersheds, or other larger, non-gridded shapes. Approaches to preparing such data in the literature vary from methods developed out of convenience to more complex measures intended to account for spatial heterogeneity. But more sophisticated methods are difficult to implement, from both a theoretical and a technical standpoint. We present a new python package designed to assist researchers in the preparation of historical and projected climate data for arbitrary spatial definitions. Users specify transformations by providing (a) sets of regions in the form of shapefiles, (b) gridded data to be transformed, and, optionally, (c) gridded weights to use in the transformation. By default, aggregation to regions is conducted such that the resulting regional data draws from each grid cell according to the cell's share of total region area. However, researchers can provide alternative weighting schemes, such that the regional data is weighted by, for example, the population or planted agricultural area within each cell. An advantage of this method is that it enables easy preparation of nonlinear transformations of the climate data before aggregation to regions, allowing aggregated variables to more accurately capture the spatial heterogeneity within a region in the transformed data. At this session, we will allow attendees to view transformed climate projections, examining the effect of various weighting schemes and nonlinear transformations on aggregate regional values, highlighting the implications for climate impact assessment work.

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

Regulations of irrigation on regional climate in the Heihe watershed, China, and its implications to water budget

Science.gov (United States)

Zhang, X.

2015-12-01

In the arid area, such as the Heihe watershed in Northwest China, agriculture is heavily dependent on the irrigation. Irrigation suggests human-induced hydro process, which modifies the local climate and water budget. In this study, we simulated the irrigation-induced changes in surface energy/moisture budgets and modifications on regional climate, using the WRF-NoahMP modle with an irrigation scheme. The irrigation scheme was implemented following the roles that soil moisture is assigned a saturated value once the mean soil moisture of all root layers is lower than 70% of fileld capacity. Across the growth season refering from May to September, the simulated mean irrigation amount of the 1181 cropland gridcells is ~900 mm, wihch is close to the field measurments of around 1000 mm. Such an irrigation largely modified the surface energy budget. Due to irrigation, the surface net solar radiation increased by ~76.7 MJ (~11 Wm-2) accouting for ~2.3%, surface latent and senbile heat flux increased by 97.7 Wm-2 and decreased by ~79.7 Wm-2 respectively; and local daily mean surface air temperature was thereby cooling by ~1.1°C. Corresponding to the surface energy changes, wind and circulation were also modified and regional water budget is therefore regulated. The total rainfall in the irrigation area increased due to more moisture from surface. However, the increased rainfall is only ~6.5mm (accounting for ~5% of background rainfall) which is much less than the increased evaporation of ~521.5mm from surface. The ~515mm of water accounting for 57% of total irrigation was transported outward by wind. The other ~385 mm accounting for 43% of total irrigation was transformed to be runoff and soil water. These results suggest that in the Heihe watershed irrigation largely modify local energy budget and cooling surface. This study also implicate that the existing irrigation may waste a large number of water. It is thereby valuable to develope effective irrigation scheme to

Climate modelling on the GRID Experiences in the EU-project EELA

Energy Technology Data Exchange (ETDEWEB)

Fernandez-Quiruelas, V.; Fernandez, J.; Cofino, A. S.; Gutierrez, J. M.; Baeza Retamal, C.; Abarca del Rio, R.; Miguel San Martin, R.; Carrillo, M.

2007-07-01

Recent trends in climate modeling find in GRID computing a powerful way to achieve results by sharing computing and data distributed resources. In particular, ensemble prediction is based on the generation of multiple simulations from perturbed model conditions to sample the existing uncertainties. In this work, we present a GRID application consisting of a sequence of two state-of-the-art climate models (one global model and one regional model), operable through a web portal (based on Genius). The main goal of the application is providing ensemble-based regional predictions. This requires managing a complex work flow involving long-term jobs and job dependencies in a user-transparent way. In doing so, we identified the weaknesses of current middle ware tools and developed a robust work flow by merging the optimal existing applications with an underlying self-developed work flow application based on the communication with metadata catalogs (currently AMGA) storing application status and dynamic model output generation. As an illustrative scientific challenge, the application is applied to study the El Nino phenomenon, by simulating an El Nino year with different forcing conditions and analyzing the precipitation response over south-american countries subject to flooding risk. GRID computing; Climate models; CAM model; WRF model; Work flow. (Author)

Climate modelling on the GRID Experiences in the EU-project EELA

International Nuclear Information System (INIS)

Fernandez-Quiruelas, V.; Fernandez, J.; Cofino, A. S.; Gutierrez, J. M.; Baeza Retamal, C.; Abarca del Rio, R.; Miguel San Martin, R.; Carrillo, M.

2007-01-01

Recent trends in climate modeling find in GRID computing a powerful way to achieve results by sharing computing and data distributed resources. In particular, ensemble prediction is based on the generation of multiple simulations from perturbed model conditions to sample the existing uncertainties. In this work, we present a GRID application consisting of a sequence of two state-of-the-art climate models (one global model and one regional model), operable through a web portal (based on Genius). The main goal of the application is providing ensemble-based regional predictions. This requires managing a complex work flow involving long-term jobs and job dependencies in a user-transparent way. In doing so, we identified the weaknesses of current middle ware tools and developed a robust work flow by merging the optimal existing applications with an underlying self-developed work flow application based on the communication with metadata catalogs (currently AMGA) storing application status and dynamic model output generation. As an illustrative scientific challenge, the application is applied to study the El Nino phenomenon, by simulating an El Nino year with different forcing conditions and analyzing the precipitation response over south-american countries subject to flooding risk. GRID computing; Climate models; CAM model; WRF model; Work flow. (Author)

Atmospheric stability and turbulence fluxes at Horns Rev—an intercomparison of sonic, bulk and WRF model data

DEFF Research Database (Denmark)

Pena Diaz, Alfredo; Hahmann, Andrea N.

2012-01-01

anemometer at 15 m height and potential temperature differences between the water and the air above. Surface flux estimations from the advanced weather research and forecast (WRF) model are also validated against the sonic and bulk data. The correlation between the sonic and bulk estimates of friction...... to the surface, not only from a systematic bulk and WRF under‐prediction of the friction velocity when compared with the sonic value but also because of the lower magnitude of the sonic heat flux compared with that from the WRF simulations. Although they are not measured but parameterized or estimated, the bulk......–WRF comparisons of friction velocity and 10 m wind speed show good agreement. It is also shown that on a long‐term basis, the WRF and bulk estimates of stability are nearly equal and that a correction towards a slightly stable atmospheric condition has to be applied to the long‐term wind profile at Horns Rev...

High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China

Science.gov (United States)

Zhang, Xuezhen; Xiong, Zhe; Zheng, Jingyun; Ge, Quansheng

2018-02-01

The community of climate change impact assessments and adaptations research needs regional high-resolution (spatial) meteorological data. This study produced two downscaled precipitation datasets with spatial resolutions of as high as 3 km by 3 km for the Heihe River Basin (HRB) from 2011 to 2014 using the Weather Research and Forecast (WRF) model nested with Final Analysis (FNL) from the National Center for Environmental Prediction (NCEP) and ERA-Interim from the European Centre for Medium-Range Weather Forecasts (ECMWF) (hereafter referred to as FNLexp and ERAexp, respectively). Both of the downscaling simulations generally reproduced the observed spatial patterns of precipitation. However, users should keep in mind that the two downscaled datasets are not exactly the same in terms of observations. In comparison to the remote sensing-based estimation, the FNLexp produced a bias of heavy precipitation centers. In comparison to the ground gauge-based measurements, for the warm season (May to September), the ERAexp produced more precipitation (root-mean-square error (RMSE) = 295.4 mm, across the 43 sites) and more heavy rainfall days, while the FNLexp produced less precipitation (RMSE = 115.6 mm) and less heavy rainfall days. Both the ERAexp and FNLexp produced considerably more precipitation for the cold season (October to April) with RMSE values of 119.5 and 32.2 mm, respectively, and more heavy precipitation days. Along with simulating a higher number of heavy precipitation days, both the FNLexp and ERAexp also simulated stronger extreme precipitation. Sensitivity experiments show that the bias of these simulations is much more sensitive to micro-physical parameterizations than to the spatial resolution of topography data. For the HRB, application of the WSM3 scheme may improve the performance of the WRF model.

Evaluation of the climate change impact on wind resources in Taiwan Strait

International Nuclear Information System (INIS)

Chang, Tsang-Jung; Chen, Chun-Lung; Tu, Yi-Long; Yeh, Hung-Te; Wu, Yu-Ting

2015-01-01

Highlights: • We propose a new statistical downscaling framework to evaluate the climate change impact on wind resources in Taiwan Strait. • The statistical model relates Weibull distribution parameters to output of a GCM model and regression coefficients. • Validation of the simulated wind speed distribution presents an acceptable agreement with meteorological data. • Three chosen GCMs show the same tendency that the eastern half of Taiwan Strait stores higher wind resources. - Abstract: A new statistical downscaling framework is proposed to evaluate the climate change impact on wind resources in Taiwan Strait. In this framework, a two-parameter Weibull distribution function is used to estimate the wind energy density distribution in the strait. An empirically statistical downscaling model that relates the Weibull parameters to output of a General Circulation Model (GCM) and regression coefficients is adopted. The regression coefficients are calculated using wind speed results obtained from a past climate (1981–2000) simulation reconstructed by a Weather Research and Forecasting (WRF) model. These WRF-reconstructed wind speed results are validated with data collected at a weather station on an islet inside the strait. The comparison shows that the probability distributions of the monthly wind speeds obtained from WRF-reconstructed and measured wind speed data are in acceptable agreement, with small discrepancies of 10.3% and 7.9% for the shape and scale parameters of the Weibull distribution, respectively. The statistical downscaling framework with output from three chosen GCMs (i.e., ECHAM5, CM2.1 and CGCM2.3.2) is applied to evaluate the wind energy density distribution in Taiwan Strait for three future climate periods of 2011–2040, 2041–2070, and 2071–2100. The results show that the wind energy density distributions in the future climate periods are higher in the eastern half of Taiwan Strait, but reduce slightly by 3% compared with that in the

Regional hydro-climatic impacts of contemporary Amazonian deforestation

Science.gov (United States)

Khanna, Jaya

More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of

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)

Performance Assessment of New Land-Surface and Planetary Boundary Layer Physics in the WRF-ARW

Science.gov (United States)

The Pleim-Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the f...

Air-quality and Climatic Consequences of Bioenergy Crop Cultivation

Science.gov (United States)

Porter, William Christian

Bioenergy is expected to play an increasingly significant role in the global energy budget. In addition to the use of liquid energy forms such as ethanol and biodiesel, electricity generation using processed energy crops as a partial or full coal alternative is expected to increase, requiring large-scale conversions of land for the cultivation of bioenergy feedstocks such as cane, grasses, or short rotation coppice. With land-use change identified as a major contributor to changes in the emission of biogenic volatile organic compounds (BVOCs), many of which are known contributors to the pollutants ozone (O 3) and fine particulate matter (PM2.5), careful review of crop emission profiles and local atmospheric chemistry will be necessary to mitigate any unintended air-quality consequences. In this work, the atmospheric consequences of bioenergy crop replacement are examined using both the high-resolution regional chemical transport model WRF/Chem (Weather Research and Forecasting with Chemistry) and the global climate model CESM (Community Earth System Model). Regional sensitivities to several representative crop types are analyzed, and the impacts of each crop on air quality and climate are compared. Overall, the high emitting crops (eucalyptus and giant reed) were found to produce climate and human health costs totaling up to 40% of the value of CO 2 emissions prevented, while the related costs of the lowest-emitting crop (switchgrass) were negligible.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description, evaluation of meteorological predictions, and aerosol-meteorology interactions

Science.gov (United States)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-07-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and

A SIMULATION STUDY ON THE SHRUNK WETLAND AROUND QINGHAI LAKE AND REGIONAL CLIMATE

Institute of Scientific and Technical Information of China (English)

WANG HanJie; JING Li; GAO YunXiao

2005-01-01

Because of the increasing concerns about global climate change, it has been known by more and more peoples that there is a close relationship between wetland and/or peatland resources and climate change. This paper presents a new methodology to study the local climate variation caused by wetland shrinking around Qinghai Lake, the largest in-land salty lake in China, by use of a regional climate model (RCM) that commonly used in climate change study. The objective focuses on the regional climate effect of the shrunk wetland coverage in recent years. The results of numerical experiment showed that if the wetland coverage around Qinhai Lake were recovered as if in early 50s of last century,the regional climate in this area could be better with more cloud covers, higher relative humidity and more precipitation. In the other word, the area of wetland reduced is one of the most important reasons that caused regional climate aridification,eco-environmental deterioration and even desertification around Qinhai Lake.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

Science.gov (United States)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for

The Community WRF-Hydro Modeling System Version 4 Updates: Merging Toward Capabilities of the National Water Model

Science.gov (United States)

McAllister, M.; Gochis, D.; Dugger, A. L.; Karsten, L. R.; McCreight, J. L.; Pan, L.; Rafieeinasab, A.; Read, L. K.; Sampson, K. M.; Yu, W.

2017-12-01

The community WRF-Hydro modeling system is publicly available and provides researchers and operational forecasters a flexible and extensible capability for performing multi-scale, multi-physics options for hydrologic modeling that can be run independent or fully-interactive with the WRF atmospheric model. The core WRF-Hydro physics model contains very high-resolution descriptions of terrestrial hydrologic process representations such as land-atmosphere exchanges of energy and moisture, snowpack evolution, infiltration, terrain routing, channel routing, basic reservoir representation and hydrologic data assimilation. Complementing the core physics components of WRF-Hydro are an ecosystem of pre- and post-processing tools that facilitate the preparation of terrain and meteorological input data, an open-source hydrologic model evaluation toolset (Rwrfhydro), hydrologic data assimilation capabilities with DART and advanced model visualization capabilities. The National Center for Atmospheric Research (NCAR), through collaborative support from the National Science Foundation and other funding partners, provides community support for the entire WRF-Hydro system through a variety of mechanisms. This presentation summarizes the enhanced user support capabilities that are being developed for the community WRF-Hydro modeling system. These products and services include a new website, open-source code repositories, documentation and user guides, test cases, online training materials, live, hands-on training sessions, an email list serve, and individual user support via email through a new help desk ticketing system. The WRF-Hydro modeling system and supporting tools which now include re-gridding scripts and model calibration have recently been updated to Version 4 and are merging toward capabilities of the National Water Model.

Climate change and fire management in the mid-Atlantic region

Science.gov (United States)

Kenneth L. Clark; Nicholas Skowronski; Heidi Renninger; Robert. Scheller

2014-01-01

In this review, we summarize the potential impacts of climate change on wildfire activity in the mid-Atlantic region, and then consider how the beneficial uses of prescribed fire could conflict with mitigation needs for climate change, focusing on patters of carbon (C) sequestration by forests in the region. We use a synthesis of field studies, eddy flux tower...

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Science.gov (United States)

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

Using AIRS retrievals in the WRF-LETKF system to improve regional numerical weather prediction

Directory of Open Access Journals (Sweden)

Takemasa Miyoshi

2012-09-01

Full Text Available In addition to conventional observations, atmospheric temperature and humidity profile data from the Atmospheric Infrared Sounder (AIRS Version 5 retrieval products are assimilated into the Weather Research and Forecasting (WRF model, using the local ensemble transform Kalman filter (LETKF. Although a naive assimilation of all available quality-controlled AIRS retrieval data yields an inferior analysis, the additional enhancements of adaptive inflation and horizontal data thinning result in a general improvement of numerical weather prediction skill due to AIRS data. In particular, the adaptive inflation method is enhanced so that it no longer assumes temporal homogeneity of the observing network and allows for a better treatment of the temporally inhomogeneous AIRS data. Results indicate that the improvements due to AIRS data are more significant in longer-lead forecasts. Forecasts of Typhoons Sinlaku and Jangmi in September 2008 show improvements due to AIRS data.

Constraining estimates of methane emissions from Arctic permafrost regions with CARVE

Science.gov (United States)

Chang, R. Y.; Karion, A.; Sweeney, C.; Henderson, J.; Mountain, M.; Eluszkiewicz, J.; Luus, K. A.; Lin, J. C.; Dinardo, S.; Miller, C. E.; Wofsy, S. C.

2013-12-01

Permafrost in the Arctic contains large carbon pools that are currently non-labile, but can be released to the atmosphere as polar regions warm. In order to predict future climate scenarios, we need to understand the emissions of these greenhouse gases under varying environmental conditions. This study presents in-situ measurements of methane made on board an aircraft during the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), which sampled over the permafrost regions of Alaska. Using measurements from May to September 2012, seasonal emission rate estimates of methane from tundra are constrained using the Stochastic Time-Inverted Lagrangian Transport model, a Lagrangian particle dispersion model driven by custom polar-WRF fields. Preliminary results suggest that methane emission rates have not greatly increased since the Arctic Boundary Layer Experiment conducted in southwest Alaska in 1988.

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

Science.gov (United States)

Case, Jonathan L.; Blankenship, Clay B.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Berndt, Emily B.

2014-01-01

weather research and forecasting ===== The NASA Short-term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2-km northwestern-hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra-tropical cyclones with intense non-convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified-WRF (NU-WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real-time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU-WRF, EMS, LIS, and GSI.

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

Climate Change and Climate Variability in the Latin American Region

Science.gov (United States)

Magrin, G. O.; Gay Garcia, C.; Cruz Choque, D.; Gimenez-Sal, J. C.; Moreno, A. R.; Nagy, G. J.; Nobre, C.; Villamizar, A.

2007-05-01

Over the past three decades LA was subjected to several climate-related impacts due to increased El Niño occurrences. Two extremely intense episodes of El Niño and other increased climate extremes happened during this period contributing greatly to augment the vulnerability of human systems to natural disasters. In addition to weather and climate, the main drivers of the increased vulnerability are demographic pressure, unregulated urban growth, poverty and rural migration, low investment in infrastructure and services, and problems in inter-sector coordination. As well, increases in temperature and increases/decreases in precipitation observed during the last part of 20th century have yet led to intensification of glaciers melting, increases in floods/droughts and forest fires frequency, increases in morbidity and mortality, increases in plant diseases incidence; lost of biodiversity, reduction in dairy cattle production, and problems with hydropower generation, highly affecting LA human system. For the end of the 21st century, the projected mean warming for LA ranges from 1 to 7.5ºC and the frequency of weather and climate extremes could increase. Additionally, deforestation is projected to continue leading to a reduction of 25 percent in Amazonia forest in 2020 and 40 percent in 2050. Soybeans planted area in South America could increase by 55 percent by 2020 enhancing aridity/desertification in many of the already water- stressed regions. By 2050 LA population is likely to be 50 percent larger than in 2000, and migration from the country sides to the cities will continue. In the near future, these predicted changes are very likely to severely affect a number of ecosystems and sectors distribution; b) Disappearing most tropical glaciers; c) Reducing water availability and hydropower generation; d) Increasing desertification and aridity; e) Severely affecting people, resources and economic activities in coastal areas; f) Increasing crop's pests and diseases

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.

Regional climate, local climate and ozone air pollution in Tours and Orleans cities

International Nuclear Information System (INIS)

Berthelot, M.

2006-10-01

The importance of the relations between climate and the air pollution justifies the interest related to the role of the urban heat island of heat with respect to the night persistence of ozone in urban environment. When the days are favourable with important ozone concentrations, the agglomerations of the area observe a dynamics day laborer of ozone different from that observed in rural environment. The study is undertaken on the towns of Turns and Orleans where the observations of Lig'Air revealed a night persistence of ozone whereas the concentrations drop more quickly in periphery. This phenomenon is remarkable during the little broken down anticyclonic days. The region region Centre is a ground of study privileged for ozone because of its situation in the south-west of the Island of France rich in precursors of ozone. When flow is of continental origin, the Centre area is found then under the influence of the Paris area. The investigation of a study of the air pollution must take into account the notes of the regional climate and local climate. Several preliminary studies must intervene to answer our principal problems. First of all a descriptive study of the regional climate is carried out with the participation of Meteo-France. The current absence of climatic atlas as well as the many disparities of the climate related to extended from the territory partly justify the interest of our study. The regional approach of the climate is also essential for the continuation of work on a finer scale on the agglomerations of Turns and Orleans in order to detect the urban heat island of heat there. Collaboration with Meteo-France and Lig'Air made it possible to establish a satisfying network of measurement making it possible to obtain notable thermal differences between the downtown area and the surrounding rural environment. The correlation between meteorology and the proven air pollution leads us to establish the climatology of ozone. Many are the studies having

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 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.

Shifts in climate suitability for wine production as a result of climate change in a temperate climate wine region of Romania

Science.gov (United States)

Irimia, Liviu Mihai; Patriche, Cristian Valeriu; Quenol, Hervé; Sfîcă, Lucian; Foss, Chris

2018-02-01

Climate change is causing important shifts in the suitability of regions for wine production. Fine scale mapping of these shifts helps us to understand the evolution of vineyard climates, and to find solutions through viticultural adaptation. The aim of this study is to identify and map the structural and spatial shifts that occurred in the climatic suitability for wine production of the Cotnari wine growing region (Romania) between 1961 and 2013. Discontinuities in trends of temperature were identified, and the averages and trends of 13 climatic parameters for the 1961 to 1980 and 1981 to 2013 time periods were analysed. Using the averages of these climatic parameters, climate suitability for wine production was calculated at a resolution of 30 m and mapped for each time period, and the changes analysed. The results indicate shifts in the area's historic climatic profile, due to an increase of heliothermal resources and precipitation constancy. The area's climate suitability for wine production was modified by the loss of climate suitability for white table wines, sparkling wines and wine for distillates; shifts in suitability to higher altitudes by about 67 m, and a 48.6% decrease in the area suitable for quality white wines; and the occurrence of suitable climates for red wines at lower altitudes. The study showed that climate suitability for wine production has a multi-level spatial structure, with classes requiring a cooler climate being located at a higher altitude than those requiring a warmer climate. Climate change has therefore resulted in the shift of climate suitability classes for wine production to higher altitudes.

Regional model simulations of New Zealand climate

Science.gov (United States)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

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.

Distribution and transport of water vapor in the UTLS over the Tibetan Plateau as inferred from the MLS satellite data and WRF model simulations

Science.gov (United States)

Jain, S.; Kar, S. C.

2016-12-01

Water vapor is an important minor constituent in the lower stratosphere as it influences the stratospheric chemistry and total radiation budget. The spatial distribution of water vapor mixing ratio (WVMR) obtained from Aura Microwave Limb Sounder (MLS) satellite at 100 hPa level shows prominent maxima over the Tibetan Plateau during August 2015. The Asian monsoon upper level anticyclone is also known to occur over this region during this period. The Indian Meteorological Department (IMD) and National Centre of Medium Range Weather Forecasting (NCMRWF) observed daily gridded rainfall data shows moderate to heavy rainfall over the Tibetan Plateau, suggesting active convection from 26 July to 10 August 2015. The atmospheric conditions are simulated over the Asian region for the 15-day period using the Weather Research Forecasting (WRF) model. The simulations are carried out using two nested domains with resolution of 12 km and 4 km. The initial and boundary conditions are taken from the NGFS (up-graded version of the NCEP GFS) data. The WRF WVMR profiles are observed to be comparatively moist than the MLS profiles in the UTLS region over the Tibetan Plateau. This may be due to the relatively higher temperatures (1-2 K) simulated in the WRF model near 100 hPa level. It is noted that the WRF model has a drying tendency at all the levels. The UTLS WVMR and temperatures show poor sensitivity to the convective schemes. The parent domain and the explicit convective scheme simulate almost same moisture over time in the inner domain. The cloud micro-physics is observed to play a rather important role in controlling the UTLS water vapor content. The WSM-6 convective scheme is observed to simulate the UTLS moisture comparatively well and therefore the processes associated with the formation of ice, snow and graupel formation may be of much more importance in controlling the UTLS WVMR in the WRF model. The 24 hr, 48 hr and 72 hr forecast averaged for the 15-day period shows that

Monthly statistics for WRF with and without MODIS vegetation

Data.gov (United States)

U.S. Environmental Protection Agency — The 2006 monthly average statistical metrics for 2m Q (g kg-1) domain-wide for the base and MODIS WRF simulations against MADIS observations. This dataset is...

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.

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.

Evaluation of the atmospheric model WRF on the Qatar peninsula for a converging sea-breeze event

Science.gov (United States)

Balan Sobhana, Sandeepan; Nayak, Sashikant; Panchang, Vijay

2016-04-01

Qatar, a narrow peninsula covering an area of 11437 sq km, extends northwards into the Arabian Gulf for about 160km and has a maximum width of 88km. The convex shape of the coast-line and narrowness of the peninsula results in the Qatar region experiencing complex wind patterns. The geometry is favorable for formation of the land-sea breeze from both coastal sides of the peninsula. This can lead to the development of sea breeze convergence zones in the middle of the country. Although circulations arising from diurnal thermal contrast of land and water are amongst most intensively studied meteorological phenomena, there is no reported study for the Qatar peninsula and very few studies are reported for the Arabian Gulf region as whole. It is necessary to characterize the wind field for applications such as assessing air pollution, renewable energy etc. A non-hydrostatic mesoscale model, Weather Research and Forecast (WRF) with a nested high resolution grid permits the investigation of such fine scale phenomena. Data from eighteen land based Automated Weather Stations (AWS) and two offshore buoys deployed and maintained by the Qatar Meteorological Department were analyzed. Based on the analysis a clear case of sea breeze convergence were seen on 18 September 2015. Model simulations were used to investigate the synoptic conditions associated with the formation of this event. The season is characterized by week ambient north westerly wind over the Arabian Gulf. The WRF model performance is validated using observed in-situ data. Model simulations show that vertical extent of sea breeze cell was up to 1 km and the converging sea breeze regions were characterized with high vertical velocities. The WRF simulation also revealed that with high resolution, the model is capable of reproducing the fine scale patterns accurately. The error of predictions in the inner domain (highest resolution) are found to be relatively lower than coarse resolution domain. The maximum wind speed

Point Climat no. 26 'Regional Climate - Air - Energy Plans at the heart of the debate on the energy transition'

International Nuclear Information System (INIS)

Bordier, Cecile; Leseur, Alexia

2013-01-01

Among the publications of CDC Climat Research, 'Climate Briefs' presents, in a few pages, hot topics in climate change policy. This issue addresses the following points: On the eve of the introduction of the environmental assessment procedure for planning documents, almost all Regional Climate - Air - Energy Plans have now been published. This Climate Brief assesses regional climate strategies, which rely on significant commitment from those involved, including citizens by changing their behaviour, companies by improving their energy efficiency and the banking sector through financial support. Identification of these challenges and areas for action will feed into the national debate on energy transition which began last autumn

High-resolution, regional-scale crop yield simulations for the Southwestern United States

Science.gov (United States)

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

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and

Operational on-line coupled chemical weather forecasts for Europe with WRF/Chem

Science.gov (United States)

Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Flandorfer, Claudia; Langer, Matthias

2014-05-01

Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for the assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. Meteorology is simulated simultaneously with the emissions, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. The emphasis of the application is on predicting pollutants over Austria. Two domains are used for the simulations: the mother domain covers Europe with a resolution of 12 km, the inner domain includes the alpine region with a horizontal resolution of 4 km; 45 model levels are used in the vertical direction. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. On-line coupled models allow considering two-way interactions between different atmospheric processes including chemistry (both gases and aerosols), clouds, radiation, boundary layer, emissions, meteorology and climate. In the operational set-up direct-, indirect and semi-direct effects between meteorology and air chemistry are enabled. The model is running on the HPCF (High Performance Computing Facility) of the ZAMG. In the current set-up 1248 CPUs are used. As the simulations need a big amount of computing resources, a method to safe I/O-time was implemented. Every MPI task writes all its output into the shared memory filesystem of the compute nodes. Once the WRF/Chem integration is finished, all split NetCDF-files are merged and saved on the global file system. The merge-routine is based on parallel-NetCDF. With this method the model runs about 30% faster on the SGI

Assessments of regional climate change and its impacts in Northern Europe

Science.gov (United States)

Omstedt, Anders; von Storch, Hans; Reckermann, Marcus; Quante, Markus

2015-04-01

Regional climate change assessments are urgently needed to complement the big picture with regional results and scenarios of higher resolution and with relevance for local decision makers and stakeholders. A new type of assessment report originated in the original BACC report of 2008 (BALTEX Assessment of Climate Change for the Baltic Sea region) which has served as role model for other assessments published or in preparation. It represents an approach to assessing and making available current knowledge on regional climate change and its regional impacts on the physical, biogeochemical and biological environment (ecosystems, socio-economic sphere). Reports of this type which are available or underway are the original BACC book (2008), the second BACC book (2015), the climate report for the greater Hamburg area (2011), and the NOSCCA report (North Sea Climate Change Assessment) which is expected to be published in 2016. The assessments are produced by teams of scientists from the region, led by lead authors who recruit experts from relevant topics to contribute. The process is not externally funded and completely based on published scientific evidence, and not biased by political or economic interest groups. The BACC-type reports aim to bring together consolidated knowledge that has broad consensus in the scientific community, but also acknowledging issues for which contradicting opinions are found in the literature, so that no consensus can be reached ("consensus on dissensus"). An international steering committee is responsible for overlooking the process, and all manuscripts are anonymously peer-reviewed by independent international experts. An outstanding outreach aspect of these reports is the close collaboration with regional stakeholders (for the BACC reports: HELCOM, the intergovernmental Baltic Marine Environment Protection Commission and the major regional science-policy interface in the Baltic Sea region; for the Hamburg climate report: the Hamburg city

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Directory of Open Access Journals (Sweden)

Y. Zhang

2013-07-01

Full Text Available Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID (WRF/Chem-MADRID are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN, outgoing longwave radiation flux (OLR, temperature at 2 m (T2, specific humidity at 2 m (Q2, relative humidity at 2 m (RH2, wind speed at 10 m (WS10, wind direction at 10 m (WD10, and precipitation (Precip are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

Science.gov (United States)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial

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.

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